Computational Neuroscience


Ever wondered how the millions of neurons inside our brain work?How they communicate with each other?How they process all this information?

Computational Neuroscience aims to decode the functions of the brain in terms of information processing properties of the structures that constitute our nervous system.It is an  interdisciplinary science that links the fields of neuroscience,psychology and cognitive science with computer science,electrical engineering along with mathematics and physics.Computational Neuroscience uses the above fields in the following ways:

  • Computers are used to stimulate and model brain function
  • Principles of mathematics and physics are used to understand he functions of the brain
  • And finally we try to understand how the brain performs computations

Given the enormity of the subject how do we go about understanding the functions of the brain?Various schemes are being implemented to understand how the brain “actually works”. Scientists and researchers mainly focus the level of analysis.David Marr divided this level of analysis into 3 different types,computational,the algorithmic and the implementation levels.

The computational level is the most abstract and describes  the problem to be solved, what computations are being performed. Optimality,modularity etc are the kind of principles that are studied under this level. The algorithmic level deals with the structure of the solution,for example the nature of the subroutines used to perform a calculation. Finally, the implementation level describes how this algorithm is actually implemented in a machine. The differences between the algorithmic and implementation levels is similar to a high level language and its platform specific implementation.

Finally computational neuroscience can be thought of an amalgamation of artificial neural networks,neuroscience and dynamic systems.

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