Dopamine and deep brain stimulation accelerate the neural dynamics of volitional action in Parkinson's disease.

The ability to initiate volitional action is fundamental to human behaviour. Loss of dopaminergic neurons in Parkinson's disease is associated with impaired action initiation, also termed akinesia. Both dopamine and subthalamic deep brain stimulation (DBS) can alleviate akinesia, but the underlying mechanisms are unknown. An important question is whether dopamine and DBS facilitate de novo build-up of neural dynamics for motor execution or accelerate existing cortical movement initiation signals through shared modulatory circuit effects. Answering these questions can provide the foundation for new closed-loop neurotherapies with adaptive DBS, but the objectification of neural processing delays prior to performance of volitional action remains a significant challenge. To overcome this challenge, we studied readiness potentials and trained brain signal decoders on invasive neurophysiology signals in 25 DBS patients (12 female) with Parkinson's disease during performance of self-initiated movements. Combined sensorimotor cortex electrocorticography (ECoG) and subthalamic local field potential (LFP) recordings were performed OFF therapy (N = 22), ON dopaminergic medication (N = 18) and ON subthalamic deep brain stimulation (N = 8). This allowed us to compare their therapeutic effects on neural latencies between the earliest cortical representation of movement intention as decoded by linear discriminant analysis classifiers and onset of muscle activation recorded with electromyography (EMG). In the hypodopaminergic OFF state, we observed long latencies between motor intention and motor execution for readiness potentials and machine learning classifications. Both, dopamine and DBS significantly shortened these latencies, hinting towards a shared therapeutic mechanism for alleviation of akinesia. To investigate this further, we analysed directional cortico-subthalamic oscillatory communication with multivariate granger causality. Strikingly, we found that both therapies independently shifted cortico-subthalamic oscillatory information flow from antikinetic beta (13-35 Hz) to prokinetic theta (4-10 Hz) rhythms, which was correlated with latencies in motor execution. Our study reveals a shared brain network modulation pattern of dopamine and DBS that may underlie the acceleration of neural dynamics for augmentation of movement initiation in Parkinson's disease. Instead of producing or increasing preparatory brain signals, both therapies modulate oscillatory communication. These insights provide a link between the pathophysiology of akinesia and its' therapeutic alleviation with oscillatory network changes in other non-motor and motor domains, e.g. related to hyperkinesia or effort and reward perception. In the future, our study may inspire the development of clinical brain computer interfaces based on brain signal decoders to provide temporally precise support for action initiation in patients with brain disorders.

Generalized sleep decoding with basal ganglia signals in multiple movement disorders.

Sleep disturbances profoundly affect the quality of life in individuals with neurological disorders. Closed-loop deep brain stimulation (DBS) holds promise for alleviating sleep symptoms, however, this technique necessitates automated sleep stage decoding from intracranial signals. We leveraged overnight data from 121 patients with movement disorders (Parkinson's disease, Essential Tremor, Dystonia, Essential Tremor, Huntington's disease, and Tourette's syndrome) in whom synchronized polysomnograms and basal ganglia local field potentials were recorded, to develop a generalized, multi-class, sleep specific decoder - BGOOSE. This generalized model achieved 85% average accuracy across patients and across disease conditions, even in the presence of recordings from different basal ganglia targets. Furthermore, we also investigated the role of electrocorticography on decoding performances and proposed an optimal decoding map, which was shown to facilitate channel selection for optimal model performances. BGOOSE emerges as a powerful tool for generalized sleep decoding, offering exciting potentials for the precision stimulation delivery of DBS and better management of sleep disturbances in movement disorders.

Contribution of basal ganglia activity to REM sleep disorder in Parkinson's disease.

