Parkinson's disease uncovers an underlying sensitivity of subthalamic nucleus neurons to beta-frequency cortical input in vivo

Abstract

Abnormally sustained beta-frequency synchronisation between the motor cortex and subthalamic nucleus (STN) is associated with motor symptoms in Parkinson's disease (PD). It is currently unclear whether STN neurons have a preference for beta-frequency input (12-35 Hz), rather than cortical input at other frequencies, and how such a preference would arise following dopamine depletion. To address this question, we combined analysis of cortical and STN recordings from awake human PD patients undergoing deep brain stimulation surgery with recordings of identified STN neurons in anaesthetised rats. In these patients, we demonstrate that a subset of putative STN neurons is strongly and selectively sensitive to magnitude fluctuations of cortical beta oscillations over time, linearly increasing their phase-locking strength with respect to the full range of instantaneous amplitude in the beta-frequency range. In rats, we probed the frequency response of STN neurons in the cortico-basal-ganglia-network more precisely, by recording spikes evoked by short bursts of cortical stimulation with variable frequency (4-40 Hz) and constant amplitude. In both healthy and dopamine-depleted rats, only beta-frequency stimulation led to a progressive reduction in the variability of spike timing through the stimulation train. This suggests, that the interval of beta-frequency input provides an optimal window for eliciting the next spike with high fidelity. We hypothesize, that abnormal activation of the indirect pathway, via dopamine depletion and/or cortical stimulation, could trigger an underlying sensitivity of the STN microcircuit to beta-frequency input.

Dopamine and DBS accelerate the neural dynamics of volitional action in Parkinson’s disease

“…Surrogate estimates from time-reversed signals were subtracted to normalize the resulting timefrequency estimates while reducing the impact of measurement noise. 22 A previously reported cortico-subthalamic driving of beta oscillations 23 is visible throughout all conditions with an appreciable but temporally inconsistent difference between OFF therapy and ON levodopa states at end of baseline resting period (−2 s; Figure 3A). At the time of motor intention, the ON levodopa condition was associated with a significant cluster of cortico-subthalamic coupling in the theta band (4-10 Hz; peak significance at 7 Hz, −0.9 s, P≤0.05 cluster corrected) when compared to the OFF therapy condition (Figure 3C,E).…”

“…Beta oscillations and their coupling have been proposed to signal the maintenance of a "status quo" that is suppressed by behavioral, motor and cognitive state changes 34 . Cortex drives beta activity in the basal ganglia, which can develop a vulnerability to beta hypersynchrony in the absence of dopamine 12 . An impactful rodent study has demonstrated this vulnerability in individually identified striatal medium spiny neurons in vivo in a dopaminergic lesion model of PD 35 .…”

“…ECoG and STN-LFP signals were referenced in a bipolar setup and notch-filtered to remove line noise (50, 100 and 150 Hz). Band power was calculated for each bipolar channel via fast Fourier transform with a frequency resolution of 1 Hz and power at each frequency was normalized to samples from the previous 10 s. Band power at each time step was then averaged for 7 frequency bands: theta (4-7 Hz), alpha (8)(9)(10)(11)(12), low beta (13-20 Hz), high beta (21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35), low gamma (60-80 Hz), high gamma (90-200 Hz), high frequency activity (201-400 Hz).…”

“…For this, we trained multivariate machine learning classifiers on the oscillatory premotor patterns from all available channels. ECoG and STN-LFP signals were decomposed into seven frequency bands (theta (4-7 Hz), alpha (8)(9)(10)(11)(12), low beta (13-20 Hz), high beta (21-35 Hz), low gamma (60-80 Hz), high gamma (90-200 Hz), high frequency activity (HFA; 201-400 Hz)) at a temporal resolution of 100 ms.…”

Current approaches to characterize micro- and macroscale circuit mechanisms of Parkinson’s disease in rodent models

“…In rodent PD models, indirect pathway SPN exhibited pathological synchronization ( Sharott et al, 2017 ) and a hyperresponsiveness to cortical and thalamic stimulation ( Escande et al, 2016 ) while spiking activity in the down-stream entopeduncular nucleus (EPN, mouse analogue to human GPi) were abnormally correlated with STN hyperactivity ( Aristieta et al, 2019 ). In addition, pathological changes in this indirect pathway likely increases the sensitivity of the STN to beta frequency activation ( Baaske et al, 2020 ). Combining optogenetics with juxtacellular recordings in PD rats has been used to identify the GP as a critical hub driving pathological spiking patterns and synchronization within basal ganglia networks ( Crompe et al, 2020 ).…”