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Objective: Beta bursts of local fields potentials (LFPs) recorded from subthalamic nucleus (STN) have been recently proposed as a new temporal feature for patients with Parkinson's disease (PD). We introduce a new technique for the adaptive time-domain segmentation of STN-LFP recordings such that the constructed time segments are proportional to the duration of stationary beta activity. We investigated whether the spectral entropy of the adaptively captured beta oscillations can describe the improvement in motor signs following dopaminergic medication., Methods: STN-LFP recordings from externalized chronic deep brain stimulation (DBS) leads were obtained in 9 PD patients. During this monitoring, each patient underwent 3 medication intake cycles where short acting agents (L-DOPA equivalent dose) were administered. We analyzed 2-minute resting state LFP data in each OFF and L-DOPA-induced ON medication states and constructed time domain segmentation of LFP signal in which the length segmentations are adapted to time-varying nature of the oscillatory activity., Results: Adaptively constructed segments were noted to be significantly longer in OFF- and shorter in ON-state (p<0.001). Interestingly, in the OFF state, the peak frequency of long beta bursts (>375 ms) was in the low range (12-23 Hz) of the beta spectrum, whereas shorter beta bursts (<375 ms) were widespread in the 13-30 Hz band. Measured clinical improvement was highly correlated with the difference in the spectral entropy of beta bursts between OFF and ON states (r = -0.83, p<0.01)., Conclusion and Significance: Our findings suggest that beta oscillations can be adaptively segmented without the use of a predetermined amplitude threshold, thereby allowing for objective quantification of burst itself. Compared to the shorter ones, longer oscillations with duration ≥ 375 ms were highly correlated with the clinical improvement, supporting a pathological role for them. Overall, these findings coupled with our adaptive approach could enable the quantitative use of temporal dynamics of beta activity in assessing severity of PD and improvements in motor features.

Despite having remarkable utility in treating movement disorders, the lack of understanding of the underlying mechanisms of high-frequency deep brain stimulation (DBS) is a main challenge in choosing personalized stimulation parameters. Here we investigate the modulations in local field potentials induced by electrical stimulation of the subthalamic nucleus (STN) at therapeutic and non-therapeutic frequencies in Parkinson's disease patients undergoing DBS surgery. We find that therapeutic high-frequency stimulation (130-180 Hz) induces high-frequency oscillations (~300 Hz, HFO) similar to those observed with pharmacological treatment. Along with HFOs, we also observed evoked compound activity (ECA) after each stimulation pulse. While ECA was observed in both therapeutic and non-therapeutic (20 Hz) stimulation, the HFOs were induced only with therapeutic frequencies, and the associated ECA were significantly more resonant. The relative degree of enhancement in the HFO power was related to the interaction of stimulation pulse with the phase of ECA. We propose that high-frequency STN-DBS tunes the neural oscillations to their healthy/treated state, similar to pharmacological treatment, and the stimulation frequency to maximize these oscillations can be inferred from the phase of ECA waveforms of individual subjects. The induced HFOs can, therefore, be utilized as a marker of successful re-calibration of the dysfunctional circuit generating PD symptoms.

Objective: Cross-frequency coupling has been reported in the STN of patients with PD, but its significance and functional role are still not well understood. This study investigates pharmacological modulations of subthalamic oscillations and their nonlinear cross-frequency interactions across three consecutive cycles over unique 24-hour-long recordings., Background: Identifying neurobiomarkers for PD can drive the development of novel personalized treatments by providing objective assessment of impairment. In particular, distinct frequency bands in LFP recordings and their interaction with one another have been shown to modulate with dopaminergic medication and thus, proposed as such biomarkers., Methods: We recorded local field potentials 3 weeks postoperatively from externalized leads in 9 patients and correlated the neural patterns with improvements in motor signs over three medication intake cycles. We used two modalities to assess symptoms in the unmedicated OFF and the l-dopa-induced motor ON state: a subsection of the UPDRS and a keyboard tapping score measuring bradykinesia., Results: In the OFF state, the amplitude of high-frequency oscillations in the 200- to 300-Hz range was coupled with the phase of low-beta (13-22 Hz) in all patients. After transition to the ON state, three distinct coupling patterns were observed among subjects. Among these, patients showing ON coupling between high-beta (22-30 Hz) and high-frequency oscillations in the 300- to 400-Hz range had significantly greater improvement in bradykinesia, according to the keyboard scores., Conclusion: Observing diminished coupling in the ON state, previous studies have hypothesized that the sole existence of coupling in STN has an "impeding" effect on normal processes, and thus it was considered to be pathological. In contrast, our observation of ON state coupling at distinct frequencies associated with the improvements in motor features suggest that the underlying mechanism of coupling might have impeding or enhancing effects depending on the coupled frequencies. © 2019 International Parkinson and Movement Disorder Society., (© 2019 International Parkinson and Movement Disorder Society.)

The subthalamic nucleus (STN) is a commonly used target in deep brain stimulation (DBS) to control the motor symptoms of Parkinson's Disease (PD). Identification of the spiking patterns in the STN is important in order to understand the neuropathophysiology of PD and can also assist in electrophysiological mapping of the structure. This study aims to provide a tool for grouping these firing patterns based on several extracted features from the spiking data. Single neuronal activity from the STN of PD subjects was detected and sorted to compute the binary spike trains. Several features including loca variation, bursting index and the prominence of the peak frequency of the power spectrum were extracted. Clustering of spike train segments was performed based on combination of features in 3D space to scrutinize how well they describe different firing regimes. The results show that this approach could be used to automate the grouping of stereotypic firing patterns in STN.