BACKGROUND: Rapid eye movement (REM) sleep behaviour disorder (RBD) is one of the most common sleep problems and represents a key prodromal marker in Parkinson's disease (PD). It remains unclear whether and how basal ganglia nuclei, structures that are directly involved in the pathology of PD, are implicated in the occurrence of RBD. METHOD: Here, in parallel with whole-night video polysomnography, we recorded local field potentials from two major basal ganglia structures, the globus pallidus internus and subthalamic nucleus, in two cohorts of patients with PD who had varied severity of RBD. Basal ganglia oscillatory patterns during RBD and REM sleep without atonia were analysed and compared with another age-matched cohort of patients with dystonia that served as controls. RESULTS: We found that beta power in both basal ganglia nuclei was specifically elevated during REM sleep without atonia in patients with PD, but not in dystonia. Basal ganglia beta power during REM sleep positively correlated with the extent of atonia loss, with beta elevation preceding the activation of chin electromyogram activities by ~200 ms. The connectivity between basal ganglia beta power and chin muscular activities during REM sleep was significantly correlated with the clinical severity of RBD in PD. CONCLUSIONS: These findings support that basal ganglia activities are associated with if not directly contribute to the occurrence of RBD in PD. Our study expands the understanding of the role basal ganglia played in RBD and may foster improved therapies for RBD by interrupting the basal ganglia-muscular communication during REM sleep in PD.

Invasive neurophysiology and whole brain connectomics for neural decoding in patients with brain implants.

Brain computer interfaces (BCI) provide unprecedented spatiotemporal precision that will enable significant expansion in how numerous brain disorders are treated. Decoding dynamic patient states from brain signals with machine learning is required to leverage this precision, but a standardized framework for identifying and advancing novel clinical BCI approaches does not exist. Here, we developed a platform that integrates brain signal decoding with connectomics and demonstrate its utility across 123 hours of invasively recorded brain data from 73 neurosurgical patients treated for movement disorders, depression and epilepsy. First, we introduce connectomics-informed movement decoders that generalize across cohorts with Parkinson's disease and epilepsy from the US, Europe and China. Next, we reveal network targets for emotion decoding in left prefrontal and cingulate circuits in DBS patients with major depression. Finally, we showcase opportunities to improve seizure detection in responsive neurostimulation for epilepsy. Our platform provides rapid, high-accuracy decoding for precision medicine approaches that can dynamically adapt neuromodulation therapies in response to the individual needs of patients.

Pathological pallidal beta activity in Parkinson's disease is sustained during sleep and associated with sleep disturbance.

Parkinson's disease (PD) is associated with excessive beta activity in the basal ganglia. Brain sensing implants aim to leverage this biomarker for demand-dependent adaptive stimulation. Sleep disturbance is among the most common non-motor symptoms in PD, but its relationship with beta activity is unknown. To investigate the clinical potential of beta activity as a biomarker for sleep quality in PD, we recorded pallidal local field potentials during polysomnography in PD patients off dopaminergic medication and compared the results to dystonia patients. PD patients exhibited sustained and elevated beta activity across wakefulness, rapid eye movement (REM), and non-REM sleep, which was correlated with sleep disturbance. Simulation of adaptive stimulation revealed that sleep-related beta activity changes remain unaccounted for by current algorithms, with potential negative outcomes in sleep quality and overall quality of life for patients.

Unlocking potential: low frequency subthalamic nucleus stimulation enhances executive function in Parkinson's disease patients with postural instability/gait disturbance.

Postural instability/gait disturbance (PIGD) is very common in advanced Parkinson's disease, and associated with cognitive dysfunction. Research suggests that low frequency (5-12 Hz) subthalamic nucleus-deep brain stimulation (STN-DBS) could improve cognition in patients with Parkinson's disease (PD). However, the clinical effectiveness of low frequency stimulation in PIGD patients has not been explored. This study was designed in a double-blinded randomized cross-over manner, aimed to verify the effect of low frequency STN-DBS on cognition of PIGD patients. Twenty-nine PIGD patients with STN-DBS were tested for cognitive at off (no stimulation), low frequency (5 Hz), and high frequency (130 Hz) stimulation. Neuropsychological tests included the Stroop Color-Word Test (SCWT), Verbal fluency test, Symbol Digital Switch Test, Digital Span Test, and Benton Judgment of Line Orientation test. For conflict resolution of executive function, low frequency stimulation significantly decreased the completion time of SCWT-C (p = 0.001) and Stroop interference effect (p < 0.001) compared to high frequency stimulation. However, no significant differences among stimulation states were found for other cognitive tests. Here we show, low frequency STN-DBS improved conflict resolution of executive function compared to high frequency. Our results demonstrated the possibility of expanding the treatment coverage of DBS to cognitive function in PIGD, which will facilitate integration of low frequency stimulation into future DBS programming.

