Managerial Neuro - Hybrid Decision Architecture · PDF fileManagerial Neuro - Hybrid Decision Architecture Lt Col (Dr) J Satpathy 1.2 & Dr Bhabani P Mishra 3 1. Faculty, Academics

Imperial Journal of Interdisciplinary Research (IJIR)

Vol-3, Issue-10, 2017

ISSN: 2454-1362, http://www.onlinejournal.in

Imperial Journal of Interdisciplinary Research (IJIR) Page 245

Managerial Neuro - Hybrid Decision

Architecture

Lt Col (Dr) J Satpathy 1.2

& Dr Bhabani P Mishra 3

1. Faculty, Academics Department, Officers Training Academy, Gaya

2. Higher Doctoral Candidate, Department of Management, UPES, Dehradun-248007, India

3. Senior General Manager (HRD) and First Appellate Authority, Odisha Hydro Power

Corporation, Bhubaneswar, Odisha

Abstract: For centuries, theoreticians have focused

entirely on use of additive utility representations to

describe decision behaviour. This basic framework

has been modified to account challenging

empirical results. However, each revision has

consistently confronted differing evidence.

Independent studies have come to a similar

conclusion. Scholarship is at a ‘tipping point’. This

seems to be result of potent mix of four factors:

volatility, uncertainty, complexity and ambiguity

fueled by rapid advances in biology, neuroscience

and computer science (Forbes; 2016). ‘It is an

empirical fact that natural sciences have

progressed only when they have taken secondary

principles as point of departure, instead of trying

to discover the essence of things. Pure political

economy has therefore a great interest in relying

as little as possible on the domain of psychology’ (Busino; 1964). In this Paper, attempt is to

describe a formal approach for scholarship of

managerial decision’ (Platt and Glimcher; 1999).

PART - I: HYBRID MODELING

Introduction

‘I am a monomaniac. What I am a monomaniac

about is decision-’. …. Herbert A. Simon

History of scholarship on judgment and decision

is noticeable by iterative tension between

‘prescriptive’ and ‘descriptive’ advances.

Prescriptive models define efficient / optimal

decision. Descriptive empirical advances suggest

that prescriptive models do not precisely describe

managerial emotion. Working from theoretically

powerful assumption that all managerial emotion

maximise ‘utility’, neoclassical theorists succeed in

developing a coherent framework for

understanding ‘what manager should choose’. They hypothesise that there had to be some sense

in which managers could be pronounced as

rationally unswerving and all-powerful tools of

deductive logic could be brought to bear on

scholarship of managerial decision. This

conclusion was followed, however, by a series of

descriptive insights that indicated that initial

neoclassic models were not consistent with

managerial decision. This meant either that

managers could not be described as logically

consistent in any sense or models developed during

the neoclassical revolution were flawed, or both

(Glimcher; 2008).

Decision making is not getting any easier.

Today's decisions are becoming complex, with

uncertainty, increasing time pressure, more rapidly

changing conditions and higher stakes. The

revolution engendered by advent of rational

decision modeling had two profound effects during

second half of 20th century; it succeeded in

defining set of tools that describe how manager

should behave to achieve maximisation. At

emotional level, it proved that individuals did not

reliably behave in the way predicted by existing

corpus of model. This insight led Herbert Simon

(1947) to conclude that managerial decision

makers could be regarded as rational utility

maximisers in partial or bounded sense.

What should the manager do? What are

managers categorically try to accomplish? How do

managers make decisions? Do managers choose

what they like, or do they like what we choose?

Literature in psychology shows that decisions

affect preferences, with chosen alternatives being

positively re - evaluated after decision. Certainty is

that business world is a multidimensional

ecosystem where future is capricious and frenzied.

Why is it that some organisations continue to thrive

in VUCA (Volatile, Uncertain, Complex and

Ambiguous) business world while others dissipate

away with first odours of transformation? Why is it

that certain organisations manage to navigate

through complexity of interconnected economies

and downturns of volatile forces but still continue

to reflect results, while others fail miserably even

at the slightest changes in models or situation?

http://www.onlinejournal.in/



Vol-3, Issue-10, 2017



Changing decision situation, VUCA biosphere

and globalisation (‘push’ and ‘pull’) put challenges

before managers. While managers constantly find

ways to strengthen competitive edge besides

sustain it in face of ever-increasing prospects,

complexities are heightened by change of agents,

factors and elements with pressure on complexities

for managerial decisions. Is this why organisations

fail to realise envisioned benefits? Is there an

accomplishment canticle for managing changes in

VUCA ecosphere? Decisions in VUCA ecosphere

need great beams to manoeuvre with adroitness.

They need to have shockwave absorbers to feel less

bumpy. That is where technology senses pulse on

ground. How can (neuro) technology help speed up

decision to respond to changing realities? May be

the solution lies in ‘Decision V - U - C - A

‘Managerial’ Order’. This paper investigates

decisional aspects and decision need in a dynamic

volatility, uncertainty, complexity and ambiguity

(VUCA) context of a manager.

Managers, in a connected but unstable realm, are

in an era of rapid change, dynamic managerial

development where stability is passing phase,

instability is ‘norm’ and complexity is

accumulating. They are in a business world where

volatility and uncertainty have become ‘New

Normal’. Economic turbulence and rapid rate of

change are throwing managers, confronted with

uncertainty and ambiguity, off - balance, as they

are unable to keep pace with vagaries of VUCA.

Critical thinking managers will prevail in VUCA

(Volatility, Uncertainty,

Complexity and Ambiguity) decision business

world. Not only do they have to contend with

rapidly changing trends and fluid situations, data

they get becomes redundant with no time giving

rise to confusion and chaos. This can be alleviated

by use of scenario based decision- where managers

draw up possible scenarios that they have to

contend with in short , medium and longer term.

There are still few questions unanswered.

Addressing 'how' to think instead of 'what' will

help managers negotiate rapid changes and

uncertainty. Point is, when there is so much

uncertainty, it becomes tough to anticipate actions.

Hence, by drawing up scenarios that simulate worst

and best, decisions can be taken that would derive

advantage to manager. When one adds complexity

to uncertainty and ambiguity, one is muddied and

muddled to take decisions. For this, managing

present is a challenge and hence leave forecasts to

managers.

Managers need to have vision to see

opportunities in challenges, courage to act with

conviction in face of uncertainty and risk, character

to do the right thing in difficult times and bounce

back when things do not go as expected. Decision

is a process that involves responding to short and

immediate term events and incidents as well as

strategising for long term with sustainable and

durable plans. This mix of reactive decision in

response to changing threats and proactive decision

geared towards long term is challenging. Whether

manager is responding to immediate events or

strategising for future, bottom line is that manager

is trying grip on external forces that impact in an

increasingly uncertain decision business world.

Point is that need for certainty and control over

future determine actions of managers in 21st

century. Need for speed and desire to stand

triumphant over long term manifest themselves in

ways managers confront business decision

landscape. In order to actualise these, managers

turn to a variety of tools and techniques that help

them decide.

How managers search for information and make

decisions when circumstances give little time to

ponder options and cognitive resources are partial.

How can they juggle simultaneous demands of

uncertainty, data scarcity and deadlines? These are

the rule rather than an exception in decision-. Some

information on complexity is available or can be

predicted. VUCA represents nature, speed, volume,

magnitude and dynamics of change. The situation

is unstable and of unpredictable duration.

Difficulties come unexpectedly or are unstable or

erratic. Understanding the situation may not

actually be difficult and available knowledge may

be plentiful. It is not a surprising situation as

information about the challenge is already

prophesied. Therefore, separating facts from

opinions is significant. One needs to gather facts

from various sources do logical enquiry, reasoning

and weigh alternatives. Formulating thoughts,

ensuring clarity in communication, predictability of

issues and events and predicting outcome generally

results in substantial transformation.

Improbability pervades neuromanagerial

decision. Nearly all decisions involve some form of

psychological uncertainty, whether about

likelihood of event or about nature of preferences.

Despite a lack of other information, basic cause

and effect of situation is acknowledged. Change

may be possible but is not a given. Complexity, a

growing number of problematic situations have

many highly interconnected elements. The large

amount of information available makes processing

and interpreting interdependencies difficult to

control. To meet challenges, managers need to

understand differences between four elements of

VUCA. Volatility has to do with the nature, speed




Vol-3, Issue-10, 2017



and magnitude of change. Uncertainty relates to

unpredictability of issues and events. Complexity,

multiple and difficult to understand poses a

challenge. Ambiguity adds and makes it difficult to

understand meaning of fast, moving, unclear and

complex events (Satpathy; 2016).

Brain technologies have motivated

neuromanagerial studies of internal order of mind.

By far the most studies in cognitive neuroscience

have studied how the brain responds to

experimental events. These studies have revealed

how information processing in the brain is

determined by external input. But the brain is not

just a passive receiver of information; the brain

continuously generates its own internal processes,

and any input from outside the brain interacts with

this spontaneous internal context. It promises a

fundamental change in how managers think,

observe and model decision in context. Brain

absorbs information, recognises and frames

problematic situations towards appropriate

responses. Decision- is based on complexly

interlinked technologies with links to bandwidth of

managerial decision. Manager often fail to design

‘rational’ decisions. Processes by which Managers

reach decisions embody differing tenets. Question

is how Manager makes decisions. How decisions

are carried out in brain? Interest is on assumptions,

beliefs, habits and tactics that Manager uses to

make decisions. How do parts of brain govern

decision-, coordinate, face obscurity and engage in

strategic simplification while deciding? What

happens in brain or is activated? Is scholarship of

decision making geometry via neuromanagement

relevant? What are the limits? How does previous

experience alter emotional?




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There are unsolved problems in (managerial)

cognition. What are the general implications?

Managerial cognition plays a role. Sensing is as an

important aspect and there is evidence of how

evolutionary patterns are shaped by beliefs and

attention allocation. How does Manager decide in

state of VUCA (Uncertainty, Vulnerability,

Complexity and Ambiguity? While there are

several benefits of using neuromanagerial

techniques in understanding decision, there are

questions that neuromanagerial science cannot

answer by itself and needs help of experimental

methodology and models to understand how

Managers decide. The key limitation is identifying

different regions of brain in certain situations

(VUCA). These techniques are not able to provide

an explanation or a reason (neuromanagerial) as to

why we respond in the manner that we do. What

happens in brain or what is activated when

Managers make decisions or are in process of

decisions or responding to outcomes? It does not

give insight into why we make decisions and why

we respond in the manner that we do. This is where

experimental methodology would help bolster

understanding. A synergy between

neuromanagerial techniques and experiments

provide insight into understanding Managerial

decision. In this, neuromanagement seeks to

explain decision-, ability to process alternatives

and choose optimal course of action (Satpathy and

Gankar; 2017). It studies how management

emotional shape understanding of brain and guide

coherent brain geometry towards decision-? These

elements present the context in which either

confound decisions or sharpen capacity to look

ahead, plan ahead and move ahead.

Uncertainty is a fact. Considered in

psychological context, uncertainty reflects absence

of desired information; timing, content, value or

certainty of future rewards. Uncertainty pervades

real-business world decisions in many contexts.

Uncertainty is intimately connected to reward

valuation. Not only is business growing complex

and uncertain at a faster and faster pace, old

decision- models are failing. In most decisions,

consequences are tied explicitly to outcome of

events. Previous studies indicate that psychological

weight attached to event, called ‘decision weight’, usually differs from probability of that event.

Faced with imperfectability of decision, theorists

have sought ways to achieve, if not optimal

outcomes, at least acceptable ones. Gigerenzer

urges to make virtue of partial time and knowledge

by mastering simple heuristics called ‘fast and

frugal’ reasoning. Etzioni proposes ‘humble

decision,’ an assortment of non - heroic tactics that

include tentativeness, delay, and hedging. How do

managers make rational decisions? How do they

form expectations? Can situation influence

managerial decisions? If so, in what way? The

answers to these questions lie in the concept of

uncertainty linking the two schools of thought

(Conceição; 2005).

VUCA sets the stage for how Managers view

conditions under which they make decisions, plan

forward, manage risks, foster change and solve

problems, In general, VUCA tend to shape capacity

to:

Anticipate issues that shape conditions,

Understand consequences of issues and

actions,

Appreciate interdependence of variables,

Prepare for alternative realities and challenges,

and

Interpret and address relevant opportunities.

Managerial Challenges

In natural and human systems, rapid changes are

occurring triggered by human activities. First,

managers have to consider these possible changes

in decision-. Plans have to be flexible. Second,

managers have to perceive actual changes and

adapt plans and management accordingly

(Mitchell; 2002). Due to complexity and changes,

managers do not have complete information about

all factors influencing a decision. They have to

make decisions despite lack of information for

which decisions have consequences (Ewert; 2004

and Mitchell; 2002). Different, often differing,

values and perspectives are involved in decision.

Managers are faced with conflict situations. They

have to recognise and mediate between differing

sides. This is associated with inter - generational

equity implied in ‘sustainability’ (Mitchell 2002).

What are the changes in management decisions?

Managers have been faced with need to make

decisions. Business decision situation is changing.

Managers face variety of changes that influence

decision. In particular, managers may challenges in

decision process because of lack of pertinent

information and partial expertise of managers.

Managers rely more than ever on data and metrics

to aid in decision. Evidence-based management has

become the expectation. Intuition no longer is

enough. Managers must have facts and data to

support decisions and be prepared to defend those

decisions (Leigh Richards; 2016). Fortunately, they

have a wide range of data and information to aid

them and multiple tools to help crunch the

numbers. Internet has opened floodgates to mass of

information that is readily available to managers to




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help them in sound decisions. This can be a great

benefit, but it can create challenges.

Managers must decide which information is

useful and pertinent based on decision they are

contemplating. They must determine when they

have gathered enough information and when it is

time to move forward with a decision. In addition,

not all information found online is credible.

Managers must be able to separate ‘wheat from

chaff’ and rely on precise, relevant and timely

information. Managers recognise that they alone

are not responsible for decisions. In addition, they

are not anticipated to act individualistically.

Collaborative form of work style means that

managers not only have ability to gather input from

variety of sources, but there is an expectation that

they do so. The ability to involve others is a change

from old ‘command - and - control’ style of

management.

Things become much more complex in the

business world of unreasonableness. Much of

traditional economics becomes outmoded when

complex relationships based on often counter-

intuitive behaviours are taken into account. Are

managers ready to manage in an irrational business

world? Despite the glut of research and evidence

suggesting that we are all, in fact, irrational, my

impression is that the lessons are very slow to take

hold in most business disciplines. Today’s business

environment is described as VUCA; Volatile,

Uncertain, Complex and Ambiguous. VUCA is,

quite simply, the expression of the fact that the rate

of change is outpacing our ability to adapt. Many

managers are struggling to stay afloat and aligned

in the volatile, uncertain, complex, and ambiguous

nature of today’s global business environment.

Turbulence, the rapid rate of change, is swirling

around many of us, tipping us this way and that as

we attempt to navigate a safe passage through it all.

We are moving from a business world of problems,

which demand speed, analysis, and elimination of

uncertainty to solve, to a business world

of dilemmas, which demand patience, sense

making, and an engagement of uncertainty.

Managers cannot always be sure which decision

will eventually matter most. Managers need to take

each decision based on best possible information

and shaped by best possible judgement. Decision

that seems shrewd could quickly look misguided,

as new information becomes available or context

changes. In addition, decision that backs wrong

model may cause systemic failure. Over the past

half century, researchers have responded to

challenges by either bounding reach of theory or

turning to descriptive approaches. One recent trend

may reconcile this tension between prescriptive

and descriptive approaches. There is hope that it

may yield a theory that is constrained and

parsimonious while offering significant predictive

power under range of conditions. Trend is amongst

economists and neuroscientists in physical

mechanisms by which neuromanagerial decisions

are made within brain. There is reason to believe

that basic outlines of neuromanagerial decision

architecture are known and reveal actual

computations that brain performs when making

decisions. If this is true, then combination of

economic and neuro - scientific approaches may

succeed in providing a methodology for

prescriptive and descriptive economics by

producing predictive and parsimonious model

based on actual computations performed by brain.

While both have been fruitful, neither has provided

a clear programmatic approach that aspires to

complete understanding of neuro managerial

decision. The history has been marked by iterative

tension between prescriptive and descriptive

advances (Satpathy; 2016).

The business world has always been irrational. It

is safe to assume that business world is irrational

and build strategies. Therefore, significant question

to answer today is ‘How to manage in an irrational

business world with rational management process?’ Management decisions are based on rational

thinking. So how to manage an irrational business

world? Are managers ready to manage in an

irrational business world, is the question posed.

Asking this question is like that, researchers have

suddenly discovered a new business world

phenomenon that researchers have to gear. The

antidote to VUCA is about moving from volatility

to vision, from uncertainty to understanding, from

complexity to clarity and from ambiguity to agility.

First, to become an adaptive manager for VUCA

times, he has to define success in prior roles and

models, essentially shedding impact of years of

performance reinforcement and standards and set

to measure up new ones. Second, manager needs to

keep his ego in check. Third, manager should

have keen desire to keep learning and ability to see

completely new set of skills. Fourth, manager

needs to adopt ‘open - to - everyone’ stance.

Finally, manager should have ability to work with

contradictions and paradoxes while with navigating

VUCA business world. The aspects, in this, include

mindfulness, intuition and wisdom.

Mindfulness: Mindfulness refers to present -

moment, non - judgmental awareness of internal

and external phenomena (Brown and Ryan; 2003).

A good portion of mindfulness research is

concerned with antecedents and consequences of




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consciously paying attention to present moment

increasing awareness of different perspectives and

interpretations that exist within present moment

experience. Mindfulness is a multi - level construct

that can be practiced through non-meditative

processes and routines (Sutcliffe; 2016).

Mindfulness can equip with self and situational

awareness and ability to pause before reacting

(Garland ; 2011). This lends to variety of improved

outcomes including less bias and reliance on

outmoded mental heuristics (Fiol and O’Connor;

2003). Mindfulness can be placed within decision-

making realm alongside perspectives that

acknowledge limitations of bounded rationality

(March and Simon 1993) and human inference

(Kahneman et al. 1982). One intention is to train

contemplative traditions as ‘bare attention’ (Gunaratana 2009), a quality of attention that

enables phenomenon to be absorbed without

judgment, with limited influence of the past, and

without immediate categorization into existing

cognitive schemas. This characteristic of

mindfulness supports equanimity and allows

decision makers to treat equally information and

data that are both confirmatory and dis-

confirmatory of a preferred point of view

(Santorelli 2011). As information is processed, not

all of it will be interpreted equally since our prior

experiences, habits and biases may color what

information we notice and how we absorb it.

