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Self-perception and Experiential Schemata in the Addicted Brain
Rex Cannon Æ Joel Lubar Æ Debora Baldwin
� Springer Science+Business Media, LLC 2008
Abstract This study investigated neurophysiological
differences between recovering substance abusers (RSA)
and controls while electroencephalogram (EEG) was con-
tinuously recorded during completion of a new assessment
instrument. The participants consisted of 56 total subjects;
28 RSA and 28 non-clinical controls (C). The participants
completed the self-perception and experiential schemata
assessment (SPESA) and source localization was compared
utilizing standardized low-resolution electromagnetic
tomography (sLORETA). The data show significant dif-
ferences between groups during both the assessment
condition and baselines. A pattern of alpha activity as
estimated by sLORETA was shown in the right amygdala,
uncus, hippocampus, BA37, insular cortex and orbito-
frontal regions during the SPESA condition. This activity
possibly reflects a circuit related to negative perceptions of
self formed in specific neural pathways. These pathways
may be responsive to the alpha activity induced by many
substances by bringing the brain into synchrony if only for
a short time. In effect this may represent the euphoria
described by substance abusers.
Keywords Addiction � Self-perception �Neurophysiological assessment � EEG biofeedback �LORETA
Introduction
Substance use disorders (SUD) continue to exact sub-
stantial costs on society, families and the individual alike
and are the most frequently diagnosed disorders in the
Diagnostic and Statistical Manual of Mental Disorders
(DSM-IV-TR) (APA 2000). SUD continue to create chal-
lenges for both researchers and clinicians due to the high
incidence of recidivism (relapse) and the many components
involved; including, biological, neurophysiological, socio-
economic, cultural and psychological elements. It is
suggested that heritability plays an important role in SUD
(Blum et al. 2007); however, to what extent environment,
perception and synaptic permanency or plasticity influence
the course of genetic adaptation or development of mal-
adaptive self-image requires further investigation.
To date many of the most utilized assessment instru-
ments for SUD focus on information relating to substance
abuse or personality mechanisms (Alterman et al. 2007;
Bryer et al. 1990; Cannon et al. 1990; Gallucci 1997;
McDermott et al. 1996; Rouse et al. 1999; Stein et al.
1999); however, no current instrument provides neuro-
physiological evidence of the construct being measured.
Assessment construction involves careful consideration of
the theoretical construct to be measured and operational
definitions of components to be scaled with the consider-
ation that the final version is dependent on how well the
final data complement and confirm the theoretical construct
(Cronbach and Meehl 1955). It is important that the
question of self identity be addressed before any type of
social (Matto et al. 2007) or family identity can be oper-
ationalized with meaning. Evidence demonstrates that
attachment and interactions between parents and child play
a significant role in normal development; alternatively,
impaired parental bonding appears to be a major risk factor
R. Cannon (&) � J. Lubar � D. Baldwin
Brain Research and Neuropsychology Laboratory,
Department of Psychology, University of Tennessee
at Knoxville, Austin Peay Bldg, Suite 312, Knoxville,
TN 37996, USA
e-mail: [email protected]
123
Appl Psychophysiol Biofeedback
DOI 10.1007/s10484-008-9067-9
for development of mental illness, substance abuse and
possible substance dependence later in life (Canetti et al.
1997; Newcomb and Felix-Ortiz 1992; Petraitis et al. 1995;
Brook et al. 1989). Negative experiences in early child-
hood such as abuse and neglect are shown to be involved in
the development of obesity, cardiovascular diseases, and
other behavioral and psychological problems (McEwen
2000). It is within this context that this study and the
Self-Perception and Experiential Schemata Assessment
(SPESA) were formulated.
The SPESA is designed for sensitivity to negative,
average or positive perceptions of self, experiences and self-
in-experience in three life domains; childhood, adolescence
and adulthood. There are a total of 45 items, each with four
possible responses. The items are scored (2, 1, -1, -2). The
items are similar in content in dissimilar order for each
domain of development. The SPESA takes less than 10 min
to administer and 10 min to score. It provides important
insight into the perceptual, visceral, affective and cognitive
processes that may preclude the actual physical or psycho-
logical substance abuse or dependence. This instrument
divulges perceptual information regarding the endogenous
and exogenous experiences of the individual; including,
physical, sexual or emotional abuse, self-efficacy, self-
image, view of self in relation to family and peers, in
addition to perceptions of alienation and inadequacy. This
type of information is often obtained late in the typical
treatment regimen, if at all. Perception of self is an important
component for formulating a comprehensive understanding
of the client in order to produce effective treatment planning
and continued care monitoring. We utilize an operational
definition for the term SUD to apply to the misuse and abuse
of all mood altering chemicals with the hypothesis that
dissimilar substances may create different biological and
neurological consequences; however, there is some dis-
cernable neurophysiological commonality among the
population of recovering substance abusers (RSA) in this
study regardless of substance abused or drug of choice.
A recent review (Sokhadze et al. 2008) provides com-
prehensive information relating to EEG, event related
potentials (ERP) and EEG-biofeedback (neurofeedback) in
addiction research and treatment. EEG differences between
alcoholics and controls are shown in beta activity in frontal
and central regions of the cortex with beta 1 activity (12–
16 Hz) showing increased amplitude globally (Rangasw-
amy et al. 2002). Lower frontal alpha and slow-beta
coherence is shown in alcohol-dependent males and
females (Kaplan et al. 1985); in addition, individuals with
a family history of alcoholism show increased alpha
activity in posterior regions after alcohol consumption and
rate it more difficult to resist further drinking than controls
(Kaplan et al. 1988). Males at risk for alcoholism show
increased low-alpha EEG activity (7.5–10 Hz) after
ingesting alcohol as compared to males at low risk (Cohen
et al. 1993).
