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Computational Neuroscience By: Computational Neuroscience Laboratory, Sahand University of Technology By: Computational.

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Presentation on theme: "Computational Neuroscience By: Computational Neuroscience Laboratory, Sahand University of Technology By: Computational."— Presentation transcript:

1 Computational Neuroscience By: Computational Neuroscience Laboratory, Sahand University of Technology By: Computational Neuroscience Laboratory, Sahand University of Technology

2 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.

3 Interdisciplinary Science Neuroscience Electrical Engineering Psychology Mathematics Physics Cognitive Science Computer Science

4 History 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

5 History 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

6 History 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

7 Difference between computational and experimental neuroscience in terminology Computational neuroscience relies heavily on computer simulation and modeling and so is not, perhaps purely theoretical.

8 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.

9 Aspects 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

10 Temporal representation  Temporal representation deals with how neurons represent time-varying signals

11 Population representation  Population representation deals with issues of distributed representation.

12 Levels of Computational Brain analysis in Marr’s book  Computational theory  Representation and algorithm  Hardware implementation  Computational theory  Representation and algorithm  Hardware implementation

13 Computational neuroscience Experimental facts Experimental predictions Application Quantitative knowladge psychology neuroanatomy neurophysiology neuroanatomy neurophysiolog psychology Role of computational neuroscience in the integration of experimental facts New question reflnement feedback

14 References  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


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