Abstract

The current study examined the structural and functional connectivity of the cerebro-cerebellar network of verbal working memory as proposed by Chen and Desmond (2005a). Diffusion spectrum imaging was employed to establish structural connectivity between cerebro-cerebellar regions co-activated during a verbal working memory task. The inferior frontal gyrus, inferior parietal lobule, pons, thalamus, superior cerebellum and inferior cerebellum were used as regions of interest to reconstruct and segment the contralateral white matter cerebro-cerebellar circuitry. The segmented pathways were examined further to establish the relationship between structural and effective connectivity as well as the relationship between structural connectivity and verbal working memory performance. No direct relationship between structural and effective connectivity was found but the results demonstrated that structural connectivity is indirectly related to effective connectivity as DCM models that resembled more closely with underlying white matter pathways had a higher degree of model inference confidence. Additionally, it was demonstrated that the structural connectivity of the ponto-cerebellar tract was associated with individual differences in response time for verbal working memory. The findings of the study contribute to further our understanding of the relationship between structural and functional connectivity and the impact of variability in verbal working memory performance.

Highlights

  • Working memory is defined as a system or systems that are necessary for keeping things in mind while performing cognitive tasks such as comprehension or learning (Baddeley, 2010)

  • diffusion spectrum imaging (DSI) was used to conduct deterministic tractography of fronto-cerebellar and parieto-cerebellar white matter tracts connecting cerebro-cerebellar regions involved in verbal working memory

  • We tested the relationship between structural and effective connectivity in two ways: We first examined whether providing dynamic causal models (DCM) models with more precise information about the underlying white matter structure between regions included in the models would improve the robustness of model selection

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Summary

Introduction

Working memory is defined as a system or systems that are necessary for keeping things in mind while performing cognitive tasks such as comprehension or learning (Baddeley, 2010). One of the most influential working memory models proposed by Baddeley conceptualized working memory as a system consisting of the central executive that controls cognitive processes, the visuospatial. Cerebro-Cerebellar Verbal Working Memory Network sketchpad that stores and manipulates images and the phonological loop that stores (phonological store) and manipulates (articulatory control rehearsal system) verbal information (Baddeley, 1986). A typical Sternberg task includes three distinct phases – encoding, maintenance and retrieval. The verbal information is kept in mind through subvocal rehearsal, and in the retrieval phase, the stored information is utilized for making a response

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