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Dissociating frontoparietal brain networks with neuroadaptive Bayesian optimization

Lorenz, Romy, Violante, Ines R., Monti, Ricardo Pio, Montana, Giovanni, Hampshire, Adam and Leech, Robert (2018) Dissociating frontoparietal brain networks with neuroadaptive Bayesian optimization Nature Communications, 9, 1227. pp. 1227-1.

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Abstract

Understanding the unique contributions of frontoparietal networks (FPN) in cognition is challenging because they overlap spatially and are co-activated by diverse tasks. Characterizing these networks therefore involves studying their activation across many different cognitive tasks, which previously was only possible with meta-analyses. Here, we use neuroadaptive Bayesian optimization, an approach combining real-time analysis of functional neuroimaging data with machine-learning, to discover cognitive tasks that segregate ventral and dorsal FPN activity. We identify and subsequently refine two cognitive tasks, Deductive Reasoning and Tower of London, which maximally dissociate the dorsal from ventral FPN. We subsequently investigate these two FPNs in the context of a wider range of FPNs and demonstrate the importance of studying the whole activity profile across tasks to uniquely differentiate any FPN. Our findings deviate from previous meta-analyses and hypothesized functional labels for these FPNs. Taken together the results form the starting point for a neurobiologically-derived cognitive taxonomy.

Item Type: Article
Divisions : Faculty of Health and Medical Sciences > School of Psychology
Authors :
NameEmailORCID
Lorenz, Romy
Violante, Ines R.ines.violante@surrey.ac.uk
Monti, Ricardo Pio
Montana, Giovanni
Hampshire, Adam
Leech, Robert
Date : 26 March 2018
Funders : Engineering and Physical Sciences Research Council (EPSRC)
Identification Number : 10.1038/s41467-018-03657-3
Copyright Disclaimer : © The Author(s) 2018. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/.
Uncontrolled Keywords : Cognitive control; Cognitive neuroscience; Problem solving; Psychology
Depositing User : Clive Harris
Date Deposited : 09 Apr 2018 15:10
Last Modified : 09 Apr 2018 15:15
URI: http://epubs.surrey.ac.uk/id/eprint/846151

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