Linearly decodable functions from neural population codes
نویسندگان
چکیده
The population vector is a linear decoder for an ensemble of neurons, whose response properties are nonlinear functions of the input vector. However, previous analyses of this decoder seem to have missed the obsevation that the population vector can also be used to estimate functions of the input vector. We explore how to use singular value decomposition to delineate the class of functions which are linearly decodable from a given population of noisy neural encoders.
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ورودعنوان ژورنال:
- Neurocomputing
دوره 44-46 شماره
صفحات -
تاریخ انتشار 2002