Evidence map›Paper›PMID 33185986›Full record

ArticleBrain and behavior2021

Decreased connection density and modularity of functional brain networks during n-back working memory paradigm.

Zalan Kaposzta, Orestis Stylianou, Peter Mukli, Andras Eke, Frigyes Samuel Racz

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Article in Brain and behavior, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

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14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Zalan KaposztaDepartment of Physiology, Semmelweis University, Budapest, Hungary.ORCID 0000-0002-1002-4482
Orestis StylianouDepartment of Physiology, Semmelweis University, Budapest, Hungary.ORCID 0000-0003-4457-4551
Peter MukliDepartment of Physiology, Semmelweis University, Budapest, Hungary.ORCID 0000-0003-4355-8103
Andras EkeDepartment of Physiology, Semmelweis University, Budapest, Hungary.ORCID 0000-0002-3668-2870
Frigyes Samuel RaczDepartment of Physiology, Semmelweis University, Budapest, Hungary.ORCID 0000-0001-9077-498X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionInvestigating how the brain adapts to increased mental workload through large-scale functional reorganization appears as an important research question. Functional connectivity (FC) aims at capturing how disparate regions of the brain dynamically interact, while graph theory provides tools for the topological characterization of the reconstructed functional networks. Although numerous studies investigated how FC is altered in response to increased working memory (WM) demand, current results are still contradictory as few studies confirmed the robustness of these findings in a low-density setting.

methodsIn this study, we utilized the n-back WM paradigm, in which subjects were presented stimuli (single digits) sequentially, and their task was to decide for each given stimulus if it matched the one presented n-times earlier. Electroencephalography recordings were performed under a control (0-back) and two task conditions of varying difficulty (2- and 3-back). We captured the characteristic connectivity patterns for each difficulty level by performing FC analysis and described the reconstructed functional networks with various graph theoretical measures.

resultsWe found a substantial decrease in FC when transitioning from the 0- to the 2- or 3-back conditions, however, no differences relating to task difficulty were identified. The observed changes in brain network topology could be attributed to the dissociation of two (frontal and occipitotemporal) functional modules that were only present during the control condition. Furthermore, behavioral and performance measures showed both positive and negative correlations to connectivity indices, although only in the higher frequency bands.

conclusionThe marked decrease in FC may be due to temporarily abandoned connections that are redundant or irrelevant in solving the specific task. Our results indicate that FC analysis is a robust tool for investigating the response of the brain to increased cognitive workload.

Indexed as

Brain MappingMemory, Short-TermBrainElectroencephalographyHumansMagnetic Resonance ImagingNerve Netbraincognitionelectroencephalographyfunctional connectivityworking memory

Identifiers

PMID33185986
PMCPMC7821619

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.