Why do theoretical neuroscience?
The state of modern neuroscience has often been likened to the state of physics in the 16th century. At the time, the trajectories of stars and planets in the sky were well-documented, but nobody could explain why those numbers were the way they were. It wasn’t until Kepler and Newton that it was understood that planetary motion was governed by the gravitational force exerted by the Sun, and equations were found that could not only capture all trajectory data concisely and precisely, but could also be applied to other phenomena. In neuroscience today, the situation is somewhat similar. There is a wealth of data from physiology, psychophysics, and imaging, but conceptual and rigorous frameworks that make sense of them are few and far between. Building those frameworks is the task of theoretical neuroscience.
Why use the term “computation”?
Computation as in “computational neuroscience” is used in roughly two meanings. One is the use of analytical and numerical techniques to analyze experimental data. This is done extensively by some of the other laboratories in the Computational Psychiatry Unit. In the other meaning, the brain itself is regarded as a computational device that we are trying to understand the workings of. For example, one of the most basic functions of the brain is to process sensory information in order to produce motor actions. If you are driving on the freeway and want to change lanes, you need to collect many pieces of information: how far away you are from the car in front of you, how fast you are going, whether there is a car beside you or approaching you from behind, etc. All pieces are combined to make the appropriate decision. This is an example of neural computation: the manipulation of (sensory, internal, reward) information in the brain, aimed at generating behavior. Because of the double meaning of the term “computation”, some people who work on the second meaning prefer the term “theoretical neuroscience” for what they are doing.
Why work at the systems/cognitive level?
Neuroscience has many fascinating levels of study, and which ones are of greatest interest is to a large extent a matter of taste. However, the big questions of the field have commonly revolved around the interplay between behavior (including perception, cognition, and social behavior) and neural activity. Is it possible to explain perception, memory, learning, movement, etc. in terms of the concerted activity of many neurons? Addressing such questions rigorously requires a formalization of human behavior as well as a theory of neural coding. It often also requires narrowing down “behavior” to a specific type of well-defined and experimentally controllable behavior. In my laboratory, we try to apply our theories to as wide a range of cognitive phenomena as possible. Currently, we study multisensory perception, decision-making, visual search, and visual short-term memory. The ultimate goal is not only to explain perceptual behaviors, but also to explain or even predict the neural mechanisms that underlie these behaviors.
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