Studying the mindful processing of information

allows researchers to consider how such bottom-

up, non- or pre-judgment related processes may

prompt decision makers to break habitual,

potentially less effective, decision-making patterns

in VUCA business world.

Intuition: Intuition is understood as direct

knowing without any use of conscious reasoning

(Sinclair and Ashkanasy; 2005). It refers to ability

to process subconsciously or access directly

information without engagement of rational

thinking, be it in form of analysis or development

of logical argument. Managers think of a problem

or see a situation and simply know the answer,

albeit they are not aware that any deliberation on

our part occurred. That is why intuition is

sometimes called ‘knowing what without knowing

how’ (Vaughan; 1979). Dual-process theories

(Epstein; 1990, Stanovich and West; 2000) suggest

that brain activates different regions, for different

reasons, and various mental processes strengthen

certain regions of brain. Whilst brain and mind is

not synonymous (Sinclair 2016), for intuition,

which is considered primitive evolutionary process,

its neural network is used as default setting until or

unless the situation calls for an intentional

employment of reasoning faculty. This conclusion

is supported by brain mapping studies that

identified two distinct neural systems used for each

type of information processing respectively

(Lieberman et al; 2004). The intuitive mechanism

is activated in fast-paced, ambiguous, or uncertain

situations when we do not have access to adequate

information or time to process it (Behling and

Eckel 1991;

Wisdom: Wisdom is a higher-order insight

available into complex, dynamic and uncertain

issues and adds a new layer that focuses on

creation of insight. Cognitive process deals with

exploitation of ideas and requires different

information processing at different levels of

consciousness and helps explain findings from

Managership research. Managers typically seem to

use intuition in edging and retreating phase of

sense making. Incorporating both processes opens

possibility of different way of knowing and offers

another useful tool for contemporary decision-

making. It suggests a model for integrating modes

of information processing, as suited to activity and

context of each transitory moment.

Volatility: The business world has changed as

we entered the new situation full of volatility,

uncertainty, complexity, and ambiguity. Business

managers in 21st century operate in a vastly

different terrain. The landscape that confronts the

managers today is characterised by VUCA

principle or Volatility, Uncertainty, Complexity,

and Ambiguity characteristics. The business world

has been transformed from a series of loosely

connected economies with reasonably predictable

flows between them to a complex web of

relationships where global impact of local events is

felt almost instantaneously. A comprehensive

theory is needed and is reasoned that concepts of

managership theory can provide synthetic theory

that provides integrated framework for many

partial theories. Drawing on formal approaches, it

is reasoned that insights can combine with

managerial perspectives to clarify and synthesise

strategic issues. Judgmental decision-making,

involving acting on a synthesis of all available

information, is the defining characteristic.

Perceptions of risk are subjective. Faced with

volatility of environment, manager faces

information cost (cost of maintaining up-to-date

information about the environment). Four

dimensions of environmental shock lead to

different forms of managership. Managers create

identify and monitor sources of volatility and

channel information to key decision makers. The

standard rational action model is generalised to an

uncertain business world of volatility and

differential access to information, which generates




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differing perceptions of environment, which

managers exploit. The managerial synthesis of

information identifies new opportunities. It relates

capabilities of manager to nature of business

environment, especially regarding volatility.

To be able to cope with this situation, an

organization has to translate the challenges into a

clear vision and action. A managership style that is

agile to adapt with the magnitude and the

characteristic of the occurring problem is

obligatory. Transformational managership is a

participative managership style that is not only able

to motivate and drive the organization vertically

and horizontally but also always be agile in every

circumstance. Thus, the organizational capacity to

achieve the shared vision and mission will be

encouraged. Applied neuroscience gives an

understanding about the activities and mechanism

of the brain, which improves the required

competences of a manager. Therefore, applied

neuroscience will help a manager transform the

organization. This study shows that applied

neuroscience can help a transformational

managership achieve a ‘physically, emotionally,

and mentally safe’ state and encourage an

organization to transform itself effectively.

Uncertainty: Uncertainty is a common feature

of decisions. Uncertainty arises in a situation that

has limited or incalculable information about

predicted outcomes of behaviour. Decision making

is the important task of manager and it is difficult

one. Domain of decision analysis models falls

between two extreme cases. This depends upon

degree of knowledge we have about outcome of

actions. One ‘pole’ is deterministic. The opposite

‘pole’ is pure uncertainty. Between these two

extremes are problems under risk. The degree of

certainty varies among managers depending upon

how much knowledge each one has. This reflects

recommendation of a different solution by each.

Probability is used to measure likelihood of

occurrence for event. When probability is used,

deterministic side has probability of one (or zero),

while other end has flat (all equally probable)

probability.

When managers make choices or decisions under

risk, they somehow incorporate this risk into

decision-making process. Conditions of risk occur

when manager make a decision for which outcome

is not known with certainty. Under conditions of

risk, managers make a list of possible outcomes

and assign probabilities to various outcomes. To

measure risk associated with decision, the manager

can examine several characteristics of the

probability distribution of outcomes for the

decision. The rules for making decisions under risk

require information about different characteristics

of probability distribution of outcomes: (1)

expected value (or mean) of distribution, (2)

variance and standard deviation, and (3) coefficient

of variation. These can guide managers in analysis

of risky decision making. The actual decisions

made depend on manager's willingness to take risk.

Managers' propensity to take risk can be classified

in risk adverse, risk loving, or risk neutral.

Do dynamic brains predict the business world? To

make sense of chaotic inputs, brain makes educated

guesses as to what generates them. It seems that

mind has first to construct forms independently.

The mystery is, and remains, how manages think,

imagine, dream and conduct intelligent action.

Brains have to make sense of chaotic, often

uncertain input by making predictions about what

might be generating signals impinging on us. Brain

analyses incoming signals, finds patterns of ever-

increasing complexity, and makes sense of what’s

out there by matching observed patterns against

internal representations (Clark; 2016). To

successfully cope with these, nervous system has to

estimate, represent and eventually resolve

uncertainty at various levels. Modeling human

behaviour using computational approaches has

provided some insight into potential mechanisms

involved in decision-making under uncertainty.

Entrepreneurs get used to uncertainty because

they see no other alternative. Entrepreneurs

overcome uncertainty because they are certain

about their idea. Entrepreneurs embrace

uncertainty because they like it. Entrepreneurs face

uncertainty with a strong sense of pragmatism and

resilience. Entrepreneurs use their networks as

shield and testing ground reducing the uncertainty

in their close surroundings (Peia;

2012). Uncertainty and ambiguity of potential

future threats are central to understanding

generation of anxiety and anxiety disorders.

Managers who had difficulty tolerating uncertain

future had relatively enlarged striatum. There are

three main forms, expected uncertainty (including

risk), unexpected uncertainty and volatility and

review theoretical and empirical evidence that

support this dissociation. Future research should

therefore form clear distinction between

unexpected uncertainty and volatility to explore

how to successfully estimate, represent, and

resolve these different forms of uncertainty.

Complexity: Complexity describes behaviour of

system / models whose components interact in

multiple ways and follow rules, meaning there is




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no reasonable higher instruction to define various

possible interactions. In ‘complexity’, the

consensus is that there is no agreement about

specific definition of complexity. One problem in

addressing complexity has been formalizing

intuitive conceptual distinction between large

number of variances in relationships extant in

random collections and sometimes large, but

smaller, number of relationships between elements

in systems where constraints (related to correlation

of otherwise independent elements) simultaneously

reduce variations from element independence and

create distinguishable regimes of more - uniform,

or correlated, relationships, or interactions.

Complexity within VUCA framework refers to

interconnectivity and interdependence. Nonlinear

interactions and interdependencies render capacity

for control over the system through direct

intervention limited. In complex systems, capacity

to align directly elements towards some desired

future goal is limited. The response to this is to

focus on creating the context that succeeds.

Disorganised complexity results from particular

system having large number of parts. However,

interactions of parts in a ‘disorganised complexity’ situation can be seen as largely random, properties

of system as a whole can be understood by using

probability methods. Organised complexity resides

in non-random, or correlated, interaction between

the parts. These correlated relationships create a

differentiated structure that can, as a system,

interact with other systems. The coordinated

system manifests properties not carried or dictated

by individual parts. The organized aspect of this

form of complexity vis-a-vis to other systems than

the subject system can be assumed to ‘emerge,’ without any ‘guiding hand’. When faced with

uncertainty and environmental turbulence,

managers emulate strategies and practices to

simplify complex problem. In times of turbulence

and ambiguity, managers feel safe imitating rivals

rather than going out on a limb with a novel

strategy. Nevertheless, essence is to develop

unique system of activities that enables to

differentiate itself from competition or deliver at

lower cost than rivals. Copying strategies and

practices will not produce unique and defensible

position. It takes courage to stand - alone when

rivals engage in herd behaviour.

In many situations, managers cope with

complexity by adopting a rule of thumb, or

heuristic, to simplify complicated decision. These

reduce amount of information that decision-makers

need to process and shorten time required to

analyse complex problem. Many develop heuristics

to simplify screening and evaluation process. These

two rules of thumb enable managers to weed out

unattractive deals very quickly. In most cases,

heuristics enable managers to cope with ambiguity

and make sound judgments in an efficient manner.

Rules of thumb can be dangerous, though. They do

not apply equally well to all situations. There are

always exceptions.

Ambiguity: Ambiguity is not lack of data, but

torrent of data. When environments become

complex, simple linear cause and effect

descriptions of events break down and ambiguity

arises due to lack of models to explain observed

phenomena. Resolving ambiguity means

understanding context within which event takes

place. It requires systems thinking to see

interconnections, gain different perspectives in

order to build up full context within which event

can be properly understood. Ambiguity is quality

of being open to more than one interpretation. It

results in haziness of reality; potential for

misreading and mixed meanings to conditions.

Traditionally, managers search for linear cause and

effect models to explain phenomena within

environment. Reductionism in management

reduces description of phenomena to single

dimensional perspective. This creates brittle

models. When environments become complex,

traditional linear cause and effect models start to

break down, become redundant and even worse.

The result can be a shock. Due to their nature,

linear models do not fail gracefully. Complex

environments require investing in developing

models that capture context within which events

play out. This means a switch from trying to

analyse and understand events themselves in

isolation to understanding space around them that

gives them context. This is where systems thinking

comes in and places emphasis upon understanding

relations that give object or event its place within

some environment.

Instead of trying to describe and understand

event by describing properties, systems thinking

reasons backward. By first having overview to

environment, managers can understand a system

through its connections to other systems. Thus,

understanding it with respect to its place within

whole environment . By doing so, managers can

gain multiple different perspectives. Each

perspective give richer and robust

multidimensional understanding. The net result is

containment or confinement of ambiguity to

limited set of possible interpretations. Even if

managers do not fully understand phenomena, by

having deeper understanding of context, managers

are able to have some parameters within which to

interpret individual event. Thus, it is still required




Vol-3, Issue-10, 2017



that managers learn to make decisions without

absolute knowledge and information and are able

to hold two contrasting ideas. Leaders in complex

environments need to be able to handle ambiguity

and make judgments when ‘facts’ are unclear or

evolving. In other words, not be overly dependent

upon quantitative, fact-based methods of reasoning

in supporting their decision making

Decision under ambiguity (uncertainty with

unknown probabilities) has been attracting

attention in behavioural neurodecisions. However,

recent neuroimaging studies have mainly focused

on gain domains while little attention has been paid

to magnitudes of outcomes. The first step is to

identify available options. In real business world,

however, options often cannot be enumerated or

articulated fully. Furthermore, as options are

articulated and explored, new options and sub-

options tend to emerge. This is particularly true if

options depend on how future events unfold. The

second step is to develop criteria for rating options.

As anyone who has been involved in deciding on

contentious issue will confirm, it is extremely

difficult to agree on a set of decision criteria for

issues that affect different stakeholders in different

ways. The third step is to rate options. The problem

here is that real-business world options often

cannot be quantified or rated in meaningful way.

Summarising the discussion thus far: rational

decision approaches are based on assumption that

managers have shared understanding of decision

problem as well as the facts and assumptions

around it. These conditions are clearly violated in

case of ambiguous decision problems. Therefore,

when confronted with a decision problem that has

even a hint of ambiguity, the first order is to help

reach shared understanding of problem. This is

essentially an exercise in sense making, the art of

collaborative problem formulation. However, this

is far from straightforward because ambiguity

tends to evoke negative emotions and attendant

defensive behaviours. The upshot of all this is

that any approach to tackle ambiguity must begin

by taking the concerns of individual managers

seriously. Unless this is done, it will be impossible

for the group to coalesce around a consensus

decision.

‘Managerial’ Neuro - Order’

Decision is a commitment to a proposition or

plan. Decision process encompasses steps that lead

to commitment. This is often termed ‘deliberation

among options’. These options may take form of

actions, plans, hypotheses or propositions. Most

decisions are based on a variety of factors:

evidence bearing on prior knowledge about

options, prior knowledge concerning relative merit

of options, expected costs and rewards associated

with matrix of possible decisions and outcomes and

costs associated with gathering evidence (Shadlen;

2012). Decision implies end of deliberation and

beginning of action. How to leverage calculated

science of algorithmic decision making to enhance

intuitive managerial cognitive decision system?

Can framework of decision model capture salient

characteristics of managerial emotion that do not fit

unrealistic models of rationality? Managers

typically make efforts to control emotion

experiences. This leaves open a possibility that

decision effects attributed to acute emotions may

be affected by regulatory strategies. If so, this

raises the additional possibility that different

regulation strategies could have different

implications for managerial decisions. Can

understanding of emotion influences on managerial

decision improve existing and future algorithmic

decision systems that interact with managers?

Decisions frequently require choosing among mu

ltiple alternatives. Models about managerial

decision include; Augmenting Principle, Bounded

Rationality, Bias Correction, Explanatory

Coherence, Filter Model, Involvement, Multi -

Attribute Decision, Mere Exposure Model,

Perceptual Contrast Effect, Priming, Self -

Determination Model, Self - Regulation Model and

Transtheoretical Model of Change. Compared

to binary decision paradigms, much less is known

about computational norm of decisions with more

than two options. Previous experiments have

revealed puzzling properties involving more than

two options, such as interactions among these

options and time - dependent decision thresholds.

Time is an important dimension of human

subjective experience, yet we know quite little

about how the human brain encodes time. A

distinction has to be drawn between explicit

time perception and implicit timing, currently

subject to two separate research fields. Explicit

time perception refers to situations in which we

overtly estimate a time interval, while implicit

timing refers to situations in which temporal

regularities are used to form temporal expectations,

even when no explicit timing is required. An

interesting and important question is whether these

two seemingly different timing processes rely on

(at least partially shared) versus completely

separate neural and cognitive mechanisms.

Interestingly, participants use even subtle temporal

regularities in the stimulation to create temporal

expectations which improve performance, i.e. in a

perceptual task. An intriguing question is why on

the one hand these implicit timing processes



https://eight2late.wordpress.com/2016/03/15/what-is-sensemaking/


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function quite reliably, while when asked to overtly

estimate a time interval, human observers perform

quite poorly.

Are decision models simple to explain intricacies

of brain processes? No. models were initially

designed to explain decisions in situations that, just

like managerial brains, are complex. The purpose

was to find logical mapping between

characteristics of causes and consequences. Rather

than trying to explain all events at once, model

breaks situation into small pieces and focuses on a

subset of them. It deliberately ignores

characteristics that are orthogonal or modify

magnitude of effect, simply because these extra

elements pollute analysis (TREND; 2007). Is

neurodecision scholarship of decision- processes

relevant for economics? Depending on how we

define, it may or may not be relevant (TREND;

2007). Most models of decision postulate that

decisions are or should be based on two pillars:

beliefs and values.

A decision maker’s beliefs are reflection of his

perceptions of reality, including facts, opinions and

uncertainties. Beliefs can and should be informed

by science that reflect his sense of what to strive

for or to achieve, including goals, objectives and

associated trade - offs. This exists in all decision

models, including prescriptive ones, expected

utility model and subjective expected utility model

and prospect model. Why nervous system ought to

have such properties and how they functionally

relate to each other remains poorly understood. To

address these, studies have derived normative

strategies for general value - based decisions with

multiple options, and have identified optimal

stopping-rules for value - based evidence

accumulation. The resulting strategy appears

complex but is approximated by remarkably simple

neural mechanism, with time - dependent activity -

standardisation in a recurrent circuit controlled by

an urgency signal. Archetype reveals why nervous

system requires activity normalisation / urgency

signal. They allow nervous system to implement

efficient decisions under multi - alternative

decisions. The archetype predicts time - dependent

normalisation that constrains neural population

activity during decision (Drugowitsch; 2016).

Fundamental challenge is to link observed

activities to unobserved biophysical mechanisms

that produce it. In some cases, experimental

manipulations permit detailed assessment.

Constraints from neurophysiological data can be

used to test between models that are otherwise

difficult to distinguish. Convergence of

psychological theory and neurophysiological data

suggests that common theoretical framework is

sufficient to account for simple decision-making

data at neural and behavioural levels. Emerging

technologies facilitate high-throughput experiments

and accelerate neurons observed simultaneously,

targeted experimental manipulations become

infeasible or intractable. Challenge of rigorously

connecting observed neuronal activity to

underlying biophysical mechanisms is critical to

address fundamental questions. To address

challenge of linking data to mechanisms is through

development of computational models in which

unobserved biological mechanisms can be

expressed and controlled. These models typically

possess variables and parameters, and rigorous

'matching' of the model to the observed neuronal

data.

Neuro Perceptions

Studies of managerial emotional have

historically been distributed across very diverse

disciplines, whose practitioners seldom spoke with

one another or exchanged ideas and insights.

earliest psychologists studied mental phenomena at

purely abstract level, undaunted by sparseness of

biological knowledge of their time. Likewise,

cognitive psychology of late 20th century was

focused largely on mental function, often explicitly

not concerned with brain structure. At the same

time, studies of rational decision were largely the

province of economic model that focused primarily

on understanding what the rational emotional

of ‘Economic Man’ should be. This disciplinary

division of labour reflect three levels of analysis;

computational level of problem, brain's algorithms

and functional organisation, and neurology

concerned with details of implementation. All that

has changed in recent decades, and in almost all

aspects of emotional sciences, there is now a trend

to bring disciplines together and to build models

that at once address the phenomena in question at

all three levels of analysis. While this is certainly a

step in the right direction, marrying long estranged

fields is a precarious business. Some caution must

be taken in choosing which conceptual components

are most valuable for guiding the fields towards a

unified direction that is a fruitful one, rather than

merely entrenching them all towards the same

limiting assumptions.

