1-s2.0-S1053811920310958-main.pdf 1,68MB
1000 Titel
  • Integration and segregation across large-scale intrinsic brain networks as a marker of sustained attention and task-unrelated thought
1000 Autor/in
  1. Zuberer, Agnieszka |
  2. Kucyi, Aaron |
  3. Yamashita, Ayumu |
  4. Wu, Charley M. |
  5. Walter, Martin |
  6. Valera, Eve M. |
  7. Esterman, Michael |
1000 Erscheinungsjahr 2021
1000 LeibnizOpen
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2021-01-06
1000 Erschienen in
1000 Quellenangabe
  • 229:117610
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2021
1000 Lizenz
1000 Verlagsversion
  • |
1000 Ergänzendes Material
  • |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Sustained attention is a fundamental cognitive process that can be decoupled from distinct external events, and instead emerges from ongoing intrinsic large-scale network interdependencies fluctuating over seconds to minutes. Lapses of sustained attention are commonly associated with the subjective experience of mind wandering and task-unrelated thoughts. Little is known about how fluctuations in information processing underpin sustained attention, nor how mind wandering undermines this information processing. To overcome this, we used fMRI to investigate brain activity during subjects' performance (n=29) of a cognitive task that was optimized to detect and isolate continuous fluctuations in both sustained attention (via motor responses) and task-unrelated thought (via subjective reports). We then investigated sustained attention with respect to global attributes of communication throughout the functional architecture, i.e., by the segregation and integration of information processing across large scale-networks. Further, we determined how task-unrelated thoughts related to these global information processing markers of sustained attention. The results show that optimal states of sustained attention favor both enhanced segregation and reduced integration of information processing in several task-related large-scale cortical systems with concurrent reduced segregation and enhanced integration in the auditory and sensorimotor systems. Higher degree of mind wandering was associated with losses of the favored segregation and integration of specific subsystems in our sustained attention model. Taken together, we demonstrate that intrinsic ongoing neural fluctuations are characterized by two converging communication modes throughout the global functional architecture, which give rise to optimal and suboptimal attention states. We discuss how these results might potentially serve as neural markers for clinically abnormal attention. SIGNIFICANCE STATEMENT: Most of our brain activity unfolds in an intrinsic manner, i.e., is unrelated to immediate external stimuli or tasks. Here we use a gradual continuous performance task to map this intrinsic brain activity to both fluctuations of sustained attention and mind wandering. We show that optimal sustained attention is associated with concurrent segregation and integration of information processing within many large-scale brain networks, while task-unrelated thought is related to sub-optimal information processing in specific subsystems of this sustained attention network model. These findings provide a novel information processing framework for investigating the neural basis of sustained attention, by mapping attentional fluctuations to genuinely global features of intra-brain communication.
1000 Sacherschließung
lokal Segregation
lokal Sustained attention
lokal Integration
lokal fMRI
lokal Spontaneous thought
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
1000 Label
1000 Förderer
  1. Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung |
  2. Bundesministerium für Bildung und Forschung |
  3. Deutsche Forschungsgemeinschaft |
  4. U.S. Department of Veterans Affairs |
1000 Fördernummer
  1. P2ZHP1_181435
  2. 01IS18039A
  3. EXC 2064/1 – 390727645
  4. I01CX001653
1000 Förderprogramm
  1. -
  2. Tübingen AI Center
  3. Germany’s Excellence Strategy
  4. Clinical Sciences Research and Development
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung |
    1000 Förderprogramm -
    1000 Fördernummer P2ZHP1_181435
  2. 1000 joinedFunding-child
    1000 Förderer Bundesministerium für Bildung und Forschung |
    1000 Förderprogramm Tübingen AI Center
    1000 Fördernummer 01IS18039A
  3. 1000 joinedFunding-child
    1000 Förderer Deutsche Forschungsgemeinschaft |
    1000 Förderprogramm Germany’s Excellence Strategy
    1000 Fördernummer EXC 2064/1 – 390727645
  4. 1000 joinedFunding-child
    1000 Förderer U.S. Department of Veterans Affairs |
    1000 Förderprogramm Clinical Sciences Research and Development
    1000 Fördernummer I01CX001653
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6426467.rdf
1000 Erstellt am 2021-03-26T10:42:02.544+0100
1000 Erstellt von 242
1000 beschreibt frl:6426467
1000 Bearbeitet von 122
1000 Zuletzt bearbeitet Tue Mar 30 08:48:10 CEST 2021
1000 Objekt bearb. Tue Mar 30 08:48:09 CEST 2021
1000 Vgl. frl:6426467
1000 Oai Id
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1000 Sichtbarkeit Metadaten public
1000 Sichtbarkeit Daten public
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