
Computational Neuroscience
 Computational neuroscience is a branch of computational
science that relies on computers to perform numerical
simulation/analysis of complex neural circuitry.
 It is based on a set of mathematical equations
that govern the operation of the brain.
 It uses the computer to solve these sets of equations
such that the complexity can be reduced by observing
the results from these simulations/analyses.
 A brain simulator is essential a numerical engine
that solves these brain equations so that we can
alter any of its parameters with ease, and observe
the results it produces.
 Since the signals obtained from a real brain
are often too complex for human to comprehend,
computer is often used to process these information
to reduce their complexity so that the results
can be easily digested by human.
 It is also based on the acknowledgement that
human brain is inefficient in solving complex mathematical
equations, and allows the computer to do the hard
work of number crunching
 It also acknowledges that the human brain is
very efficient in generalizing complex concepts
much better than computers. So it is the marriage
between the brain and the computer in which the
computer does the hard work of number crunching,
and the brain does the generalizationg and abstraction
of concepts from the results crunched out by the
computer.
Computational Neuroscience 101
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