Time-resolved quantification of fine hand movements as a proxy for evaluating bradykinesia-induced motor dysfunction.

Bradykinesia is a behavioral manifestation that contributes to functional dependencies in later life. However, the current state of bradykinesia indexing primarily relies on subjective, time-averaged categorizations of motor deficits, which often yield poor reliability. Herein, we used time-resolved analyses of accelerometer recordings during standardized movements, data-driven factor analyses, and linear mixed effects models (LMEs) to quantitatively characterize general, task- and therapy-specific indices of motor impairment in people with Parkinson's disease (PwP) currently undergoing treatment for bradykinesia. Our results demonstrate that single-trial, accelerometer-based features of finger-tapping and rotational hand movements were significantly modulated by divergent therapeutic regimens. Further, these features corresponded well to current gold standards for symptom monitoring, with more precise predictive capacities of bradykinesia-specific declines achieved when considering kinematic features from diverse movement types together, rather than in isolation. Herein, we report data-driven, sample-specific kinematic profiles of diverse movement types along a continuous spectrum of motor impairment, which importantly, preserves the temporal scale for which biomechanical fluctuations in motor deficits evolve in humans. Therefore, this approach may prove useful for tracking bradykinesia-induced motor decline in aging populations the future.

Modulation of DBS-induced cortical responses and movement by the directionality and magnitude of current administered.

Subthalamic deep brain stimulation (STN-DBS) is an effective therapy for alleviating motor symptoms in people with Parkinson's disease (PwP), although some may not receive optimal clinical benefits. One potential mechanism of STN-DBS involves antidromic activation of the hyperdirect pathway (HDP), thus suppressing cortical beta synchrony to improve motor function, albeit the precise mechanisms underlying optimal DBS parameters are not well understood. To address this, 18 PwP with STN-DBS completed a 2 Hz monopolar stimulation of the left STN during MEG. MEG data were imaged in the time-frequency domain using minimum norm estimation. Peak vertex time series data were extracted to interrogate the directional specificity and magnitude of DBS current on evoked and induced cortical responses and accelerometer metrics of finger tapping using linear mixed-effects models and mediation analyses. We observed increases in evoked responses (HDP ~ 3-10 ms) and synchronization of beta oscillatory power (14-30 Hz, 10-100 ms) following DBS pulse onset in the primary sensorimotor cortex (SM1), supplementary motor area (SMA) and middle frontal gyrus (MFG) ipsilateral to the site of stimulation. DBS parameters significantly modulated neural and behavioral outcomes, with clinically effective contacts eliciting significant increases in medium-latency evoked responses, reductions in induced SM1 beta power, and better movement profiles compared to suboptimal contacts, often regardless of the magnitude of current applied. Finally, HDP-related improvements in motor function were mediated by the degree of SM1 beta suppression in a setting-dependent manner. Together, these data suggest that DBS-evoked brain-behavior dynamics are influenced by the level of beta power in key hubs of the basal ganglia-cortical loop, and this effect is exacerbated by the clinical efficacy of DBS parameters. Such data provides novel mechanistic and clinical insight, which may prove useful for characterizing DBS programming strategies to optimize motor symptom improvement in the future.

Mapping Subcortico-Cortical Coupling-A Comparison of Thalamic and Subthalamic Oscillations.

BACKGROUND: The ventral intermediate nucleus of the thalamus (VIM) is an effective target for deep brain stimulation in tremor patients. Despite its therapeutic importance, its oscillatory coupling to cortical areas has rarely been investigated in humans. OBJECTIVES: The objective of this study was to identify the cortical areas coupled to the VIM in patients with essential tremor. METHODS: We combined resting-state magnetoencephalography with local field potential recordings from the VIM of 19 essential tremor patients. Whole-brain maps of VIM-cortex coherence in several frequency bands were constructed using beamforming and compared with corresponding maps of subthalamic nucleus (STN) coherence based on data from 19 patients with Parkinson's disease. In addition, we computed spectral Granger causality. RESULTS: The topographies of VIM-cortex and STN-cortex coherence were very similar overall but differed quantitatively. Both nuclei were coupled to the ipsilateral sensorimotor cortex in the high-beta band; to the sensorimotor cortex, brainstem, and cerebellum in the low-beta band; and to the temporal cortex, brainstem, and cerebellum in the alpha band. High-beta coherence to sensorimotor cortex was stronger for the STN (P = 0.014), whereas low-beta coherence to the brainstem was stronger for the VIM (P = 0.017). Although the STN was driven by cortical activity in the high-beta band, the VIM led the sensorimotor cortex in the alpha band. CONCLUSIONS: Thalamo-cortical coupling is spatially and spectrally organized. The overall similar topographies of VIM-cortex and STN-cortex coherence suggest that functional connections are not necessarily unique to one subcortical structure but might reflect larger frequency-specific networks involving VIM and STN to a different degree. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Parkinsonian rest tremor can be distinguished from voluntary hand movements based on subthalamic and cortical activity.

