Movement disorders arise from the complex interplay of multiple changes to neural circuits. Successful treatments for these disorders could interact with these complex changes in myriad ways, and as a consequence their mechanisms of action and their amelioration of symptoms are incompletely understood. Using Parkinson's disease as a case-study, we review here how computational models are a crucial tool for taming this complexity, across causative mechanisms, consequent neural dynamics, and treatments. For mechanisms, we review models that capture the effects of losing dopamine on basal ganglia function; for dynamics, we discuss models that have transformed our understanding of how beta-band (15-30 Hz) oscillations arise in the parkinsonian basal ganglia. For treatments, we touch on the breadth of computational modelling work trying to understand the therapeutic actions of deep brain stimulation. Collectively, models from across all levels of description are providing a compelling account of the causes, symptoms, and treatments for Parkinson's disease.
Figure 1: Consequences of dopamine depletion in the striatum.A The basal ganglia nuclei and main connections (bar: inhibitory; arrow: excitatory). Striatum divides into two projection neurons populations expressing D1 and D2 type receptors for dopamine. Routes from the D1 and D2 populations to the output nuclei (GPi) have historically been labelled the "direct" and "indirect" pathways. For clarity, we omit here some pathways, including the projection from GPe to the striatum, and the local connections within the striatum. STN: subthalamic nucleus; GPe: globus pallidus, external segment; GPi: globus pallidus, internal segment. B Single neuron models predict that dopamine differentially affects the excitability of D1 and D2-receptor expressing projection neurons. Consequently, dopamine depletion reduces excitability of D1-expressing neurons, and increases the excitability of D2-expressing neurons. Redrawn from [13]. C Distributions of the correlations between spontaneous neuron firing in intact and dopamine-depleted striatal network models [16]. The models predict that the spontaneous activity of the intact network is sparse, irregular and uncorrelated; but that dopamine depletion creates spontaneous activity that is anti-correlated (negative correlations). Such changes within the striatum's dynamics are in addition to any changes to the drive or synchrony of its cortical input caused by dopamine depletion. D Schematics showing how network models of the basal ganglia predict a breakdown of action selection in Parkinson's disease [cartoon of the results in e.g. 18, 20, 23]. Under normal conditions, a phasic input to the basal ganglia from cortex (top) produces (middle) a transient suppression of activity in a small group of GPi neurons (blue); this transient suppression of inhibition allows "selection" to occur by disinhibiting the thalamic and brainstem targets of these GPi neurons. Following dopamine depletion (bottom), the GPi activity barely changes in response to ...