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dc.contributor.author
Velarde, Osvaldo Matias  
dc.contributor.author
Urdapilleta, Eugenio  
dc.contributor.author
Mato, German  
dc.contributor.author
Dellavale Clara, Hector Damian  
dc.date.available
2021-01-22T18:26:00Z  
dc.date.issued
2019-11-15  
dc.identifier.citation
Velarde, Osvaldo Matias; Urdapilleta, Eugenio; Mato, German; Dellavale Clara, Hector Damian; Bifurcation structure determines different phase-amplitude coupling patterns in the activity of biologically plausible neural networks; Academic Press Inc Elsevier Science; Journal Neuroimag; 202; 116031; 15-11-2019; 1-20  
dc.identifier.issn
1053-8119  
dc.identifier.uri
http://hdl.handle.net/11336/123495  
dc.description.abstract
Phase-amplitude cross frequency coupling (PAC) is a rather ubiquitous phenomenon that has been observed in a variety of physical domains; however, the mechanisms underlying the emergence of PAC and its functional significance in the context of neural processes are open issues under debate. In this work we analytically demonstrate that PAC phenomenon naturally emerges in mean-field models of biologically plausible networks, as a signature of specific bifurcation structures. The proposed analysis, based on bifurcation theory, allows the identification of the mechanisms underlying oscillatory dynamics that are essentially different in the context of PAC. Specifically, we found that two PAC classes can coexist in the complex dynamics of the analyzed networks: 1) harmonic PAC which is an epiphenomenon of the nonsinusoidal waveform shape characterized by the linear superposition of harmonically related spectral components, and 2) nonharmonic PAC associated with “true” coupled oscillatory dynamics with independent frequencies elicited by a secondary Hopf bifurcation and mechanisms involving periodic excitation/inhibition (PEI) of a network population. Importantly, these two PAC types have been experimentally observed in a variety of neural architectures confounding traditional parametric and nonparametric PAC metrics, like those based on linear filtering or the waveform shape analysis, due to the fact that these methods operate on a single one-dimensional projection of an intrinsically multidimensional system dynamics. We exploit the proposed tools to study the functional significance of the PAC phenomenon in the context of Parkinson's disease (PD). Our results show that pathological slow oscillations (e.g. β band) and nonharmonic PAC patterns emerge from dissimilar underlying mechanisms (bifurcations) and are associated to the competition of different BG-thalamocortical loops. Thus, this study provides theoretical arguments that demonstrate that nonharmonic PAC is not an epiphenomenon related to the pathological β band oscillations, thus supporting the experimental evidence about the relevance of PAC as a potential biomarker of PD.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Academic Press Inc Elsevier Science  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/  
dc.subject
BIFURCATION STRUCTURE  
dc.subject
CROSS-FREQUENCY COUPLING  
dc.subject
NEURAL NETWORK  
dc.subject
PARKINSON'S DISEASE  
dc.subject
PHASE-AMPLITUDE COUPLING  
dc.subject.classification
Otras Ciencias Físicas  
dc.subject.classification
Ciencias Físicas  
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS  
dc.title
Bifurcation structure determines different phase-amplitude coupling patterns in the activity of biologically plausible neural networks  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2020-12-16T18:26:01Z  
dc.journal.volume
202  
dc.journal.number
116031  
dc.journal.pagination
1-20  
dc.journal.pais
Países Bajos  
dc.description.fil
Fil: Velarde, Osvaldo Matias. Comisión Nacional de Energía Atómica. Gerencia del Área de Energía Nuclear. Instituto Balseiro; Argentina. Universidad Nacional de Cuyo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte; Argentina  
dc.description.fil
Fil: Urdapilleta, Eugenio. Comisión Nacional de Energía Atómica. Gerencia del Área de Energía Nuclear. Instituto Balseiro; Argentina. Universidad Nacional de Cuyo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte; Argentina  
dc.description.fil
Fil: Mato, German. Comisión Nacional de Energía Atómica. Gerencia del Área de Energía Nuclear. Instituto Balseiro; Argentina. Universidad Nacional de Cuyo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte; Argentina  
dc.description.fil
Fil: Dellavale Clara, Hector Damian. Comisión Nacional de Energía Atómica. Gerencia del Área de Energía Nuclear. Instituto Balseiro; Argentina. Universidad Nacional de Cuyo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte; Argentina  
dc.journal.title
Journal Neuroimag  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://reader.elsevier.com/reader/sd/pii/S1053811919306123?token=84A7B68FD18EE64C83E1D40E69265629ED0A56152E92FC9075970659A986D633B7552B4A4D74332782EFA0E494F11C3C  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/https://doi.org/10.1016/j.neuroimage.2019.116031