OBJECTIVE: To distinguish Parkinsonian rest tremor and different voluntary hand movements by analyzing brain activity. METHODS: We re-analyzed magnetoencephalography and local field potential recordings from the subthalamic nucleus of six patients with Parkinson's disease. Data were obtained after withdrawal from dopaminergic medication (Med Off) and after administration of levodopa (Med On). Using gradient-boosted tree learning, we classified epochs as tremor, fist-clenching, forearm extension or tremor-free rest. RESULTS: Subthalamic activity alone was insufficient for distinguishing the four different motor states (balanced accuracy mean: 38%, std: 7%). The combination of cortical and subthalamic features, in contrast, allowed for a much more accurate classification (balanced accuracy mean: 75%, std: 17%). Adding a single cortical area improved balanced accuracy by 17% on average, as compared to classification based on subthalamic activity alone. In most patients, the most informative cortical areas were sensorimotor cortical regions. Decoding performance was similar in Med On and Med Off. CONCLUSIONS: Electrophysiological recordings allow for distinguishing several motor states, provided that cortical signals are monitored in addition to subthalamic activity. SIGNIFICANCE: By combining cortical recordings, subcortical recordings and machine learning, adaptive deep brain stimulation systems might be able to detect tremor specifically and to respond adequately to several motor states.

The importance of pyramidal tract integrity for cortical plasticity and related functionality in patients with multiple sclerosis.

Background: Cortical plasticity induced by quadripulse stimulation (QPS) has been shown to correlate with cognitive functions in patients with relapsing-remitting multiple sclerosis (RRMS) and to not be reduced compared to healthy controls (HCs). Objective: This study aimed to compare the degree of QPS-induced plasticity between different subtypes of multiple sclerosis (MS) and HCs and to investigate the association of the degree of plasticity with motor and cognitive functions. We expected lower levels of plasticity in patients with progressive MS (PMS) but not RRMS compared to HCs. Furthermore, we expected to find positive correlations with cognitive and motor performance in patients with MS. Methods: QPS-induced plasticity was compared between 34 patients with PMS, 30 patients with RRMS, and 30 HCs using linear mixed-effects models. The degree of QPS-induced cortical plasticity was correlated with various motor and cognitive outcomes. Results: There were no differences regarding the degree of QPS-induced cortical plasticity between HCs and patients with RRMS (p = 0.86) and PMS (p = 0.18). However, we only found correlations between the level of induced plasticity and both motor and cognitive functions in patients with intact corticospinal tract integrity. Exploratory analysis revealed significantly reduced QPS-induced plasticity in patients with damage compared to intact corticospinal tract integrity (p < 0.001). Conclusion: Our study supports the notion of pyramidal tract integrity being of more relevance for QPS-induced cortical plasticity in MS and related functional significance than the type of disease.

Prevalence and prognostic value of neurological affections in hospitalized patients with moderate to severe COVID-19 based on objective assessments.