Michael et al. (1993) found higher central alpha and
slow-beta coherence in frontal and parietal electrodes in
relatives of alcoholics and lower parietal alpha and slow-
beta coherence in males with alcohol dependence. Notably,
other findings indicate that morphine, alcohol and mari-
juana increase alpha 2 power in the spectral EEG and relate
this to the euphoric state produced by the drugs (Lukas
1991, 1993; Lukas et al. 1995). Winterer and colleagues
(2003a, b) describe higher alpha and slow-beta coherence
in left-temporal regions and higher slow-beta coherence in
right temporal and frontal electrode pairs in alcohol-
dependent males and females. Moderate-to-heavy alcohol
consumption is associated with differences in synchroni-
zation of brain activity during rest (baseline) and mental
rehearsal with heavy drinkers displaying a loss of hemi-
spheric asymmetry of EEG synchronization in the alpha
and low-beta band. Contrarily, moderate to heavy drinking
males showed lower fast-beta band synchronization (De
Bruin et al. 2004, 2006). Elevated alpha power amplitude
is suggested to be a potential threat indicator for the
development of alcoholism and men with fathers having
alcohol use disorders are more likely to have high-voltage
alpha than men with unaffected fathers at baseline or after
receiving placebo (Ehlers and Schuckit 1988, 1990, 1991;
Ehlers et al. 1989). Based on the available research the
alpha and beta frequency domains appear to play a com-
plex role in addiction and may prove important in
formulating theories of neurophysiological antecedents to
SUD and the associated psychological and behavioral
processes.
Standardized low-resolution electromagnetic tomogra-
phy (sLORETA) is an inverse solution for estimating
cortical electrical current density originating from scalp
electrodes utilizing optimal smoothing in order to estimate
a direct 3D solution for the electrical activity distribution.
This method computes distributed electrical activity within
the cerebral volume, which is discretized and mapped onto
a dense grid array containing sources of electrical activity
at each point in the 3D grid. This methodology produces a
low error solution for source generators and provides sta-
tistical maps modeling distribution currents of brain
activity utilizing realistic electrode coordinates for a three-
concentric-shell spherical head model co-registered on a
standardized MRI atlas. This allows a reasonable approx-
imation of anatomical labeling within the neocortical
volume, including the anterior cingulate (AC) and hippo-
campus. LORETA and the standardized version are
accessible as freeware for research purposes and LORETA
is the only inverse solution developed for real-time neu-
rofeedback use. It is also demonstrated to estimate current
density sources efficiently with 19 electrodes (Congedo
Appl Psychophysiol Biofeedback
123
2003, 2006; Congedo et al. 2004; Lancaster et al. 1997,
2000; Lehmann et al. 2001, 2005, 2006; Pascual-Marqui
et al. 1994, 1999, 2002a, b, Pascual-Marqui 1999, 2002;
Talairach and Tournoux 1988; Towle et al. 1993).
SUD are multifaceted disorders that involve numerous
learning, social, experiential and cognitive components.
Smythies (1966) postulates that conditioned reflexes and
learning occur in the amygdala, the reticular formation and
other subcortical and limbic regions. EEG and functional
magnetic resonance imaging (fMRI) research demonstrat-
ing activity increase in the AC, amygdala, hippocampus,
uncinate gyrus, orbitofrontal (OFC) and inferior frontal
lobes during self-reference, reward acquisition, affective
tasks, decision making, emotional processing, autobio-
graphical memory and addictive disorders indicate a
complex role for these regions in numerous executive and
cognitive functions (Cabeza et al. 2004; Chambers et al.
2001; Dayas et al. 2007; De Witte 2004; del Olmo et al.
2006; Fossati et al. 2003, 2004; Gusnard 2005).
Social anxiety and other interpersonal difficulties are
posited to be increased risk factors for development of
SUD (Buckner et al. 2008). Individuals that have experi-
enced negative life events are more susceptible to alcohol
abuse (Brennan and Moos 1990). Moreover, individuals
that report childhood sexual abuse or other forms of
physical and emotional abuse are more likely to develop
SUD (Fergusson et al. 2008). Likewise, alcohol and other
drugs are suggested to buffer the stress and anxiety of life
events and temporarily improve self-esteem and lower
anxiety and depression levels (Josephs and Steele 1990).
Individuals with low self-esteem, negative self-efficacy,
negative self-image and a perceived lack of power or
control are more prone to use alcohol (Brett et al. 1990;
Bandura 1977; Holahan and Moos 1987). Furthermore,
data demonstrates deficits in executive functioning,
including, decision making and inhibitory processes among
the addicted population regardless of substance abused
(Lyvers and Yakimoff 2003; Wiers et al. 2005; De Bellis
et al. 2000; Grant and Dawson 1997; Tapert et al. 2004).
This concept is of primary interest concerning the behav-
ioral, social, impulsivity and decision making problems
that often plague addicted persons even after substantial
periods of abstinence.
