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Computational Modeling of Cognitive Activity. Prof. Larry M. Manevitz Course Slides: 2012. Aim of Course: To view some of the methods and results of Cognitive and Brain Modeling What is it good for? What does it replace?

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Computational modeling of cognitive activity

Computational Modeling of Cognitive Activity

Prof. Larry M. Manevitz

Course Slides: 2012



Some cognitive tasks
Some Cognitive Tasks Cognitive and Brain Modeling

  • Memory

    • Declarative

    • Procedural

    • Associative

  • Decision Making

  • Pattern Identification

  • Language

  • Speech

  • Reading


  • What is the brain? Cognitive and Brain Modeling

  • What is cognition?

    • We can think of brain activity as a computation.

    • Can we do “reverse engineering”?

    • Can we explain activity?

  • Many approaches

    • Physiological Explanations

    • Computational Explanations

    • Cognitive Explanations


Related fields related methods
Related Fields, Related Methods? Cognitive and Brain Modeling

  • Neurophysiology

    • Cell Structure

    • System Biology

  • Cognitive Psychology

    • Psychophysical Experiments

  • Important Tools

    • fMRI

    • EEG

    • Others …



What tools are appropriate
What tools are appropriate? Cognitive and Brain Modeling


Basic structure of neural system
Basic Structure of Neural System Cognitive and Brain Modeling

  • From work of Cajal (as opposed to Golgi), the neural system is separated into discrete cells.

  • So we need to understand at least

    • Computational aspect of separate cells

    • Computational aspect of network of cells


  • Let’s start with the simplest model. Cognitive and Brain Modeling

  • The neural system is known to be cellular.

    That means there is not continuous connections (like an electric wire) but discrete elements.


Examples of neurons
Examples of Neurons Cognitive and Brain Modeling


Neuron stains
Neuron Stains Cognitive and Brain Modeling



Definitions and history
Definitions and History understand how the brain works.

  • McCullough –Pitts Neuron

  • Perceptron

  • Adaline

  • Linear Separability

  • Multi-Level Neurons

  • Neurons with Loops

L. Manevitz U. Haifa


Natural versus artificial neuron
Natural versus Artificial Neuron understand how the brain works.

  • Natural Neuron McCullough Pitts Neuron

L. Manevitz U. Haifa


Sample feed forward network no loops
Sample Feed forward Network (No loops) understand how the brain works.

Weights

Output

Weights

Weights

Input

Wji

Vik

F(S wji xj

L. Manevitz U. Haifa


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