Mechanisms of Correlated Neuronal Activity in the Globus Pallidus
TL;DR
A computational model was developed in which GPe neurons are represented as coupled phase oscillators influenced by experimentally derived phase-response curves and extrinsic inputs, showing that while the model captures general trends, discrepancies exist in peak amplitude and decay rates, suggesting that key biological details of the GPe are not represented in the model.
Abstract
This thesis investigates the mechanisms of correlated neuronal activity in the globus pallidus externus (GPe), a key structure in the basal ganglia. Neuronal activity in the GPe is reportedly decorrelated in healthy subjects but can become highly correlated in Parkinson’s disease. However, high-density neuronal recordings in the GPe of healthy rats reveal a surprising degree of correlated activity. This raises the question of whether intrinsic properties or network connectivity alone can account for such patterns. To explore this, a computational model was developed in which GPe neurons are represented as coupled phase oscillators influenced by experimentally derived phase-response curves and extrinsic inputs. The study compared simulated cross-correlation patterns with experimental rat data, showing that while the model captures general trends, discrepancies exist in peak amplitude and decay rates, suggesting that key biological details of the GPe are not represented in the model. The findings highlight the significant impact of connection topography and synaptic dynamics on neural synchrony, emphasizing the complexity of GPe network activity and its implications for understanding both healthy brain function and pathological states like Parkinson’s disease.