We define experiential schemata (ES) as a neurologic
progression in human development involving a funda-
mental self-organization process. This process is based in
the formulation of concepts of self originating in percep-
tions of self (endogenous) formed through interactions with
others and the environment (exogenous). These encoded
schemata become the foundation for prevailing emotions,
motivations, attitudes, and attributions relating to self and
self-in-the-world that are maintained, reinforced and
entrenched in neural coding mechanisms formed through
dendritic arborization over the lifespan. The aforemen-
tioned behaviors and attributions have a possible etiology
in specific neurophysiological pathways involving regions
that are known to be involved in emotion, cognition, self-
reference and sensory processing and these pathways are
the direct result of dendritic pruning that occurs in early
development and progresses throughout adolescence into
adulthood. In normal development ES involving experi-
ences, behaviors, learning and organization of self are
engrained or reinforced in neural circuits with much of the
acquired information being necessary for social function-
ing, and overall survival in most circumstances. The
drawback to this process is that it can be extremely difficult
to introduce new concepts relating to self—identity to an
individual as well as novel learning material. There is an
extended period of time between infancy and adulthood in
which the environment contributes to the formation of
neural circuits through learning and experience (Anderton
2002; Gogate et al. 2001; Hyman and Malenka 2001;
Johnson 2001; Luczak 2006; van Pelt 1997).
The SPESA was developed with the intent to decrease
the gap that exists in relating neurologic functions with
perceptual, behavioral and psychological components or
experiential schemata. Based upon critical concepts from a
variety disciplines contributing to addiction research, we
propose that a common neurophysiological pattern exists in
RSA when evaluating self and self-in-experience that is
significantly different from non-clinical controls. Of par-
ticular interest to this study are the possible frequency
specific differences in cortical regions during both base-
lines and experimental condition electroencephalograms
(EEG). The cortical and subcortical regions identified in
addiction research offer reasonable insight into the linear,
often concretized cognitive patterns exhibited by addicted
individuals, in addition to the behavioral and decision
making difficulties exhibited by this population even after a
substantial period of abstinence from all mood altering
chemicals.
Methods
Participants
This study was conducted with a total of 56 participants.
Twenty-eight were in each group, RSA and controls (C).
The RSA group consisted of volunteers obtained from
regional Alcoholics and Narcotics Anonymous meetings.
All RSA members have completed at least one inpatient
treatment (28 days or longer) for chemical dependency and
received an Axis I diagnosis for chemical dependency from
medical professionals in the Veterans Administration or at
local chemical dependency treatment centers. The majority
Appl Psychophysiol Biofeedback
123
of the RSA group was classified with polysubstance, crack
cocaine and alcohol use disorders. The C group consisted
of participants obtained from the University of Tennessee
Human Research Participation pool who received extra
course credit for their participation. Exclusion criteria
consisted of previous head trauma, neurological or neuro-
vascular disease, or recent drug or alcohol use (2 weeks).
Because of the high comorbidity rate in SUD populations,
especially with respect to depression and anxiety, partici-
pants were excluded from the study only if they exhibited
psychosis, delusions or hallucinations. These were coded
and included in the analysis. All subjects read, signed and
agreed to protocol approved by the University Institutional
Review Board. The RSA groups’ mean time of abstinence
was calculated in days (384.11), range (14–1,825), SD
(459.46). Table 1 contains the demographic information
for the experimental groups.
Data Collection
Participants were prepared for EEG recording using a
measure of the distance between the nasion and inion to
determine the appropriate cap size for recording (Electro-
cap, Inc; Blom and Anneveldt 1982). The head was
measured and marked prior to EEG recording. The ears and
forehead were cleaned for recording with a mild abrasive
gel (Nuprep) to remove any oil and dirt from the skin. After
fitting the caps, each electrode site was injected with
electrogel and prepared so that impedances between indi-
vidual electrodes and each ear were \6 KX. The EEG
recording was conducted using the 19-leads standard
international 10/20 system (FP1, FP2, F3, F4, Fz, F7, F8,
C3, C4, Cz, T3, T4, T5, T6, P3, P4, Pz, O1 and O2). The
data were collected and stored with a band pass set at 0.5–
64.0 Hz at a rate of 256 samples per second using the
Truscan acquisition system (Deymed Diagnostics). We
utilized linked ears and ground reference with 9 mm tin
cups. The Electrocap was also referenced at FPz. All
recordings were carried out in a comfortably lit, sound
attenuated room in the Neuropsychology and Brain
Research Laboratory at the University of Tennessee,
Knoxville. Lighting and temperature were held constant for
the duration of the experiment. Each session required
approximately 60 min to complete. Three-minute eyes
opened and eyes-closed baselines were collected for brain
imaging comparison. Subjects were then recorded while
completing the SPESA. The participant responses to each
item were marked within the EEG record. In addition, the
participants in this study provided a written record of their
mental processes employed during the procedures and also
completed a paper version of the SPESA. Table 2 shows
actual items for each domain in the SPESA.
Data Pre-processing
We extracted the item responses from the EEG record, with
4s on each side of the response marker. We then processed
the subsequent EEG condition and baseline data with
particular attention given to the frontal and temporal leads.
All episodic eye blinks, eye movements, teeth clenching,
jaw tension, body movements and possible EKG (Elec-
trocardiogram) were removed from the EEG stream.
