Spectral and anatomical patterns of large-scale synchronization predict human attentional capacity

Rouhinen, S., Siebenhühner, F., Palva, J. M. and Palva, S. (2020) Spectral and anatomical patterns of large-scale synchronization predict human attentional capacity. Cerebral Cortex, 30(10), pp. 5293-5308. (doi: 10.1093/cercor/bhaa110) (PMID:32484218)

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The capacity of visual attention determines how many visual objects may be perceived at any moment. This capacity can be investigated with multiple object tracking (MOT) tasks, which have shown that it varies greatly between individuals. The neuronal mechanisms underlying capacity limits have remained poorly understood. Phase synchronization of cortical oscillations coordinates neuronal communication within the fronto-parietal attention network and between the visual regions during endogenous visual attention. We tested a hypothesis that attentional capacity is predicted by the strength of pretarget synchronization within attention-related cortical regions. We recorded cortical activity with magneto- and electroencephalography (M/EEG) while measuring attentional capacity with MOT tasks and identified large-scale synchronized networks from source-reconstructed M/EEG data. Individual attentional capacity was correlated with load-dependent strengthening of theta (3–8 Hz), alpha (8–10 Hz), and gamma-band (30–120 Hz) synchronization that connected the visual cortex with posterior parietal and prefrontal cortices. Individual memory capacity was also preceded by crossfrequency phase–phase and phase–amplitude coupling of alpha oscillation phase with beta and gamma oscillations. Our results show that good attentional capacity is preceded by efficient dynamic functional coupling and decoupling within brain regions and across frequencies, which may enable efficient communication and routing of information between sensory and attentional systems.

Item Type:Articles
Additional Information:This work was supported by Academy of Finland (SA 266402 and 1303933 to SP and SA 253130 and 256472 MP).
Glasgow Author(s) Enlighten ID:Palva, Professor Satu and Palva, Professor Matias
Authors: Rouhinen, S., Siebenhühner, F., Palva, J. M., and Palva, S.
College/School:College of Medical Veterinary and Life Sciences > School of Psychology & Neuroscience
Journal Name:Cerebral Cortex
Publisher:Oxford University Press
ISSN (Online):1460-2199
Published Online:02 June 2020
Copyright Holders:Copyright © 2020 The Authors
First Published:First published in Cerebral Cortex 30(10): 5293-5308
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher

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