Literature DB >> 29649562

Carrying the past to the future: Distinct brain networks underlie individual differences in human spatial working memory capacity.

Siwei Liu1, Jia-Hou Poh1, Hui Li Koh1, Kwun Kei Ng1, Yng Miin Loke1, Joseph Kai Wei Lim1, Joanna Su Xian Chong1, Juan Zhou2.   

Abstract

Spatial working memory (SWM) relies on the interplay of anatomically separated and interconnected large-scale brain networks. EEG studies often observe load-associated sustained negative activity during SWM retention. Yet, whether and how such sustained negative activity in retention relates to network-specific functional activation/deactivation and relates to individual differences in SWM capacity remain to be elucidated. To cover these gaps, we recorded concurrent EEG-fMRI data in 70 healthy young adults during the Sternberg delayed-match-to-sample SWM task with three memory load levels. To a subset of participants (N = 28) that performed the task properly and had artefact-free fMRI and EEG data, we employed a novel temporo-spatial principal component analysis to derive load-dependent negative slow wave (NSW) from retention-related event-related potentials. The associations between NSW responses with SWM capacity were divergent in the higher (N = 14) and lower (N = 14) SWM capacity groups. Specifically, larger load-related increase in NSW amplitude was associated with greater SWM capacity for the higher capacity group but lower SWM capacity for the lower capacity group. Furthermore, for the higher capacity group, larger NSW amplitude was related to greater activation in bilateral parietal areas of the fronto-parietal network (FPN) and greater deactivation in medial frontal gyrus and posterior mid-cingulate cortex of the default mode network (DMN) during retention. In contrast, the lower capacity group did not show similar pattern. Instead, greater NSW was linked to higher deactivation in right posterior middle temporal gyrus. Our findings shed light on the possible differential EEG-informed neural network mechanism during memory maintenance underlying individual differences in SWM capacity.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Default mode network; EEG-fMRI; Fronto-parietal network; Individual difference; Negative slow wave; Spatial working memory

Mesh:

Year:  2018        PMID: 29649562     DOI: 10.1016/j.neuroimage.2018.04.014

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  4 in total

1.  Distributed Patterns of Functional Connectivity Predict Working Memory Performance in Novel Healthy and Memory-impaired Individuals.

Authors:  Emily W Avery; Kwangsun Yoo; Monica D Rosenberg; Abigail S Greene; Siyuan Gao; Duk L Na; Dustin Scheinost; Todd R Constable; Marvin M Chun
Journal:  J Cogn Neurosci       Date:  2019-10-29       Impact factor: 3.225

2.  Emergence of the Affect from the Variation in the Whole-Brain Flow of Information.

Authors:  Soheil Keshmiri; Masahiro Shiomi; Hiroshi Ishiguro
Journal:  Brain Sci       Date:  2019-12-21

3.  Multimodal network dynamics underpinning working memory.

Authors:  Andrew C Murphy; Maxwell A Bertolero; Lia Papadopoulos; David M Lydon-Staley; Danielle S Bassett
Journal:  Nat Commun       Date:  2020-06-15       Impact factor: 14.919

4.  Distinguishing vigilance decrement and low task demands from mind-wandering: A machine learning analysis of EEG.

Authors:  Christina Yi Jin; Jelmer P Borst; Marieke K van Vugt
Journal:  Eur J Neurosci       Date:  2020-06-28       Impact factor: 3.386

  4 in total

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