Brain is a product of evolution, which rests on

two fundamental principles: natural selection and

descent with modification. The first of these is

widely acknowledged in model, motivating search

for mechanisms that confer selective advantage.

The second principle is valuable for developments

of models that span across levels of analysis. This




Vol-3, Issue-10, 2017



is because evolution is remarkably conservative,

powerfully constrained by phylogenetic history.

Evolution can only work with existing ancestral

system, and make modifications that maintain

system's integrity. In language of optimisation

model, it does not perform exhaustive search but is

highly myopic and constrained to local regions

whose basins may be separated from other classes

of solutions by impassable crevasses. Major

evolutionary change is primarily driven by changes

in the situation, not by sudden creative leaps in the

genome (Cisek; 2014).

How are decisions carried out in brain? Question

is how manager make decisions. Psychological

models of decision explain that managers gradually

accumulate evidence for a particular choice over

time, and execute that choice when evidence

reaches critical level. Brain considers sources of

information before decision. In particular, the

processes by which managers reach decisions have

been ignored. Problems confronting decision

makers often embody differing values. Manager

often fail to design ‘rational’ decisions. When

faced with obscure decision, managers engage in

strategic simplifications of decision problems. How

do parts of the brain that govern decision-

coordinate their activity when a decision? This

paper explores certain neuro - underpinnings in

managerial decision modeling (Satpathy; 2016).

In neurosciences, how the brain processes

different sensory stimuli (such as images or

sounds) and which are the neural basis involved in

deciding what we perceive, have been the deeply

studied in the past decades. Impairments in

decision- are at the core of a variety of

psychological and neurological impairments. Brain

accumulates evidence when faced with a choice

and triggers an action once that evidence reaches a

tipping point. Nevertheless, how do we know

where we are, where we have been and where we

are going? It is important to understand intricacy of

managerial brain. Brain is main organ of nervous

scheme. It has the same general structure as brains

of other mammals, but with developed cerebral

cortex. Model of brain function can explain a wide

range of anatomical and physiological aspects of

brain schemes (Satpathy; 2016).

A basic question, intimately tied to the problem

of action choice, is that of how actions are

assembled into organised sequences. Models of

routine sequential emotional have long

acknowledged that it must rely not only on

situational cues but also on some internal

representation of temporal or task context. It is

assumed, in most models, that such internal

representations must be organised into a strict

hierarchy, mirroring the hierarchical structure of

naturalistic sequential emotional Based on recent

neuroscience evidence, we model the brain as a

dual-scheme organisation subject to three conflicts:

asymmetric information, temporal horizon, and

incentive salience. Under the first and second

conflicts, we show that the uninformed scheme

imposes a positive link between consumption and

labour at every period. Furthermore, decreasing

impatience endogenously emerges In decision-,

purposes must first be established, purposes must

be classified and placed in order of importance,

substitute actions must be developed, the substitute

must be evaluated against all the purposes, the

substitute that is able to achieve all the purposes is

the tentative decision, the tentative decision is

evaluated for more possible consequences, the

decisive actions are taken, and additional actions

are taken to prevent any adverse consequences

from becoming problems and starting both

schemes (problem scrutiny and decision) all over

again.

There are steps that are generally followed that

result in a decision model that can be used to

determine an optimal production plan and in a

situation featuring conflict, role-playing may be

helpful for predicting decisions to be made by

involved parties. Each of these factors leads to a

fresh perspective. A neural level focuses on the

basic forebrain functions and shows how

processing demands dictate the extensive use of

timing-based circuitry and an overall organisation

of tabular memories. An embodiment level

organisation works in reverse, extensive use of

multiplexing and on-demand processing to achieve

fast analogous calculation. An awareness level

focuses on the brain’s representations of emotion,

attention and consciousness, showing that they can

operate with great economy in the context of the

neural and embodiment substrates. Each step in the

decision- process may include social, cognitive and

cultural obstacles to successfully negotiating

dilemmas. It has been suggested that becoming

more aware of these obstacles allows one to better

anticipate and overcome them. Neuroscience and

social science have witnessed tremendous advance

in Neurodecisions and Neuromanagement since

birth of these interdisciplinary fields at turn of

Century.

In order to explain cognitive and neural

underpinning of managerial decision, ability to

process multiple substitutes and to choose optimal

course of action, especially in managerial context.

Nerve management is contemporary developments

in cognitive neuroscience, neural imaging




Vol-3, Issue-10, 2017



technology progress and traditional management

research across field of study, through study of

manager in management activities such as acts of

neurophysiologic underpinning, thereby from brain

science perspective on managerial management

activities of mechanisms behind, and brings

forward corresponding management measures and

strategies. And neurodecisions, nerve management

emphasis on exact situations, manager differences

and the operational level of emotional, study

different conditions managed object evolution rule

and achieve most effective management method.

Decision makers must have vast amounts of

information in order to make use of the rational

comprehensive decision- technique. There needs to

be an ability to predict the future consequences of

decisions made. In addition, problems confronting

decision makers often embody differing values. In

addition, it is tough to ignore sunk costs of former

decisions, these may foreclose many substitutes.

Central argument is that decision- is at core of all

managerial functions and future of any

organisation lies on vital decisions made. However,

there are certain critical issues coupled with factors

such as uncertainties, multiple objectives,

interactive complexity and anxiety make decision-

process difficult. At times when a decision is

complex or there are many interests at stake, then

we realize the need for strategic decision-.

Questions include; how to choose in tough

situations where stakes are high and there are

multiple differing objectives? How should we

plan? How can we deal with risks and uncertainties

involved in a decision? How can we create options

that are better than ones are originally available?

How can we become better decision makers? What

resources will be invested in decision - ? What are

the potential responses to a particular problem or

opportunity? Who will make this decision? Every

prospective action has strengths and weaknesses;

how should they be evaluated? How will they

decide? Which of the things that could happen

would happen? How can we ensure decision will

be carried out? These questions are crucial for

understanding complex human emotion (Satpathy;

2015).

The consequences of phylogenetic constraints

cannot be overemphasized. Contrary to persisting

opinions, brain evolution is not characterised by

addition of new structures or modules. The idea

that brain proceeds by superimposing ‘mammalian’ cerebral cortex has long ago been rejected by

studies of comparative neuroanatomy. Evolution

cannot simply invent a new structure, complete

with full developmental schedule and connect it up

to existing system. Instead, brain evolution

involves elaboration and specialization of existing

structures and elongation of ancestral circuits

whose neuroanatomical topology is remarkably

conserved. Acknowledging and addressing

phylogenetic constraints of any evolved system

may appear as a burden for theorists. Managers are

of precisely the opposite opinion. What theoretical

neuroscience needs most are more constraints, not

fewer, for they provide guidelines for effectively

choosing which conceptual path is most promising.

Even the most elegant and optimal model is a dead-

end if it is incompatible with constraints of

phylogenetic descent. By contrast, outline of

evolutionarily grounded model is a promising topic

for further scholarship. Furthermore, Managers

believe that an evolutionary perception also helps

choose what kinds of questions to ask, and which

to ask first.

Managerial Emotion

Mental reactions to what Managers actually get

and what Managers can sensibly expect to get may

frequently involve compromises with harsh reality.

Managers can differ greatly in their abilities to

convert the same resources into valuable

functioning (‘beings’ and ‘doings’). Evaluation that

focuses only on means, without considering what

particular manager can do with them, is

insufficient. Manager can internalise harshness of

circumstances so that they do not desire what they

can never expect to achieve. Calculation that

concentrates on subjective mental metrics is

inadequate without considering whether that

matches with what an unbiased witness would

perceive as unprejudiced conditions. Whether or

not manager take up the options they have, the fact

that they do have valuable options is significant.

Evaluation must be sensitive to both actual

achievements (‘functioning’s’) and effective

freedom (‘capability’). Reality is complicated and

evaluation should reflect that complexity rather

than take a short cut by excluding all sorts of

information from consideration in

advance. Consequently, evaluation of how well

manager are doing must seek to be as open-minded

as possible (Sen; 2004).

Propensity to experience apprehension is

relatively a consistent managerial trait. This

suggests that it has stable underlying neural

substrates and may be an important factor driving

emotional variation in decision-. In managers

suffering from apprehension disorders, heightened

apprehension interferes with the ability to

adaptively function in everyday tasks. Although it

is clear for managers that their pathological

apprehension influences their daily decisions, a




Vol-3, Issue-10, 2017



more nuanced understanding of the relationship

between apprehension and decision is needed.

While apprehension has long been known to

involve emotional aberrations in face of potential

negative outcomes, burgeoning field of

neurodecisions provides structured approach to

studying computational and neurobiological

mechanisms underlying this dysfunction.

Neurodecision studies typically define

mathematically the optimal or normative emotional

in a decision- task, allowing precise quantification

of managerial deviations from these norms. These

parameters can then be used to probe the neural

correlates of decision biases. Characterizing

specific decision biases occurring with

apprehension may enhance our understanding of

consequences of managerial variability in non-

clinical trait apprehension, as well as nature of

dysfunction underlying apprehension disorders

(Hartley and Phelps; 2013).

Across a range of neurodecision decision- tasks,

particularly those involving uncertainty or potential

loss, a circuitry involving the amygdala, insular

cortex and prefrontal cortex has been observed.

The amygdala is a key component of the brain

systems mediating fear and apprehension and their

cognitive effects. At the same time, the prefrontal

cortex is critically involved in the control of fear

and decreased prefrontal engagement is observed

in trait and clinical apprehension. We propose that

this shared architecture may yield predictable

effects of apprehension on decision-. Specifically,

apprehension increases the attention to negative

choice options, the likelihood that ambiguous

options will be interpreted negatively, and the

propensity to avoid potential negative outcomes,

even at the cost of missing potential gains.

Importantly, the neural systems enabling one to

alter these maladaptive decision processes may be

more difficult to engage with high apprehension

(Hartley and Phelps; 2013).

Emotional economics often describes decision

tendencies, such as risk or loss aversion, as if they

were immutable managerial characteristics. In this

inter – disciplinary review, we suggest that such

tendencies are influenced by trait apprehension,

which is thought to be relatively stable. However,

recent research has focused on how managers can

alter fear or apprehension responses in specific

circumstances. These studies demonstrate that fear

can be altered through a variety of techniques

including the formation of new extinction

memories, the use of intentional cognitive

regulation strategies, performing actions that limit

exposure to fear-related stimuli, or through

pharmacological or emotional disruption of learned

fear associations. This research on the control of

fear suggests that modulation of anticipatory

responses to potential aversive outcomes in a

decision- context might similarly enable flexibility

in managerial choice tendencies. In this inner -

disciplinary review, we have discussed the

influence of apprehension upon choice as though

the response of anxious manager to negative

decision options is relatively consistent. However,

this is almost certainly an overly simplistic

perspective. Future neurodecision research

examining how the regulation of apprehension

influences our decisions will no doubt reveal a

relationship between apprehension and choice that

is both more malleable and more complex than our

present understanding (Hartley and Phelps; 2013).

Real-business world problems are often

complicated. Psychological scientists have been

interested in how people make decisions for several

decades, but philosophers and economists have

been studying decision for centuries. Highlighting

areas of overlap between cognitive modeling and

multi-attribute judgment will stimulate further

cross-fertilization and inspire research examining

the boundary conditions of various models.

Deciphering brain - situation transactions requires

mechanistic understandings of neurobiological

processes that implement value dependent

organisational decision-. There is a crucial

difference between ‘thinking about thinking’ and

actually enhancing brain and mental processes by

developing latent potential of each individual.

Theoretical accounts posit that human brain

accomplishes this through a series of neural

computations, in which expected future reward of

different organisational decision options are

compared with one another and then option with

highest expected value is selected. If human brain

is compared with computer, one aspect is crucially

missing. Humans define goals for information

processing in computers, whereas goals for

biological brains are determined by need for

survival in uncertain and competitive situations.

How to handle brains behind businesses in age of

dramatic change and growing uncertainty? What

then are the coherent brain dynamics underlying

prediction, control and organisational decision-?

(Satpathy; 2016).

Brain Imaging Applications

Last two decades have witnessed emergence and

rapid development in cognitive neuroscience. This

field combines two traditionally distinct

disciplines, cognitive psychology and neurology, to

address neural underpinnings of human cognition.

The impact of cognitive neuroscience has been felt

beyond disciplines as diverse as anthropology,

philosophy, linguistics, sociology, and economics.




Vol-3, Issue-10, 2017



Many brain-imaging tools are available, including

positron emission tomography (PET), near infrared

spectroscopy (NIRS), magneto encephalogram

(MEG), electroencephalography (EEG), and

functional magnetic resonance imaging (fMRI).

EEG and fMRI are widely used tools.

Electroencephalography (EEG): Discovered

about a century ago, EEG measures electrical

activities of brain from electrodes placed on scalp.

Usually, EEG is collected from tens to hundreds of

electrodes positioned on different locations on

scalp. Most EEG systems used in cognitive

neuroscience research employ 64 to 256 electrodes.

Scalp EEG represents the aggregates of post-

synaptic currents of millions of neurons. EEG

signals usually reflect two types of brain

activities, spontaneous and event-related activities.

Spontaneous EEG reflects neuronal responses that

occur unprovoked, i.e., in absence of any

identifiable stimulus, with or without behavioural

manifestations. spontaneous EEG hold key to

unraveling patterns of functional connectivity and

synchronicity among brain regions underlying

states of consciousness ( default network) (Mantini,

Perrucci, Del Gratta, Romani, and Corbetta; 2007).

By combining with resting-state fMRI, generators

of spontaneous EEG activities can be localized

(Salek-Haddadi, Friston, Lemieux, and Fish; 2003).

Event-related potentials (ERPs) are associated

with specific stimuli or thoughts. The amplitudes

of ERPs tend to be low, ranging from less than a

microvolt to several microvolts, compared to tens

of microvolts for spontaneous EEG. To detect

these low-amplitude potentials against ongoing

background EEG, EKG (cardiac artifacts), EMG

(muscle activation artifacts) and other biological

signals and ambient noise, repeated stimulus

presentations and signal processing techniques

(averaging) are required in ERP studies. Major

techniques to detect event-related potentials can be

divided into two categories, time-locked

averaging techniques and spectral

analysis techniques. Time-locked averaging

techniques are usually used to detect evoked

activities, which are time-locked to presentation of

stimuli. Because most noise occurs randomly,

time-locked averaging techniques can greatly

reduce the noise while preserving the event-related

signals in the EEG. Time-locked averaging can be

either stimulus-locked or response-locked. In

addition to time-locked responses, there may be

signals in EEG that are related to stimulus

processing without well-defined temporal relation

to event. These responses are called induced

activity. An example of induced activity is

oscillatory activity (gamma oscillations), which

might have different phase in each single

measurement and therefore would cancel one

another in time-locked averaging.

However, induced activity can be detected using

spectral analysis, in which EEG recordings are

decomposed into a number of frequency

(sinusoidal) components, such as delta (0-3Hz),

theta (4-7Hz), alpha (8-12Hz), beta (12-30 Hz),

gamma (30-50 Hz), and high gamma (80-150 Hz).

Among spectral analysis techniques, Fourier

transform (FT) is traditionally the preferred method

because it is time-shift invariant in both time and

frequency domains. However, in FT, any time-

varying spectral content of the signal is ignored

because it assumes that the signal is stationary over

time. This assumption is in contradiction to fact

that EEG signals are non-stationary. To overcome

this limitation, Wavelet transform (WT) is now

considered more suitable than Fourier transform in

analysing induced activities (Akin, 2002).

Functional Magnetic Resonance Imaging

(fMRI): fMRI a recently developed forms of

neuroimaging technique. Since early 1990s, fMRI

has become dominant method in cognitive

neuroscience because of its low invasiveness, lack

of radiation exposure, and relatively wide

availability. In brain, neural activities lead to

metabolic activities such as increased blood flow

and oxygen supply to local vasculature. Several

techniques can be used to detect changes of

metabolic activities following neural activities,

including contrast fMRI, blood-oxygen-level

dependent (BOLD) fMRI, and perfusion fMRI.

Contrast fMRI requires injection of contrast agents,

such as iron oxide coated with sugar or starch. The

signals associated with contrast agents are

proportional to cerebral blood volume (CBV).

Although this method can provide relatively strong

signals, researchers are reluctant to use this semi-

invasive method with healthy volunteers. Perfusion

fMRI uses ‘arterial spin labeling’ (ASL) to

magnetically label hydrogen nuclei in the arterial

blood and then images their distribution in brain.

This method is sensitive to cerebral blood flow

(CBF), considered good correlate of neuronal

activity. This method does not require any contrast

agents. Compared to BOLD responses , signal in

perfusion fMRI is stable and noise is much whiter.

However, relatively weak signal and length of

image acquisition time have limited use of

perfusion fMRI in cognitive neuroscience.

Currently, widely used fMRI method is BOLD

imaging, which detects difference in magnetic

susceptibility between oxygenated hemoglobin and

deoxygenated hemoglobin. Hemoglobin is

diamagnetic when oxygenated but paramagnetic




Vol-3, Issue-10, 2017



when deoxygenated. The magnetic property of

blood therefore depends on its oxygenation level.

Although neuronal activities consume some

oxygen, the increase in blood flow following

neuronal activities supplies more oxygen than the

neuronal consumption, resulting in an increase in

oxygenated hemoglobin and therefore increased

BOLD response. Although BOLD fMRI is an

indirect measure of neuronal activities, there is

strong empirical evidence that the BOLD signals

are highly correlated with neuronal activities

(Logothetis et al., 2001). Because BOLD signals

are usually stronger and require less time to acquire

than perfusion signals, BOLD fMRI is popular than

perfusion fMRI.

Comparison of EEG and fMRI: EEG and

fMRI have their respective strengths and

weaknesses. Ideally, experiments employing these

methods must be carefully designed and conducted

to maximize strengths and minimize weaknesses.

Salient feature of EEG is its high temporal

resolution at a level of milliseconds. It is a direct

measure of neuronal response. Nevertheless, EEG

has several limitations. First, EEG is sensitive to

post-synaptic potentials generated in superficial

layers of the cortex. It is not sensitive to neuronal

responses from structures that are deep in brain,

such as the striatum or hippocampus. In addition,

currents that are tangential to the skull make little

contribution to the EEG signal. Second, the spatial

resolution of EEG is very low. Third, it is almost

impossible to reconstruct a unique intracranial

current source distribution for a given EEG signal,

although substantial recent progress has been made

in this area.

