Big-C Computational Neuroscience

There are two types of computational neuroscientist: A small-c computational neuroscientist uses computer simulations to understand how the hardware in the brain operates. For example, scientists often build detailed bio-physical models of neurons that capture the shape of the neuron and the way ions move through the membrane. The model can be verified by experiments to see whether it is a good description of real neurons.

A big-C Computational neuroscientist is interested in a different type of question: understanding the computational principles that shape the neurobiology of the brain. That is, principles like efficient information processing, efficient use of energy and other resourses, sparse representations, and so on. Of course many big-C Computational neuroscientists use computer simulations in their research, but their focus is figuring out what the brain is computing, rather than on understanding the hardware with which it computes.

My neuroscience research mainly focuses on big-C questions. In particular I'm interested in visual and auditory neural processing and the principles which the brain uses to process these signals in order to solve complicated tasks like recognising objects and separating and localising audio sources.