Abstract
Functional imaging has been used extensively to identify and validate disease-specific networks as biomarkers in neurodegenerative disorders. It is not known, however, whether the connectivity patterns in these networks differ with disease progression compared to the beneficial adaptations that may also occur over time. To distinguish the 2 responses, we focused on assortativity, the tendency for network connections to link nodes with similar properties. High assortativity is associated with unstable, inefficient flow through the network. Low assortativity, by contrast, involves more diverse connections that are also more robust and efficient. We found that in Parkinson's disease (PD), network assortativity increased over time. Assoratitivty was high in clinically aggressive genetic variants but was low for genes associated with slow progression. Dopaminergic treatment increased assortativity despite improving motor symptoms, but subthalamic gene therapy, which remodels PD networks, reduced this measure compared to sham surgery. Stereotyped changes in connectivity patterns underlie disease progression and treatment responses in PD networks.
Original language | English (US) |
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Pages (from-to) | 917-932 |
Number of pages | 16 |
Journal | Cerebral Cortex |
Volume | 33 |
Issue number | 4 |
DOIs | |
State | Published - Feb 15 2023 |
Keywords
- FDG PET
- Parkinson's disease
- brain networks
- graph theory
- metabolic connectivity
ASJC Scopus subject areas
- Cognitive Neuroscience
- Cellular and Molecular Neuroscience