Please use this identifier to cite or link to this item: http://dx.doi.org/10.25673/36129
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dc.contributor.authorHerold, Fabian-
dc.contributor.authorGronwald, Thomas-
dc.contributor.authorScholkmann, Felix-
dc.contributor.authorZohdi, Hamoon-
dc.contributor.authorWyser, Dominik-
dc.contributor.authorMüller, Notger Germar-
dc.contributor.authorHamacher, Dennis-
dc.date.accessioned2021-03-24T07:41:21Z-
dc.date.available2021-03-24T07:41:21Z-
dc.date.issued2020-
dc.date.submitted2020-
dc.identifier.urihttps://opendata.uni-halle.de//handle/1981185920/36362-
dc.identifier.urihttp://dx.doi.org/10.25673/36129-
dc.description.abstractIn the literature, it is well established that regular physical exercise is a powerful strategy to promote brain health and to improve cognitive performance. However, exact knowledge about which exercise prescription would be optimal in the setting of exercise–cognition science is lacking. While there is a strong theoretical rationale for using indicators of internal load (e.g., heart rate) in exercise prescription, the most suitable parameters have yet to be determined. In this perspective article, we discuss the role of brain-derived parameters (e.g., brain activity) as valuable indicators of internal load which can be beneficial for individualizing the exercise prescription in exercise–cognition research. Therefore, we focus on the application of functional near-infrared spectroscopy (fNIRS), since this neuroimaging modality provides specific advantages, making it well suited for monitoring cortical hemodynamics as a proxy of brain activity during physical exercise.-
dc.description.sponsorshipDFG-Publikationsfonds 2020-
dc.language.isoeng-
dc.relation.ispartofhttps://www.mdpi.com/journal/brainsci-
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/-
dc.subjectCognitioneng
dc.subjectPersonalized medicineeng
dc.subjectExercise prescription-
dc.subject.ddc510-
dc.titleNew directions in exercise prescription : is there a role for brain-derived parameters obtained by functional near-infrared spectroscopy?eng
dc.typeArticle-
dc.identifier.urnurn:nbn:de:gbv:ma9:1-1981185920-363625-
local.versionTypepublishedVersion-
local.bibliographicCitation.journaltitleBrain Sciences-
local.bibliographicCitation.volume10-
local.bibliographicCitation.issue6-
local.bibliographicCitation.pagestart1-
local.bibliographicCitation.pageend23-
local.bibliographicCitation.publishernameMDPI AG-
local.bibliographicCitation.publisherplaceBasel-
local.bibliographicCitation.doi10.3390/brainsci10060342-
local.openaccesstrue-
dc.identifier.ppn1701698463-
local.bibliographicCitation.year2020-
cbs.sru.importDate2021-03-24T07:36:42Z-
local.bibliographicCitationEnthalten in Brain Sciences - Basel : MDPI AG, 2011-
local.accessrights.dnbfree-
Appears in Collections:Medizinische Fakultät (OA)

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