Neurological manifestations of coronavirus disease 2019 (COVID-19) have been frequently described. In this prospective study of hospitalized COVID-19 patients without a history of neurological conditions, we aimed to analyze their prevalence and prognostic value based on established, standardized and objective methods. Patients were investigated using a multimodal electrophysiological approach, accompanied by neuropsychological and neurological examinations. Prevalence rates of central (CNS) and peripheral (PNS) nervous system affections were calculated and the relationship between neurological affections and mortality was analyzed using Firth logistic regression models. 184 patients without a history of neurological diseases could be enrolled. High rates of PNS affections were observed (66% of 138 patients receiving electrophysiological PNS examination). CNS affections were less common but still highly prevalent (33% of 139 examined patients). 63% of patients who underwent neuropsychological testing (n = 155) presented cognitive impairment. Logistic regression models revealed pathology in somatosensory evoked potentials as an independent risk factor of mortality (Odds Ratio: 6.10 [1.01-65.13], p = 0.049). We conclude that hospitalized patients with moderate to severe COVID-19 display high rates of PNS and CNS affection, which can be objectively assessed by electrophysiological examination. Electrophysiological assessment may have a prognostic value and could thus be helpful to identify patients at risk for deterioration.

Temporal dynamics of oscillatory activity during nonlexical language decoding: Evidence from Morse code and magnetoencephalography.

Understanding encoded languages, such as written script or Morse code, requires nonlexical and lexical processing components that act in a parallel and interactive fashion. Decoding written script-as for example in reading-is typically very fast, making the investigation of the lexical and nonlexical components and their underlying neural mechanisms challenging. In the current study, we aimed to accomplish this problem by using Morse code as a model for language decoding. The decoding of Morse code is slower and thus allows a better and more fine-grained investigation of the lexical and nonlexical components of language decoding. In the current study, we investigated the impact of various components of nonlexical decoding of Morse code using magnetoencephalography. For this purpose, we reconstructed the time-frequency responses below 40 Hz in brain regions significantly involved in Morse code decoding and word comprehension that were identified in a previous study. Event-related reduction in beta- and alpha-band power were found in left inferior frontal cortex and angular gyrus, respectively, while event-related theta-band power increase was found at frontal midline. These induced oscillations reflect working-memory encoding, long-term memory retrieval as well as demanding cognitive control, respectively. In sum, by using Morse code and MEG, we were able to identify a cortical network underlying language decoding in a time- and frequency-resolved manner.

Local Field Potentials Predict Motor Performance in Deep Brain Stimulation for Parkinson's Disease.

BACKGROUND: Deep brain stimulation (DBS) is an effective treatment option for patients with Parkinson's disease (PD). However, clinical programming remains challenging with segmented electrodes. OBJECTIVE: Using novel sensing-enabled neurostimulators, we investigated local field potentials (LFPs) and their modulation by DBS to assess whether electrophysiological biomarkers may facilitate clinical programming in chronically implanted patients. METHODS: Sixteen patients (31 hemispheres) with PD implanted with segmented electrodes in the subthalamic nucleus and a sensing-enabled neurostimulator were included in this study. Recordings were conducted 3 months after DBS surgery following overnight withdrawal of dopaminergic medication. LFPs were acquired while stimulation was turned OFF and during a monopolar review of both directional and ring contacts. Directional beta power and stimulation-induced beta power suppression were computed. Motor performance, as assessed by a pronation-supination task, clinical programming and electrode placement were correlated to directional beta power and stimulation-induced beta power suppression. RESULTS: Better motor performance was associated with stronger beta power suppression at higher stimulation amplitudes. Across directional contacts, differences in directional beta power and the extent of stimulation-induced beta power suppression predicted motor performance. However, within individual hemispheres, beta power suppression was superior to directional beta power in selecting the contact with the best motor performance. Contacts clinically activated for chronic stimulation were associated with stronger beta power suppression than non-activated contacts. CONCLUSIONS: Our results suggest that stimulation-induced ß power suppression is superior to directional ß power in selecting the clinically most effective contact. In sum, electrophysiological biomarkers may guide programming of directional DBS systems in PD patients. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Long-term potentiation-like plasticity is retained during relapse in patients with Multiple Sclerosis.

