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Alterations in Brain Connectivity Underlying Beta Oscillations in Parkinsonism

Overview of attention for article published in PLoS Computational Biology, August 2011
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Title
Alterations in Brain Connectivity Underlying Beta Oscillations in Parkinsonism
Published in
PLoS Computational Biology, August 2011
DOI 10.1371/journal.pcbi.1002124
Pubmed ID
Authors

Rosalyn J. Moran, Nicolas Mallet, Vladimir Litvak, Raymond J. Dolan, Peter J. Magill, Karl J. Friston, Peter Brown

Abstract

Cortico-basal ganglia-thalamocortical circuits are severely disrupted by the dopamine depletion of Parkinson's disease (PD), leading to pathologically exaggerated beta oscillations. Abnormal rhythms, found in several circuit nodes are correlated with movement impairments but their neural basis remains unclear. Here, we used dynamic causal modelling (DCM) and the 6-hydroxydopamine-lesioned rat model of PD to examine the effective connectivity underlying these spectral abnormalities. We acquired auto-spectral and cross-spectral measures of beta oscillations (10-35 Hz) from local field potential recordings made simultaneously in the frontal cortex, striatum, external globus pallidus (GPe) and subthalamic nucleus (STN), and used these data to optimise neurobiologically plausible models. Chronic dopamine depletion reorganised the cortico-basal ganglia-thalamocortical circuit, with increased effective connectivity in the pathway from cortex to STN and decreased connectivity from STN to GPe. Moreover, a contribution analysis of the Parkinsonian circuit distinguished between pathogenic and compensatory processes and revealed how effective connectivity along the indirect pathway acquired a strategic importance that underpins beta oscillations. In modelling excessive beta synchrony in PD, these findings provide a novel perspective on how altered connectivity in basal ganglia-thalamocortical circuits reflects a balance between pathogenesis and compensation, and predicts potential new therapeutic targets to overcome dysfunctional oscillations.

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Geographical breakdown

Country Count As %
United Kingdom 11 3%
United States 9 3%
Germany 5 1%
France 2 <1%
China 2 <1%
Canada 2 <1%
Netherlands 1 <1%
Japan 1 <1%
Cuba 1 <1%
Other 0 0%
Unknown 303 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 87 26%
Researcher 86 26%
Student > Master 40 12%
Professor 18 5%
Student > Bachelor 18 5%
Other 59 18%
Unknown 29 9%
Readers by discipline Count As %
Neuroscience 78 23%
Agricultural and Biological Sciences 74 22%
Medicine and Dentistry 44 13%
Psychology 35 10%
Engineering 29 9%
Other 33 10%
Unknown 44 13%