Distributed and dynamic storage of working memory stimulus information in extrastriate cortex

Kartik K. Sreenivasan, Jason Vytlacil, Mark D'Esposito

Research output: Contribution to journalArticlepeer-review

Abstract

The predominant neurobiological model of working memory (WM) posits that stimulus information is stored via stable, elevated activity within highly selective neurons. On the basis of this model, which we refer to as the canonical model, the storage of stimulus information is largely associated with lateral PFC (lPFC). A growing number of studies describe results that cannot be fully explained by the canonical model, suggesting that it is in need of revision. In this study, we directly tested key elements of the canonical model.We analyzed fMRI data collected as participants performed a task requiring WM for faces and scenes. Multivariate decoding procedures identified patterns of activity containing information about the items maintained in WM (faces, scenes, or both). Although information about WM items was identified in extrastriate visual cortex (EC) and lPFC, only EC exhibited a pattern of results consistent with a sensory representation. Information in both regions persisted even in the absence of elevated activity, suggesting that elevated population activity may not represent the storage of information in WM. Additionally, we observed that WM information was distributed across EC neural populations that exhibited a broad range of selectivity for the WM items rather than restricted to highly selective EC populations. Finally, we determined that activity patterns coding for WM information were not stable, but instead varied over the course of a trial, indicating that the neural code for WM information is dynamic rather than static. Together, these findings challenge the canonicalmodel of WM.

Original languageEnglish (US)
Pages (from-to)1141-1153
Number of pages13
JournalJournal of Cognitive Neuroscience
Volume26
Issue number5
DOIs
StatePublished - 2014

ASJC Scopus subject areas

  • Cognitive Neuroscience

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