Literature DB >> 31911186

The role of coupling connections in a model of the cortico-basal ganglia-thalamocortical neural loop for the generation of beta oscillations.

Chen Liu1, Changsong Zhou2, Jiang Wang3, Chris Fietkiewicz4, Kenneth A Loparo4.   

Abstract

Excessive neural synchronization in the cortico-basal ganglia-thalamocortical circuits in the beta (β) frequency range (12-35 Hz) is closely associated with dopamine depletion in Parkinson's disease (PD) and correlated with movement impairments, but the neural basis remains unclear. In this work, we establish a double-oscillator neural mass model for the cortico-basal ganglia-thalamocortical closed-loop system and explore the impacts of dopamine depletion induced changes in coupling connections within or between the two oscillators on neural activities within the loop. Spectral analysis of the neural mass activities revealed that the power and frequency of their principal components are greatly dependent on the coupling strengths between nuclei. We found that the increased intra-coupling in the basal ganglia-thalamic (BG-Th) oscillator contributes to increased oscillations in the lower β frequency band (12-25 Hz), while increased intra-coupling in the cortical oscillator mainly contributes to increased oscillations in the upper β frequency band (26-35 Hz). Interestingly, pathological upper β oscillations in the cortical oscillator may be another origin of the lower β oscillations in the BG-Th oscillator, in addition to increased intra-coupling strength within the BG-Th network. Lower β oscillations in the BG-Th oscillator can also change the dominant oscillation frequency of a cortical nucleus from the upper to the lower β band. Thus, this work may pave the way towards revealing a possible neural basis underlying the Parkinsonian state.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Beta oscillations; Cortico-basal ganglia-thalamocortical circuits; Coupling strength; Double-oscillator system; Neural mass model

Mesh:

Year:  2019        PMID: 31911186     DOI: 10.1016/j.neunet.2019.12.021

Source DB:  PubMed          Journal:  Neural Netw        ISSN: 0893-6080


  3 in total

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  3 in total

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