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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