In contrast, fMRI has high spatial resolution and

a comprehensive coverage of whole brain.

Conventional BOLD fMRI has a typical spatial

resolution of 3-6 millimeters; high-resolution fMRI

can reach about 1 millimeter spatial resolution at

expense of whole-brain coverage. fMRI is sensitive

to BOLD signals from both the cortical surface and

deep brain structures. The only limiting factor for

coverage is susceptibility artifacts in ventromedial

prefrontal cortex and temporal poles. This problem

has been partly resolved by some newly developed

scanning sequences, or by using contrast fMRI and

perfusion MRI. The major limitation of fMRI is its

temporal resolution because BOLD response is

very slow. Moreover, BOLD signal is an indirect

measure of neuronal activity, and is susceptible to

influence by many physiological activities of body

that are un-related to neuronal processes.

PART - II: NEURO - DECISION

MODELING

(Pre - Frontal Cortex)

Decisions are not so simple. Decision involves

knowing future expected rewards of possible state.

Many real-life decision problems incorporate

higher-order structure, involving interdependencies

between different stimuli, actions and subsequent

rewards. It is not known whether brain regions

implicated in decision making, such as

ventromedial prefrontal cortex, employ stored

model of task structure to guide choice (model -

based decision) or merely learn action or state

values without assuming higher - order structure.

Managers, in general, are not particularly good at

making decisions. One way to examine this is by

looking at brain activity making decisions. Two

regions near front of brain are known to be

involved in manager decision. However,

researchers disagree as to what these two regions

are actually doing when we make decisions. Brain

is a simplifier. Simplicity is not always a virtue,

however, and complexity should not always be

avoided. When faced with complex problem, it

does not dispassionately weigh all available

information before selecting course of action.

Instead, it takes in a situation, simplifies it and

applies behavioural rules that have worked in past.

Brain’s ability to make quick decision based on

limited information is remarkably efficient. Brains

have variety of tools for decision, some rational

and others emotional and good decisions come

from applying right tool in right circumstances.

Researchers encounter dilemmas that brain is

less equipped to confront, from mundane situations

to life -changing questions. Increasingly, cognitive

neuroscientists have been rising to the challenge,

complementing group-based analysis with analysis

of individual difference variables. Clear sign that

neuroscience and behavioural psychology are

converging is the growing number of neuro-

imaging studies aimed at investigating extent to

which activity of circumscribed brain regions

directly predict behaviour. Question is which

algorithms by brain and what brain structures

execute different algorithmic components towards

a decision? How brain learns structure, with

internal abstract states and associated expected

reward values, on which it later infers state

activities to guide decision.




Vol-3, Issue-10, 2017



GEOMETRIC - ALGORITHMS OF BRAIN

BRODMANN

CORTICAL NUMBERS ARCHITECTURE

Brodmann area 10 (BA10, frontopolar prefrontal

cortex, rostrolateral prefrontal cortex, or anterior

prefrontal cortex) is the anterior-most portion of

the prefrontal cortex in the human brain. BA10 is

the largest cytoarchitectonic area in the human

brain. It has been described, as “one of the least

well understood regions of the human brain”

.BA10 is a subdivision of

the cytoarchitecturally defined frontal region of

cerebral cortex. It occupies the most rostral

portions of the superior frontal gyrus and

the middle frontal gyrus. In humans, on the medial

aspect of the hemisphere it is bounded ventrally by

the superior rostral sulcus. It does not extend as far

as the cingulate sulcus. Cytoarchitecturally it is

bounded dorsally by the granular frontal area 9,

caudally by the middle frontal area 46, and

ventrally by the orbital area 47 and by the rostral




Vol-3, Issue-10, 2017



area 12 or, in an early version of Brodmann's

cortical map (Brodmann-1909), the

prefrontal Brodmann area. Although this region is

extensive in humans, its function is poorly

understood. Processing of 'cognitive branching' is

the core function of the frontopolar cortex.

Cognitive branching enables a previously running

task to be maintained in a pending state for

subsequent retrieval and execution upon

completion of the on-going one. Many of our

complex behaviours and mental activities require

simultaneous engagement of multiple tasks, and

they suggest the anterior prefrontal cortex may

perform a domain-general function in these

scheduling operations.

Decision-making plays an important role in

transformation of incoming sensory information to

purposeful actions. Many decisions have important

biological consequences, while others may have

limited impact. Neural mechanisms of decision-

making currently constitute an important subject

under intense investigation in field of cognitive and

behavioural neuroscience. Among investigations,

those involving sensory discrimination tasks using

visual motion provide information about nature of

neural circuitry required to perform perceptual

decision. Prefrontal cortex has been shown to

participate in decision-making in free - choice

conditions. Although several attempts have been

made to understand neural mechanisms of

decision-making, further investigations are

required to understand these mechanisms. Future

studies should evaluate effects of emotions on

decision-making and attempt to integrate

neurophysiological, psychological and

computational approaches to decision-making

(Funahashi; 2008).

VENTRAL AND LATERAL VIEWS OF FRONTAL LOBES

In keeping with dominance of neurological

method's, focus is on particular concerns when

conducting neuroimaging work, and especially

functional magnetic resonance neuroimaging

(fMRI) based research (Hedgcock and Rao; 2009).

There are studies that use alternative research

methods and they possess their own unique

caveats. Investigation into neural and

computational bases of decision-making has

proceeded in two parallel but distinct streams.

Perceptual decision-making (PDM) is concerned

with how observers detect, discriminate, and

categorize noisy sensory information. Decision-

making explores how options are selected based on

reinforcement history. Traditionally, perceptual

decision-making employed different paradigms,

proposed different mechanistic models, explored

different brain regions, disagreed about whether

decisions approach optimality. Nevertheless, there

is common framework for understanding decisions

made in both tasks, under which agent has to

combine sensory information (what is the stimulus)

with value information (what is it worth). Although

parietal cortex is implicated in integration of



http://onlinelibrary.wiley.com/doi/10.1111/ijmr.12071/full#ijmr12071-bib-0023


Vol-3, Issue-10, 2017



sensory evidence, there is evidence for its role in

encoding expected value of decision (Summerfield;

2012).

Frontal lobe provides valuable insights into

neuropsychological determinants of functions of

prefrontal cortex (PFC). Prefrontal cortex is

classified as multimodal association cortex as

processed information from sensory modalities is

integrated in a precise fashion to form physiologic

constructs of memory, perception and diverse

cognitive processes. Manager neuropsychological

studies support notion of different functional

operations within prefrontal

cortex. In brain anatomy, prefrontal cortex is

cerebral cortex that covers front part of the frontal

lobe. This region has been concerned in planning

complex cognitive behaviour and decision-

making. Basic activity of this brain region is

considered orchestration of thoughts and actions in

accordance with internal goals. The

typical function is managerial function considered

product of coordinated operation of various

processes. The mechanism or system responsible

for coordinated operation is managerial control.

There are three possible ways to define

prefrontal cortex:

As granular frontal cortex,

As projection zone of medial dorsal

nucleus of thalamus, and

As part of frontal cortex, whose electrical

stimulation does not evoke movements?

3 - D IMAGE: PREFRONTAL CORTEX

The lateral prefrontal cortex is critically involved

in broad aspects of managerial behavioural control.

Early studies emphasized its role in short-term

retention of information retrieved from cortical

association areas and in inhibition of pre - potent

responses. Recent studies of managers have

revealed role of this area in general aspects of

behavioural planning. Novel findings of neuronal

activity have specified how neurons in this area

select intended action. Furthermore, involvement

of lateral prefrontal cortex in implementation of

behavioural rules and setting multiple behavioural

goals have begun to reveal neuronal mechanisms

for strategic behavioural planning at conceptual

level.




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BEHAVIOUR OF FRONTAL CORTEX DURING DECISION MAKING

Specifically, medial frontal region (anterior

cingulate area) appears to be involved in bimanual

coordination, attention to demanding cognitive

tasks, modulation of body arousal, spatial memory,

self-initiated movement and conflict resolution

(medial prefrontal and medial orbital regions).

Anterior cingulate cortex is involved in perception

of pain and possibly in mediating emotional

response behind it. Ventromedial region plays role

in decision making and retrieval of information

from metacognitive processes.

Managerial Function

There is growing biological interest within

management and managerial studies. Hannah et al.




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(2013) term this a ‘cognitive revolution’, which has

brought greater attention to bear on understanding

how mental processes of managers may explain

their behaviours and effectiveness. They go on to

argue that, to date, ‘this revolution has been limited

largely to conjecture of what occurs inside ‘black

box’ of managers’ (Hannah et al; 2013) and

suggest similar revolution in methodology. The

managerial cognitive neuroscience approach … is not concerned with only application of

neuroscience methodologies to managerial research

questions. Instead, ‘managerial cognitive

neuroscience’ designates genuinely

multidisciplinary approach, in terms of both theory

and method … managerial cognitive neuroscience is not simply study of brain systems themselves but

may incorporate the use of prior knowledge of

brain systems to develop new hypotheses about

managerially relevant issues. Thus, it both provides

inclusive scope and defines key cross-disciplinary

nature of managerial cognitive neuroscience, in

that research in this area may contribute both to

managerial and cognitive neuroscientific

knowledge. (Senior et al.; 2011). For Hannah et al.

(2013), this represents multidisciplinary and multi-

method approach to conceptualization of

management and managers. Like many similar

reports, Hannah et al. (2013) focus on

neuroimaging research. However, there is a far

wider diversity of methods and potential

contributions available to researchers in the area

(Lee et al.; 2012 and Senior et al.; 2011) and

research reviewed reveals this.

Economic choice is the behaviour observed

when individuals select one among many available

options. There is no intrinsically 'correct' answer:

economic choice depends on subjective

preferences. This behaviour is traditionally the

object of economic analysis and is of primary

interest in psychology. However, the underlying

mental processes and neuronal mechanisms are not

well understood. As regards, model-based decision

making in manager brain, many real-life decision

makes incorporate higher-order structure involving

interdependencies between different stimuli,

actions. It is not known whether brain regions

implicated in decision making, such as

ventromedial prefrontal cortex, employ stored

model of task structure to guide choice or learn

action or state values without assuming higher-

order structure. Theories of manager have a

cornerstone in concept of 'value'. Nevertheless,

where and how values are represented in brain is

unclear. During economic choice, neurons in

orbitofrontal cortex (OFC) encode value of offered

and chosen goods. Notably, OFC neurons encode

value independently of visuo - spatial factors and

motor responses.

A manager has to make decisions under different

conditions and situations. While taking a decision

how a manager perceives things, how does he react

and how does he try to resolve, all this is human

behaviour. A manager must have clear

understanding of existing environment. ‘Economic

man’ model is applicable to routine and repetitive

decisions that are programmed. The predetermined

rules and procedures are applied for taking routine

decisions. Economic man is always in search of

optional solution or best way of doing things for

maximising benefits. Manager is governed by

economic considerations and uses mathematical

and statistical tools for solving problems.

Manager’s rationality is bounded by the fact that

manager may not have access to all type of

required information or information may not be

available, rational decision - making requires

search and analysis of various alternatives, there

may be a situation where multiple and conflicting

objectives may be involved, process of

compromise and adjustment becomes necessary for

taking decisions rather than rationality, decisions

are made to be implemented in future, problem

requiring solution may be complex and

unstructured, it may not be defined with rationality,

in real life situation decision-making is sub -

rational, fragmented and pragmatic activity.

Prefrontal cortex is of significant importance

when top - down processing is desired. Top - down

processing by definition is when behaviour is

guided by internal states or intentions. According

to the two, ‘PFC is critical in situations when

mappings between sensory inputs, thoughts and

actions either are weakly established relative to

other existing ones or are rapidly changing’. Miller

and Cohen conclude that implications of theory can

explain how much of a role PFC has in guiding

control of cognitive actions. Depending on their

target of influence, representations in PFC can

function variously as attentional templates, rules,

or goals by providing top - down bias signals to

other parts of the brain that guide the flow of

activity along the pathways needed to perform a

task’. Ventromedial prefrontal cortex (VMF) is

thought to be important in manager decision

making, but studies to date have focused on

decision making under conditions of uncertainty,

including risky or ambiguous decisions. Other lines

of evidence suggest that this area of the brain

represents quite basic information about the

relative ‘economic’ value of options, predicting a

role for this region in value-based decision making

even in the absence of uncertainty.











Vol-3, Issue-10, 2017



Representative Images of

MANAGER BRAIN UNDER CERTAINTY

Perceptual decision making typically entails

processing of sensory signals, formation of

decision, planning and execution of motor

response. Recent studies in managers have revealed

possible neural mechanisms for perceptual decision

making, much less is known about how decision is

subsequently transformed into motor action and

whether or not decision is represented at abstract

level, i.e., independently of specific motor

response. To address this issue, research used

functional MRI to monitor changes in brain activity

while manager subjects discriminated direction of

motion in random-dot visual stimuli that varied in

coherence and responded with either button presses

or saccadic eye movements. They hypothesised

that areas representing decision variables should

respond more to high than to low - coherence

stimuli independent of motor system used to

express decision. Four areas are reported that

fulfilled this condition: left posterior dorsolateral

prefrontal cortex (DLPFC), left posterior cingulate

cortex, left inferior parietal lobule and left fusiform

/ parahippocampal gyrus. Researchers previously

found that, when subjects made categorical

decisions about degraded face and house stimuli,

left posterior DLPFC showed a greater response to

high- relative to low-coherence stimuli.

Furthermore, left posterior DLPFC appears to

perform a comparison of signals from sensory

processing areas during perceptual decision. These

data suggest that involvement of left posterior

DLPFC in perceptual decision - making transcends

task and response specificity, thereby enabling

flexible link among sensory evidence, decision and

action.




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PREFRONTAL CORTEX IN PERCEPTUAL DECISION MAKING

Prefrontal cortex (DLPFC) contains a region that

integrates sensory evidence supporting perceptual

decisions. Perceptual decisions are made when

sensory evidence accumulated over time reaches

decision threshold. Because decisions are guided

by prior information, one important factor that is

likely to shape how a decision is adaptively tuned

to its context is predictability of forthcoming

events. However, little is known about mechanisms

underlying. Findings from single-cell recording

studies suggest that comparison of outputs of

different pools of selectively tuned lower-level

sensory neurons may be a general mechanism by

which higher-level brain regions compute

perceptual decisions. Categorical choices are

preceded by the accumulation of sensory evidence

in favour of one action or another. Current models

describe evidence accumulation as a continuous

process occurring at a constant rate, but this view is

inconsistent with accounts of a psychological

refractory period during sequential information

processing.

Decision Power House

The ventromedial prefrontal cortex is a part of

prefrontal cortex in brain. Ventral medial prefrontal

is located in frontal lobe at bottom of the cerebral

hemispheres and is implicated in the processing of

risk and fear. It plays role in inhibition of

emotional responses and in process of decision

making. It is involved in cognitive evaluation

of morality. Ventromedial prefrontal cortex is

connected to and receives input from ventral

tegmental area, amygdala, temporal lobe, olfactory

system and dorsomedial thalamus. It, in turn, sends

signals to different brain regions. This includes

temporal lobe, amygdala, lateral hypothalamus,

hippocampal formation, cingulate cortex and other

regions of prefrontal cortex. Neurodecision models

assume that decisions are based on activity of offer

value cells in the orbitofrontal cortex (OFC).

Testing this assertion has proven difficult. In

principle, decision made on a given trial should

correlate with stochastic fluctuations of these cells.

However, this correlation, measured as a choice

probability (CP), is small. Importantly, neurons

reflects not only its individual contribution to

decision, but intensity and structure of correlated

variability across neuronal population.



http://reliawire.com/vta/

http://reliawire.com/vta/

http://reliawire.com/amygdala/


Vol-3, Issue-10, 2017




VENTROMEDIAL PREFRONTAL CORTEX

Functional differences between orbitofrontal and

ventromedial areas of pre-frontal cortex have not

yet been clearly established, although areas of

ventromedial cortex superior to orbitofrontal

cortex are much less associated with functions and

with pure emotion regulation. Neural networks in

ventromedial prefrontal cortex are rapidly

developing supporting emotion regulation through

amygdala, being associated with decrease

in cortisol levels. There are reports of early-onset

vmPFC damage during childhood, but these

individuals tend to have severe antisocial

behaviour and impaired moral judgment.




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Prefrontal cortex (PFC) subserves decision-

making and managerial control. Prefrontal cortex

comprises two arbitration systems: (1) peripheral

system comprising premotor/caudal PFC regions

and orbitofrontal regions involved in selection of

actions based on perceptual cues and reward

values, respectively and embedded in behavioural

sets associated with external contingencies inferred

as being stable; (2) core system comprising

ventromedial, dorsomedial, lateral and polar PFC

regions involved in superordinate probabilistic

reasoning for arbitrating online between

exploiting/adjusting previously learned behavioural

sets and exploring/creating new ones for efficient

adaptive behaviour in variable and open-ended

environments. Prefrontal cortex is described as sub

serving decision-making and managerial control.

Decision-making research focuses on PFC function

in action selection according to perceptual cues and

reward values. Managerial control research focuses

on PFC function in switching between behavioural

rules or sets that guide action . These two lines of

inquiry have been carried out independently.


PREFRONTAL CORTEX AND MANAGERIAL REPRESENTATIONS

REPRESENTATIVE IMAGE OF DORSOMEDIAL PREFRONTAL CORTEX

Frontal cortex comprises a third of manager

brain; it is structure that enables to engage in

higher cognitive. What processes serve as building

blocks of higher cognitive functions and how are

these implemented in frontal cortex? Neural basis

of decision making has been an elusive concept

largely due to sub - processes associated with it.

Recent efforts involving neuroimaging and

neuropsychological studies indicate that prefrontal

cortex plays central role in several of sub

processes. Frontal lobes involved in tasks ranging

from making binary choices to making multi-

attribute decisions require explicit deliberation and

integration of diverse sources of information. In

categorising different aspects of decision making,

division of prefrontal cortex into three primary

regions is proposed. Orbitofrontal and

ventromedial areas are relevant to deciding based

on values and contribute affective information

regarding decision attributes and options.




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Dorsolateral prefrontal cortex is critical in making

decisions that call for consideration of multiple

sources of information and may recruit separable

areas when making well defined vs. poorly defined

decisions. Anterior and ventral cingulate cortex

appears especially relevant in sorting among

conflicting options, as well as signalling outcome-

relevant information. This is broadly relevant to

cognitive neuroscience as a discipline, as it

generally comprises several aspects of cognition

and may involve numerous brain regions

depending on situation.

