Automating the design of informative sequences of sensory stimuli.
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.
Lewi
Jeremy
J
Georgia Institute of Technology, Atlanta, GA 30332, USA.
Schneider
David M
DM
Woolley
Sarah M N
SM
Paninski
Liam
L
D000161:Acoustic Stimulation / Q000379:methods; D000200:Action Potentials / Q000502:physiology; D000818:Animals; D001331:Automation; D003198:Computer Simulation; D046369:Finches; D006801:Humans; D007257:Information Theory; D016014:Linear Models; D008959:Models, Neurological; D011984:Sensory Receptor Cells / Q000145:classification / Q000502:physiology*; D013997:Time Factors