Christian Machens, Cold Spring Harbor Laboratory, 3/18/03
<br>
<br>
Finding the optimal stimulus ensemble online by information maximization
<br>
<br>

Recent work has shown that neurons are often optimized towards certain
statistical properties of an animal's natural environment. Usually,
these conclusions have been drawn by a combined analysis of natural
stimuli and neural response properties. Alternatively, the stimulus
statistics that a given system ``expects'' might be extracted directly
from the system in online experiments. We demonstrate the feasibility
of this idea in electrophysiological experiments on locust auditory
receptor neurons. Using a recently developed algorithm
(Phys. Rev. Lett. 88:228104), we adapt the parameters of an initial
stimulus ensemble so as to maximize the mutual information between
stimulus and neural response. We show that the concept of optimality
cannot be treated in isolation but rather depends on further
assumptions about the system. Here, we present the optimal stimulus
ensemble for the case of a rate code and a spike timing code. [joint
work with Tim Gollisch, Olga Kolesnikova, and Andreas V. M. Herz]