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Direct modulation index: A measure of phase amplitude coupling for neurophysiology data.
Scherer, Maximilian; Wang, Tianlu; Guggenberger, Robert; Milosevic, Luka; Gharabaghi, Alireza.
Afiliación
  • Scherer M; Institute for Neuromodulation and Neurotechnology, University Hospital and University of Tübingen, Tübingen, Germany.
  • Wang T; Krembil Brain Institute, University Health Network, Toronto, Canada.
  • Guggenberger R; Institute for Biomedical Engineering, University of Toronto, Toronto, Canada.
  • Milosevic L; Institute for Neuromodulation and Neurotechnology, University Hospital and University of Tübingen, Tübingen, Germany.
  • Gharabaghi A; Institute for Neuromodulation and Neurotechnology, University Hospital and University of Tübingen, Tübingen, Germany.
Hum Brain Mapp ; 44(5): 1862-1867, 2023 04 01.
Article en En | MEDLINE | ID: mdl-36579658
ABSTRACT
Neural communication across different spatial and temporal scales is a topic of great interest in clinical and basic science. Phase-amplitude coupling (PAC) has attracted particular interest due to its functional role in a wide range of cognitive and motor functions. Here, we introduce a novel measure termed the direct modulation index (dMI). Based on the classical modulation index, dMI provides an estimate of PAC that is (1) bound to an absolute interval between 0 and +1, (2) resistant against noise, and (3) reliable even for small amounts of data. To highlight the properties of this newly-proposed measure, we evaluated dMI by comparing it to the classical modulation index, mean vector length, and phase-locking value using simulated data. We ascertained that dMI provides a more accurate estimate of PAC than the existing methods and that is resilient to varying noise levels and signal lengths. As such, dMI permits a reliable investigation of PAC, which may reveal insights crucial to our understanding of functional brain architecture in key contexts such as behaviour and cognition. A Python toolbox that implements dMI and other measures of PAC is freely available at https//github.com/neurophysiological-analysis/FiNN.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Encéfalo / Neurofisiología Límite: Humans Idioma: En Revista: Hum Brain Mapp Asunto de la revista: CEREBRO Año: 2023 Tipo del documento: Article País de afiliación: Alemania

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Encéfalo / Neurofisiología Límite: Humans Idioma: En Revista: Hum Brain Mapp Asunto de la revista: CEREBRO Año: 2023 Tipo del documento: Article País de afiliación: Alemania