OBJECTIVE: To investigate the degree of synaptic plasticity in Multiple Sclerosis (MS) patients during acute relapses compared to stable MS patients and healthy controls (HCs) and to analyze its functional relevance. METHODS: Facilitatory quadripulse stimulation (QPS) was applied to the primary motor cortex in 18 acute relapsing and 18 stable MS patients, as well as 18 HCs. The degree of synaptic plasticity was measured by the change in motor evoked potential amplitude following QPS. Symptom recovery was assessed three months after relapse. RESULTS: Synaptic plasticity was induced in all groups. The degree of induced plasticity did not differ between acute relapsing patients, HCs, and stable MS patients. Plasticity was significantly higher in relapsing patients with motor disability compared to relapsing patients without motor disability. In most patients (n = 9, 50%) symptoms had at least partially recovered three months after the relapse, impeding meaningful analysis of the functional relevance of baseline synaptic plasticity. CONCLUSIONS: QPS-induced synaptic plasticity is retained during acute MS relapses. Subgroup analyses suggest that stabilizing metaplastic mechanisms may be more important to prevent motor disability but its functional relevance needs to be verified in larger, longitudinal studies. SIGNIFICANCE: New insights into synaptic plasticity during MS relapses are provided.

Alterations of PAC-based resting state networks in Parkinson's disease are partially alleviated by levodopa medication.

Introduction: Parkinson's disease (PD) is a neurodegenerative disorder affecting the whole brain, leading to several motor and non-motor symptoms. In the past, it has been shown that PD alters resting state networks (RSN) in the brain. These networks are usually derived from fMRI BOLD signals. This study investigated RSN changes in PD patients based on maximum phase-amplitude coupling (PAC) throughout the cortex. We also tested the hypothesis that levodopa medication shifts network activity back toward a healthy state. Methods: We recorded 23 PD patients and 24 healthy age-matched participants for 30 min at rest with magnetoencephalography (MEG). PD patients were measured once in the dopaminergic medication ON and once in the medication OFF state. A T1-MRI brain scan was acquired from each participant for source reconstruction. After correcting the data for artifacts and performing source reconstruction using a linearly constrained minimum variance beamformer, we extracted visual, sensorimotor (SMN), and frontal RSNs based on PAC. Results: We found significant changes in all networks between healthy participants and PD patients in the medication OFF state. Levodopa had a significant effect on the SMN but not on the other networks. There was no significant change in the optimal PAC coupling frequencies between healthy participants and PD patients. Discussion: Our results suggest that RSNs, based on PAC in different parts of the cortex, are altered in PD patients. Furthermore, levodopa significantly affects the SMN, reflecting the clinical alleviation of motor symptoms and leading to a network normalization compared to healthy controls.

A First Methodological Development and Validation of ReTap: An Open-Source UPDRS Finger Tapping Assessment Tool Based on Accelerometer-Data.

Bradykinesia is a cardinal hallmark of Parkinson's disease (PD). Improvement in bradykinesia is an important signature of effective treatment. Finger tapping is commonly used to index bradykinesia, albeit these approaches largely rely on subjective clinical evaluations. Moreover, recently developed automated bradykinesia scoring tools are proprietary and are not suitable for capturing intraday symptom fluctuation. We assessed finger tapping (i.e., Unified Parkinson's Disease Rating Scale (UPDRS) item 3.4) in 37 people with Parkinson's disease (PwP) during routine treatment follow ups and analyzed their 350 sessions of 10-s tapping using index finger accelerometry. Herein, we developed and validated ReTap, an open-source tool for the automated prediction of finger tapping scores. ReTap successfully detected tapping blocks in over 94% of cases and extracted clinically relevant kinematic features per tap. Importantly, based on the kinematic features, ReTap predicted expert-rated UPDRS scores significantly better than chance in a hold out validation sample (n = 102). Moreover, ReTap-predicted UPDRS scores correlated positively with expert ratings in over 70% of the individual subjects in the holdout dataset. ReTap has the potential to provide accessible and reliable finger tapping scores, either in the clinic or at home, and may contribute to open-source and detailed analyses of bradykinesia.

Neuroimaging-based analysis of DBS outcomes in pediatric dystonia: Insights from the GEPESTIM registry.

