Dissociating frontoparietal brain networks with neuroadaptive Bayesian optimization

Romy Lorenz; Ines R. Violante; Ricardo Pio Monti; Giovanni Montana; Adam Hampshire; Robert Leech

doi:10.1038/s41467-018-03657-3

Nature Communications (Mar 2018)

Dissociating frontoparietal brain networks with neuroadaptive Bayesian optimization

Romy Lorenz,
Ines R. Violante,
Ricardo Pio Monti,
Giovanni Montana,
Adam Hampshire,
Robert Leech

Affiliations

Romy Lorenz: Department of Medicine, Computational, Cognitive and Clinical Neuroscience Laboratory (C3NL), Imperial College London
Ines R. Violante: School of Psychology, Faculty of Health and Medical Sciences, University of Surrey
Ricardo Pio Monti: Gatsby Computational Neuroscience Unit, University College London
Giovanni Montana: Department of Mathematics, Imperial College London
Adam Hampshire: Department of Medicine, Computational, Cognitive and Clinical Neuroscience Laboratory (C3NL), Imperial College London
Robert Leech: Centre for Neuroimaging Science, King’s College London

DOI: https://doi.org/10.1038/s41467-018-03657-3
Journal volume & issue: Vol. 9, no. 1
pp. 1 – 14

Abstract

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The unique contributions of different frontoparietal networks (FPNs) in cognition remains unclear. Here, authors use neuroadaptive Bayesian optimization to identify cognitive tasks that segregate dorsal and ventral FPNs and reveal complex many-to-many mappings between cognitive tasks and FPNs.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

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