Neuroimaging studies of manager’s show that

storage and managerial processes are major

functions of frontal cortex. Distinction between

short - term storage and managerial processes

appears to be major organisational principle of

PFC. With regard to storage, PFC areas

consistently activated show modality specificity

(verbal vs. spatial vs. object information) and

generally they appear to mediate rehearsal

processes, at least for verbal and spatial

information. Neuroimaging analyses of managerial

processes are quite recent, and they have yet to

lead to clear dissociations between processes.

Perhaps priority is to turn attention to managerial

processes and implementation in frontal cortex.

Although there is lack of consensus about

taxonomy of managerial processes, there is

agreement that they include (i) focusing attention

on relevant information and processes and

inhibiting irrelevant ones (‘attention and

inhibition’) (ii) scheduling processes in complex

tasks, which requires switching of focused

attention between tasks (‘task management’) (iii)

planning sequence of subtasks to accomplish goal

(‘planning’) (iv) updating and checking contents of

working memory to determine next step in

sequential task (‘monitoring’) and (v) coding

representations in working memory for time and

place of appearance(‘coding’).

REPRESENTATIVE IMAGE OF

COGNITIVE MODULATION IN MEDIAL ORBITOFRONTAL CORTEX




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PART - III: NEURO - DECISION MODELING

(Somatic Marker Mechanism)

Until the 20th century, the study of emotion and

cognition was largely a philosophical matter.

Although modern perspectives on the mind and its

disorders remain heavily influenced by the

introspective measures that defined this earlier era

of scholarship, the last several decades have

witnessed the emergence of powerful new tools for

assaying the brain and a remarkable acceleration of

research to elucidate the interplay of emotion and

cognition (Pessoa; 2013,Braver et al.; 2014

and Dolcos and Denkova, 2014). At the core of the

modern study of neuroscience is the idea that all

behaviour is a reflection of brain function. Solid

understanding of decision-making can, and

should, be applied to create meaningful

change. What role(s) do emotions have in decision

preference? Individuals’ decisions depend on their

memories and cognition but on their current

emotional state. Emotions can play a necessary

functional role in decision-making, but in doing

this, emotions can alter the stability of the

process. Important decisions made are second level

decisions that evaluate the values or expected

values of the available options. Neuroimaging

research shows that the orbitofrontal cortex and the

ventromedial prefrontal cortex in the brain

(O/VMPFC) are related to these kinds of decision-

making. They connect to our sensory system in two

ways. One is a direct connection and the other is an

indirect pathway where it goes through the

amygdala. The amygdala in the brain performs as a

major role in processing emotions, which suggests

that emotions might be involved when we make

level two decisions. Can inhibiting level two

decision-making leads to more rational decisions?

Although we are far from a complete

understanding of the inner workings of the brain,

neuroscience research into decision-making has

both complemented and updated traditional views

of decision-making derived from such fields as

psychology and economics. Emotions are

ordinarily conceived as irrational occurrences that

cloud judgment and distort reasoning. Emotions

can shape decision processes by altering valuation

signals, risk perception, and strategic orientation.

Although multiple theories posit a role for affective

processes in mediating the influence of frames on

decision making, empirical studies have yet to

demonstrate that manipulated affect modulates

framing phenomena. Mental process of decision-

making is (or should be) rational: a formal process

based on optimizing utility. What role(s) do

emotions have in decision preference? Individuals’ decisions depend on their memories and cognition

but on their current emotional state. Emotions can

play a necessary functional role in decision-

making. In doing this, emotions can alter the

stability of the process. Cognitive neuroscience of

emotions is a rapidly growing field. It focuses on

the neural basis of emotional and social processes

and strongly contributes to the better understanding

of the biological basis of emotional processing. It

integrates the results of neural and behavioural

levels of analysis in healthy and clinical

populations as well. The main topics and questions

in cognitive neuroscience of emotions are the role

of emotions in information processing, their neural

basis for both cortical and sub-cortical levels, the

perception of arousing and neutral stimuli,

emotions and memory, the role of emotion in

decision making, detecting emotional versus

neutral faces, and individual differences in

emotionality and their biological background.

Brain imaging techniques (e.g., functional

magnetic resonance imaging–fMRI) are used both

for examining functional connections between

emotion and perception, attention, memory and

decision making, and for localizing specific



http://journal.frontiersin.org/article/10.3389/fnhum.2015.00058/full#B167




Vol-3, Issue-10, 2017



psychological functions to specific brain areas. In

this paper we discuss not only current research

trends and methods but some important brain areas

responsible for emotions (e.g., amygdala, anterior

cingular cortex, prefrontal cortex) as well (Deak;

2011).

Somatic markers inform the brain structure that

represents the state of the body, especially the

right-hemisphere’s insula. This brain processing

comprises the feeling that precedes, and informs,

decision-making, which also involves frontal-lobe

processing of cognitions and emotions (largely of

limbic origin). If an individual playing the

ultimatum game is presented an unfair offer, at

least one somatic marker (heart-rate deceleration)

is apt to rapidly inform the insular cortex, which

will pass along that and other representations of

bodily state. Clearly, the perception that one has

been presented with an unfair offer triggers a

number of bodily reactions, some of which occur

quickly and can serve as somatic markers, and

some of which develop too slowly to be somatic

markers.

The search for somatic markers is important not

only for neuroeconomics, but for the social

sciences as well. Various somatic theories of

human social behavior have emerged, which are

based loosely, and largely uncritically, on a

synthesis of (i) the SMH, (ii) Bowlby’s (1988)

attachment theory, and (iii) the self-psychology

first articulated by Kohut (1977) and elaborated by

Schore (2003). This theorizing has spawned, or

developed together with, applications in embodied

mind theory (Lakoff and Johnson, 1999), the

evolution of human morality (Narvaez, 2014),

performativity linguistics (Robinson, 2008), speech

act theory (Felman, 2003), actor training

development (Sellers-Young,1998), and notions of

bodily-kinesthetic intelligence (Gardner, 1983).

There is a certain wildness to such theorizing,

much of which is based on shaky neuroscientific

grounds, but such forays into “the wild blue

yonder” (TenHouten, 1992) have endeavored to

explore the interface between body, brain, mind,

and society. We can only hope that clarification of

the SMH will better ground such extrapolation of

the SMH to the social world.

Emotion is a subjective lens on

an objective world; decision-making should discard

emotion whenever possible. This is particularly

important for managers, who make significant

decisions on a daily basis. Understanding the role

of emotion in decision-making that is influence by

current emotional state on a moment-to-moment

basis, strongly effecting stability of decision has

important clinical implications. The first idea is

that emotions can influence decisions through

altering temporarily altering perceptions of

benefits, costs, intertemporal tradeoffs and

risks. There is a strong link back to the topic of

intertemporal decision as visceral effects can be

seen as the underlying cause for why we place such

a heavy weight on the immediate present. The

second idea is that emotions play an important role

in how people behave in economic interactions.

The third idea, related to the second, is that

emotions may themselves be influenced by rational

considerations. The fourth main idea is that we are

bad at predicting how our emotions will respond to

changes in events, an area of study titled ‘affective

forecasting’.

Emotional decision-making can improve

decisions when managed as part of decision

process. current environment of information

overload will likely lead to a greater amount of

emotional decision making. Human brain research

has suggested that, as our minds have more to

process, the likelihood to decide emotionally

increases. It makes sense that less time for

reflection will lead to more decisions that seem

irrational. A very emotional decision is very fast in

comparison to a rational decision. This is reactive

(and largely subconscious) and can be useful when

faced with immediate danger, or in decisions of

minimal significance. Some studies suggest an

emotional insistence to respect the life of another

human being. Emotions may provide a way for

coding and compacting experience, enabling fast

response selection. This may point to why expert's

"gut" level decisions have high accuracy rates.

Emotions are possible signals from the

subconscious that provide information about what

we really choose. Decisions that start with logic

may need emotions to enable the final selection,

particularly when confronted with near equal

options. Individuals care about the emotional

features of decision options. Emotions often drive

us in directions conflicting with self-interest.




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Different sectors of the human prefrontal cortex

are involved in distinctive cognitive and

behavioural operations. The somatic marker

hypothesis provides a systems-level

neuroanatomical and cognitive framework for

decision making and the influence on it by

emotion. The key idea of this hypothesis is that

decision making is a process that is influenced by

marker signals that arise in bioregulatory

processes, including those that express themselves

in emotions and feelings. This influence can occur

at multiple levels of operation, some of which

occur consciously and some of which occur non-

consciously. Here we review studies that confirm

various predictions from the hypothesis. The

orbitofrontal cortex represents one critical structure

in a neural system sub serving decision making.

Decision making is not mediated by the

orbitofrontal cortex alone, but arises from large-

scale systems that include other cortical and

subcortical components. Such structures include

the amygdala, the somatosensory/insular cortices

and the peripheral nervous system.

When individuals make decisions, they must

assess the incentive value of the choices available

to them, using cognitive and emotional processes.

When the individuals face complex and conflicting

choices, they may be unable to decide using only

cognitive processes, which may become

overloaded. Emotions, consequently, are

hypothesized to guide decision-making. The

somatic marker hypothesis proposes that a defect in

emotion and feeling plays an important role in

impaired decision making. The hypothesis

specifies a number of structures and operations

required for the normal operation of decision

making. Because emotion is most importantly

expressed through changes in the representation of

body state, though not solely, and because the

results of emotion are primarily represented in the

brain in the form of transient changes in the

activity pattern of somatosensory structures, the

emotional changes are designated under the

umbrella term ‘somatic state’. The term ‘somatic’ thus refers to internal milieu, visceral and

musculoskeletal, of the soma rather than just to the

musculoskeletal aspects. It should be noted that

although somatic signals are based on structures

which represent the body and its states, from the

brainstem and hypothalamus to the cerebral cortex,

the ‘somatic’ signals do not need to originate in the

body in every instance and can be generated

intracerebrally (Damasio; 1994, 1995).

The somatic marker hypothesis is based on the

following main assumptions: (i) that human

reasoning and decision making depend on many

levels of neural operation, some of which are

conscious and overtly cognitive, some of which are

not; conscious, overtly cognitive operations depend

on sensory images based on the activity of early

sensory cortices; (ii) that cognitive operations,

regardless of their content, depend on support

processes such as attention, working memory and

emotion; (iii) that reasoning and decision making

depend on the availability of knowledge about

situations, actors, options for action and outcomes;

such knowledge is stored in ‘dispositional’ form

throughout higher-order cortices and some

subcortical nuclei (the term dispositional is

synonymous with implicit and non-topographically

organized) [details on dispositional knowledge and

the convergence zone framework are presented

elsewhere (Damasio, 1989a,b, 1994; Damasio and

Damasio, 1994)]; dispositional knowledge can be

made explicit in the form of (a) motor responses of

varied types and complexity (some combinations

of which are part of emotions) and (b) images. The

results of motor responses, including those that are

not generated consciously, can be represented in

images; and (iv) that knowledge can be classified

as follows: (a) innate and acquired knowledge

concerning bioregulatory processes and body states

and actions, including those which are made

explicit as emotions; (b) knowledge about entities,

facts (e.g. relations, rules), actions and action-

complexes (stories), which are usually made

explicit as images; (c) knowledge about the

linkages between (b) and (a) items, as reflected in

individual experience; and (d) knowledge resulting

from the categorizations of items in (a), (b) and (c).

The ventromedial prefrontal cortex is a

repository of dispositionally recorded linkages

between factual knowledge and bioregulatory




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states. Structures in ventromedial prefrontal cortex

provide the substrate for learning an association

between certain classes of complex situation, on

the one hand, and the type of bioregulatory state

(including emotional state) usually associated with

that class of situation in past individual experience.

The ventromedial sector holds linkages between

the facts that compose a given situation, and the

emotion previously paired with it in an individual's

contingent experience. The linkages are

‘dispositional’ in the sense that they do not hold the

representation of the facts or of the emotional state

explicitly, but hold rather the potential to reactivate

an emotion by acting on the appropriate cortical or

subcortical structures (Damasio,

1989a,b, 1994; Damasio and Damasio, 1994). The

experience we acquire regarding a complex

situation and its components—a certain

configuration of actors and actions requiring a

response; a set of response options; a set of

immediate and long-term outcomes for each

response option—is processed in sensory imagetic

and motor terms and is then recorded in

dispositional and categorized form. But because the

experience of some of those components has been

associated with emotional responses, which were

triggered from cortical and subcortical sites that are

dispositionally prepared to respond, it is proposed

that the ventromedial prefrontal cortex establishes

a linkage between the disposition for a certain

aspect of a situation (for instance, the long-term

outcome for a type of response option), and the

disposition for the type of emotion that in past

experience has been associated with the situation.

The re-activation described above can be carried

out via a ‘body loop’, in which the soma actually

changes in response to the activation and the

ensuing changes are relayed to somatosensory

cortices; or via an ‘as-if body loop’, in which the

body is bypassed and re-activation signals are

conveyed to the somatosensory structures which

then adopt the appropriate pattern. From both

evolutionary and ontogenetic perspectives, the

‘body loop’ is the original mechanism but has been

superseded by the ‘as-if body loop’ and is possibly

used less frequently than it. The results of either

the ‘body loop’ or the ‘as-if body loop’ may

become overt (conscious) or remain covert (non-

conscious).

With the exception of a few theories on decision

making (Janis and Mann, 1977; Mann, 1992), most

current theories of choice use a cognitive

perspective. These theories assume that decisions

derive from an assessment of the future outcomes

of various options and alternatives through some

type of cost– benefit analyses. Some of these

theories have addressed emotion as a factor in

decision making, but mostly as a consequence of

a decision (e.g. the disappointment or regret

experienced after some risky decision) rather than

as the reactions arising directly from the decision

itself at the time of deliberation. The somatic

marker hypothesis proposes that individuals make

judgements not only by assessing the severity of

outcomes and their probability of occurrence, but

and primarily in terms of their emotional quality.

Lesions of the VM prefrontal cortex interfere with

the normal processing of somatic or emotional

signals, but leave other cognitive functions

minimally affected. This damage leads to

pathological impairments in the decision-making

process which seriously compromise the efficency

of everyday-life decisions. The somatic marker

proposal is consistent with the views of others who

invoke a primary role for mood, affect and emotion

in decision making (Schwartz and Clore,

1983; Zajonc, 1984; LeDoux, 1996). However, it

differs from the view that body signals only

introduce noise into the decision-making system

(Rolls, 1999). Shallice has proposed a model for

decision making that invokes the idea of marking

various options with a value (Shallice, 1993).

However, the nature of these markers is not

specified, and it is implied that they are cognitive

in nature. Thus, the views of both Rolls

and Shallice are more consistent with the ‘as-if

body loop’ component of the somatic marker

hypothesis. The fundamental notion of the somatic

marker hypothesis is that bioregulatory signals,

including those that constitute feeling and emotion,

provide the principal guide for decisions and are

the basis for the development of the ‘as-if body

loop’ mode of operation.

Acquisition of somatic markers is performed in

the pre-frontal cortices (they receive signals from

all other sensory regions in which images are

formed, they receive signals from several bio-

regulatory sectors of the brain, they themselves

represent categorisations of the situations in which

the organism has been involved and they are

ideally suited to deciding and reasoning because

they are directly connected to every avenue of

motor and chemical response available). The

somatic marker hypothesis and the experimental

strategies used to study decision making in

neurological patients provide parallels and direct

implications for understanding the nature of several

psychiatric disorders. For instance, substance

abusers are similar to VM patients in that when

faced with a choice that brings some immediate

reward (i.e. taking a drug), at the risk of incurring a

loss of reputation, job, home and family, they

choose the immediate reward and ignore the future

consequences. Using the gambling task (Grant et




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al., 1997; Petry et al., 1998; Bechara et al., 1999b)

or related decision-making tasks (Rogers et al.,

1999), recent studies have indicated that

impairment in decision making may stand at the

core of the problem of substance abuse. Similarly,

the personality profile of VM patients bears some

striking similarities to psychopathic (or

sociopathic) personality, so much so that we have

used the term ‘acquired sociopathy’ to describe the

condition of patients with VM damage (Damasio et

al., 1990). The qualifier ‘acquired’ signifies that

the condition in VM patients follows the onset of

brain injury, and occurs in persons whose

personalities and social conduct were previously

normal. The patients are usually not destructive or

harmful to others, a feature that tends to distinguish

the ‘acquired’ form of the disorder from the

standard ‘developmental’ form. Indeed, recent

evidence has indicated that the earlier the onset of

VM damage, the more severe the antisocial

behaviour, suggesting that early dysfunction in the

prefrontal cortex may, by itself, cause abnormal

development of social and moral behaviour

(Anderson et al., 1999). Recent studies have begun

to look at the possibility that the psychopathic

behaviour seen in cases in which no neurological

history has been identified may be linked to

abnormal operation of the neural system involving

the VM (Schmitt et al., 1999).

In complex situations, cognitive processes may

become overloaded and be unable to provide an

informed option. In these cases (and others),

Somatic Markers can aid decision process. In the

environment, reinforcing stimuli induce an

associated physiological affective state. These

types of associations are stored as Somatic

Markers, possibly in ventromedial prefrontal cortex

(VMPFC; a subsection of orbitomedial PFC). In

future situations, these Somatic-Marker

associations are reinstated physiologically and bias

cognitive processing. In cases where complex and

uncertain decisions need to be made, Somatic

Markers from all reward - and punishment-

associated experiences with the relevant stimuli are

summed to produce a net Somatic state. This

overall state is used to direct (or bias) the selection

of the appropriate action. This biasing process may

occur covertly (unconsciously), via the brainstem

and ventral striatum, or overtly (consciously),

engaging higher cortical cognitive processing.

Somatic Markers are proposed to direct attention

away from the most disadvantageous options,

simplifying the decision process. Before

considering the MEBDS hypothesis, it is useful to

note Damasio’s (1994) Somatic Marker

hypothesis which bases a model of decision-

making systems on similar neurophysiological

foundations but emphasises the role of emotion and

feelings, downplaying economic considerations.

Decision-making reflects the Marker signals laid

down in bioregulatory systems by conscious and

non-conscious emotion and feeling; hence, Bechara

and Damasio (2005; see Bechara et al., 2000)

argue that in dealing with decision-making

economic theory ignores emotion. Management is

exclusively concerned with ‘rational Bayesian

maximization of expected utility, as if humans

were equipped with unlimited knowledge, time,

and information processing power’. They point, by

contrast, to neural evidence which shows that

‘sound and rational’ decision-making requires

antecedent accurate emotional processing (Bechara

and Damasio, 2005, p. 336; see Phelps and Sokol-

Hessner, 2012).



