Spontaneous pauses in firing of external pallidum neurons are associated with exploratory behavior.

Spontaneous pauses in firing are the hallmark of external pallidum (GPe) neurons. However, the role of GPe pauses in the basal ganglia network remains unknown. Pupil size and saccadic eye movements have been linked to attention and exploration. Here, we recorded GPe spiking activity and the corresponding pupil sizes and eye positions in non-human primates. We show that pauses, rather than the GPe discharge rate per se, were associated with dilated pupils. In addition, following pause initiation there was a considerable increase in the rate of spontaneous saccades. These results suggest that pauses are a powerful mechanism by which the GPe may influence basal ganglia downstream structures and play a role in exploratory behavior.

Machine learning-based personalized subthalamic biomarkers predict ON-OFF levodopa states in Parkinson patients.

Objective.Adaptive deep brain stimulation (aDBS) based on subthalamic nucleus (STN) electrophysiology has recently been proposed to improve clinical outcomes of DBS for Parkinson's disease (PD) patients. Many current models for aDBS are based on one or two electrophysiological features of STN activity, such as beta or gamma activity. Although these models have shown interesting results, we hypothesized that an aDBS model that includes many STN activity parameters will yield better clinical results. The objective of this study was to investigate the most appropriate STN neurophysiological biomarkers, detectable over long periods of time, that can predict OFF and ON levodopa states in PD patients.Approach.Long-term local field potentials (LFPs) were recorded from eight STNs (four PD patients) during 92 recording sessions (44 OFF and 48 ON levodopa states), over a period of 3-12 months. Electrophysiological analysis included the power of frequency bands, band power ratio and burst features. A total of 140 engineered features was extracted for 20 040 epochs (each epoch lasting 5 s). Based on these engineered features, machine learning (ML) models classified LFPs as OFF vs ON levodopa states.Main results.Beta and gamma band activity alone poorly predicts OFF vs ON levodopa states, with an accuracy of 0.66 and 0.64, respectively. Group ML analysis slightly improved prediction rates, but personalized ML analysis, based on individualized engineered electrophysiological features, were markedly better, predicting OFF vs ON levodopa states with an accuracy of 0.8 for support vector machine learning models.Significance.We showed that individual patients have unique sets of STN neurophysiological biomarkers that can be detected over long periods of time. ML models revealed that personally classified engineered features most accurately predict OFF vs ON levodopa states. Future development of aDBS for PD patients might include personalized ML algorithms.

Movement context modulates neuronal activity in motor and limbic-associative domains of the human parkinsonian subthalamic nucleus.

The subthalamic nucleus (STN), a preferred target for treating movement disorders, has a crucial role in inhibition and execution of movement. To better understand the mechanism of movement regulation in the STN of Parkinson's disease patients, we compared the same movement with different context, facilitation vs. inhibition context. We recorded subthalamic multiunit activity intra-operatively while parkinsonian patients (off medications, n = 43 patients, 173 recording sites) performed increasingly complex oddball paradigms with frequent and deviant tones: first, passive listening to tone series with no movement ('None-Go' task, n = 7, 28 recording sites); second, pressing a button after every tone ('All-Go' task, n = 7, 26 recording sites); and third, pressing a button only for frequent tones, thus adding inhibition of movement following deviant tones ('Go-NoGo' task, n = 29, 119 recording sites). The STN responded mainly to movement-involving tasks. In the limbic-associative STN, evoked response to the deviant tone (inhibitory cue) was not significantly different between the Go-NoGo and the All-Go task. However, the evoked response to the frequent tone (go cue) in the Go-NoGo task was significantly reduced. The reduction was mainly prominent in the negative component of the evoked response amplitude aligned to the press. Successful movement inhibition was correlated with higher baseline activity. We suggest that the STN in Parkinson's disease patients adapts to movement inhibition context by selectively decreasing the amplitude of neuronal activity. Thus, the STN enables movement inhibition not by increasing responses to the inhibitory cue but by reducing responses to the release cue. The negative component of the evoked response probably facilitates movement and a higher baseline activity enables successful inhibition of movement. These discharge modulations were found in the ventromedial, non-motor domain of the STN and therefore suggest a significant role of the limbic- associative STN domains in movement planning and in global movement regulation.

Theta-alpha oscillations characterize emotional subregion in the human ventral subthalamic nucleus.

BACKGROUND: Therapeutic outcomes of STN-DBS for movement and psychiatric disorders depend on electrode location within the STN. Electrophysiological and functional mapping of the STN has progressed considerably in the past years, identifying beta-band oscillatory activity in the dorsal STN as a motor biomarker. It also has been suggested that STN theta-alpha oscillations, involved in impulse control and action inhibition, have a ventral source. However, STN local field potential mapping of motor, associative, and limbic areas is often limited by poor spatial resolution. OBJECTIVES: Providing a high-resolution electrophysiological map of the motor, associative and limbic anatomical sub-areas of the subthalamic nucleus. METHODS: We have analyzed high-spatial-resolution STN microelectrode electrophysiology recordings of PD patients (n = 303) that underwent DBS surgery. The patients' STN intraoperative recordings of spiking activity (933 electrode trajectories) were combined with their imaging data (n = 83 patients, 151 trajectories). RESULTS: We found a high theta-alpha (7-10 Hz) oscillatory area, located near the STN ventromedial border in 29% of the PD patients. Theta-alpha activity in this area has higher power and lower central frequency in comparison to theta-alpha activity in more dorsal subthalamic areas. When projected on the DISTAL functional atlas, the theta-alpha oscillatory area overlaps with the STN limbic subarea. CONCLUSIONS: We suggest that theta-alpha oscillations can serve as an electrophysiological marker for the ventral subthalamic nucleus limbic subarea. Therefore, theta-alpha oscillations can guide optimal electrode placement in neuropsychiatric STN-DBS procedures and provide a reliable biomarker input for future closed-loop DBS device. © 2019 International Parkinson and Movement Disorder Society.

Subthalamic theta activity: a novel human subcortical biomarker for obsessive compulsive disorder.

Obsessive-compulsive disorder (OCD) is a common and serious psychiatric disorder. Although subthalamic nucleus deep brain stimulation (DBS) has been studied as a treatment for OCD patients the underlying mechanism of this treatment and the optimal method of stimulation are unknown. To study the neural basis of subthalamic nucleus DBS in OCD patients we used a novel, implantable DBS system with long-term local field potential sensing capability. We focus our analysis on two patients with OCD who experienced severe treatment-resistant symptoms and were implanted with subthalamic nucleus DBS systems. We studied them for a year at rest and during provocation of OCD symptoms (46 recording sessions) and compared them to four Parkinson's disease (PD) patients implanted with subthalamic nucleus DBS systems (69 recording sessions). We show that the dorsal (motor) area of the subthalamic nucleus in OCD patients displays a beta (25-35 Hz) oscillatory activity similar to PD patients whereas the ventral (limbic-cognitive) area of the subthalamic nucleus displays distinct theta (6.5-8 Hz) oscillatory activity only in OCD patients. The subthalamic nucleus theta oscillatory activity decreases with provocation of OCD symptoms and is inversely correlated with symptoms severity over time. We conclude that beta oscillations at the dorsal subthalamic nucleus in OCD patients challenge their pathophysiologic association with movement disorders. Furthermore, theta oscillations at the ventral subthalamic nucleus in OCD patients suggest a new physiological target for OCD therapy as well as a promising input signal for future emotional-cognitive closed-loop DBS.