Fourier cross-spectral matrices were computed and aver-
aged over 75% overlapping four-second artifact-free
epochs, which resulted in one cross-spectral matrix for
each subject and for each discrete frequency. The average
common reference is computed prior to the sLORETA
estimations.
Data Analysis
In order to assess the electrophysiological differences
between experimental conditions over the entire neo-cor-
tex, we conducted all voxel-by-voxel t-tests setting the
threshold to abs (t) = 4.0 utilizing a multiple hypothesis
testing procedure for the within subjects experimental
design (NovatechEEG), which adopts multiple compari-
sons procedures based on the t-max test using the step-
down version of the procedure with 5,000 random data
permutations. Randomization and Permutation tests are
Table 1 Demographics for EEG groups
Group Total l age SD M F RH LH
Addict 28 37.89 13.33 21 7 26 2
Control 28 21.21 5.07 14 14 27 1
Table 2 Items from the SPESA for each life domain
6: In childhood, with my family I felt
A: Like I belonged
B: I wanted to belong
C: I did not want to belong
D: Like I did not belong
27: In my teenage years, regarding my family, I felt
A: Like I belonged
B: Like I did not belong
C: I wanted to belong
D: I did not want to belong
37: In my adult relationships with family, I feel
A: Like I belong
B: Like I do not belong
C: I want to belong
D: I do not want to belong
Appl Psychophysiol Biofeedback
123
demonstrated to produce significant control of the family
wise error rate (Type I error) in multiple hypothesis testing
(Edgington 1987; Good 1993, 2005) and are frequently
utilized in neuroimaging studies (Blair and Karniski 1994;
Holmes et al. 1996; Westfall and Young 1993). Current
density for total relative power was extracted. The statis-
tical analysis was conducted using the Multiple Hypothesis
Testing (MhyT3!) software (Nova Tech EEG, Inc.). The
statistical differences within conditions were corrected for
all multiple comparisons using non-parametric analysis.
All data were normalized, log transformed and smoothed
with a 21 mm moving average filter (MAF 3-D) before
entering statistical analysis. The specific contrast between
conditions was entered into one sample t-test correspond-
ing to a corrected p \ .01. This method of analysis has
been utilized in studies by our lab and others (Cannon et al.
2004, 2007, 2008; Congedo et al. 2004; Papageorgiou
et al. 2007; Sherlin et al. 2006; Zumsteg et al. 2006). All
voxels were examined and statistical data were transformed
into sLORETA images. We analyzed the EEG data uti-
lizing the following frequency domains: Delta (0.5–
3.5 Hz); Theta (3.5–7.5 Hz); Alpha 1 (7.5–10.0 Hz); Alpha
2 (10.0–12.0 Hz); Beta 1 (12.0–18.0 Hz); Beta 2 (18.0–
21.0 Hz); Beta 3 (21.0–24.0 Hz); Beta 4 (24.0–28.0 Hz)
and Beta 5 (28.0–32.0 Hz). We also compared the obtained
assessment scores for significance using independent t-tests
assuming equal variance using SPSS 15.
Results
In the following subsections we describe the results for the
voxel by voxel comparisons between RSA and C groups
for the EEG SPESA, eyes-closed and eyes-opened base-
lines and for the obtained SPESA scores. The sLORETA
images are the result of voxel by voxel t-tests with a t-max
threshold set at (4.0). The images from left to right are
horizontal, saggital and axial views of the brain. The red in
the image indicates increased current source density
a B .01. The blue in the image indicates decreased current
source density a B .01. In the subsequent section we
address the results for the comparisons between the
obtained scores between groups, and the influence of
endorsed items within the assessment on the index scores.
SPESA Condition
Figures 1 and 2 show the significant differences between
RSA and C during the SPESA phase of the experiment.
Figure 1 shows the differences for the alpha 1 frequency
(7.5–10.0 Hz). The region (voxel) of maximum increase in
current density as estimated by sLORETA is at Talairach
coordinates (X = 4, Y = -11, Z = -6) Brodmann area
(BA) 37, parahippocampal gyrus, limbic lobe. Figure 2
shows the differences in the alpha 2 frequency. The region
(voxel) of maximum increase in current density as esti-
mated by sLORETA is at Talairach coordinates (X = 39,
Y = 3, Z = 15) BA 13 in the insular cortex of the right
temporal lobe. These are the only differences between the
groups shown by the statistical program for the SPESA
condition.
Eyes Opened and Eyes-Closed sLORETA Comparisons
Table 3 shows the results for the comparison between RSA
and C for the eyes-opened baseline recordings. In the table
from left to right are the frequency domain, the Talairach x,
y and z coordinates, Brodmann Area (BA), anatomical
label and hemisphere-location. Maximum increase in cur-
rent source density did not meet statistical criteria
(t [ 4.0), thus only voxels of maximal decrease in current
source density are shown in the table. Table 4 shows the
results for the comparison between RA and C for the eyes-
closed baselines. In the table from left to right are the
frequency domain and maximum/minimum voxel identi-
fied by sLORETA, Talairach coordinates, BA, anatomical
label and hemisphere-location.