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Damasio’s (1994) hypothesis is the outcome of

brain lesion studies in which damage to the

ventromedial prefrontal cortex (vmPFC) was found

to be associated with behaving in ways that were

personally harmful, especially insofar as they

contributed to injury to the social and financial

status of the individual and to their social

relationships. Although many aspects of these

patients’ intellectual functioning such as long-term

memory were unimpaired, they were notably

disadvantaged with respect to learning from

experience and responding appropriately to

emotional situations. Moreover, their general

emotional level was described as ‘flat’. Damasio’s

observation on these findings was that ‘the primary

dysfunction of patients with vmPFC damage was

an inability to use emotions in decision making,

particularly decision making in the personal,

financial and moral realms’ (Naqvi ; 2006). Thus

was born the central assumption of the Somatic

Marker hypothesis that ‘emotions play a role in

guiding decisions, especially in situations in which

the outcomes of one’s decisions, in terms of reward

and punishment, are uncertain’ (Bechara; 2011). Of

relevance here is the finding that the vmPFC may

be implicated in activity of the parasympathetic

nervous system (PNS), which in contrast to the

sympathetic nervous system (SNS) is involved in

the explorative monitoring of the environment and

the discovery of novelty (Eisenberger and Cole,

2012). This is corroborative of both Damasio’s

view and the nature and neurodecision Managerial

economic behaviour of innovative Manager

discussed below.

Inherent in the Somatic Marker hypothesis is the

attempt to describe not only the separate functions

of the brain regions involved in emotional

processing but the interconnections between them

(Haber, 2009). The starting point is operant

neurodecision Managerial economic behaviour,

particularly the mechanisms of reinforcement

learning (Daw, 2013; Daw and Tobler, 2013).

Specific neurodecision Managerial economic

behaviours eventuate in rewards as a result of

which the amygdala triggers emotional/bodily

states. These states are then associated via a

learning process to the neurodecision Managerial

economic behaviours that brought them about by

means of mental representations. As each

neurodecision Managerial economic behavioural

alternative is subsequently deliberated upon in the

course of decision-making, the Somatic state

corresponding to it is re-enacted by the vmPFC.

After being brought to mind in the course of

decision-making the Somatic states are represented

in the brain by sensory processes in two ways.

First, emotional states are related to cortical

activation (e.g., insular cortex) in the form

of conscious ’gut feelings’ of desire or aversion

that are mentally attributed to the neurodecision

Managerial economic behavioural options as they

are considered. Secondly, there is an unconscious

mapping of the Somatic states at the subcortical

level—e.g., in the mesolimbic dopaminergic

system; in this case, individuals choose the more

beneficial option without knowingly feeling the

desire for it or the averseness of a less beneficial

alternative (Ross et al., 2008; see Di Chiara,

2002; Robbins and Everitt, 2002;Tobler and

Kobayashi, 2009).

The rapidity with which the impulsive system

acts in propelling neurodecision Managerial

economic behaviour is underlined by Rolls’s

(2005) theory of emotion in which the reinforcing

stimuli consequent on a neurodecision Managerial

economic behavioural act as conditioned stimuli

that elicit emotion feelings. The automaticity of

this interaction of operant and Pavlovian

conditioning may explanation for neurodecision

Managerial economic behaviour in two ways. The

emotion feeling may function as an internal

discriminative stimulus to increase the probability

of the neurodecision Managerial economic

behaviour that produced it being reprised; it is

equally likely that the emotion feeling is the

ultimate reward of the neurodecision Managerial

economic behaviour in question and that, by

definition, it performs a reinforcing role (Foxall,

2011). Either way, the effects of basic emotions on

subsequent responding is immediate and

uninfluenced by reflection at the cognitive level.

While the criticism of Management shown by the

authors of the Somatic Marker hypothesis appears

to rule an economic orientation out of their

purview, the MEBDS approach actively builds on

insights from operant neurodecision Managerial

economic behavioural Management (Bickel et al.,

1999, 2010, 2011a,b; Bickel and Vuchinich,

2000; Bickel and Marsch, 2001; Bickel and

Johnson, 2003).

While the Somatic Marker hypothesis relied in

its inaugural stages on lesion studies, the central

research technique of cognitive neuropsychology,

the work of Rolls (2005) offers confirmation of the

role of operant neurodecision Managerial economic

behaviour in the emerging paradigm. Recording

single neurons’ activity levels, Rolls

(2005, 2008) reports that vmPFC neurons respond

to the receipt of primary reinforcers such as

pleasant-tasting foods. The integrity of the

conditioning paradigm is evinced by the finding

that devaluation of the reinforce, for example

through satiety, reduced the responses of such

areas to these primary reinforcers. fMRI studies

offer corroboration. Gottfried et al. (2003) report

that when a predicted primary reinforcer is

































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devalued then vmPFC activity engendered by that

reinforcer is reduced. Hence, the vmPFC

contributes to the prediction of the reward values

of alternative neurodecision Managerial economic

behaviours by reference to their capacity to

generate rewarding consequences in prior

occasions. Schoenbaum et al. (2003) used lesion

and physiological studies to show that this capacity

to encode predictive reward value depends on an

intact amygdala.

The MEBDS model differs in emphasis from

Damasio’s Somatic Marker hypothesis. Their

underlying similarity inheres in an

acknowledgement that separate functions are

performed within the overall impulsive-executive

system. But Bickel draws attention to the

interconnected operations of the impulsive system

and the executive system in the production of

neurodecision Managerial economic behaviour

(Bickel et al., 2007). The MEBDS hypothesis is

open, moreover, to the incorporation of economic

analysis in the form of neurodecision Managerial

economic behavioural Management and

neuroManagement (Bickel et al., 2011a). Impulsive

action, defined as the decision of a smaller but

sooner reward (SSR) over a larger but later reward

(LLR), is certainly associated with the over-

activation of the older limbic and paralimbic areas,

while the valuation and planning of future events

and outcomes engages the relatively new (in

evolutionary terms) PFC. However, it is the

interaction of these areas, which are densely inter-

meshed, that generates overt neurodecision

Managerial economic behaviours. The MEBDS

hypothesis thus stresses the continuity of the

components of the neurophysiological-based

decision system and Bickel’s conception is

therefore one of a continuum on which the

impulsive and executive systems are arrayed

theoretically as polar opponents (Porcelli and

Delgado, 2009).

Specifically, Bickel et al. (2012a) identify, in

addition to trait impulsivity, four kinds of state

impulsivity: neurodecision Managerial economic

behavioural disinhibition, attentional deficit

impulsivity, reflection impulsivity and impulsive

decision. Trait impulsivity is associated with

mesolimbic OFC and correlates with medial PFC,

pregenual anterior cingulate cortex (ACC) and

ventrolateral PFC; venturesomeness (sensation-

seeking) correlates with right lateral orbitofrontal

cortex, subgenual anterior cingualate cortex, and

left caudate nucleus activations. The concept of

trait impulsivity recognizes neurodecision

Managerial economic behavioural regularities that

are cross-situationally resilient. Within this broad

construct, sensation-seeking or venturesomeness is

widely known to be related to a need to reach an

optimum stimulation level. Bickel et al.

(2012a) associate it with sensitivity to

reinforcement, the theory of which has been

extensively developed by Corr (2008b) and is

discussed in greater detail below. Of the four state

impulsivities discussed by Bickel et al. (2012a),


disinhibition is associated with deficiencies in the

anterior cingulate and prefrontal cortices,

attentional deficit impulsivity with impairments of

caudate nuclei, ACC, and parietal cortical

structures, and with strong activity in insular

cortex; reflection impulsivity with impaired frontal

lobe function; and impulsive decision with

increased activation in limbic and paralimbic

regions in the course of the selection of immediate

rewards.

This latter is again strongly predicted by RST

(McNaughton and Corr, 2008). It is debatable

whether the state impulsivities mentioned here are

anything other than the neurodecision Managerial

economic behavioural manifestations of trait

impulsivity in particular contexts. The four state

impulsivities that Bickel et al. (2012a) note are

probably outcomes of a general tendency to act

impulsively from which they are predictable.

Neurodecision Managerial economic behavioural

disinhibition is the inability to arrest a pattern of


once it has started; it is evinced in acting

prematurely with deleterious outcomes. Attentional

deficit impulsivity is failure to concentrate, to

persevere with salient stimuli. Again, the outcome

is the adoption of risky neurodecision Managerial

economic behavioural modes with poor

consequences. Reflection impulsivity is failure to

gather sufficient information before deciding and

acting; inability to get an adequate measure of the

situation leads to unrewarding neurodecision

Managerial economic behaviours. Impulsive

decision is a neurodecision Managerial economic

behavioural preference for a SSR over a LLR for

which the individual must wait. All of these state

impulsivities are actually neurodecision

Managerial economic behaviours, the outcomes of

trait impulsivity. More relevant to the present

discussion ispreference reversal in which a longer-

term, more advantageous goal is preferred (e.g.,

verbally) at the outset only to decline dramatically

in relative value as the delivery of the earlier less

advantageous reward becomes imminent.

Bickel et al. (2012a) define EFs as

‘neurodecision Managerial economic behaviour

that is self-directed toward altering future

outcomes’ (p. 363; see Barkley, 2012) and point

out that EFs are consensually associated with

activity in the PFC. PFC is generally recognized as

implicated in the integration of motivational


















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information and subsequent decision-making

(Wantanabe, 2009), exerting a supervisory function

that governs the regulation of neurodecision

Managerial economic behaviour (Bickel et al.,

2012a); hence, Bickel et al. (2012a) point out, its

designation as a supervisory attentional system

(SAS; Shallice and Cooper, 2011).

While some authors emphasise a single element

of EFs such as the attentional control of

neurodecision Managerial economic behaviour or

working memory or inhibition, others stress groups

of elements: planning, working memory,

attentional shifting or valuing future events,

emotional aspects of decision-making. Addiction

can then be viewed as a breakdown in the

operations of the EFs or as impaired response

inhibition leading to the increased salience of

addiction-orientated cues. Bickel et al.

(2012a) concentrate on Attention, Neurodecision

Managerial economic behavioural flexibility,

Planning, Working memory, Emotional activation

and self-regulation (EASR) which they group into

three major categories: (1) the cross-temporal

organisation of neurodecision Managerial

economic behaviour (CTOB) which is concerned

with the awareness of the future consequences of

current or contemplated neurodecision Managerial

economic behaviour and therefore with planning

for events that will occur later; (2) EASR which

involves the processing of emotion-related

information and ‘initiating and maintaining goal-

related responding’; and (3) metacognition which

includes social cognition and insight, empathy, and

theory of mind (ToM).

The CTOB comprises attention (closely related

to dorsolateral prefrontal cortex

(DLPFC), neurodecision Managerial economic

behavioural flexibility (frontal gyrus activity;

lesioning of PFC is well-known to be associated

with the diminution of neurodecision Managerial

economic behavioural flexibility (Damasio,

1994; Bechara, 2011), neurodecision Managerial

economic behavioural inhibition (right inferior

frontal cortex and insula are activated during


inhibition which is associated with reduced

activity in left DLPFC, the right frontal gyrus, right

medial gyrus, left cingulate, left putamen, medial

temporal, and inferior parietal cortex), planning (in

which DLPFC the VMPFC, parietal cortex, and

striatum are implicated), valuing future events(in

the case of previewing and selecting immediate

rewards: limbic and paralimbic regions; in the case

of long-term decisions: prefrontal regions;

see McClure et al., 2004); and working

memory (DLPFC, VMPFC, dorsal cingulate,

frontal poles, medial inferior parietal cortex, frontal

gyrus, medial frontal gyrus, and precentral

gyrus; Bickel et al., 2012a, pp. 363–367).

EASR concerned with the management of

emotional responses is implemented in Medial

PFC, lateral PFC, ACC, OFC. Metacognitive

processes (MP) involve recognition of one’s own

motivation and that of others which is implemented

in the case of insight or self-awareness by the

insula and ACC, and in the case of social

cognition by medial PFC, right superior temporal

gyrus, left temporal parietal junction, left

somatosensory cortex, right DLPFC;

moreover, impaired social cognition follows

lesions to VMPFC (Damasio, 1994; Bechara,

2005; Bickel et al., 2012a, pp. 367–368).

RST (Gray, 1982; Corr, 2008b; Smillie, 2008)

includes the excitatory (impulsivity) and inhibition

(executive) components of the MEBDS model but

permits us to make extensions relating to the

expected neurodecision Managerial economic

behaviour patterns that follow from each and the

way in which individual differences can be

summed up in terms of an ascription of personality

types.1 RST proposes that the basic neurodecision

Managerial economic behavioural processes of

approach and avoidance are differentially

associated with reinforcement and punishment and

that individuals show variations in their sensitivity

to these stimuli.2

Approach is neurodecision Managerial economic

behaviour under the control of positively

reinforcing or appetitive stimuli and is mediated by

neurophysiological reward circuitry that the theory

categorizes as a Neurodecision Managerial

economic behavioural Approach System or BAS.

The BAS consists in the basal ganglia, especially in

the mesolimbic dopaminergic system that projects

from the ventral tegmental area (VTA) to the

ventral striatum (notably the nucleus accumbens)

and mesocortical DA PFC (Smillie, 2008;

cf. Pickering and Smillie, 2008). For recent

discussion of the role of the striatum in decision-

making and the processing of rewards, see Delgado

and Tricomi (2011). Recent research demonstrating

the role of this dopaminergic system in formulating

‘reward prediction errors’ is consonant with this

understanding. Unpredicted reward is followed by

increase in phasic dopaminergic activity whereas

unpredicted non-reward is followed by a decrease

and unchanged when reward is entirely predicted

(Schultz, 2000, 2002;Schultz and Dickinson,

2000; Schultz et al., 2008). Unpredicted reward

instantiates the activity of the BAS, therefore, and

predicted reward maintains its operation.

Moreover, BAS activity increases positive reward

(pleasure) and motivates approach to reinforcing

stimuli and stimuli that predict reinforcement. Such

approach is characteristic of the extraverted




















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personality; Corr (2008b, p. 10) sums up the

personality type as ‘optimism, reward-orientation

and impulsivity’ and notes that it maps clinically

on to addictive neurodecision Managerial

economic behaviours.

These emotional and motivational outcomes

represent one pole of a continuum of individual

differences that manifest differential BAS and

Neurodecision Managerial economic behavioural

Inhibition System (BIS) reactions to stimuli. There

is a corresponding though antithetical explanation

of avoidance in RST. Avoidance is shaped by

sensitivity to stimuli of punishment and threat and

mediated by two bio-neurodecision Managerial

economic behaviourally based systems of emotion

and motivation. The first of these, the Fight-Flight-

Freeze system (FFFS), is triggered by aversive

stimuli and the resulting feeling of fear, what Corr

(2008b, p. 10) refers to as the ‘get me out of here

emotion’; the FFFS’s motivational output is a


pattern characterized as ‘defensive avoidance’. However, if the consequential stimuli involved are

mixed in terms of their emotional valence then the

BIS, which is involved generally in the resolution

of goal-conflict is activated; in this case, the

emotional output is anxiety, the ‘watch out for

danger’ emotion Corr (2008b, p. 11) and the


outputs are risk evaluation and cautiousness which

are described as manifesting defensive approach.

Hence, in summary, reward sensitivity leads to

positive emotion and approach and a response

pattern that is characterized as ‘extraversion’ via


observation or psychometric testing; by contrast,

punishment sensitivity leads to negative emotion

and avoidance and a personality characterized in

terms of neuroticism (Smillie, 2008).

RST relates the FFFS and BIS to specific

neurophysiological systems. In the case of the

FFFS this is the periaquedital gray, which is

implicated in acute or proximal threat, and the

medial hypothalamus, amygdala and interia

cingulate cortex, implicated in distal threats. The

BIS comprises the septo-hippocampal system and

the amygdala. The emotional output of the FFFS is

fearfulness while that of the BIS is anxiety. In

either case, the emotional outputs are negative and

most forms of RST relate this to neuroticism. The

value of employing explanatory constructs

referring to personality types such as extraversion

and neuroticism is that they summaries individual

differences in reinforcement sensitivity, adding

both to the interpretation of neurodecision

Managerial economic behaviour and to its

prediction in novel environments.

Dysfunctional neurodecision Managerial

economic behaviours are those dominated by either

the impulsive system or the executive system. The

impulsive system evolved because it was

evolutionarily-adaptive as far as inclusive fitness

was concerned. Its preoccupation with short-term

goals and its immediate response to opportunities

ensured its contribution to survival of the

individual and thereby to its biological fitness. It is

closely related to the kinds of modular functioning

posited by Fodor (1983) which allows rapid

responses to environmental concerns. It is closely

related to the emotion-feelings associated with

such response capacity, pleasure in particular but

arousal and dominance. These are the ultimate

rewards of instrumentally conditioned


(Rolls, 2008; Foxall, 2011).

When we speak of the dysfunctional

consequences of a hyperactive impulsive system in

seeking to understand and explain a Manager’s


repertoire we are referring to hyperactivity in these

emotional-reward systems which leads, for

instance, to preoccupation with short-term goals at

the expense of undertaking longer-term planning,

the reckless taking of investment decisions

promising rapid high returns and a consequent

over-cautiousness, and an unwillingness to invest

in future. Another manifestation is rigidity in the

pursuit of a previously selected goal even though

the environment has changed and flexibility is

called for. We are suggesting that it is unlikely that

this impulsive-hyperactivity occurs in isolation

from hypoactivity of the executive system. Hence,

imbalance occurs because Managers place

disproportionate importance on the emotional highs

resulting from activities that result in immediate or

near-immediate reinforcement at the expense of the

pursuit of considered action that would be under

the control of the executive system. Moreover, both

utilitarian reinforcement and informational

reinforcement are engendered which brings about

high levels of pleasure and arousal, and in a

context that permits the emotion-feeling of high

dominance (Kringelbach, 2010;Foxall, 2011). This

is probably the strongest combinations of

interacting reinforcement for the maintenance of

Managerial neurodecision Managerial economic

behaviour. From the organisation’s point of view,

if this neurodecision Managerial economic

behavioural style becomes characteristic of a

function, department or even of the firm as a

whole, the outcome will be an overconcentration

on administrative and operational activities at the

expense of a strategic perspective which embraces

and anticipates the opportunities and threats of the

changing market-competitive environment.














