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Scientific article
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English

Spontaneous Network Coupling Enables Efficient Task Performance without Local Task-Induced Activations

Contributors

Allaman, Leslie; Mottaz, Anais; Kleinschmidt, Andréas Karl; Guggisberg, Adrian

Published in

Journal of Neuroscience, vol. 40, no. 50, p. 9663-9675

Publication date

2020

Abstract

Neurobehavioral studies in humans have long concentrated on changes in local activity levels during repetitive executions of a task. Spontaneous neural coupling within extended networks has latterly been found to also influence performance. Here, we intend to uncover the underlying mechanisms, the relative importance, and the interaction between spontaneous coupling and task-induced activations. To do so, we recorded two groups of healthy participants (male and female) during rest and while they performed either a visual perception or a motor sequence task. We demonstrate that, for both tasks, stronger activations during the task as well as greater network coupling through spontaneous α rhythms at rest predict performance. However, high performers present an absence of classical task-induced activations and, instead, stronger spontaneous network coupling. Activations were thus a compensation mechanism needed only in subjects with lower spontaneous network interactions. This challenges classical models of neural processing and calls for new strategies in attempts to train and enhance performance.SIGNIFICANCE STATEMENT Our findings challenge the widely accepted notion that task-induced activations are of paramount importance for behavior. This will have an important impact on interpretations of human neurobehavioral research. They further link the widely used techniques of quantifying network communication in the brain with classical neuroscience methods and demonstrate possible ways of how network communication influences human behavior. Traditional training methods attempt to enhance neural activations through task repetitions. Our findings suggest a more efficient neural target for learning: enhancing spontaneous neural interactions. This will be of major interest for a large variety of scientific fields with very broad applications in schools, work, and others.

Keywords

  • Event-related desynchronization
  • Motor planning
  • Neural coupling
  • Visual perception

UNIGE affiliation entities

UNIGE research groups

Funding

Citation (ISO format)

ALLAMAN, Leslie et al. Spontaneous Network Coupling Enables Efficient Task Performance without Local Task-Induced Activations. In: Journal of Neuroscience, 2020, vol. 40, n° 50, p. 9663–9675. doi: 10.1523/JNEUROSCI.1166-20.2020

Main files (2)

Article (Published version)
CC BY-NC
Article (Accepted version)
CC BY-NC

Identifiers

Additional URL for this publication

https://www.jneurosci.org/content/40/50/9663

Journal ISSN

0270-6474
332views
252downloads

Technical informations

Creation

17/12/2020 12:56:00

First validation

17/12/2020 12:56:00

Update

17/01/2025 16:14:13

Status update

17/01/2025 16:14:13

Last indexation

17/01/2025 16:26:25
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