INTRODUCTION: Deep brain stimulation (DBS) is an established treatment in patients of various ages with pharmaco-resistant neurological disorders. Surgical targeting and postoperative programming of DBS depend on the spatial location of the stimulating electrodes in relation to the surrounding anatomical structures, and on electrode connectivity to a specific distribution pattern within brain networks. Such information is usually collected using group-level analysis, which relies on the availability of normative imaging resources (atlases and connectomes). Analysis of DBS data in children with debilitating neurological disorders such as dystonia would benefit from such resources, especially given the developmental differences in neuroimaging data between adults and children. We assembled pediatric normative neuroimaging resources from open-access datasets in order to comply with age-related anatomical and functional differences in pediatric DBS populations. We illustrated their utility in a cohort of children with dystonia treated with pallidal DBS. We aimed to derive a local pallidal sweetspot and explore a connectivity fingerprint associated with pallidal stimulation to exemplify the utility of the assembled imaging resources. METHODS: An average pediatric brain template (the MNI brain template 4.5-18.5 years) was implemented and used to localize the DBS electrodes in 20 patients from the GEPESTIM registry cohort. A pediatric subcortical atlas, analogous to the DISTAL atlas known in DBS research, was also employed to highlight the anatomical structures of interest. A local pallidal sweetspot was modeled, and its degree of overlap with stimulation volumes was calculated as a correlate of individual clinical outcomes. Additionally, a pediatric functional connectome of 100 neurotypical subjects from the Consortium for Reliability and Reproducibility was built to allow network-based analyses and decipher a connectivity fingerprint responsible for the clinical improvements in our cohort. RESULTS: We successfully implemented a pediatric neuroimaging dataset that will be made available for public use as a tool for DBS analyses. Overlap of stimulation volumes with the identified DBS-sweetspot model correlated significantly with improvement on a local spatial level (R = 0.46, permuted p = 0.019). The functional connectivity fingerprint of DBS outcomes was determined to be a network correlate of therapeutic pallidal stimulation in children with dystonia (R = 0.30, permuted p = 0.003). CONCLUSIONS: Local sweetspot and distributed network models provide neuroanatomical substrates for DBS-associated clinical outcomes in dystonia using pediatric neuroimaging surrogate data. Implementation of this pediatric neuroimaging dataset might help to improve the practice and pave the road towards a personalized DBS-neuroimaging analyses in pediatric patients.

Long-Term Follow-Up of Pediatric Patients with Dyskinetic Cerebral Palsy and Deep Brain Stimulation.

BACKGROUND: Deep brain stimulation (DBS) has been increasingly used in the management of dyskinetic cerebral palsy (DCP). Data on long-term effects and the safety profile are rare. OBJECTIVES: We assessed the efficacy and safety of pallidal DBS in pediatric patients with DCP. METHODS: The STIM-CP trial was a prospective, single-arm, multicenter study in which patients from the parental trial agreed to be followed-up for up to 36 months. Assessments included motor and non-motor domains. RESULTS: Of the 16 patients included initially, 14 (mean inclusion age 14 years) were assessed. There was a significant change in the (blinded) ratings of the total Dyskinesia Impairment Scale at 36 months. Twelve serious adverse events (possibly) related to treatment were documented. CONCLUSION: DBS significantly improved dyskinesia, but other outcome parameters did not change significantly. Investigations of larger homogeneous cohorts are needed to further ascertain the impact of DBS and guide treatment decisions in DCP. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Reduced syntactic recursion in spontaneous speech of Parkinson's disease patients.

Although characterized as a movement disorder, Parkinson's disease (PD) affects more than just the motor system. Within the heterogenous non-motor symptoms, language impairment is frequent but poorly understood beyond semantic processing. This study investigates the impact of PD on syntactic subordination in spontaneous language production. Fifteen PD patients in ON levodopa status narrated a short story guided by a set of pictures. Thirteen PD patients were also assessed in OFF levodopa status. Narrations were digitally recorded, subsequently transcribed and annotated, making the produced speech accessible to systematical quantitative analysis. Compared to a healthy matched control group, PD patients showed a significant reduction of subordinating structures while the number of non-embedding sentences remained unaffected. No significant effect comparing ON versus OFF levodopa status emerged. Our results suggest a contribution of the basal ganglia to language processing, such as syntactic composition, which, however, does not seem to be dopamine dependent.

Slowing of Frontal ß Oscillations in Atypical Parkinsonism.

