Grounding Adaptive Cognitive Control in the Intrinsic, Functional Brain Organization: An HD-EEG Resting State Investigation

In a recent study, we used the dynamic temporal prediction (DTP) task to demonstrate that the capability to implicitly adapt motor control as a function of task demand is grounded in at least three dissociable neurofunctional mechanisms: expectancy implementation, expectancy violation and response i...

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Autores principales:	Gian Marco Duma, Maria Grazia Di Bono, Giovanni Mento
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	cognitive control functional connectivity high-density EEG machine learning resting-state Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
Acceso en línea:	https://doaj.org/article/82546a4c9024464d8e8774d500bdefcb
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id	oai:doaj.org-article:82546a4c9024464d8e8774d500bdefcb
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spelling	oai:doaj.org-article:82546a4c9024464d8e8774d500bdefcb2021-11-25T16:58:46ZGrounding Adaptive Cognitive Control in the Intrinsic, Functional Brain Organization: An HD-EEG Resting State Investigation10.3390/brainsci111115132076-3425https://doaj.org/article/82546a4c9024464d8e8774d500bdefcb2021-11-01T00:00:00Zhttps://www.mdpi.com/2076-3425/11/11/1513https://doaj.org/toc/2076-3425In a recent study, we used the dynamic temporal prediction (DTP) task to demonstrate that the capability to implicitly adapt motor control as a function of task demand is grounded in at least three dissociable neurofunctional mechanisms: expectancy implementation, expectancy violation and response implementation, which are supported by as many distinct cortical networks. In this study, we further investigated if this ability can be predicted by the individual brain’s functional organization at rest. To this purpose, we recorded resting-state, high-density electroencephalography (HD-EEG) in healthy volunteers before performing the DTP task. This allowed us to obtain source-reconstructed cortical activity and compute whole-brain resting state functional connectivity at the source level. We then extracted phase locking values from the parceled cortex based on the Destrieux atlas to estimate individual functional connectivity at rest in the three task-related networks. Furthermore, we applied a machine-learning approach (i.e., support vector regression) and were able to predict both behavioral (response speed and accuracy adaptation) and neural (ERP modulation) task-dependent outcome. Finally, by exploiting graph theory nodal measures (i.e., degree, strength, local efficiency and clustering coefficient), we characterized the contribution of each node to the task-related neural and behavioral effects. These results show that the brain’s intrinsic functional organization can be potentially used as a predictor of the system capability to adjust motor control in a flexible and implicit way. Additionally, our findings support the theoretical framework in which cognitive control is conceived as an emergent property rooted in bottom-up associative learning processes.Gian Marco DumaMaria Grazia Di BonoGiovanni MentoMDPI AGarticlecognitive controlfunctional connectivityhigh-density EEGmachine learningresting-stateNeurosciences. Biological psychiatry. NeuropsychiatryRC321-571ENBrain Sciences, Vol 11, Iss 1513, p 1513 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	cognitive control functional connectivity high-density EEG machine learning resting-state Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
spellingShingle	cognitive control functional connectivity high-density EEG machine learning resting-state Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571 Gian Marco Duma Maria Grazia Di Bono Giovanni Mento Grounding Adaptive Cognitive Control in the Intrinsic, Functional Brain Organization: An HD-EEG Resting State Investigation
description	In a recent study, we used the dynamic temporal prediction (DTP) task to demonstrate that the capability to implicitly adapt motor control as a function of task demand is grounded in at least three dissociable neurofunctional mechanisms: expectancy implementation, expectancy violation and response implementation, which are supported by as many distinct cortical networks. In this study, we further investigated if this ability can be predicted by the individual brain’s functional organization at rest. To this purpose, we recorded resting-state, high-density electroencephalography (HD-EEG) in healthy volunteers before performing the DTP task. This allowed us to obtain source-reconstructed cortical activity and compute whole-brain resting state functional connectivity at the source level. We then extracted phase locking values from the parceled cortex based on the Destrieux atlas to estimate individual functional connectivity at rest in the three task-related networks. Furthermore, we applied a machine-learning approach (i.e., support vector regression) and were able to predict both behavioral (response speed and accuracy adaptation) and neural (ERP modulation) task-dependent outcome. Finally, by exploiting graph theory nodal measures (i.e., degree, strength, local efficiency and clustering coefficient), we characterized the contribution of each node to the task-related neural and behavioral effects. These results show that the brain’s intrinsic functional organization can be potentially used as a predictor of the system capability to adjust motor control in a flexible and implicit way. Additionally, our findings support the theoretical framework in which cognitive control is conceived as an emergent property rooted in bottom-up associative learning processes.
format	article
author	Gian Marco Duma Maria Grazia Di Bono Giovanni Mento
author_facet	Gian Marco Duma Maria Grazia Di Bono Giovanni Mento
author_sort	Gian Marco Duma
title	Grounding Adaptive Cognitive Control in the Intrinsic, Functional Brain Organization: An HD-EEG Resting State Investigation
title_short	Grounding Adaptive Cognitive Control in the Intrinsic, Functional Brain Organization: An HD-EEG Resting State Investigation
title_full	Grounding Adaptive Cognitive Control in the Intrinsic, Functional Brain Organization: An HD-EEG Resting State Investigation
title_fullStr	Grounding Adaptive Cognitive Control in the Intrinsic, Functional Brain Organization: An HD-EEG Resting State Investigation
title_full_unstemmed	Grounding Adaptive Cognitive Control in the Intrinsic, Functional Brain Organization: An HD-EEG Resting State Investigation
title_sort	grounding adaptive cognitive control in the intrinsic, functional brain organization: an hd-eeg resting state investigation
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/82546a4c9024464d8e8774d500bdefcb
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_version_	1718412847315156992

Grounding Adaptive Cognitive Control in the Intrinsic, Functional Brain Organization: An HD-EEG Resting State Investigation

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