Comparisons for Obtained Assessment Scores
Table 5 shows the results for the comparison for the
obtained SPESA scores between RSA and C. The table
contains subsections comparing coded responses A =
score comparisons between groups. The results show that
the mean scores for the RSA group differ from C in neg-
ative fashion at significant levels. Section B = (Abuse)
shows the results for those that endorsed abuse compared
to those that did not. Those that endorsed these items rate
all domains more negatively. Section C = (MD) those
reporting prior depression diagnosis. Those subjects
endorsing this item tend to rate all categories more nega-
tively. Those reporting a family history of use D = (FHU)
rate items more negatively except in the childhood domain;
those endorsing items relative to forlornness E = (F) (we
consider this to mean forsaken, despaired, wretched,
hopeless, abandoned, deprived, deserted and pitiful) rate all
domains more negatively; similarly, those endorsing items
of inadequacy F = (INA) (we consider this to mean
insufficient, defective or deficient, failing or lacking, not
measuring up, less than and useless) rate all domains more
negatively. For these categories 44.6% report a history of
abuse; 32.1% report a prior diagnosis of depression; 69%
report a history of use in family of origin; 33.9% report
positive for items relating to forlornness; and 50% report
positive for items relating to inadequacy. The reliability
analysis for this group of 56 show inter-item correlations
Appl Psychophysiol Biofeedback
123
(ICC) between domains tested (child/adol = .798), (child/
adult = .516), (adol/adult = .590). The results of the two-
way random effects model with a consistency definition
provide an intra-class correlation coefficient of .825 for
average measures.
Discussion and Conclusion
This is the first study of its kind to evaluate EEG patterns of
self-perception and experiential schemata in a group of
RSA as well as controls. The significant differences
between groups in the SPESA condition may provide
insight into a very probable neural pathway which stands to
be an idiosyncratic neurologic anomaly for the RSA pop-
ulation in this study, in addition to a possible antecedent to
SUD. The excess alpha activity in SUD when processing
perception of self and self-in experience may reflect a state
of desynchronization (or an idling fear and evaluator
response guided by maladaptive ES) within the individual,
given that alpha is generated in the thalamus (Lorincz et al.
2008) and is known to be involved in both attention and
memory processes (Cannon et al. in press-a). This alpha
excess possibly places demands on resources otherwise
employed for the homeostatic functioning of the individ-
ual; including, autonomic, perceptual, attentional, social,
cognitive and sensory processes. Notably, research dem-
onstrates the use of certain chemicals produces widespread
alpha power increases in the cortex (see introduction),
thereby, at least for this study group and their reports of
‘using’ and ‘drinking’ thought patterns, bringing the brain
into synchrony, if only for a very short period of time. We
Fig. 1 Shows the maximum
increase in current source
density between addict and
controls during the completion
of the SPESA in the alpha 1
frequency. The maximum
region of increase is (X = 4,
Y = -11, Z = -6) Brodmann
area 37, Parahippocampal
Gyrus, Limbic Lobe
Fig. 2 Shows the maximum increase in current source density
between addict and control during the completion of the SPESA. The
maximum region of increase in the alpha 2 frequency is at (X = 39,
Y = 3, Z = 15) Brodmann area 13, Insula, Sub-lobar. There is also
increased current density in the alpha 2 frequency in BA 13, BA 47,
BA 34 and BA 37, as well as the amygdaloid complex; including the
uncus, amygdala and hippocampus
Table 3 Eyes-opened comparison between RA and C
Eyes-opened resting condition
Frequency domain Talairach x, y, z, coordinates Brodmann area Anatomical label Hemisphere/location
Delta -38, 3, 36 9 Pre-central gyrus Left frontal lobe
Theta -45, -4, 43 6 Pre-central gyrus Left frontal lobe
Alpha 2 39, -81, 29 19 Superior occipital gyrus Right occipital lobe
Note: All voxels listed meet statistical criteria with t [ 4.0 and are significant B.01
Appl Psychophysiol Biofeedback
123
believe this to be the euphoria addicted individuals speak
of so fondly and is one possible reason for the difficulty in
treating these disorders in addition to the high relapse rates.
The excess alpha activity during the task is possibly
attributable to ES and the associated emotions relating to
internal and external conflict and confusion distinguishing
past from present and the brain’s reaction to re-experi-
encing the past. The regions shown active in the RSA
group are shown to be involved in learning and numerous
cognitive and affective processes. The hippocampus is
active during the processing of emotion, stress, autobio-
graphical memory, learning and long-term potentiation
(LTP) of stress (Diamond et al. 2007; Frey et al. 2007;
Joels et al. 2007). This function of LTP as it applies to
learning, memory and emotional consolidation lends sup-
port to our concept of ES, such that experiential
information is encoded with the internal perceptions and
emotions associated with the experience. The amygdala has
extensive projections throughout the brain and is active
during studies of appetite, sex, aggressivity, reward, deci-
sion making, aversion, emotion, memory (Chen et al.
2007; Cooke et al. 2007; Dardou et al. 2007; de Ruiter
et al. 2007; Evans et al. 2007; Friederich et al. 2007) and
addictive disorders (Adinoff 2004; Ahmed et al. 2005;
Andrzejewski et al. 2005; Bechara and Damasio 2002;
Cardinal et al. 2004; Carelli et al. 2003; Childress et al.