Background: The efficacy of deep brain stimulation (DBS) therapy in Parkinson's disease (PD) patients is highly dependent on the precise localization of the target structures such as subthalamic nucleus (STN). Most commonly, microelectrode single unit activity (SUA) recordings are performed to refine the target. This process is heavily experience based and can be technically challenging. Local field potentials (LFPs), representing the activity of a population of neurons, can be obtained from the same microelectrodes used for SUA recordings and allow flexible online processing with less computational complexity due to lower sampling rate requirements. Although LFPs have been shown to contain biomarkers capable of predicting patients' symptoms and differentiating various structures, their use in the localization of the STN in the clinical practice is not prevalent. Methods: Here we present, for the first time, a randomized and double-blinded pilot study with intraoperative online LFP processing in which we compare the clinical benefit from SUA- versus LFP-based implantation. Ten PD patients referred for bilateral STN-DBS were randomly implanted using either SUA or LFP guided targeting in each hemisphere. Although both SUA and LFP were recorded for each STN, the electrophysiologist was blinded to one at a time. Three months postoperatively, the patients were evaluated by a neurologist blinded to the intraoperative recordings to assess the performance of each modality. While SUA-based decisions relied on the visual and auditory inspection of the raw traces, LFP-based decisions were given through an online signal processing and machine learning pipeline. Results: We found a dramatic agreement between LFP- and SUA-based localization (16/20 STNs) providing adequate clinical improvement (51.8% decrease in 3-month contralateral motor assessment scores), with LFP-guided implantation resulting in greater average improvement in the discordant cases (74.9%, n = 3 STNs). The selected tracks were characterized by higher activity in beta (11–32 Hz) and high-frequency (200–400 Hz) bands (p < 0.01) of LFPs and stronger non-linear coupling between these bands (p < 0.05). Conclusion: Our pilot study shows equal or better clinical benefit with LFP-based targeting. Given the robustness of the electrode interface and lower computational cost, more centers can utilize LFP as a strategic feedback modality intraoperatively, in conjunction to the SUA-guided targeting. [ABSTRACT FROM AUTHOR]

Although motor subtypes of Parkinson's disease (PD), such as tremor dominant (TD) and postural instability and gait difficulty (PIGD), have been defined based on symptoms since the mid- 1990s, no underlying neural correlates of these clinical subtypes have yet been identified. Very limited data exist regarding the electrophysiological abnormalities within the subthalamic nucleus (STN) that likely accompany the symptom severity or the phenotype of PD. Here, we show that activity in subbands of local field potentials (LFPs) recorded with multiple microelectrodes from subterritories of STN provide distinguishing neurophysiological information about the motor subtypes of PD. We studied 24 patients with PD and found distinct patterns between TD (n = 13) and PIGD (n = 11) groups in high-frequency oscillations (HFOs) and their nonlinear interactions with beta band in the superior and inferior regions of the STN. Particularly, in the superior region of STN, the power of the slow HFO (sHFO) (200-260 Hz) and the coupling of its amplitude with beta-band phase were significantly stronger in the TD group. The inferior region of STN exhibited fast HFOs (fHFOs) (260-450 Hz), which have a significantly higher center frequency in the PIGD group. The cross-frequency coupling between fHFOs and beta band in the inferior region of STN was significantly stronger in the PIGD group. Our results indicate that the spatiospectral dynamics of STN-LFPs can be used as an objective method to distinguish these two motor subtypes of PD. These observations might lead to the development of sensing and stimulation strategies targeting the subterritories of STN for the personalization of deep-brain stimulation (DBS). [ABSTRACT FROM AUTHOR]

Background: Deep brain stimulation (DBS) is an emerging treatment strategy for severe, medication-refractory Tourette syndrome (TS). Thalamic (Cm-Pf) and pallidal (including globus pallidus interna, GPi) targets have been the most investigated. While the neurophysiological correlates of Parkinson's disease (PD) in the GPi and subthalamic nucleus (STN) are increasingly recognized, these patterns are not well characterized in other disease states. Recent findings indicate that the cross-frequency coupling (CFC) between beta band and high frequency oscillations (HFOs) within the STN in PD patients is pathologic. Methods: We recorded intraoperative local field potentials (LFPs) from the postero-ventrolateral GPi in three adult patients with TS at rest, during voluntary movements, and during tic activity and compared them to the intraoperative GPi-LFP activity recorded from four unmedicated PD patients at rest. Results: In all PD patients, we noted excessive beta band activity (13-30 Hz) at rest which consistently modulated the amplitude of the co-existent HFOs observed between 200 and 400 Hz, indicating the presence of beta-HFO CFC. In all 3TS patients at rest, we observed theta band activity (4-7 Hz) and HFOs. Two patients had beta band activity, though at lower power than theta oscillations. Tic activity was associated with increased high frequency (200-400 Hz) and gamma band (35-200 Hz) activity. There was no beta-HFO CFC in TS patients at rest. However, CFC between the phase of 5-10 Hz band activity and the amplitude of HFOs was found in two TS patients. During tics, this shifted to CFC between the phase of beta band activity and the amplitude of HFOs in all subjects. Conclusions: To our knowledge this is the first study that shows that beta-HFO CFC exists in the GPi of TS patients during tics and at rest in PD patients, and suggests that this pattern might be specific to pathologic/involuntary movements. Furthermore, our findings suggest that during tics, resting state 5-10 Hz-HFO CFC shifts to beta-HFO CFC which can be used to trigger stimulation in a closed loop system when tics are present. [ABSTRACT FROM AUTHOR]