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How Behavioral Constraints May Determine Optimal Sensory Representations
 

Summary: How Behavioral Constraints May Determine
Optimal Sensory Representations
Emilio Salinas
Department of Neurobiology and Anatomy, Wake Forest University School of Medicine, Winston-Salem, North Carolina, United States of America
The sensory-triggered activity of a neuron is typically characterized in terms of a tuning curve, which describes the
neuron's average response as a function of a parameter that characterizes a physical stimulus. What determines the
shapes of tuning curves in a neuronal population? Previous theoretical studies and related experiments suggest that
many response characteristics of sensory neurons are optimal for encoding stimulus-related information. This notion,
however, does not explain the two general types of tuning profiles that are commonly observed: unimodal and
monotonic. Here I quantify the efficacy of a set of tuning curves according to the possible downstream motor
responses that can be constructed from them. Curves that are optimal in this sense may have monotonic or
nonmonotonic profiles, where the proportion of monotonic curves and the optimal tuning-curve width depend on the
general properties of the target downstream functions. This dependence explains intriguing features of visual cells
that are sensitive to binocular disparity and of neurons tuned to echo delay in bats. The numerical results suggest that
optimal sensory tuning curves are shaped not only by stimulus statistics and signal-to-noise properties but also
according to their impact on downstream neural circuits and, ultimately, on behavior.
Citation: Salinas E (2006) How behavioral constraints may determine optimal sensory representations. PLoS Biol 4(12): e387. DOI: 10.1371/journal.pbio.0040387
Introduction
Sensory neurons respond to physical stimuli, and this
relationship is often quantified by plotting their evoked

  

Source: Andrzejak, Ralph Gregor - Departament de Tecnologia, Universitat Pompeu Fabra

 

Collections: Computer Technologies and Information Sciences