Optimal subthalamic stimulation sites and related networks for freezing of gait in Parkinson's disease.

Freezing of gait is a common and debilitating symptom in Parkinson's disease. Although high-frequency subthalamic deep brain stimulation is an effective treatment for Parkinson's disease, post-operative freezing of gait severity has been reported to alleviate, deteriorate or remain constant. We conducted this study to explore the optimal stimulation sites and related connectivity networks for high-frequency subthalamic deep brain stimulation treating freezing of gait in Parkinson's disease. A total of 76 Parkinson's disease patients with freezing of gait who underwent bilateral high-frequency subthalamic stimulation were retrospectively included. The volumes of tissue activated were estimated based on individual electrode reconstruction. The optimal and sour stimulation sites were calculated at coordinate/voxel/mapping level and mapped to anatomical space based on patient-specific images and stimulation settings. The structural and functional predictive connectivity networks for the change of the post-operative Freezing of Gait-Questionnaire were also identified based on normative connectomes derived from the Parkinson's Progression Marker Initiative database. Leave-one-out cross-validation model validated the above results, and the model remained significant after including covariates. The dorsolateral two-thirds of the subthalamic nucleus was identified as the optimal stimulation site, while the ventrocentral portion of the right subthalamic nucleus and internal capsule surrounding the left central subthalamic nucleus were considered as the sour stimulation sites. Modulation of the fibre tracts connecting to the supplementary motor area, pre-supplementary motor area and pedunculopontine nucleus accounted for the alleviation of freezing of gait, whereas tracts connecting to medial and ventrolateral prefrontal cortices contributed to the deterioration of freezing of gait. The optimal/sour stimulation sites and structural/functional predictive connectivity networks for high-frequency subthalamic deep brain stimulation treating freezing of gait are identified and validated through sizable Parkinson's disease patients in this study. With the growing understanding of stimulation sites and related networks, individualized deep brain stimulation treatment with directional leads will become an optimal choice for Parkinson's disease patients with freezing of gait in the future.

The clinical application of neuro-robot in the resection of epileptic foci: a novel method assisting epilepsy surgery.

During surgery for foci-related epilepsy, neurosurgeons face significant difficulties in identifying and resecting MRI-negative or deep-seated epileptic foci. Here, we present a neuro-robotic navigation system that is specifically designed for resection of MRI negative epileptic foci. We recruited 52 epileptic patients, and randomly assigned them to treatment group with either neuro-robotic navigation or conventional neuronavigation system. For each patient, in the neuro-robotic navigation group, we integrated multimodality imaging including MRI and PET-CT into the robotic workstation and marked the boundary of foci from the fused image. During surgery, this boundary was delineated by the robotic laser device with high accuracy, guiding resection for the surgeon. For deeply seated foci, we exploited the neuro-robotic navigation system to localize the deepest point with biopsy needle insertion and methylene dye application to locate the boundary of the foci. Our results show that, compared with the conventional neuronavigation, the neuro-robotic navigation system performs equally well in MRI positive epilepsy patients (ENGEL I ratio: 71.4% vs 100%, p = 0.255) systems and show better performance in patients with MRI-negative focal cortical dysplasia (ENGEL I ratio: 88.2% vs 50%, p = 0.0439). At present, there are no documented neurosurgery robots with similar function and application in the field of epilepsy. Our research highlights the added value of using neuro-robotic navigation systems in resection surgery for epilepsy, particularly in cases that involve MRI-negative or deep-seated epileptic foci.

Sleep outcomes and related factors in Parkinson's disease after subthalamic deep brain electrode implantation: a retrospective cohort study.

