Computational and mathematical neuroscience

dynamics modeling perception
awareness vision networks
A.I. memory compartmentation
engineering simulation
systems machine learning
language   attention    theory

What is computational and mathematical neuroscience?

The brain is a very complex system composed of many interacting elements - proteins, neurons, and different anatomical regions. Understanding of how their interactions give rise to sophisticated functions often requires formal mathematical theory.

Computational neuroscience uses mathematical models to describe and explain the computations in single neurons, networks of neurons, or a whole system.

Close collaboration with experimental neuroscientists provides real biological data to constrain the models. In turn, formalizing theories of brain function by mathematical modelling generates predictions, which can then be tested in experiments.

This area of neuroscience provides a very powerful approach to studying the brain.  

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Where in BN is it mainly carried out?

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How? Methods and techniques

Techniques routinely in use include; dynamical systems theory, computer simulations, and machine learning.

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Highlights of the computational and mathematical research in BN

  • Epilepsy
  • Synchronization of different brain areas
  • Mathematcial modelling and deep brain stimulation
  • Channel dynamics
  • Decision making

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