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BackgroundSubcortical structures including the basal ganglia have been proposed to be crucial for arousal, consciousness, and behavioural responsiveness. However, how basal ganglia contributes to the loss and recovery of consciousness during anaesthesia has not been well characterized.MethodsIn this study, using local field potentials (LFPs) from subthalamic nucleus (STN) and scalp electroencephalogram in 12 Parkinson’s disease patients, we investigate STN neural signatures during propofol general anaesthesia and during intubation as an arousal intervention in anaesthesia.ResultsPropofol-induced anaesthesia resulted in changes in multiple frequency bands in STN LFPs, including increased low-frequency activities (slow-wave oscillation, delta, theta, and alpha bands) and decreased higher-frequency activities. This was also accompanied by increased STN-frontal cortical coherence in alpha frequency band. Beta and high-gamma activities in the STN temporally increased during intubation compared to the status of loss of consciousness. We also show that the dynamic changes in the high frequency activities (80-180 Hz) in STN LFPs induced by propofol and intubation correlated with power-law exponent in the power spectra between 2 and 80 Hz.ConclusionsOur findings suggest that anaesthesia and intubation induced changes in the STN LFPs in multiple frequency bands. They are also consistent with the hypothesis that the power-law exponent in the power spectra between 2 and 80 Hz reflect the excitation/inhibition balance in the STN, which is modulated by anaesthesia and intubation, and further modulate the high frequency activity.

High frequency deep brain stimulation (DBS) targeting motor thalamus is an effective therapy for essential tremor (ET). However, conventional continuous stimulation may deliver unnecessary current to the brain since tremor mainly affects voluntary movements and sustained postures in ET. We recorded LFPs from the motor thalamus, surface electromyographic (EMG) signals and/or behavioural measurements in seven ET patients during temporary lead externalization after the first surgery for DBS when they performed different voluntary upper limb movements and in nine more patients during the surgery, when they were asked to lift their arms to trigger postural tremor. We show that both voluntary movements and postural tremor can be decoded based on features extracted from thalamic LFPs using a machine learning based binary classifier. This information can be used to close the loop for DBS so that stimulation could be delivered on demand, without the need for peripheral sensors or additional invasive electrodes.