Analyzing auditory neurons by learning distance functions

Inna Weiner*, Tomer Hertz, Israel Nelken, Daphna Weinshall

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

We present a novel approach to the characterization of complex sensory neurons. One of the main goals of characterizing sensory neurons is to characterize dimensions in stimulus space to which the neurons are highly sensitive (causing large gradients in the neural responses) or alternatively dimensions in stimulus space to which the neuronal response are invariant (defining iso-response manifolds). We formulate this problem as that of learning a geometry on stimulus space that is compatible with the neural responses: the distance between stimuli should be large when the responses they evoke are very different, and small when the responses they evoke are similar. Here we show how to successfully train such distance functions using rather limited amount of information. The data consisted of the responses of neurons in primary auditory cortex (A1) of anesthetized cats to 32 stimuli derived from natural sounds. For each neuron, a subset of all pairs of stimuli was selected such that the responses of the two stimuli in a pair were either very similar or very dissimilar. The distance function was trained to fit these constraints. The resulting distance functions generalized to predict the distances between the responses of a test stimulus and the trained stimuli.

Original languageEnglish
Title of host publicationAdvances in Neural Information Processing Systems 18 - Proceedings of the 2005 Conference
Pages1481-1488
Number of pages8
StatePublished - 2005
Event2005 Annual Conference on Neural Information Processing Systems, NIPS 2005 - Vancouver, BC, Canada
Duration: 5 Dec 20058 Dec 2005

Publication series

NameAdvances in Neural Information Processing Systems
ISSN (Print)1049-5258

Conference

Conference2005 Annual Conference on Neural Information Processing Systems, NIPS 2005
Country/TerritoryCanada
CityVancouver, BC
Period5/12/058/12/05

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