Evidence map›Paper›PMID 38253775›Full record

ArticleCognitive, affective & behavioral neuroscience2024

Time-varying functional connectivity predicts fluctuations in sustained attention in a serial tapping task.

Dolly T Seeburger, Nan Xu, Marcus Ma, Sam Larson, Christine Godwin, Shella D Keilholz, Eric H Schumacher

Open access · bronzeAbstract read
In one paragraph

Article in Cognitive, affective & behavioral neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
6.5field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 20 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Dolly T SeeburgerSchool of Psychology, Georgia Institute of Technology, Atlanta, GA, USA. dseeburger3@gatech.edu.ORCID 0009-0001-9084-0868
Nan XuDepartment of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA.
Marcus MaCollege of Computing, Georgia Institute of Technology, Atlanta, GA, USA.
Sam LarsonDepartment of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA.
Christine GodwinSchool of Psychology, Georgia Institute of Technology, Atlanta, GA, USA.
Shella D KeilholzDepartment of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA.
Eric H SchumacherSchool of Psychology, Georgia Institute of Technology, Atlanta, GA, USA. eschu@gatech.edu.
Georgia Institute of Technology · US

Funding

Spatiotemporal signatures of neural activity and neurophysiology in the BOLD signalR01MH111416 · NIMH · EMORY UNIVERSITY · PI KEILHOLZ, SHELLA D · 2016 to 2020
$1.9M
Time-varying spatiotemporal causal interactions in the functional brain networksK99NS123113 · NINDS · GEORGIA INSTITUTE OF TECHNOLOGY · PI XU, NAN · 2023 to 2024
$184k
NIMH NIH HHS R01 MH111416NINDS NIH HHS K99 NS123113
6 · The paper itself

Abstract

The mechanisms for how large-scale brain networks contribute to sustained attention are unknown. Attention fluctuates from moment to moment, and this continuous change is consistent with dynamic changes in functional connectivity between brain networks involved in the internal and external allocation of attention. In this study, we investigated how brain network activity varied across different levels of attentional focus (i.e., "zones"). Participants performed a finger-tapping task, and guided by previous research, in-the-zone performance or state was identified by low reaction time variability and out-of-the-zone as the inverse. In-the-zone sessions tended to occur earlier in the session than out-of-the-zone blocks. This is unsurprising given the way attention fluctuates over time. Employing a novel method of time-varying functional connectivity, called the quasi-periodic pattern analysis (i.e., reliable, network-level low-frequency fluctuations), we found that the activity between the default mode network (DMN) and task positive network (TPN) is significantly more anti-correlated during in-the-zone states versus out-of-the-zone states. Furthermore, it is the frontoparietal control network (FPCN) switch that differentiates the two zone states. Activity in the dorsal attention network (DAN) and DMN were desynchronized across both zone states. During out-of-the-zone periods, FPCN synchronized with DMN, while during in-the-zone periods, FPCN switched to synchronized with DAN. In contrast, the ventral attention network (VAN) synchronized more closely with DMN during in-the-zone periods compared with out-of-the-zone periods. These findings demonstrate that time-varying functional connectivity of low frequency fluctuations across different brain networks varies with fluctuations in sustained attention or other processes that change over time.

Indexed as

Brain MappingMagnetic Resonance ImagingBrainHumansReaction TimeAssociation networksDefault mode networkLow-frequency fluctuationQuasi-periodic patternSustained attentionTime-varying functional connectivity

Identifiers

PMID38253775
PMCPMC10979291
OpenAlexW4391096134

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Registered trials

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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.