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However, dysfunctional neurodecision

Managerial economic behaviour may result from

hypo activity of the impulsive system and

hyperactivity of the executive system (Mojzisch

and Schultz-Hardt, 2007). The intellectual rewards

of a preoccupation with long-term planning,

obtaining and analysing information, mulling over

strategic possibilities, may lead to a lack of

strategic implementation so that the short-term

decisions necessary for the day-to-day operations

of the firm are neglected, working capital is

lacking, the firm cannot continue. The pleasures

and arousal resulting from cognitive activity and

the feeling of dominance that this provides can

manifest in organisational sclerosis which over-

values intellectual engagement with Marker

structures, competition and, especially, the

strategic scope of the organisation. From the

organisation’s viewpoint, if this neurodecision

Managerial economic behavioural style becomes

widespread, there will be an imbalance in favour of

strategic planning and decision-making at the

expense of the day-to-day imperatives of the firm’s

response to the tactical neurodecision Managerial

economic behaviour of competitors and the

vagaries of consumer decision. The executive

system evolved because it favoured biological

fitness. Its operation is much like that of the central

cognitive function posited by Fodor (1983).

In view of the importance of avoiding a general

tendency towards either kind of imbalance in the

neurodecision Managerial economic behaviour of

the firm, it might be argued that our unit of analysis

should be the organisation as a whole since it is

presumably structural elements in the

organisation’s culture that require attention if the

problem is to be overcome. This is undeniably

correct but our present objective is less to

overcome problems of imbalance, which are

anyway the subject of innumerable management

texts, and more to understand how individual

Managers may be prone to one or other


style. The central factor involved in diagnosing

either extreme at the individual level is the

temporal horizon of the Manager since this

correlates highly with the influence of the

impulsive and/or executive systems. This is best

considered, however, after the way in which

cognitive language is used in neuro-neurodecision

Managerial economic behavioural decision theory,

which brings further understanding of the role of

temporal horizon in decision-making. It suggests a

means of overcoming problems of impulsive-

hyperactivity and executive-hypo activity at the

individual level which must be evaluated before an

organisation-level solution can be proposed and

appraised.

Neuroscience and neurodecision Managerial

economic behavioural science employ extensional

language, the third-personal mode which is taken

as the hallmark of science (Dennett, 1969). The

truth value of extensional sentences is preserved

when co-designative terms are substituted for one

another. The phrase, ‘the fourth from the sun’ can

be substituted for ‘Mars’ in the sentence ‘That

planet is Mars’ without surrendering the truth value

of the sentence. However, the truth value of a

sentence containing intentional language, such as

‘believes’, ‘desires’ or ‘feels’, is not maintained

when co-designative are substituted. Given the

sentence, ‘John believes that that planet is Mars’, we are not at liberty to say, ‘John believes that

planet is the fourth from the sun’; since John may

not know that Mars is the fourth planet. Intentional

sentences have another unique property:

the intentional inexistence of their subjects. The

truth-value of my saying ‘I am driving to

Edinburgh this weekend’, an extensionally-

expressed statement, is established by there being a

place called Edinburgh to which I can travel. But if

I say that I am seeking the golden mountain,

looking for the fountain of youth or yearning for

absolute truth, none of the entities named in these

intentional expressions need actually exist for the

truth value of the sentences to be upheld. Finally, it

is not possible to translate intentional sentences

into extensional ones without altering their

meaning. Intentional sentences usually take the

form of an ‘attitude’ or verb such as believes,

desires or wants followed by a proposition such as

‘that today is Tuesday’ or ‘that eggs are too

expensive’; hence, such sentences are known as

‘propositional attitudes’ (Chisholm, 1957).

The proposed development of the MEBDS

hypothesis involves more than terminological

clarification. The principles just described govern

not only linguistic usage but the kinds of theories

we invoke in order to explain our subject matter

and care must be taken to ensure that each is

confined to the level of explanation or

interpretation to which it is appropriate. Cognitive

terminology is intentional and belongs only at the

level of the person (Bennett and Hacker, 2003).

Dennett (1969) distinguishes the sub-personal

level of explanation, that of ‘brains and neuronal

functioning’ from the personal level of explanation,

that of ‘Managers and minds’. The sub-personal

level thus entails a separate kind of scientific

purview and approach to explanation: by

encompassing neuronal activity it is the domain of

the neuroscientist and leads to an extensional

explanation. The personal level which is the

domain of mental phenomena is that of the

psychologist; it requires an intentional explanation.

A third level of explanation is required, however,










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in order to cover the whole range of phenomena

and sciences that deal with them in a

comprehensive approach to the explanation of


(Foxall, 2004). This is the super-personal level of

explanation which encompasses operancy, the

respect in which the rate of neurodecision

Managerial economic behaviour is contingent upon

its reinforcing and punishing consequences; this is

the field of extensional neurodecision Managerial

economic behavioural science.

Care is necessary to maintain the separation of

these three levels since the mode of explanation

which each entails is unique and cannot be

combined with the others in a simple fashion. The

fundamental difference in mode of explanation

which must be constantly recognized is as follows.

The sub- and super-personal levels, which are

based on the neuro- and neurodecision Managerial

economic behavioural-sciences respectively,

require the use of extensional language and

explanation. Both of which are in principle

amenable to experimental (‘causal’) analysis, or

failing this to the quasi-causal analysis made

possible by statistical inference. They differ from

one another in terms of the kind of stimuli and

responses (independent and dependent variables)

that must be taken into consideration in empirical

testing of the hypotheses to which they give rise.

They differ more fundamentally from the personal

level of explanation, which attracts a wholly

different mode of analysis, namely that of

intentional psychology; the approach to

explanation in this case relies on the ascription of

beliefs, desires and feelings on the basis of non-

causal criteria.

The proposed development of the MEBDS

hypothesis involves more than terminological

clarification. The principles just described govern

not only linguistic usage but the kinds of theories

we invoke in order to explain our subject matter

and care must be taken to ensure that each is

confined to the level of explanation or

interpretation to which it is appropriate. Cognitive

terminology is intentional and belongs only at the

level of the person (Bennett and Hacker, 2003).

Critique of MEBDS hypothesis takes the form

therefore of conceptual development. MEBDS

hypothesis is described by Bickel and colleagues in

neuroscientific, cognitive and neurodecision

Managerial economic behavioural terms without

regard to domains of explanation to which each of

these categories belongs. For example, although

they offer what purports to be a neurodecision

Managerial economic behavioural definition of EF,

they define several of its component parts in terms

that are cognitive. Following Barkley (1997a,b),

they define EF as ‘as neurodecision Managerial

economic behaviour that is self- directed toward

altering future outcomes’ (Bickel et al., 2012a, p.

363), but they list among those of its elements

which suggest ‘CTOB’: attention, planning,

valuing future events and working memory. These

clearly are or involve cognitive events. Similarly,

among the elements that make up ‘emotional and

activation self-regulation’, they list: ‘the processing

of emotional information’ and ‘initiating and

maintaining goal-related responding’. Finally, as

elements of ‘MP’ they list: ‘social cognition’ or

‘ToM’ and ‘insight’. Bickel et al. (2012a) define

impulsivity neurodecision Managerial economic

behaviourally in terms of actions prematurely

performed that eventuate in disadvantageous

outcomes. They go on, however, to describe

impulsivity as consisting in the trait of

impulsiveness, a structural personality variable that

incorporates sensation-seeking, deficits in attention

and reflection impulsivity which is an inability to

collect and evaluate information prior to taking a

decision. All of these are intentional.

So far we have advocated that neurodecision

Managerial economic behavioural and

neuroscientists maintain the appropriate syntax in

speaking of intentional concepts such as beliefs and

desires as opposed to extensional objects such as

neurons and neurodecision Managerial economic

behaviour patterns. This means understanding and

maintaining the sub-personal, personal and super-

personal levels of exposition and employing only

the appropriate language at each level. A more

satisfying outcome for neuro-neurodecision

Managerial economic behavioural decision theory

would be to incorporate a level of cognitive

exposition the content of which complemented the

extensional sciences we have discussed. This

section sets out the criteria that such an explanation

should fulfill; the following section evaluates

picoManagement (Ainslie, 1992) as that cognitive

component.

There are four requirements of any candidate for

the cognitive component of neuro-neurodecision

Managerial economic behavioural decision theory.

It must first be capable of filling the need for a

personal level explanation of the causes of

neurodecision Managerial economic behaviour.

Second, it must provide an intentional explanation.

Third, it should be capable of linking to the


Management and neuroManagement analyses that

are found in the hypothesis. And, finally, it must

relate philosophically to broader disciplinary

concerns including neurophysiology and operancy.

A cognitive explanation is required to provide

understanding of the ways in which individuals

subjectively respond to the circumstances which

influence their neurodecision Managerial economic











Vol-3, Issue-10, 2017



behaviour towards rewards that may have short-

term benefits but which entail longer-term

deleterious consequences. Being able to

characterize what individual’s desire and believe in

these situations, what they perceive and how they

feel, provide an indication of their underlying

disposition to respond in a particular way to

rewards and punishments occurring at different

times. This is of course a highly theoretical

enterprise; in order to avoid undue speculation and

conjecture, therefore, it is important that the

cognitive requirements of neuro-neurodecision

Managerial economic behavioural decision theory

are provided by a coherent body of knowledge

relating personal level factors to situations that

promote consumption.

The required personal level exposition must

indicate the particular intentional terms that are

applicable to the explanation of normal and

addictive neurodecision Managerial economic

behaviours within the framework of an overall

theory that can systematically relate the two

antipodal neurodecision Managerial economic

behaviour patterns. It must be capable of

explaining how intentional entities like beliefs and

desires, perceptions and emotions would act upon

the impulsion towards fulfillment of immediate

wants, such as consumption of an addictive

substance, in order to bring about a more

advantageous long-term result. This calls for a

well-worked out theory of human neurodecision

Managerial economic behaviour over the

continuum of normal to addictive neurodecision

Managerial economic behaviours rather than an ad

hoc application of intentional language on the basis

of rapid observation of an individual’s


MEBDS hypothesis relies heavily on operant


Management and neuroManagement in order to

explain the reinforcer pathologies that underlie

addictive patterns of neurodecision Managerial

economic behaviour. It would be advantageous,

therefore, for the cognitive component of the

model to link to the basic exposition in economic

terms. The usefulness of the cognitive explanation

might be questioned because of its inherently

theoretical nature; this objection can be overcome

if its explanation of neurodecision Managerial

economic behaviour can be specified in language

that is consonant with the provisions of

consumption in the face of extremely high

elasticity of demand and temporal discounting of

the consequences of neurodecision Managerial

economic behaviour.

A broader relationship between the cognitive

explanation of neurodecision Managerial economic

behaviour and the underlying neuroscience and


science that comprise the MEBDS hypothesis is

necessary that goes beyond economic integration.

Although a major point of the present argument is

that cognitive explanations differ fundamentally

from those provided by the extensional sciences,

the intentional component must be consistent with

what is known of the neurophysiological basis of

addiction and with its relationship to the

reinforcers and punishers that follow neurodecision

Managerial economic behaviour.

Herrnstein’s (1997) matching law suggests that

the value of a reinforcer is inversely proportional to

its delay, i.e., as the delay becomes shorter, the

value increases dramatically. This is the essence of

hyperbolic discounting. The key difference

between exponential and hyperbolic discounting is

that in the former the LLR is always preferable to

the SSR, regardless of time elapsed, whereas in the

latter there is a period during which the SSR is so

highly valued (because the time remaining to its

possible realization is so short) that it is preferred

to the LLR (Ainslie, 1992; Ainslie and

Monterosso; 2003). This is clearly not because of

its objective value which is by definition less than

that which can be obtained through patience, but

because the time remaining to its possible

realization is now so short, that it is preferred to the

later but larger reward. Ainslie notes that these

findings harmonize with Freud’s observations that

an infant behaves as if expecting immediate

gratification but becomes, with experience, willing

to wait for the longer-term alternative. In other

words, still paraphrasing Freud, if the pleasure

principle is resisted, the outcome will be the

exercise of the reality principle. In the terminology

of neurodecision Managerial economic behavioural

psychology, the operant relevant to each of these

principles are shaped by their respective outcomes.

Ainslie argues that the two principles can be

represented as two interests, each of which seems

to employ devices that undermine the other.

In discussing what these devices are, Ainslie

(1992) gives a clue as to how we may speak of the

operations of mental mechanisms and how they

are organised to produce phenomena in a cognitive

explanation, i.e., one that conforms to the use of

cognitive logic as we have defined it and to the

strictures of grounded modularity as they were

developed above. His first device, for instance,

is pre - commitment, in which for instance one

joins a slimming club in order to be able to call

upon social pressures in order to reach long term

goals. The very language of this explanation

indicates the relevance of the models of cognition

we have developed. The processes are

unobservable, adopted in order to make











Vol-3, Issue-10, 2017



intelligible once the extensional explanations of


and neuro-science have been exhausted. Secondly,

the interests may hide information from one

another, e.g., about the imminence of rewards.

Thirdly, the emotions that control short-term

responding may be incapable of suppression once

they are in train or they may be foreshortened by

long-term interests. Finally, current decisions may

be used as predictors of the whole pattern of


consisting in a sequence of multiple neurodecision

Managerial economic behaviours belonging to the

same operant class that the individual will engage

in future. An individual may, that is, see her

present decision of a chocolate éclair as indicative

that she will make this selection repeatedly and

often in the future. Individual decisions are thus

perceived as precedents. The resulting strategy is

what Ainslie later described as bundling, in which

the outcomes of a series of future events are seen

cumulatively as giving rise to a single value. When

this value, rather than that of a single future event,

is brought into collision with the value of the single

immediate decision, the long-term interest is

thereby strengthened (Baumeister and Vohs; 2003).

Subsequent neurodecision Managerial economic

behaviour that serves the longer rather than the

shorter term interest is apparently rule governed

rather than contingency shaped (Skinner, 1969).

However, the ‘rules’ exist only in the mind of the

individual who may not have encountered the

contingencies. It is intellectually dishonest to refer

to them as rules in the sense proffered by radical

neurodecision Managerial economic behaviourists

who require empirical confirmation that the

individual has previously encountered similar

contingencies or whose rule following


from others of similar kind to the present has been

reinforced. Since we have no empirical, in

particular, experimental indication of this nature,

we would more accurately refer to them as beliefs.

Our use of intentional language indicates the nature

of our explanation or, better perhaps, interpretation.

Ainslie himself refers to bundling as the basis of

‘personal rules’ but we can have no this- personal

evidence of even the existence of such, let alone

their efficacy. Better to characterize our

explanation as interpretation and make this explicit

by using intentional language.

Ainslie’s picomanagement portray the conflict

between a smaller reward that is available sooner

and a larger reward available later in terms of

clashing intrapersonal interests. These are personal

level events because their purpose is to render

intelligible the neurodecision Managerial economic

behaviour of an individual when it is no longer

obvious how the contingencies of

reinforcement/punishment and his neurophysiology

are affecting his neurodecision Managerial

economic behaviour. The neurodecision

Managerial economic behaviour we are attempting

to understand is often a single instance of activity

(we are taking a molecular perspective) but the


which we employ to generate and justify the

intentional interpretation we have to make is

a pattern of neurodecision Managerial economic

behaviour: here we are taking a molar standpoint.

There must be a pattern of neurophysiological

activity which supports the strategic assumptions

we are making about the individual. In addition,

the pattern of reinforcement (Foxall, 2013) is of

crucial importance in interpreting his neurodecision

Managerial economic behaviour. We are ascribing

interests and their effects in determining

neurodecision Managerial economic behaviour but

we employ constructs in order to accomplish this

that are unobservable posits: they cannot enter into

an experimental analysis. We use the molar


pattern, the pattern of reinforcement and

neurophysiology to underpin these strategic

assumptions and to justify our interpretation. The

language of picoManagement consists therefore in

strategic assumptions that derive from an

interpretation of the neurodecision Managerial

economic behaviour and neurophysiology of the

individual. The strategic assumptions we make and

the way we use them must be consistent with the

evolution of the species by natural selection, the

ontogenetic development of the individual’s


through operancy, and the evolutionary psychology

of the prevalent neurodecision Managerial

economic behaviour of the species. We need to

show how the neurodecision Managerial economic

behavioural sensitivity to patterns of reinforcement

(which are the subject of our studies of operons and

evolutionary psychology) are in turn related to

evolution by natural selection via synaptic

plasticity.

PicoManagement explanations for neurodecision

Managerial economic behaviour using intentional

language, specifically the cognitive language of

decision-making and problem solving. In

particular, as a theory of ‘the strategic interaction

of successive motivational states within the person’ (Ainslie, 1992), it is dynamically concerned with

the internal weighing of information about the

outcomes of alternative courses of action and the

motivational states they engender. Can the actions

of the interests themselves be economically

modeled at the intentional level? Is Ainslie’s

picoManagement entirely a cognitive theory or








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does it lend itself to microeconomic analysis? In

fact, Ross (2012) puts forward an array of

economic models of the strategic interactions

proposed by picoManagement among competing

preferences. Analysis of neurodecision Managerial

economic behaviour in terms of the pattern of

reinforcement it has previously resulted in draws

upon operant neurodecision Managerial economic

behavioural Management which is central to the

MEBDS: specifically, the analysis of discounting

relates neurodecision Managerial economic

behaviour to its consequences, but operant


Management establishes that individuals maximize

utility and the particular combinations of

reinforcement that constitute utility.

It is particularly important from the point of view

of the research program within which the current

investigation is being performed (see Foxall,

2007a) that the cognitive interpretation of


here picoManagement, can be defended

philosophically in terms of the underlying


and neuroscience (Foxall, 2004). This is clearly the

case with picoManagement (Foxall, 2007b). Now

that picoManagement has been established as a

cognitive component for neuro-neurodecision


its usefulness as a means of overcoming

Managerial dysfunction with respect to temporal

horizon can be evaluated. As Section Organisation-

Level Strategies for Changing Managerial

Neurodecision Managerial economic behaviour

indicates, the general thrust of picoManagement is

towards clinical application that may not fit most

Managerial situations. In that case, alternative

approaches to management are discussed, notably

adaption-innovation theory, which are founded on

similar neurophysiological bases but which suggest

more practicable solutions.

An advantage of picoManagement in the current

context is that it suggests means of overcoming the

Managerial problems likely to arise when

individual Managers are strongly motivated by the

goals and neurodecision Managerial economic

behavioural patterns that reflect hyperactivity in

the impulsive system and hypo activity in the

executive system. Ainslie (1992)proposes a

number of strategies through which the individual

might overcome the temporal discounting that is

the hallmark of this tendency. It is here that RST

underpins the current analysis by providing

neurophysiological systems that underlie not only

the more extreme impulsive—approach tendency

(BAS) the fear—engendered escape—avoidance

tendency (FFFS), but the goal-resolving tendency

that seeks to reconcile the alternative courses of

action (BIS). The strategies of self-control

suggested by Ainslie can be seen as attempts to aid

the BIS in its attempts at conflict-resolution.