Background: Subthalamic nucleus deep brain stimulation (STN-DBS) improves sleep qualities in Parkinson's disease (PD) patients; however, it remains elusive whether STN-DBS improves sleep by directly influencing the sleep circuit or alleviates other cardinal symptoms such as motor functions, other confounding factors including stimulation intensity may also involve. Studying the effect of microlesion effect (MLE) on sleep after STN-DBS electrode implantation may address this issue. Objective: To examine the influence of MLE on sleep quality and related factors in PD, as well as the effects of regional and lateral specific correlations with sleep outcomes after STN-DBS electrode implantation. Study Design: Case-control study; Level of evidence, 3. Data Sources and Methods: In 78 PD patients who underwent bilateral STN-DBS surgery in our center, we compared the sleep qualities, motor performances, anti-Parkinsonian drug dosage, and emotional conditions at preoperative baseline and postoperative 1-month follow-up. We determined the related factors of sleep outcomes and visualized the electrodes position, simulated the MLE-engendered volume of tissue lesioned (VTL), and investigated sleep-related sweet/sour spots and laterality in STN. Results: MLE improves sleep quality with Pittsburgh Sleep Quality Index (PSQI) by 13.36% and Parkinson's Disease Sleep Scale-2 (PDSS-2) by 17.95%. Motor (P = 0.014) and emotional (P = 0.001) improvements were both positively correlated with sleep improvements. However, MLE in STN associative subregions, as an independent factor, may cause sleep deterioration (r = 0.348, P = 0.002), and only the left STN showed significance (r = 0.327, P = 0.004). Sweet spot analysis also indicated part of the left STN associative subregion is the sour spot indicative of sleep deterioration. Conclusion: The MLE of STN-DBS can overall improve sleep quality in PD patients, with a positive correlation between motor and emotional improvements. However, independent of all other factors, the MLE in the STN associative subregion, particularly the left side, may cause sleep deterioration.

Pallidal activities during sleep and sleep decoding in dystonia, Huntington's, and Parkinson's disease.

BACKGROUND: Sleep disturbances are highly prevalent in movement disorders, potentially due to the malfunctioning of basal ganglia structures. Pallidal deep brain stimulation (DBS) has been widely used for multiple movement disorders and been reported to improve sleep. We aimed to investigate the oscillatory pattern of pallidum during sleep and explore whether pallidal activities can be utilized to differentiate sleep stages, which could pave the way for sleep-aware adaptive DBS. METHODS: We directly recorded over 500 h of pallidal local field potentials during sleep from 39 subjects with movement disorders (20 dystonia, 8 Huntington's disease, and 11 Parkinson's disease). Pallidal spectrum and cortical-pallidal coherence were computed and compared across sleep stages. Machine learning approaches were utilized to build sleep decoders for different diseases to classify sleep stages through pallidal oscillatory features. Decoding accuracy was further associated with the spatial localization of the pallidum. RESULTS: Pallidal power spectra and cortical-pallidal coherence were significantly modulated by sleep-stage transitions in three movement disorders. Differences in sleep-related activities between diseases were identified in non-rapid eye movement (NREM) and REM sleep. Machine learning models using pallidal oscillatory features can decode sleep-wake states with over 90% accuracy. Decoding accuracies were higher in recording sites within the internus-pallidum than the external-pallidum, and can be precited using structural (P < 0.0001) and functional (P < 0.0001) whole-brain neuroimaging connectomics. CONCLUSION: Our findings revealed strong sleep-stage dependent distinctions in pallidal oscillations in multiple movement disorders. Pallidal oscillatory features were sufficient for sleep stage decoding. These data may facilitate the development of adaptive DBS systems targeting sleep problems that have broad translational prospects.

Association between Cognitive Impairment and Freezing of Gait in Patients with Parkinson's Disease.

Background: Freezing of gait (FOG) is a common disabling symptom in Parkinson's disease (PD). Cognitive impairment may contribute to FOG. Nevertheless, their correlations remain controversial. We aimed to investigate cognitive differences between PD patients with and without FOG (nFOG), explore correlations between FOG severity and cognitive performance and assess cognitive heterogeneity within the FOG patients. Methods: Seventy-four PD patients (41 FOG, 33 nFOG) and 32 healthy controls (HCs) were included. Comprehensive neuropsychological assessments testing cognitive domains of global cognition, executive function/attention, working memory, and visuospatial function were performed. Cognitive performance was compared between groups using independent t-test and ANCOVA adjusting for age, sex, education, disease duration and motor symptoms. The k-means cluster analysis was used to explore cognitive heterogeneity within the FOG group. Correlation between FOG severity and cognition were analyzed using partial correlations. Results: FOG patients showed significantly poorer performance in global cognition (MoCA, p < 0.001), frontal lobe function (FAB, p = 0.015), attention and working memory (SDMT, p < 0.001) and executive function (SIE, p = 0.038) than nFOG patients. The FOG group was divided into two clusters using the cluster analysis, of which cluster 1 exhibited worse cognition, and with older age, lower improvement rate, higher FOGQ3 score, and higher proportion of levodopa-unresponsive FOG than cluster 2. Further, in the FOG group, cognition was significantly correlated with FOG severity in MoCA (r = -0.382, p = 0.021), Stroop-C (r = 0.362, p = 0.030) and SIE (r = 0.369, p = 0.027). Conclusions: This study demonstrated that the cognitive impairments of FOG were mainly reflected by global cognition, frontal lobe function, executive function, attention and working memory. There may be heterogeneity in the cognitive impairment of FOG patients. Additionally, executive function was significantly correlated with FOG severity.