BACKGROUND: Diagnosis of atypical parkinsonian syndromes (APS) mostly relies on clinical presentation as well as structural and molecular brain imaging. Whether parkinsonian syndromes are distinguishable based on neuronal oscillations has not been investigated so far. OBJECTIVE: The aim was to identify spectral properties specific to atypical parkinsonism. METHODS: We measured resting-state magnetoencephalography in 14 patients with corticobasal syndrome (CBS), 16 patients with progressive supranuclear palsy (PSP), 33 patients with idiopathic Parkinson's disease, and 24 healthy controls. We compared spectral power as well as amplitude and frequency of power peaks between groups. RESULTS: Atypical parkinsonism was associated with spectral slowing, distinguishing both CBS and PSP from Parkinson's disease (PD) and age-matched healthy controls. Patients with atypical parkinsonism showed a shift in ß peaks (13-30 Hz) toward lower frequencies in frontal areas bilaterally. A concomitant increase in θ/α power relative to controls was observed in both APS and PD. CONCLUSION: Spectral slowing occurs in atypical parkinsonism, affecting frontal ß oscillations in particular. Spectral slowing with a different topography has previously been observed in other neurodegenerative disorders, such as Alzheimer's disease, suggesting that spectral slowing might be an electrophysiological marker of neurodegeneration. As such, it might support differential diagnosis of parkinsonian syndromes in the future. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Application of a 1H Brain MRS Benchmark Dataset to Deep Learning for Out-of-Voxel Artifacts.

Neural networks are potentially valuable for many of the challenges associated with MRS data. The purpose of this manuscript is to describe the AGNOSTIC dataset, which contains 259,200 synthetic 1H MRS examples for training and testing neural networks. AGNOSTIC was created using 270 basis sets that were simulated across 18 field strengths and 15 echo times. The synthetic examples were produced to resemble in vivo brain data with combinations of metabolite, macromolecule, residual water signals, and noise. To demonstrate the utility, we apply AGNOSTIC to train two Convolutional Neural Networks (CNNs) to address out-of-voxel (OOV) echoes. A Detection Network was trained to identify the point-wise presence of OOV echoes, providing proof of concept for real-time detection. A Prediction Network was trained to reconstruct OOV echoes, allowing subtraction during post-processing. Complex OOV signals were mixed into 85% of synthetic examples to train two separate CNNs for the detection and prediction of OOV signals. AGNOSTIC is available through Dryad and all Python 3 code is available through GitHub. The Detection network was shown to perform well, identifying 95% of OOV echoes. Traditional modeling of these detected OOV signals was evaluated and may prove to be an effective method during linear-combination modeling. The Prediction Network greatly reduces OOV echoes within FIDs and achieved a median log10 normed-MSE of -1.79, an improvement of almost two orders of magnitude.

DBS-evoked cortical responses index optimal contact orientations and motor outcomes in Parkinson's disease.

Although subthalamic deep brain stimulation (DBS) is a highly-effective treatment for alleviating motor dysfunction in patients with Parkinson's disease (PD), clinicians currently lack reliable neurophysiological correlates of clinical outcomes for optimizing DBS parameter settings, which may contribute to treatment inefficacies. One parameter that could aid DBS efficacy is the orientation of current administered, albeit the precise mechanisms underlying optimal contact orientations and associated clinical benefits are not well understood. Herein, 24 PD patients received monopolar stimulation of the left STN during magnetoencephalography and standardized movement protocols to interrogate the directional specificity of STN-DBS current administration on accelerometer metrics of fine hand movements. Our findings demonstrate that optimal contact orientations elicit larger DBS-evoked cortical responses in the ipsilateral sensorimotor cortex, and importantly, are differentially predictive of smoother movement profiles in a contact-dependent manner. Moreover, we summarize traditional evaluations of clinical efficacy (e.g., therapeutic windows, side effects) for a comprehensive review of optimal/non-optimal STN-DBS contact settings. Together, these data suggest that DBS-evoked cortical responses and quantitative movement outcomes may provide clinical insight for characterizing the optimal DBS parameters necessary for alleviating motor symptoms in patients with PD in the future.