Ainslie (1992) proposes four personal strategies,

allusion to some of which was made above, by

which the individual might make a larger, albeit

longer-term, outcome more probable:

precommitment, control of attention, preparation of

emotion and reward

bundling. Precommitment involves using external

commitments to preclude the irrational decision.

The individual seeks to manipulate the external

environment in order to make neurodecision

Managerial economic behaviour leading to the

LLR more likely. Ulysses lashed himself to the

mast before temptations arose. But precommitment

need not be so dramatic. An addict may imbibe a

substance that induces nausea when alcohol is

drunk. A student might arrange for friends to take

her to the library before a favourite TV program

begins. Control of attention restricts information

processing with respect to the SSR. For example,

taking a route home from the office that avoids

bars or fast-food restaurants; thinking about the car

one can buy if you eliminate cigarette

smoking. Preparation of emotion may take the

form of inhibiting emotions that are customarily

connected with the SSR or of increasing

incompatible emotions. Hence, graphically

recalling the health risks of over-eating, smoking

or excessive alcohol consumption, thinking of the

displeasure others will show, engage cognitive

reasoning in order to eliminate the emotional

anticipation that customarily lead to consumption.

Perhaps the principal strategy, reward

bundling requires the individual to make personal

rules about the perception of the smaller-sooner

and larger-later decisions available. Instead of

imagining the present decision and its exciting

outcomes (drinking alcohol to excess) as opposed

to a single somewhat amorphous outcome of

sobriety (‘longer life’), reward bundling involves

bring a whole sequence of larger- later rewards to

oppose rewards of the immediately-available

neurodecision Managerial economic behaviour. In

the absence of such bundling, the individual is

likely to undergo repeated preference reversals but

viewing the decision as between two streams of

neurodecision Managerial economic behaviours

and outcomes makes self-control more possible.

Self-control results from perceiving a single

decision between an aggregation of LLRs and a

competing aggregation of SSRs. The sum of the

LLRs is always greater than that of the SSRs.

Decision making is then a matter of imaginatively

bringing the LLRs forward in time to the present.

The personal rules necessary to ensure this self-

control take the form of private ‘side-bets’ in











Vol-3, Issue-10, 2017



which the current decision predicts future

decisions. The important point in viewing the

reward sequences in this way is that the LLR is at

all times superior to the SSR even when an SSR is

immediately available: preference reversal is

therefore not predictable. The rule is a side bet that

the current decision will predict future decisions. If

the SSR is resisted, the bet is won: the expectation

of future reward is thus enhanced and the

individual’s probability of success in resisting

temptation is increased. Selection of the SSR

indicates that the individual has lost the bet,

however: the individual’s self-image is weakened,

along with his or her expectation of resisting the

temptation in the future.

The relevance of these strategies to Managerial

decision-making of the kind we have been

discussing is evident though it is unclear whether a

Manager would be able to recognize and change

his or her neurodecision Managerial economic

behaviour in the absence of detailed one-on-one

counseling. While this methodology obviously has

applications in therapeutic contexts, and Ainslie’s

prescriptions fit well the needs of substance and


addicts, an application that is more attuned to the

social-structural demands of organisational

management is called for in the context with which

we are here concerned.

There exists an alternative approach to

Managerial application of the neuropsychological

work that has been reviewed in this thesis, though

the following comments are indicative and call for

a dedicated research program. Adaption-innovation

theory (Kirton, 2003) suggests a means of

structuring decision-making groups that reflects

competing neuro-neurodecision Managerial

economic behavioural systems and so avoids

reliance on an individual-level prescription for

Managerial neurodecision Managerial economic

behaviour. ‘Cognitive style’ refers to a person’s

persistent preferred manner of making decisions,

the characteristic way in which they approach

problems, information gathering and processing,

and the kinds of solution they are likely to work

towards an attempt to implement. As such, it is

orthogonal to cognitive level, which is intelligence

or capacity. Kirton (2003)proposes that

individuals’ cognitive styles can be arrayed on a

continuum from those that predispose ‘doing

better’ (the adaptive pole) to those that predispose

‘doing differently’ (the innovative pole). Adaption-

innovation is measured by the Kirton Adaption-

Innovation Inventory (KAI) which evinces high

levels of reliability and validity and scores

correlate with a number of personality variables

including extraversion and impulsivity. General

population samples indicate that trait adaption-

innovation is approximately normally distributed

and general population scores, including of course

those of Managers, are arrayed over a limited

continuum which falls within the theoretical

spectrum of scores posited by adaption-innovation

theory. In line with the purview of this thesis,

therefore, the Managers of whom we speak are not

extreme in their neurodecision Managerial

economic behaviours, though they some of them

may exhibit scores towards the extremes of the

bipolar construct of adaption-innovation. The

neurodecision Managerial economic behaviour of

the extreme adaptor is generally characterized by a

tendency towards caution in decision-making and

problem-solving, use of tried-and-tested methods,

efficiency, rule-conformity and limited quantitative

creativity manifesting in the generation of

relatively few, workable solutions. The extreme

innovator is, in contrast, more outlandish in

selecting decisions, more likely to propose novel

solutions to problems (many of which are

impracticable), less efficient and more likely to

modify or even break the rules. Although

extraversion (measured, for example, by Eysenck’s

E scale) emerges as more highly correlated with

adaption-innovation (measured in the direction of

the innovativeness pole), little is known about the

underlying personality profiles of adaptive and

innovative decision-makers in relation to the

contingencies of reinforcement that shape and

maintain their preferred neurodecision Managerial

economic behavioural styles. RST (Gray and

McNaughton, 2000;McNaughton and Corr,

2004; Corr, 2008a) offers a means of investigating

the personality profiles of decision-makers and the

role of reward and punishment in their

development and maintenance. This all suggests

that a psychometric research program concerned

with the integration of a number of fields could

provide indicators for the prescription to the

problems of extreme Managerial style. The

program would need to encompass the

neurophysiology of cognition together with the

psychometric measurement of personality

dimensions that underlie cognitive style. Enough

has been said to indicate that we understand these

fields and their interactions sufficiently to embark

on such a program. In the meantime, the following

remarks are indicative of the work that needs to be

undertaken.

In contradistinction to innovators, adapters are

typically prudent, using tried and tested methods,

cautious, apparently impervious to boredom and

unwilling to bend, let alone break, the rules. They

seek the kind of efficiency that manifests in

accomplishing known tasks more effectively. An

extremely adaptive cognitive style suggests

hyperactivity of the executive system coupled with











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hypoactivity of the impulsive system. Moreover,

those aspects of the executive system that involve

ToM, the observation of social conventions, meta-

cognition, and some facets of neurodecision

Managerial economic behavioural flexibility might

be adaptor characteristics that would confirm this

categorization. The tentative conclusion is that

adaptors would cope well and perform

advantageously when involved in the intellectual,

long-term, detailed thinking that strategic planning

requires. The downside to their over-involvement

in this kind of decision-making derives from the

demands that strategic planning and commitment

sometimes exert upon the ability to undertake

‘outside-the-paradigm’ thinking. Such demands are

likely to be, relatively, occasional but they are

equally likely to arise at times of crisis in the

market and competitive environments of firms and

to benefit most from the kind of thinking which

characterizes a more innovative cognitive style. In

contradistinction to adaptors, innovators typically

proliferate ideas that require the relatively radical

change that can modify strategic direction, the

product-market scope of the firm, and possibly

diversification. At its extreme however, this

cognitive style, suggests hypoactivity of the

executive system, hyperactivity of the impulsive

system. The impulsive system is geared to the rapid

identification and evaluation of opportunities and

threats, the capacity to envisage far-reaching,

possibly disruptive, change which, in refocusing

the entire strategic scope of the enterprise carries

with it upheaval in working practices and both the

working and non-working lives of Managers and

other employees. To the extent that these are

innovator-traits, it is clear that decision groups

need to be balanced by adaptors who can supply

the capacity for sounder decision-making and the

facilitators who can explain to innovators the

rationale behind the neurodecision Managerial

economic behaviour of adaptors, who are otherwise

likely to be seen as too slow-moving to respond

appropriately to the crisis, and to adaptors that

which underpins the neurodecision Managerial

economic behaviour of innovators who would

otherwise be perceived as too outlandish to

preserve the values of the organisation. Innovators

supply strengths in organisational decision-making:

they are more likely to think outside the paradigm

within which a problem has arisen, unconfined by

the tried and tested methods currently in place, and

to take risks. These are all relevant when the

organisation faces grave uncertainties and requires

radical strategic reorganisation. But innovators

may be unsuited to more short-term decision-

making which requires the skills of prudence and

caution which are the hallmark of the adapter.

Normally, strategic thinking and planning

require the adventurous outlook of the innovator,

tempered by the prudence of the adapter. But,

without top management vigilance and the

planning of the teams that participate in decision-

making, it might well attract a preponderance of

extreme adapters. If this cognitive style dominates

the strategic function, there is likely to be a

dysfunctional emphasis on the planning of strategy

at the expense of the taking of strategic decisions

and the implementation of appropriate policies at

the operational and administrative levels. Insofar as

strategic decisions are unprogrammed, they

therefore require the inputs of innovators. So a

prolonged predominance of adapters in this role

will lead to organisational imbalance. Normally,

operational (and administrative) functions require

the efficient involvement of the adapter, tempered

by the more outward-looking tendency of the

innovator. But, again without top management

vigilance, they might attract the extreme innovator

who seeks to take risks for short-term benefits.

This will interfere with the strategic management

of the enterprise and could jeopardize the overall

operation of the firm.

‘Strategic’ decisions do not necessarily arise at a

Managerial level that is automatically higher than

that of any other kind of decision, nor do strategic

decisions inherently involve the breaking of

paradigms, and innovativeness. Just because

strategy involves long-range planning does not

preclude its occurring within a paradigm, albeit of

grand scope, that is nevertheless known and

generally-accepted; equally, the innovativeness of

eroding boundaries between small-scale

organisational systems should not be automatically

diminished (Jablokow, 2005). Adaptive and

innovative styles of cognition and creativity are

constantly required, alongside one another, in the

solving of problems. That which predominates

appropriately in any given situation depends

entirely on the specific context. Organisational

problems arise when current strategies no longer fit

the demands of the organisational environment:

when markets, reflecting demand and competition,

are no longer adequately served by the norms of

organisational neurodecision Managerial economic

behaviour (Jablokow and Kirton, 2009). Such

changing circumstances have two vital

components. The first is the changing environment

must be perceived as involving precipitating

events, i.e., the need for change by the

organisation’s leaders; it is adaptors rather than

innovators who are more adept at detecting

unforeseen developments that require Managerial

action. The second is the exploitation of the

opportunities such external change is prompting, or

the defensive action needed to avoid the threats






Vol-3, Issue-10, 2017



that the environment contains; these tasks of

advancing the required action are more likely taken

effectively by the more innovative (Tubbs et al.,

2012). This is a matter of cognitive style, not of

cognitive or decision level. This point is

summarized by the ‘paradox of structure’ (Kirton,

2003, pp. 126–134): while Managers require

structure whatever their cognitive style, but that

structure is ultimately stultifying as persons,

organisations and environments exhibit dynamic

neurodecision Managerial economic behaviours.

All the more reason for founding Managerial teams

and neurodecision Managerial economic behaviour

patterns on the contributions of all cognitive styles.

Van der Molen (1994) notes on the basis of

evolutionary logic that social animals are

motivated by two counterpoised tendencies: first,

to find satisfaction in the company of specifics

which requires a degree of cooperation and

conformity; secondly, to compete with specifics for

limited resources, such as food, sexual partners,

and territory, on which individual survival and

biological fitness rely. The personality

characteristics which reflect these motivational

forces are, in turn, ‘strongly intercorrelated’ traits

such as ‘self-will, thing-orientation, individualism

and innovative creativity on the one pole and

compliance, person-orientation, sociability,

conformity and creative adaptiveness on the other.

Individuals differ from one another as far as the

balance between these polarities [is] concerned.

This variation between individuals must have

genetic components’ (van der Molen; 1994).

Drawing on the work of Cloninger

(1986, 1987), van der Molen (1994) makes a strong

case for the evolutionary and genetic components

of adaption innovation. Cloninger’s ‘novelty-

seeking’ and ‘reward dependence’ dimensions of

personality are especially pertinent. The former is

driven predominantly by the neurotransmitter DA

which manifests in neurodecision Managerial

economic behaviour that seeks to alleviate

boredom and monotony, to deliver the sense of

exhilaration and excitement that is generally

termed ‘sensation-seeking’ (Zuckerman, 1994);

these individuals demonstrate a tendency to be

‘impulsive, quick-tempered and disorderly… quickly distracted or bored… easily provoked to prepare for flight or fight’ (van der Molen, 1994, p.

151). ‘Reward dependent’ individuals are, in

contrast, highly dependent on ‘social reward and

approval, sentiment and succour’; they are ‘eager

to help and please others, persistent, industrious,

warmly sympathetic, sentimental, and sensitive to

social cues, praise and personal succor, but able to

delay gratification with the expectation of

eventually being socially rewarded’ (ibid). These

individuals’ neurodecision Managerial economic

behaviour is strongly controlled by neither

monoamine neuromodulator nor epinephrine.

Which of these bundles of attributes manifests in

neurodecision Managerial economic behaviour that

marks out some individuals as leaders depends

entirely on the demands of the Managerial

situation: retail banking, relying for the most part

on the implementation of standard operating

procedures, may have a natural tendency to

encourage and reward those neurodecision

Managerial economic behaviours that reflect an

adaptive cognitive style; pharmaceutical

companies, whose technological, demand and

competitive environments reflect a greater

dynamism than is ordinarily the norm for retail

banking, requires for a much larger part of its

activities the presence of individuals whose

cognitive and creative styles are predominantly

innovative. Investment banking which is expected

to reflect a large adaptively-creative style of

operation but which attracts innovators is in danger

of becoming the kind of ‘casino banking’ that has

been so deleterious to both corporate and general

social welfare in the last decade. But the inability

of an organisation to achieve the right cognitive

and creative accommodation to its environment

will predictably culminate in catastrophe. For the

retail bank whose leaders fail to perceive and

respond appropriately to the changing international

competition in high-street banking, the

pharmaceutical firm that becomes over-involved in

the development and marketing of drugs that are

novel in the extreme, and for the investment bank

that over-emphasises innovative creativity to the

point where reckless decisions are made,

catastrophe is equally probable. Predominant

organisational climate, adaptive or innovative, can

be disastrous if either of these cognitive styles

comes to predominate.

These neurodecision Managerial economic

behavioural styles are remarkably consonant the

innovative and adaptive cognitive/creative styles,

respectively, described by Kirton (2003). Their

prevalence and likely genetic basis is borne out by

their consistency with the RST described above

(Corr, 2008a; see Eysenck, 2006), though the

terminology may vary. The incorporation of

adaption-innovation theory into the framework of

conceptualization and analysis suggests a wider

search for the neurophysiological basis of styles of

creativity. But these are matters for further

research.

Analyses of Managerial neurodecision

Managerial economic behaviour in

neurophysiological terms raise two difficulties. The

first is conceptual: such explanations conflate

cognitive processes with neurophysiological

events; the second relates to practical management:



















Vol-3, Issue-10, 2017



such explanations offer little by way of solution to

the personal and organisational problems that result

from neurodecision Managerial economic

behaviour that is motivated by excess influence of

either Managers’ impulsive systems or their

executive systems. This thesis has sought to

contribute to the resolution of the conceptual

problem, by introducing a cognitive dimension,

picoManagement, into neuro-neurodecision


and the adaption - innovation theory of cognitive

styles to that of the practical problem by deriving

prescriptions for changing Managerial


Conclusion: The prime conclusion is that the use

of neurophysiological theory and research in the

conceptualization of Managerial decision-making

and in approaching the solution of problems that

arise therein is entirely justified but needs to be

qualified by practical considerations suggested by

the nature of Managerial work and the ways in

which Managerial neurodecision Managerial

economic behaviour can be modified especially in

the context of large-scale organisations. Prior to

such activity, however, is the resolution of

conceptual problems in the explanation of

individual neurodecision Managerial economic

behaviour on the basis of neurophysiological

events. This thesis has pursued a central

requirement of neuro-neurodecision Managerial

economic behavioural decision theory’s use of

intentional terminology to explain human

neurodecision Managerial economic behaviour: the

role of cognitive terminology and its implication

for the shape of the overall theory. It has argued

that picoManagement provides a valuable means of

inculcating a cognitive level of explanation into the

theory and that one of its advantages is that it

suggests solutions to hyperactivity in one or other

of the impulsive and executive systems identified

by the theory which is exacerbated by hypoactivity

in the alternative system. The solutions proposed

by picoManagement may, however, be most

suitable for remedial action in clinical settings

rather than in organisational settings. The quest for

solutions to Managerial problems is more readily

achieved through organisation-level models of

Managerial activity that incorporate as fully as

possible neurophysiological understandings of

neurodecision Managerial economic behaviour that

are compatible with those found in neuro-


decision theory. One possibility in the present

context is the application of adaption-innovation

theory, dimensions of which are known to map

reliably on to the neurophysiological and

cognitive/personality factors that underpin

impulsive and executive systems. The proposal that

Managerial teams be built and managed in ways

that reflect these considerations suggests the most

relevant applications of neuro- and neurodecision

Managerial economic behavioural science, with

cognitive psychology, for the remediation of

certain Managerial excesses. These conclusions

lead predictably to a call for further research along

the lines indicated.

The advantage of this emphasis on cognitive

style is that it differentiates Managers on the basis

of their susceptibility to hyper- or hypo-activity of

either the impulsive or executive systems; and

recognizing that the Managerial functions with

which we are concerned are populated by

Managers of widely differing cognitive styles

should reduce our tendencies to stereotype

Managers on the basis of their broadly-defined

functional roles (Foxall and Hackett, 1994; Foxall

and Minkes, 1996). The neurophysiological

foundations of adaption-innovation as presented

here do not map directly on to those of RST or

neuro-neurodecision Managerial economic

behavioural decision theory. But there is sufficient

overlap to motivate further investigation.







Vol-3, Issue-10, 2017





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Documents

Managerial Neuro - Hybrid Decision Architecture · PDF fileManagerial Neuro - Hybrid Decision Architecture Lt Col (Dr) J Satpathy 1.2 & Dr Bhabani P Mishra 3 1. Faculty, Academics