Fronto-parieto-subthalamic activity decodes motor status in Parkinson's disease.

AIMS: Patients with Parkinson's disease (PD) have various motor difficulties, including standing up, gait initiation and freezing of gait. These abnormalities are associated with cortico-subthalamic dysfunction. We aimed to reveal the characteristics of cortico-subthalamic activity in PD patients during different motor statuses. METHODS: Potentials were recorded in the superior parietal lobule (SPL), the primary motor cortex (M1), premotor cortex (PMC), and the bilateral subthalamic nucleus (STN) in 18 freely walking patients while sitting, standing, walking, dual-task walking, and freezing in medication "off" (Moff) and "on" (Mon) states. Different motor status activities were compared in band power, and a machine learning classifier was used to differentiate the motor statuses. RESULTS: SPL beta power was specifically inhibited from standing to walking, and negatively correlated with walking speed; M1 beta power reflected the degree of rigidity and was reversed by medication; XGBoost algorithm classified the five motor statuses with acceptable accuracy (68.77% in Moff, 60.58% in Mon). SPL beta power ranked highest in feature importance in both Moff and Mon states. CONCLUSION: SPL beta power plays an essential role in walking status classification and could be a physiological biomarker for walking speed, which would aid the development of adaptive DBS.

Profiling the low-beta characteristics of the subthalamic nucleus in early- and late-onset Parkinson's disease.

Objectives: Low-beta oscillation (13-20 Hz) has rarely been studied in patients with early-onset Parkinson's disease (EOPD, age of onset ≤50 years). We aimed to explore the characteristics of low-beta oscillation in the subthalamic nucleus (STN) of patients with EOPD and investigate the differences between EOPD and late-onset Parkinson's disease (LOPD). Methods: We enrolled 31 EOPD and 31 LOPD patients, who were matched using propensity score matching. Patients underwent bilateral STN deep brain stimulation (DBS). Local field potentials were recorded using intraoperative microelectrode recording. We analyzed the low-beta band parameters, including aperiodic/periodic components, beta burst, and phase-amplitude coupling. We compared low-beta band activity between EOPD and LOPD. Correlation analyses were performed between the low-beta parameters and clinical assessment results for each group. Results: We found that the EOPD group had lower aperiodic parameters, including offset (p = 0.010) and exponent (p = 0.047). Low-beta burst analysis showed that EOPD patients had significantly higher average burst amplitude (p = 0.016) and longer average burst duration (p = 0.011). Furthermore, EOPD had higher proportion of long burst (500-650 ms, p = 0.008), while LOPD had higher proportion of short burst (200-350 ms, p = 0.007). There was a significant difference in phase-amplitude coupling values between low-beta phase and fast high frequency oscillation (300-460 Hz) amplitude (p = 0.019). Conclusion: We found that low-beta activity in the STN of patients with EOPD had characteristics that varied when compared with LOPD, and provided electrophysiological evidence for different pathological mechanisms between the two types of PD. These differences need to be considered when applying adaptive DBS on patients of different ages.

Adaptive deep brain stimulation for Parkinson's disease: looking back at the past decade on motor outcomes.

