Resonance in subthalamo-cortical circuits in Parkinson's disease. - Eusebio, A; Pogosyan, A; Wang, S; Averbeck, B; Gaynor, L; Cantiniaux, S; Witjas, T; Limousin, P; Azulay, J; Brown, P (2009)
Neuronal activity within and across the cortex and basal ganglia is pathologically synchronized, particularly at approximately 20 Hz in patients with Parkinson's disease. Defining how activities in spatially distributed brain regions overtly synchronize in narrow frequency bands is critical for understanding disease processes like Parkinson's disease. To address this, we studied cortical responses to electrical stimulation of the subthalamic nucleus (STN) at various frequencies between 5 and 30 Hz in two cohorts of eight patients with Parkinson's disease from two different surgical centres. We found that evoked activity consisted of a series of diminishing waves with a peak latency of 21 ms for the first wave in the series. The cortical evoked potentials (cEPs) averaged in each group were well fitted by a damped oscillator function (r > or = 0.9, P < 0.00001). Fits suggested that the natural frequency of the subthalamo-cortical circuit was around 20 Hz. When the system was forced at this frequency by stimulation of the STN at 20 Hz, the undamped amplitude of the modelled cortical response increased relative to that with 5 Hz stimulation in both groups (P < or = 0.005), consistent with resonance. Restoration of dopaminergic input by treatment with levodopa increased the damping of oscillatory activity (as measured by the modelled damping factor) in both patient groups (P < or = 0.001). The increased damping would tend to limit resonance, as confirmed in simulations. Our results show that the basal ganglia-cortical network involving the STN has a tendency to resonate at approximately 20 Hz in Parkinsonian patients. This resonance phenomenon may underlie the propagation and amplification of activities synchronized around this frequency. Crucially, dopamine acts to increase damping and thereby limit resonance in this basal ganglia-cortical network.