Heterogenous population coding of a short-term memory and decision task

Joseph K. Jun, Paul Miller, Adrián Hernández, Antonio Zainos, Luis Lemus, Carlos D. Brody, Ranulfo Romo

Research output: Contribution to journalArticle

58 Scopus citations

Abstract

We examined neural spike recordings from prefrontal cortex (PFC) while monkeys performed a delayed somatosensory discrimination task. In general, PFC neurons displayed great heterogeneity in response to the task. That is, although individual cells spiked reliably in response to task variables from trial-to-trial, each cell had idiosyncratic combinations of response properties. Despite the great variety in response types, some general patterns held. We used linear regression analysis on the spike data to both display the full heterogeneity of the data and classify cells into categories. We compared different categories of cells and found little difference in their ability to carry information about task variables or their correlation to behavior. This suggests a distributed neural code for the task rather than a highly modularized one. Along this line, we compared the predictions of two theoretical models to the data. We found that cell types predicted by both models were not represented significantly in the population. Our study points to a different class of models that should embrace the inherent heterogeneity of the data, but should also account for the nonrandom features of the population.

Original languageEnglish (US)
Pages (from-to)916-929
Number of pages14
JournalJournal of Neuroscience
Volume30
Issue number3
DOIs
StatePublished - Jan 20 2010

All Science Journal Classification (ASJC) codes

  • Neuroscience(all)

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