BACKGROUND: Adaptive deep brain stimulation (aDBS) has been reported to be an effective treatment for motor symptoms in patients with Parkinson's disease (PD). However, it remains unclear whether and in which motor domain aDBS provides greater/less benefits than conventional DBS (cDBS). OBJECTIVE: To conduct a meta-analysis and systematic review to explore the improvement of the motor symptoms of PD patients undergoing aDBS and the comparison between aDBS and cDBS. METHODS: Nineteen studies from PubMed, Embase, and the Cochrane Library database were eligible for the main analysis. Twelve studies used quantitative plus qualitative analysis; seven studies were only qualitatively analyzed. The efficacy of aDBS was evaluated and compared to cDBS through overall motor function improvements, changes in symptoms of rigidity-bradykinesia, dyskinesia, tremor, and speech function, and total electrical energy delivered (TEED). The overall motor improvement and TEED were investigated through meta-analyses, while other variables were investigated by systematic review. RESULTS: Quantitative analysis showed that aDBS, with a reduction of TEED (55% of that of cDBS), significantly improved motor functions (33.9%, p < 0.01) and may be superior to cDBS in overall motor improvement (p = 0.002). However, significant publication bias was detected regarding the superiority (p = 0.006, Egger's test). In the qualitative analysis, rigidity-bradykinesia, dyskinesia, and speech function outcomes after aDBS and cDBS were comparable. Beta-based aDBS may not be as efficient as cDBS for tremor control. CONCLUSIONS: aDBS can effectively relieve the clinical symptoms of advanced PD as did cDBS, at least in acute trials, delivering less stimulation than cDBS. Specific symptoms including tremor and axial disability remain to be compared between aDBS and cDBS in long-term studies.

Which one is the superior target? A comparison and pooled analysis between posterior subthalamic area and ventral intermediate nucleus deep brain stimulation for essential tremor.

BACKGROUND/AIMS: The efficacy and safety of posterior subthalamic area (PSA) and ventral intermediate nucleus (VIM) deep brain stimulation (DBS) in the treatment of essential tremor (ET) have not been compared in large-scale studies. We conducted a secondary analysis to identify the superior target of ET-DBS treatment. METHODS: PubMed, Embase, Cochrane Library, and Google Scholar were searched for relevant studies before September 2021. The tremor-suppression efficacy and rate of stimulation-related complications (SRCR) after PSA-DBS and VIM-DBS treating ET were quantitatively compared. Secondary outcomes, including tremor subitem scores and quality of life results, were also analyzed. Subgroup analyses were further conducted to stratify by follow-up (FU) periods and stimulation lateralities. This study was registered in Open Science Framework (DOI: 10.17605/OSF.IO/7VJQ8). RESULTS: A total of 23 studies including 122 PSA-DBS patients and 326 VIM-DBS patients were analyzed. The average follow-up time was 12.81 and 14.66 months, respectively. For the percentage improvement of total tremor rating scale (TRS) scores, PSA-DBS was significantly higher, when compared to VIM-DBS in the sensitivity analysis (p = 0.030) and main analysis (p = 0.043). The SRCR after VIM-DBS was higher than that of PSA-DBS (p = 0.022), and bilateral PSA-DBS was significantly superior to both bilateral and unilateral VIM-DBS (p = 0.001). CONCLUSIONS: This study provided level IIIa evidence that PSA-DBS was more effective and safer for ET than VIM-DBS in 12-24 months, although both PSA-DBS and VIM-DBS were effective in suppressing tremor in ET patients. Further prospective large-scale randomized clinical trials are warranted in the future.

Low-frequency oscillations link frontal and parietal cortex with subthalamic nucleus in conflicts.

Low-frequency oscillations (LFOs, 28 Hz) in the subthalamic nucleus(STN) are known to reflect cognitive conflict. However, it is unclear if LFOs mediate communication and functional interactions among regions implicated in conflict processing, such as the motor cortex (M1), premotor cortex (PMC), and superior parietal lobule (SPL). To investigate the potential contribution of LFOs to cognitive conflict mediation, we recorded M1, PMC, and SPL activities by right subdural electrocorticography (ECoG) simultaneously with bilateral STN local field potentials (LFPs) by deep brain stimulation electrodes in 13 patients with Parkinson's disease who performed the arrow version of the Eriksen flanker task. Elevated cue-related LFO activity was observed across patients during task trials, with the earliest onset in PMC and SPL. At cue onset, LFO power exhibited a significantly greater increase or a trend of a greater increase in the PMC, M1, and STN, and less increase in the SPL during high-conflict (incongruent) trials than in low-conflict (congruent) trials. The local LFO power increases in PMC, SPL, and right STN were correlated with response time, supporting the notion that these structures are critical hubs for cognitive conflict processing. This power increase was accompanied by increased functional connectivity between the PMC and right STN, which was correlated with response time across subjects. Finally, ipsilateral PMC-STN Granger causality was enhanced during high-conflict trials, with direction from STN to PMC. Our study indicates that LFOs link the frontal and parietal cortex with STN during conflicts, and the ipsilateral PMC-STN connection is specifically involved in this cognitive conflict processing.

