Computational Neuroscience

Computational Neuroscience

By: Computational Neuroscience Laboratory, Sahand University of

Technologyhttp://ee.sut.ac.ir/Labs/CNLab/index.htm

By: Computational Neuroscience Laboratory, Sahand University of

Technologyhttp://ee.sut.ac.ir/Labs/CNLab/index.htm

What is Computational Neuroscience

What is Computational Neuroscience

Computational neuroscience is the study of brain function in terms of the information processing properties of the structures that make up the nervous system.

Computational neuroscience is the study of brain function in terms of the information processing properties of the structures that make up the nervous system.

Interdisciplinary ScienceInterdisciplinary Science

NeuroscienceNeuroscience

Electrical Engineering Electrical Engineering

PsychologyPsychology Mathematics

Physics

Cognitive ScienceCognitive Science Computer Science

HistoryHistory

Louis Lapicque introduced the integrate and fire model of the neuron in 1907

Hodgkin & Huxley created the first biophysical model of the action potential in 1952

Louis Lapicque introduced the integrate and fire model of the neuron in 1907

Hodgkin & Huxley created the first biophysical model of the action potential in 1952

HistoryHistory

Hubel & Wiesel in 1959 discovered Receptive Field and Early visual processing.

David Marr's work focused on theory for cerebral neocortex

Hubel & Wiesel in 1959 discovered Receptive Field and Early visual processing.

David Marr's work focused on theory for cerebral neocortex

HistoryHistory

Wilfrid Rall presented the first multicompartmental model using cable theory in 1960

The term "computational neuroscience" was introduced by Eric L. Schwartz in 1985

Wilfrid Rall presented the first multicompartmental model using cable theory in 1960

The term "computational neuroscience" was introduced by Eric L. Schwartz in 1985

Difference between computational and experimental

neuroscience in terminology

Difference between computational and experimental

neuroscience in terminology

• Computational neuroscience relies heavily on computer simulation and modeling and so is not, perhaps purely theoretical.

• Computational neuroscience relies heavily on computer simulation and modeling and so is not, perhaps purely theoretical.

Computational neuroscience and neural computing

Computational neuroscience and neural computing

Neural computing has become mainly concerned with technical applications of the theory, interested mainly in solving difficult engineering problems, while computational neuroscience has become mainly concerned with the application of the theory to understanding natural systems.

Neural computing has become mainly concerned with technical applications of the theory, interested mainly in solving difficult engineering problems, while computational neuroscience has become mainly concerned with the application of the theory to understanding natural systems.

Aspects of representationAspects of representation

Computational neuroscience has focused on two distinct aspects of representation

temporal representation population representation

Computational neuroscience has focused on two distinct aspects of representation

temporal representation population representation

Temporal representationTemporal representation

Temporal representation deals with how neurons represent time-varying signals

Temporal representation deals with how neurons represent time-varying signals

Population representationPopulation representation

Population representation deals with issues of distributed representation.

Population representation deals with issues of distributed representation.

Levels of Computational Brain analysis in Marr’s book

Levels of Computational Brain analysis in Marr’s book

Computational theoryRepresentation and algorithmHardware implementation

Computational theoryRepresentation and algorithmHardware implementation

Computational neuroscience

Experimental facts

Experimental predictions

Application

Quantitativeknowladge

psychology

neuroanatomy

neurophysiology

neuroanatomy

neurophysiolog

psychology

Role of computational neuroscience in the integration of

experimental facts

Role of computational neuroscience in the integration of

experimental factsNew question

reflnement feedback

ReferencesReferences

Fundamental of computational neuroscience by T. Trappenberg Theoretical neuroscience by P. Dayan and L. Abbott What is computational neuroscience? by P. Churchland, C. Koch,

and T. Sejnowski Computational neuroscience by E. Schwartz Recherches quantitatives sur l'excitation électrique des nerfs traitée

comme une polarisation by L. Lapicque Lapicque's 1907 paper: from frogs to integrate-and-fire by N. Brunel

and M. VanRossum Receptive fields, binocular interaction and functional architecture in

the cat's visual cortex by D. Hubel and T. Wiesel Computational neuroscience by C. Eliasmith

Fundamental of computational neuroscience by T. Trappenberg Theoretical neuroscience by P. Dayan and L. Abbott What is computational neuroscience? by P. Churchland, C. Koch,

and T. Sejnowski Computational neuroscience by E. Schwartz Recherches quantitatives sur l'excitation électrique des nerfs traitée

comme une polarisation by L. Lapicque Lapicque's 1907 paper: from frogs to integrate-and-fire by N. Brunel

and M. VanRossum Receptive fields, binocular interaction and functional architecture in

the cat's visual cortex by D. Hubel and T. Wiesel Computational neuroscience by C. Eliasmith