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J Comput Neurosci. 2011 Feb;30(1):181-200. doi: 10.1007/s10827-010-0248-1. Epub 2010 Jun 16.

Automating the design of informative sequences of sensory stimuli.

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Georgia Institute of Technology, Atlanta, GA 30332, USA.


Adaptive stimulus design methods can potentially improve the efficiency of sensory neurophysiology experiments significantly; however, designing optimal stimulus sequences in real time remains a serious technical challenge. Here we describe two approximate methods for generating informative stimulus sequences: the first approach provides a fast method for scoring the informativeness of a batch of specific potential stimulus sequences, while the second method attempts to compute an optimal stimulus distribution from which the experimenter may easily sample. We apply these methods to single-neuron spike train data recorded from the auditory midbrain of zebra finches, and demonstrate that the resulting stimulus sequences do in fact provide more information about neuronal tuning in a shorter amount of time than do more standard experimental designs.

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