Cortical phase-amplitude coupling is key to the occurrence and treatment of freezing of gait.

Freezing of gait is a debilitating symptom in advanced Parkinson's disease and responds heterogeneously to treatments such as deep brain stimulation. Recent studies indicated that cortical dysfunction is involved in the development of freezing, while evidence depicting the specific role of the primary motor cortex in the multi-circuit pathology of freezing is lacking. Since abnormal beta-gamma phase-amplitude coupling recorded from the primary motor cortex in patients with Parkinson's disease indicates parkinsonian state and responses to therapeutic deep brain stimulation, we hypothesized this metric might reveal unique information on understanding and improving therapy for freezing of gait. Here, we directly recorded potentials in the primary motor cortex using subdural electrocorticography and synchronously captured gait freezing using optoelectronic motion-tracking systems in 16 freely-walking patients with Parkinson's disease who received subthalamic nucleus deep brain stimulation surgery. Overall, we recorded 451 timed up-and-go walking trials and quantified 7073 s of stable walking and 3384 s of gait freezing in conditions of on/off-stimulation and with/without dual-tasking. We found that (i) high beta-gamma phase-amplitude coupling in the primary motor cortex was detected in freezing trials (i.e. walking trials that contained freezing), but not non-freezing trials, and the high coupling in freezing trials was not caused by dual-tasking or the lack of movement; (ii) non-freezing episodes within freezing trials also demonstrated abnormally high couplings, which predicted freezing severity; (iii) deep brain stimulation of subthalamic nucleus reduced these abnormal couplings and simultaneously improved freezing; and (iv) in trials that were at similar coupling levels, stimulation trials still demonstrated lower freezing severity than no-stimulation trials. These findings suggest that elevated phase-amplitude coupling in the primary motor cortex indicates higher probabilities of freezing. Therapeutic deep brain stimulation alleviates freezing by both decoupling cortical oscillations and enhancing cortical resistance to abnormal coupling. We formalized these findings to a novel 'bandwidth model,' which specifies the role of cortical dysfunction, cognitive burden and therapeutic stimulation on the emergence of freezing. By targeting key elements in the model, we may develop next-generation deep brain stimulation approaches for freezing of gait.

Deep Brain Stimulation Modulates Multiple Abnormal Resting-State Network Connectivity in Patients With Parkinson's Disease.

Background: Deep brain stimulation (DBS) improves motor and non-motor symptoms in patients with Parkinson's disease (PD). Researchers mainly investigated the motor networks to reveal DBS mechanisms, with few studies extending to other networks. This study aimed to investigate multi-network modulation patterns using DBS in patients with PD. Methods: Twenty-four patients with PD underwent 1.5 T functional MRI (fMRI) scans in both DBS-on and DBS-off states, with twenty-seven age-matched healthy controls (HCs). Default mode, sensorimotor, salience, and left and right frontoparietal networks were identified by using the independent component analysis. Power spectra and functional connectivity of these networks were calculated. In addition, multiregional connectivity was established from 15 selected regions extracted from the abovementioned networks. Comparisons were made among groups. Finally, correlation analyses were performed between the connectivity changes and symptom improvements. Results: Compared with HCs, PD-off showed abnormal power spectra and functional connectivity both within and among these networks. Some of the abovementioned abnormalities could be corrected by DBS, including increasing the power spectra in the sensorimotor network and modulating the parts of the ipsilateral functional connectivity in different regions centered in the frontoparietal network. Moreover, the DBS-induced functional connectivity changes were correlated with motor and depression improvements in patients with PD. Conclusion: DBS modulated the abnormalities in multi-networks. The functional connectivity alterations were associated with motor and psychiatric improvements in PD. This study lays the foundation for large-scale brain network research on multi-network DBS modulation.

