Contribution of striatum to abnormal oscillatory activity experimentally observed in Parkinson's disease. A, Feedback loop amplifies correlation during dopamine depletion. Each column represents a different state, and within each column the x-axis represents time. The tan boxes with gray and green bell-shaped traces represent choice points, in which the subsequent state of the cortex–striatum loop depends on whether dopamine is normal (gray) or depleted (green). A normal transient increase in cortical correlation (State 1, gray cortical trace) is decorrelated by the normal striatum (State 1, striatal gray trace); thus, the cortex and striatum remain in the normal state of transient increases in correlation. In the dopamine-depleted striatum (State 1, striatal green trace), the transient increase in cortical correlation leads to a higher striatal correlation, with a subsequent transition into State 2, which has a higher cortical correlation. Feedback from the striatum to the cortex through the globus pallidus–subthalamic nucleus (GP-STN) loop contributes toward increased cortical correlation (State 2, cortical green trace). The normal striatum can decorrelate even this elevated cortical correlation (State 2, striatal gray trace), but the dopamine-depleted striatum produces an additional increase in correlation (State 2, striatal green trace) with a subsequent transition into State 3 with higher and more prolonged cortical correlation. In State 3, the striatum is unable to decorrelate the cortex; thus, no gray, low correlation striatal trace is shown. B, Raster plot of 200 MSNs in the dopamine-depleted striatal network in response to a switch in cortical input correlation from 0.3 to 0.6 at t = 1 s (indicated by arrow). C, Cortical input correlation (top) and striatal oscillations, measured as power of β-band oscillations (bottom), showing that the dopamine-depleted striatal network takes only ∼60 ms to respond to the switch in cortical input correlation. The first 0.1 s was eliminated from the analysis because it represents a transient increase as the network transitions from the down state.