Linking mathematical modeling with human neuroimaging to segregate verbal working memory maintenance processes from stimulus encoding

Benjamin S McKenna, Gregory G Brown, Sean Patrick Andrews Drummond, Travis H Turner, Quintino Rodrigues Mano

Research output: Contribution to journalArticleResearchpeer-review

10 Citations (Scopus)


A fundamental dissociation for most working memory (WM) theories involves the separation of sensory-perceptual encoding of stimulus information from the maintenance of this information. The present paper reports tests of this separability hypothesis for visually presented pseudowords at both mathematical and neuroimaging levels of analysis. Method: Levels of analysis were linked by two experimental manipulations-visual degradation and pseudoword length variation-that coupled findings from a mathematical modeling study of WM performed in a separate sample to findings from an event-related functional MRI (fMRI) study reported in the present paper. Results from the mathematical modeling study generated parametric signatures of stimulus encoding and WM rehearsal and displacement. These signatures led to specific predictions about neurophysiological responses to study manipulations in a priori regions of interest (ROI). Results: Results demonstrated predicted dissociations of activation signatures in several ROIs. Significant patterns of brain response mirroring the encode signature were observed only during the task encode interval and only in the visual cortex and posterior fusiform gyrus. In contrast, significant brain response mirroring the rehearsal/displacement signature was observed only in the dorsolateral prefrontal cortex, inferior frontal gyrus, and supramarginal gyrus. Conclusions: Present findings support the separability hypothesis insofar as brain regions that underlie sensory-perceptual processes demonstrated encode signatures whereas brain regions that support WM maintenance demonstrated the rehearsal/displacement signature. These results also provide evidence for the utility of combining mathematical modeling with fMRI to integrate information across cognitive and neural levels of analysis
Original languageEnglish
Pages (from-to)243 - 255
Number of pages13
Issue number2
Publication statusPublished - 2013
Externally publishedYes

Cite this