Models of basal ganglia function and dysfunction have long been based on a circuit diagram sketching the flow of electrical activity through the nuclei. These models have guided the development of treatments for neurodegenerative diseases of the basal ganglia, and continue to be useful for design and refinement of new treatments. The validity of the functional models and their predictive value for design of new treatments is tightly linked to accurate information on the circuitry in each of the nuclei. Our knowledge of the anatomical connectivity among neurons in basal ganglia nuclei is good and improving rapidly, but our understanding of circuit effect on the flow of electrical activity is in its infancy. In this proposal, the functional characteristics of circuits in the main input nucleus of the basal ganglia (the striatum) and that in the main output nucleus (the substantia nigra) are analyzed. The experiments use sinusoidal inputs and combinations of sinusoids over a range of frequencies to characterize the effects of local circuits on neuronal responses. These inputs engage the known resonance properties of the neurons and synapses, and they will reveal other resonances that arise from circuit interactions. In some experiments, the input is intracellularly or optogenetically delivered to some or all cell-types in the circuit, whereas in others the periodic input signal to the circuit is delivered synaptically by continuously controlling firing of upstream neurons. These experiments will reveal the circuit mechanisms that amplify or suppress rhythmic activity in the basal ganglia, including both the beta oscillations that are a principal pathophysiological component of Parkinson's disease, and the therapeutic periodic signal generated during DBS.
The proposed experiments determine how local interconnections within the basal ganglia nuclei alter signal processing and oscillatory activity generated within the basal ganglia circuit. Local processing has previously not been taken into account in models of basal ganglia that are used to predict and evaluate potential treatments for Parkinson's disease. A next generation basal ganglia model incorporating this information may improve understanding of basal ganglia disorders and predictions of treatment effectiveness.
| Higgs, Matthew H; Wilson, Charles J (2017) Measurement of phase resetting curves using optogenetic barrage stimuli. J Neurosci Methods 289:23-30 |
| Wilson, Charles J (2017) Predicting the response of striatal spiny neurons to sinusoidal input. J Neurophysiol 118:855-873 |
| Dodla, Ramana; Wilson, Charles J (2017) Effect of Phase Response Curve Shape and Synaptic Driving Force on Synchronization of Coupled Neuronal Oscillators. Neural Comput 29:1769-1814 |
| Song, S C; Beatty, J A; Wilson, C J (2016) The ionic mechanism of membrane potential oscillations and membrane resonance in striatal LTS interneurons. J Neurophysiol 116:1752-1764 |
