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2008

Designing neurophysiology experiments to optimally constrain receptive field models along parametric submanifolds

9 years 2 months ago
Designing neurophysiology experiments to optimally constrain receptive field models along parametric submanifolds
Sequential optimal design methods hold great promise for improving the efficiency of neurophysiology experiments. However, previous methods for optimal experimental design have incorporated only weak prior information about the underlying neural system (e.g., the sparseness or smoothness of the receptive field). Here we describe how to use stronger prior information, in the form of parametric models of the receptive field, in order to construct optimal stimuli and further improve the efficiency of our experiments. For example, if we believe that the receptive field is well-approximated by a Gabor function, then our method constructs stimuli that optimally constrain the Gabor parameters (orientation, spatial frequency, etc.) using as few experimental trials as possible. More generally, we may believe a priori that the receptive field lies near a known sub-manifold of the full parameter space; in this case, our method chooses stimuli in order to reduce the uncertainty along the tangent ...
Jeremy Lewi, Robert J. Butera, David M. Schneider,
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2008
Where NIPS
Authors Jeremy Lewi, Robert J. Butera, David M. Schneider, Sarah M. N. Woolley, Liam Paninski
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