What Can Local Transfer Entropy Tell Us about Phase-Amplitude Coupling in Electrophysiological Signals?
cross frequency coupling
information theory
phase amplitude coupling
transfer entropy
Journal
Entropy (Basel, Switzerland)
ISSN: 1099-4300
Titre abrégé: Entropy (Basel)
Pays: Switzerland
ID NLM: 101243874
Informations de publication
Date de publication:
06 Nov 2020
06 Nov 2020
Historique:
received:
29
09
2020
revised:
03
11
2020
accepted:
04
11
2020
entrez:
8
12
2020
pubmed:
9
12
2020
medline:
9
12
2020
Statut:
epublish
Résumé
Modulation of the amplitude of high-frequency cortical field activity locked to changes in the phase of a slower brain rhythm is known as phase-amplitude coupling (PAC). The study of this phenomenon has been gaining traction in neuroscience because of several reports on its appearance in normal and pathological brain processes in humans as well as across different mammalian species. This has led to the suggestion that PAC may be an intrinsic brain process that facilitates brain inter-area communication across different spatiotemporal scales. Several methods have been proposed to measure the PAC process, but few of these enable detailed study of its time course. It appears that no studies have reported details of PAC dynamics including its possible directional delay characteristic. Here, we study and characterize the use of a novel information theoretic measure that may address this limitation: local transfer entropy. We use both simulated and actual intracranial electroencephalographic data. In both cases, we observe initial indications that local transfer entropy can be used to detect the onset and offset of modulation process periods revealed by mutual information estimated phase-amplitude coupling (MIPAC). We review our results in the context of current theories about PAC in brain electrical activity, and discuss technical issues that must be addressed to see local transfer entropy more widely applied to PAC analysis. The current work sets the foundations for further use of local transfer entropy for estimating PAC process dynamics, and extends and complements our previous work on using local mutual information to compute PAC (MIPAC).
Identifiants
pubmed: 33287030
pii: e22111262
doi: 10.3390/e22111262
pmc: PMC7712258
pii:
doi:
Types de publication
Journal Article
Langues
eng
Subventions
Organisme : The Swartz Foundation
ID : gift
Organisme : NIH HHS
ID : 5R01-NS047293-12
Pays : United States
Organisme : NINDS NIH HHS
ID : R01 NS047293
Pays : United States
Organisme : NIMH NIH HHS
ID : RF1 MH125934
Pays : United States
Organisme : NIBIB NIH HHS
ID : R01 EB023297
Pays : United States
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