1999; Di Chiara et al. 1999). These limbic structures in
combination with thalamo-cortical-brain stem interactions
in combination with OFC, AC and insular cortices are
implicated in normal brain functions as well as psychiatric
disorders; including, schizophrenia (Lacerda et al. 2007;
Mata et al. 2008; McNamara et al. 2007; Shad et al. 2006;
Toro et al. 2006), depression, obsessive-compulsive and
anxiety disorders (Cardoner et al. 2007; Corya et al. 2006;
Drevets 2007; Toro and Deakin 2005) and more impor-
tantly to this research, personality (Fahim et al. 2007; New
Table 4 Eyes-closed
comparison between RA and C
Note: All voxels listed meet
statistical criteria with t [ 4.0
and are significant B.01
Eyes-closed resting condition
Frequency
domain
Talairach x, y, z,
coordinates
Brodmann
area
Anatomical
label
Hemisphere/
location
Delta
Max 60, -39, -27 20 Inferior temporal gyrus Right temporal lobe
Min -38, 3, 29 6 Pre-central gyrus Left frontal lobe
Theta
Max 25, 10, -34 38 Uncus Right limbic lobe
Min -38, 3, 29 6 Pre-central gyrus Left frontal lobe
Alpha 1
Max -17, 24, -20 47 Inferior frontal gyrus Left frontal lobe
Min -45, -60, 50 40 Inferior parietal lobe Left parietal lobe
Alpha 2
Max -10, 45, 1 32 Anterior cingulate Left limbic lobe
Min 46, -32, 22 13 Insula Right temporal lobe
Beta 1
Max -38, -18, -34 20 Inferior temporal gyrus Left temporal lobe
Min -45, -88, 8 19 Middle occipital gyrus Left occipital lobe
Beta 2
Max -24, -18, -20 28 Parahippocampal gyrus Left limbic lobe
Min 39, 3, 43 6 Middle frontal gyrus Right frontal lobe
Beta 3
Max -17, -11, -13 37 Parahippocampal gyrus Left limbic lobe
Min 39, 17, 29 9 Middle frontal gyrus Right frontal lobe
Beta 4
Max -24, -11, -13 AmC Amygdaloid Complex Right limbic lobe
Min 46, 38, 29 46 Middle frontal gyrus Right frontal lobe
Beta 5
Max -31, -11, -41 20 Uncus Right limbic lobe
Min 46, 31, 36 9 Middle frontal gyrus Right frontal lobe
Appl Psychophysiol Biofeedback
123
et al. 2007) and SUD (Goldstein et al. 2007a, b; Verdejo-
Garcia et al. 2007; Winstanley et al. 2007). The AC, OFC
and insular cortices are shown to be involved in decision
making, reward, learning, emotion and social processing
and are shown active during autobiographical memory and
processing of self; moreover, these regions have also been
shown to be susceptible to learning and self-regulation
using LORETA neurofeedback (Adinoff et al. 2006; Bush
et al. 2000; Cannon et al. 2006, 2007, 2008; Congedo
2003; Congedo et al. 2004; Devinsky et al. 1995; Ersche
et al. 2006; Eshel et al. 2007; Fleck et al. 2006; Frank and
Claus 2006; Krain et al. 2006; O’Doherty, 2007; Pais-
Vieira et al. 2007; Roesch et al. 2007; Sakagami and
Watanabe 2007; Verdejo-Garcia et al. 2007; Wallis 2007;
Windmann et al. 2006; Winstanley et al. 2007).
Levesque and colleagues (2004) conducted research
exploring emotional regulation in children and found that
sad film excerpts elicit activation of similar regions as this
study; namely, BA 9 and 10 in the left prefrontal cortex, as
well as the OFC, BA 11, right AC and BA 47 in right
frontal regions. Studies have proposed that emotional self-
regulation involves interactions of the mid-frontal AC with
the amygdala (Posner and Rothbart 1998) and PFC damage
in adults resembles normal reactions in children (Fox et al.
2001). The obtained data in the SPESA condition implicate
these limbic and frontal regions in emotion, perception of
self, attention to internal and external states and self-reg-
ulation in conjunction with the AC and OFC. Similar fMRI
studies of negative self-reference elicit activity in similar
posterior and central regions as this study (Bjork et al.
2007). The relationship between the amygdala and these
specific regions may in fact be a regulatory loop through
which ES relating to perception of self and self-in-experi-
ence and the associated emotional, memory, attentional and
decision making processes are functionally integrated
(Walton et al. 2007; Weiskopf et al. 2003). Efferent con-
nections from the amygdala project to extensive regions of
the brain, including the hypothalamus, basal forebrain,
etorhinal cortex, ventral striatum, cingulate gyrus, orbito-
frontal cortex, hippocampus, uncus and brainstem auto-
nomic centers (Davidson et al. 2000) that are also involved
in the acoustic startle reflex (Grillon 2007; Rosen et al.
1991). These amygdaloid efferents are suggested to per-
form an important role in early developmental sensory
processing and learning (Smythies 1966) in conjunction
with occipital, temporal and insular cortices from which
the amygdala projects and receives inputs (Malin et al.
2007). In essence self-organization, self-perception, social
and familial identity and self-definition may begin to form
very early in the developmental process.
