Personalized brain stimulation for effective neurointervention across participants.

Accumulating evidence from human-based research has highlighted that the prevalent one-size-fits-all approach for neural and behavioral interventions is inefficient. This approach can benefit one individual, but be ineffective or even detrimental for another. Studying the efficacy of the large range...

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Autores principales:	Nienke E R van Bueren, Thomas L Reed, Vu Nguyen, James G Sheffield, Sanne H G van der Ven, Michael A Osborne, Evelyn H Kroesbergen, Roi Cohen Kadosh
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/b522366557a840319f598ce0ff5ed0c4
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spelling	oai:doaj.org-article:b522366557a840319f598ce0ff5ed0c42021-12-02T19:57:49ZPersonalized brain stimulation for effective neurointervention across participants.1553-734X1553-735810.1371/journal.pcbi.1008886https://doaj.org/article/b522366557a840319f598ce0ff5ed0c42021-09-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1008886https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Accumulating evidence from human-based research has highlighted that the prevalent one-size-fits-all approach for neural and behavioral interventions is inefficient. This approach can benefit one individual, but be ineffective or even detrimental for another. Studying the efficacy of the large range of different parameters for different individuals is costly, time-consuming and requires a large sample size that makes such research impractical and hinders effective interventions. Here an active machine learning technique is presented across participants-personalized Bayesian optimization (pBO)-that searches available parameter combinations to optimize an intervention as a function of an individual's ability. This novel technique was utilized to identify transcranial alternating current stimulation (tACS) frequency and current strength combinations most likely to improve arithmetic performance, based on a subject's baseline arithmetic abilities. The pBO was performed across all subjects tested, building a model of subject performance, capable of recommending parameters for future subjects based on their baseline arithmetic ability. pBO successfully searches, learns, and recommends parameters for an effective neurointervention as supported by behavioral, simulation, and neural data. The application of pBO in human-based research opens up new avenues for personalized and more effective interventions, as well as discoveries of protocols for treatment and translation to other clinical and non-clinical domains.Nienke E R van BuerenThomas L ReedVu NguyenJames G SheffieldSanne H G van der VenMichael A OsborneEvelyn H KroesbergenRoi Cohen KadoshPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 9, p e1008886 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Nienke E R van Bueren Thomas L Reed Vu Nguyen James G Sheffield Sanne H G van der Ven Michael A Osborne Evelyn H Kroesbergen Roi Cohen Kadosh Personalized brain stimulation for effective neurointervention across participants.
description	Accumulating evidence from human-based research has highlighted that the prevalent one-size-fits-all approach for neural and behavioral interventions is inefficient. This approach can benefit one individual, but be ineffective or even detrimental for another. Studying the efficacy of the large range of different parameters for different individuals is costly, time-consuming and requires a large sample size that makes such research impractical and hinders effective interventions. Here an active machine learning technique is presented across participants-personalized Bayesian optimization (pBO)-that searches available parameter combinations to optimize an intervention as a function of an individual's ability. This novel technique was utilized to identify transcranial alternating current stimulation (tACS) frequency and current strength combinations most likely to improve arithmetic performance, based on a subject's baseline arithmetic abilities. The pBO was performed across all subjects tested, building a model of subject performance, capable of recommending parameters for future subjects based on their baseline arithmetic ability. pBO successfully searches, learns, and recommends parameters for an effective neurointervention as supported by behavioral, simulation, and neural data. The application of pBO in human-based research opens up new avenues for personalized and more effective interventions, as well as discoveries of protocols for treatment and translation to other clinical and non-clinical domains.
format	article
author	Nienke E R van Bueren Thomas L Reed Vu Nguyen James G Sheffield Sanne H G van der Ven Michael A Osborne Evelyn H Kroesbergen Roi Cohen Kadosh
author_facet	Nienke E R van Bueren Thomas L Reed Vu Nguyen James G Sheffield Sanne H G van der Ven Michael A Osborne Evelyn H Kroesbergen Roi Cohen Kadosh
author_sort	Nienke E R van Bueren
title	Personalized brain stimulation for effective neurointervention across participants.
title_short	Personalized brain stimulation for effective neurointervention across participants.
title_full	Personalized brain stimulation for effective neurointervention across participants.
title_fullStr	Personalized brain stimulation for effective neurointervention across participants.
title_full_unstemmed	Personalized brain stimulation for effective neurointervention across participants.
title_sort	personalized brain stimulation for effective neurointervention across participants.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/b522366557a840319f598ce0ff5ed0c4
work_keys_str_mv	AT nienkeervanbueren personalizedbrainstimulationforeffectiveneurointerventionacrossparticipants AT thomaslreed personalizedbrainstimulationforeffectiveneurointerventionacrossparticipants AT vunguyen personalizedbrainstimulationforeffectiveneurointerventionacrossparticipants AT jamesgsheffield personalizedbrainstimulationforeffectiveneurointerventionacrossparticipants AT sannehgvanderven personalizedbrainstimulationforeffectiveneurointerventionacrossparticipants AT michaelaosborne personalizedbrainstimulationforeffectiveneurointerventionacrossparticipants AT evelynhkroesbergen personalizedbrainstimulationforeffectiveneurointerventionacrossparticipants AT roicohenkadosh personalizedbrainstimulationforeffectiveneurointerventionacrossparticipants
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Personalized brain stimulation for effective neurointervention across participants.

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