Loss of long-term benefit from VIM-DBS in essential tremor: A secondary analysis of repeated measurements.

AIMS: Deep brain stimulation (DBS) in the ventral intermediate nucleus (Vim-DBS) is the preferred surgical therapy for essential tremor (ET). Tolerance and disease progression are considered to be the two main reasons underlying the loss of long-term efficacy of Vim-DBS. This study aimed to explore whether Vim-DBS shows long-term loss of efficacy and to evaluate the reasons for this diminished efficacy from different aspects. METHODS: In a repeated-measures meta-analysis of 533 patients from 18 studies, Vim-DBS efficacy was evaluated at ≤6 months, 7-12 months, 1-3 years, and ≥4 years. The primary outcomes were the score changes in different components of the Fahn-Tolosa-Marin Tremor Rating Scale (TRS; total score, motor score, hand-function score, and activities of daily living [ADL] score). Secondary outcomes were the long-term predictive factors. RESULTS: The TRS total, motor, and ADL scores showed significant deterioration with disease progression (p = 0.002, p = 0.047, and p < 0.001, respectively), while the TRS total (p < 0.001), hand-function (p = 0.036), and ADL (p = 0.004) scores indicated a significant long-term reduction in DBS efficacy, although the motor subscore indicated no loss of efficacy. Hand-function (p < 0.001) and ADL (p = 0.028) scores indicated DBS tolerance, while the TRS total and motor scores did not. Stimulation frequency and preoperative score were predictive factors for long-term results. CONCLUSION: This study provides level 3a evidence that long-term Vim-DBS is effective in controlling motor symptoms without waning benefits. The efficacy reduction for hand function was caused by DBS tolerance, while that for ADL was caused by DBS tolerance and disease progression. More attention should be given to actual functional recovery rather than changes in motor scores in patients with ET.

Deep Brain Stimulation Treating Dystonia: A Systematic Review of Targets, Body Distributions and Etiology Classifications.

Background: Deep brain stimulation (DBS) is a typical intervention treating drug-refractory dystonia. Currently, the selection of the better target, the GPi or STN, is debatable. The outcomes of DBS treating dystonia classified by body distribution and etiology is also a popular question. Objective: To comprehensively compare the efficacy, quality of life, mood, and adverse effects (AEs) of GPi-DBS vs. STN-DBS in dystonia as well as in specific types of dystonia classified by body distribution and etiology. Methods: PubMed, Embase, the Cochrane Library, and Google Scholar were searched to identify studies of GPi-DBS and STN-DBS in populations with dystonia. The efficacy, quality of life, mood, and adverse effects were quantitatively compared. Meta-regression analyses were also performed. This analysis has been registered in PROSPERO under the number CRD42020146145. Results: Thirty five studies were included in the main analysis, in which 319 patients underwent GPI-DBS and 113 patients underwent STN-DBS. The average follow-up duration was 12.48 months (range, 3-49 months). The GPI and STN groups were equivalent in terms of efficacy, quality of life, mood, and occurrence of AEs. The focal group demonstrated significantly better disability symptom improvement (P = 0.012) than the segmental and generalized groups but showed less SF-36 enhancement than the segmental group (P < 0.001). The primary groups exhibited significantly better movement and disability symptom improvements than the secondary non-hereditary group (P < 0.005), which demonstrated only disability symptom improvement compared with the secondary hereditary group (P < 0.005). The primary hereditary and idiopathic groups had a significantly lower frequency of AEs than the secondary non-hereditary group (P < 0.005). The correlation between disability symptom improvement and movement symptom improvement was also significant (P < 0.05). Conclusion: GPi-DBS and STN-DBS were both safe and resulted in excellent improvement in efficacy and quality of life in patients with dystonia. Compared with patients with segmental dystonia, patients with focal dystonia demonstrated better improvement in dystonia symptoms but less enhancement of quality of life. Those with primary dystonia had a better response to DBS in terms of efficacy than those with secondary dystonia. Patients who exhibit a significant improvement in movement symptoms might also exhibit excellent improvement in disability symptoms.