Decision making processes and the ability to form a
resistance to drugs, i.e. the ability to say no, involves
Table 5 Comparison of the means for the obtained assessment scoresfor each category measured by the assessment and the effects on thetotal score and each subtest score, within the table are the comparisonbetween addict and control scores (A) and comparisons for coding ofitems measured by the assessment and their effects on the total scoreand index scores (B) = (AB) abuse, (C) = (MD) major depression;(D) = (FHU) family history of use; (E) = (FOR) forlornness anddespair; (F) = (IA) inadequacy. In each of the tables are the index,degrees of freedom, obtained t and probability of t
A
Score df t p
Total 54 -9.440 **
Child 54 -6.136 **
Adol 54 -6.474 **
Adult 54 -8.253 **
B
AB df t p
Total 54 -4.339 **
Child 54 -2.658 **
Adol 54 -3.909 **
Adult 54 -4.503 **
C
MD df t p
Total 54 -4.390 **
Child 54 -3.244 **
Adol 54 -4.346 **
Adult 54 -3.566 **
D
FHU df t p
Total 54 -2.447 *
Child 54 -1.711
Adol 54 -2.429 *
Adult 54 -2.241 *
E
FOR df t p
Total 54 -5.258 **
Child 54 -3.034 **
Adol 54 -4.232 **
Adult 54 -6.056 **
F
IA df t p
Total 54 -6.753 **
Child 54 -4.013 **
Adol 54 -4.448 **
Adult 54 -8.370 **
* significant at B.05; ** significant at B.01
Appl Psychophysiol Biofeedback
123
numerous brain regions; including, the insular, somato-
sensory, OFC, AC and dorsolateral prefrontal cortices, as
well as the amygdala, hippocampus and specific thalamic
nuclei (Everitt and Robbins 2005). Damasio (1994) dis-
cusses the continuous monitoring of the body by the brain
as specific content and images are processed, exacting not
only changes in brain electrical activity but also chemical
reactions. Thus, as the brain communicates and orches-
trates the affective state of the individual in response to
these contents and images relating to self and self-in-
experience; it is plausible that a large scale feedback loop
is formed involving not only perceptual processes but rel-
ative autonomic functioning. This process possibly
reinforces the addicted person to become habituated to an
aroused cortical state (i.e. increased alpha/beta activity)
and when there is a shift to ‘normalcy’ it is errantly per-
ceived as abnormal thereby increasing the desire or need
for a substance to return to the aroused (or perceived
normal) state.
A diagnosis of substance dependence requires that an
individual display an inability to control his or her drug-
seeking/using behavior despite adverse consequences.
These characteristics can be described as perseverative and
impulsive or possibly under the control of drug-associated
cues; additionally, these patterns of behavior are similar to
individuals with orbitofrontal lesions (Verdejo-Garcia
et al. 2006). This is possibly attributed to changes pro-
duced by drugs of abuse; however, it may also be that the
OFC, AC and the identified regions in the amygdaloid
complex have an attribute of synaptic permanency and are
less susceptible to plasticity effects and novel learning
relative to self and self-in-experience. There is a growing
body of fMRI literature investigating cortical regions
involved in reflective self-awareness in both normal and
clinical groups. Studies show metabolic increases during
these tasks in the AC, mesofrontal, precuneus, middle
frontal, temporal and parietal regions (Bjork et al. 2007,
2008; Gusnard et al. 2001; Gusnard 2005).
The EOB comparisons (Table 3) indicate the RSA show
significant deficits in delta, theta and upper alpha band in
left dorsolateral prefrontal cortex (BA 9 and 6) and right
occipital-parietal lobe (BA 19). BA 19 is considered a
tertiary visual processing region in conjunction with BA
18. It is shown to be active during confrontation naming
tasks (Abrahams et al. 2003) and decreased in activity
when subjects make decisions about favorite brands of
consumer goods (Deppe et al. 2005). BA 19 is active
during unimodal visual motion stimulation (Deutschlander
et al. 2002), stereodepth perceptions (Fortin et al. 2002),
‘‘theory of mind’’ tasks (Goel et al. 1995), and in memory
retrieval (Osipova et al. 2006). Two points of interest
regarding this region in relation to addiction are its inter-
actions with the hippocampus and right AC (Cannon et al.
in press-b). Connections within these regions have been
demonstrated in the study of the organization of pyramidal
cells in the hippocampus (Casanova et al. 2007). Neuro-
feedback techniques for SUD have shown positive results
in this region of the cortex with substantial improvement in
program retention and long-term abstinence rates (Peniston
and Kulkosky 1989, 1990, 1991; Scott and Kaiser 1998;
Scott et al. 2002, 2005). However, whole head EEG was
not monitored in these studies. The regions in the left
prefrontal cortex are shown to be involved in working
memory, disinhibition and cognitive processes (Cabeza
et al. 2003; Cannon et al. 2007, 2008; du Boisgueheneuc
et al. 2006) and in imitation behaviors (Heiser et al. 2003).
Studies show that mental state considerations explicitly
reflecting on aspects of one’s own mental state or attribu-
tions made about the mental states of others employ these
dorsal AC and dorsal medial prefrontal regions (Gusnard
et al. 2001; Gusnard 2005). Similarly, imaging studies
targeting retrieval of personal or episodic memories
involving verbal and nonverbal material (Cabeza and Ny-
berg 2000; Cabeza et al. 2003, 2004) implicate this same
prefrontal region. The deficits as estimated by sLORETA
may offer insight into the decrements in decision making
and executive processing exhibited by addicted persons, in
addition to difficulty making judgments and interpretations
specific to social context.
