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Article: Characterizing the brain's dynamical response from scalp-level neural electrical signals: a review of methodology development

TitleCharacterizing the brain's dynamical response from scalp-level neural electrical signals: a review of methodology development
Authors
KeywordsEvent-related potential
Dynamical brain response
Brain response variability
ERP latency jitter
ERP decomposition
Issue Date2020
PublisherSpringer Verlag Dordrecht.
Citation
Cognitive Neurodynamics, 2020, v. 14, p. 731-742 How to Cite?
AbstractThe brain displays dynamical system behaviors at various levels that are functionally and cognitively relevant. Ample researches have examined how the dynamical properties of brain activity reflect the neural cognitive working mechanisms. A prevalent approach in this field is to extract the trial-averaged brain electrophysiological signals as a representation of the dynamical response of the complex neural system to external stimuli. However, the responses are intrinsically variable in latency from trial to trial. The variability compromises the accuracy of the detected dynamical response pattern based on trial-averaged approach, which may mislead subsequent modelling works. More accurate characterization of the brain's dynamical response incorporating single trial variability information is of profound significance in deepening our understanding of neural cognitive dynamics and brain's working principles. Various methods have been attempted to address the trial-to-trial asynchrony issue in order to achieve an improved representation of the dynamical response. We review the latest development of methodology in this area and the contribution of latency variability-based decomposition and reconstruction of dynamical response to neural cognitive researches.
Persistent Identifierhttp://hdl.handle.net/10722/288189
ISSN
2023 Impact Factor: 3.1
2023 SCImago Journal Rankings: 0.762
PubMed Central ID
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorOuyang, G-
dc.contributor.authorZhou, C-
dc.date.accessioned2020-10-05T12:09:10Z-
dc.date.available2020-10-05T12:09:10Z-
dc.date.issued2020-
dc.identifier.citationCognitive Neurodynamics, 2020, v. 14, p. 731-742-
dc.identifier.issn1871-4080-
dc.identifier.urihttp://hdl.handle.net/10722/288189-
dc.description.abstractThe brain displays dynamical system behaviors at various levels that are functionally and cognitively relevant. Ample researches have examined how the dynamical properties of brain activity reflect the neural cognitive working mechanisms. A prevalent approach in this field is to extract the trial-averaged brain electrophysiological signals as a representation of the dynamical response of the complex neural system to external stimuli. However, the responses are intrinsically variable in latency from trial to trial. The variability compromises the accuracy of the detected dynamical response pattern based on trial-averaged approach, which may mislead subsequent modelling works. More accurate characterization of the brain's dynamical response incorporating single trial variability information is of profound significance in deepening our understanding of neural cognitive dynamics and brain's working principles. Various methods have been attempted to address the trial-to-trial asynchrony issue in order to achieve an improved representation of the dynamical response. We review the latest development of methodology in this area and the contribution of latency variability-based decomposition and reconstruction of dynamical response to neural cognitive researches.-
dc.languageeng-
dc.publisherSpringer Verlag Dordrecht.-
dc.relation.ispartofCognitive Neurodynamics-
dc.rightsThis is a post-peer-review, pre-copyedit version of an article published in [insert journal title]. The final authenticated version is available online at: https://doi.org/[insert DOI]-
dc.subjectEvent-related potential-
dc.subjectDynamical brain response-
dc.subjectBrain response variability-
dc.subjectERP latency jitter-
dc.subjectERP decomposition-
dc.titleCharacterizing the brain's dynamical response from scalp-level neural electrical signals: a review of methodology development-
dc.typeArticle-
dc.identifier.emailOuyang, G: ouyangg@hku.hk-
dc.identifier.authorityOuyang, G=rp02315-
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.1007/s11571-020-09631-4-
dc.identifier.pmid33101527-
dc.identifier.pmcidPMC7568751-
dc.identifier.scopuseid_2-s2.0-85090316135-
dc.identifier.hkuros315000-
dc.identifier.volume14-
dc.identifier.spage731-
dc.identifier.epage742-
dc.identifier.isiWOS:000567347900001-
dc.publisher.placeNetherlands-
dc.identifier.issnl1871-4080-

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