The eyes-closed baseline comparisons (Table 4) show a
greater number of differences between RSA and C in all
frequencies. For the RSA group the majority of regions
showing increased current source density are shown in the
left hemisphere, while the majority of deficits are shown in
the right hemisphere. The increase in activity in the left
amygdaloid complex; including BA 20, the uncus and other
limbic regions may very well indicate a disruption in the
default mode of brain function (Harrison et al. 2008). The
central core of this default mode is suggested to utilize
more resources than a functional task and involves regions
in posterior medial and parietal regions. The RSA group
showing significantly more activity during ECB might
demonstrate valuable resources being compromised or
exhausted from normal functional processes. Similarly, it
offers support to the idea of increased dopamine production
within limbic regions in addicted populations (Blum et al.
2007; Kohnke et al. 2003) as increased dopamine produc-
tion may be reflected in excitatory frequency domains. The
prefrontal and inferior frontal lobes in the right hemisphere
are shown to be active during facial recognition and
affective memory recall especially concerning the evalua-
tion of negative emotions (Cannon et al. 2004; Kim and
Hamann, 2007; Seger et al. 2004; Tsao and Livingstone
2008). The decrease in higher frequencies in right frontal
regions in the RSA possibly elucidates many of the social
and attentional difficulties attributable to this group as
Appl Psychophysiol Biofeedback
123
these regions are also shown to be involved in executive
attention (Cannon et al. 2007, in press-a).
The comparison between the obtained scores for the
assessment show significant differences between groups for
all indexes. The five items all appear to exact negative
effects on all index scores, except for family history of use
in the childhood index. These items compose two exoge-
nous factors and three endogenous factors which appear to
exact a significant effect on systems regulating perception
of self, experience and self-in-experience. Endorsement of
emotional, physical or sexual abuse produces effects on the
index scores in negative directions. Similarly, a prior
diagnosis of depression appears to influence the index
scores in a negative direction. Family history of use
appears to produce negative effects on the total, adolescent
and adult index scores; however, it produces no effects for
the childhood index score. Forlornness and inadequacy
both produce negative effects on all index scores. Thus the
overall trend is negative for the RSA group and this group
reports significantly more instances (real or imagined) of
abuse, neglect, inadequacy and forlornness than controls.
The SPESA comparisons reflect the neurophysiology of
this negative perceptual process as well as the emotional
content of this process. The SPESA is demonstrated to be a
reliable and consistent measure of ES and self-perception
over the lifespan.
Our future research directions involve increasing the
sample size to [200; obtaining a sample of adolescents
with SUD, and developing spatial specific neurofeedback
protocols designed to focus on the regions identified in this
study (Cannon et al. in press-b). We have developed an
innovative treatment model combining LORETA neuro-
feedback, standardized group therapy, substance abuse
assignments, social-self reintegration and specialized case
management (in progress). In our discussion we must take
into consideration the limitations of the methods we uti-
lized. When we refer to the respective regions identified in
the sLORETA comparisons, we are referring to regions
delimited by a number of discrete brain volume elements
(voxels) which may be displaced as much as 3–4 cm. from
the identified maximum or minimum; however, a recent
work has addressed this issue in depth (Congedo 2006).
Similarly, the RSA group consisted of an older and more
diverse population, with many having numerous years of
substance abuse issues and the associated legal, relation-
ship and personal consequences. The control group is
younger and the groups differ in many socioeconomic and
cultural contexts to some degree.
This is the first study of its kind to investigate EEG
frequency domain patterns and sLORETA source locali-
zation of specific brain regions involved in the perception
of self and self-in-experience. Additionally, the SPESA is
the first assessment instrument of its kind to demonstrate
neurologic patterns elicited by its content. The possibility
that substance abuse interacts with specific brain regions in
specific frequencies for specific time intervals appears to be
a valid concept, noting the paradox that the resulting self-
destruction and self-deprecation to achieve a desired state
or to change or alter an undesired state transcends imme-
diate comprehension. Recent advances in the EEG-
biofeedback (neurofeedback) method (Cannon et al. 2006,
2007, 2008; Congedo 2003, 2006; Congedo et al. 2004)
offer the possibility for the individual to influence the
identified frequency anomalies in limbic and cortical
regions which in turn may influence decreases in prob-
lematic behaviors associated with SUD even after years of
continued abstinence. Many of the individuals in the RSA
group with 3 or more years of continuous abstinence report
a consistent effort to intervene on their initial reactions to
external cues and seek additional outside interpretations
from counselors, peers or family members for suggestions
in how to deal with life events, rather than go on their first
instinct. Addiction is of particular interest to our research
with spatial specific neurofeedback training and we plan to
implement studies designed to employ this methodology
for training individuals to increase low-beta activity in the
right AC which may decrease this identified alpha activity
in limbic regions as well as increase delta, theta and alpha
in the left frontal and right occipital regions. The AC and
OFC may be primary regions of interest for determining if
it is possible for individuals to learn to increase or decrease
activity in these limbic regions (Cannon et al. in press-b).
This research study is an important step in the development
of treatment protocols that afford evidence based neuro-
physiological outcome measures, in addition to providing
important information about the specific functional rela-
tionship of these cortical regions in addictive disorders.
Acknowledgements The authors express sincere gratitude to the
subjects of this study for their effort and contribution to science. We
would like to thank NovatechEEG for the use of their software;
Deymed Diagnostics for the use of their Truscan Acquisition System
and Dr. Robert Thatcher for his contribution of Neuroguide to our lab
for research purposes. We also thank Dr. Greg Reynolds for his
editorial assistance and thorough review of the manuscript.
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