Biology subjects

Schneider, G.-H.

Publications and source records attributed to Schneider, G.-H..

8 recordsLinked to original sources

bioRxiv2025

Dynamics of cortico-subthalamic neuronal patterns during dyskinesia in Parkinsons disease

Parkinson patients suffer from levodopa-induced dyskinesia, which occur adversely to chronic dopaminergic treatment. These abnormal involuntary movements can only partly be actively suppressed and affect quality of life. A lowered motor inhibition during hyperdopaminergic states, associated with structural and plasticity changes in the cortico-basal-ganglia motor network, is hypothesized to enable dyskinesia. Oscillatory cortico-subthalamic patterns associated with dyskinesia are proposed as adaptive neuromodulation biomarkers, but their dependence on behavioral states such as dyskinetic movement presence or suppression remains unknown. We studied cortico-subthalamic oscillations in 22 Parkinsons patients during dyskinesia-evoking protocols. We clinically differentiated between non-dyskinetic and dyskinetic periods, and defined movement presence with kinematics, leading to four behavioral states containing rest, voluntary movements, movement suppression during dyskinesia, and dyskinetic movements. Elevated subthalamic theta-activity and attenuated beta-activity was found during both dyskinetic movement suppression and execution, while cortico-subthalamic gamma-activity only increased during dyskinetic movement execution. Subthalamic spectral changes significantly predicted dyskinesia presence, and movement presence significantly affected the predictive performance. A movement-aware classifier enhanced dyskinesia detection based on movement-depending biomarkers containing cortical oscillations and gamma-bands. We propose movement execution during dyskinesia to be a distinct behavioral and neural microstate within a dopamine-depending dyskinetic macrostate, that can enhance dyskinesia classification for adaptive neuromodulation.

neuroscience↗

bioRxiv2025

Differential modulation of movement speed with state-dependent deep brain stimulation in Parkinson's disease

Subthalamic deep brain stimulation (STN-DBS) provides unprecedented spatiotemporal precision for the treatment of Parkinsons disease (PD), allowing for direct real-time state-specific adjustments. Inspired by findings from optogenetic stimulation in mice, we hypothesized that STN-DBS effects on movement speed depend on ongoing movement kinematics that patients exhibit during stimulation. To investigate this hypothesis, we implemented a motor state-dependent closed-loop neurostimulation algorithm, adapting DBS burst delivery to ongoing movement speed in 24 PD patients. We found a stronger anti-bradykinetic effect, raising movement speed to the level of healthy controls, when STN-DBS was applied during fast but not slow movements, while only stimulating 5% of overall movement time. To study underlying brain circuits and neurophysiological mechanisms, we investigated the behavioral effects with MRI connectomics and motor cortex electrocorticography. Finally, we demonstrate that machine learning-based brain signal decoding can be used to predict continuous movement speed for fully embedded state-dependent closed-loop algorithms. Our findings provide novel insights into the state-dependency of invasive neuromodulation, which could inspire advanced state-dependent neurostimulation algorithms for brain disorders.

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bioRxiv2025

Beyond beta: Aperiodic broadband power reflects Parkinson's disease severity - a multicenter study

Parkinsons disease is linked to increased beta oscillations in the subthalamic nucleus, which correlate with motor symptoms. However, findings across studies have varied. Our standardized analysis of multicenter datasets shows that small sample sizes contributed to these discrepancies--a challenge we address by pooling datasets into one large cohort (n=119). Moving beyond beta power, we disentangled spectral components reflecting distinct neural processes. Combining aperiodic offset, low beta, and low gamma oscillations explained significantly more variance in symptom severity than beta alone. Moreover, interhemispheric within-patient analyses showed that, unlike beta oscillations, aperiodic broadband power-likely reflecting spiking activity-was increased in the more affected hemisphere. These findings identify aperiodic broadband power as a potential biomarker for adaptive deep brain stimulation and provide novel insights into the relationship between subthalamic hyperactivity and motor symptoms in human Parkinsons disease.

neuroscience↗

bioRxiv2024

Shared pathway-specific network mechanisms of dopamine and deep brain stimulation for the treatment of Parkinson's disease

Deep brain stimulation is a brain circuit intervention that can modulate distinct neural pathways for the alleviation of neurological symptoms in patients with brain disorders. In Parkinsons disease, subthalamic deep brain stimulation clinically mimics the effect of dopaminergic drug treatment, but the shared pathway mechanisms on cortex - basal ganglia networks are unknown. To address this critical knowledge gap, we combined fully invasive neural multisite recordings in patients undergoing deep brain stimulation surgery with normative MRI-based whole-brain connectomics. Our findings demonstrate that dopamine and stimulation exert distinct mesoscale effects through modulation of local neural population activity. In contrast, at the macroscale, stimulation mimics dopamine in its suppression of excessive interregional network synchrony associated with indirect and hyperdirect cortex - basal ganglia pathways. Our results provide a better understanding of the circuit mechanisms of dopamine and deep brain stimulation, laying the foundation for advanced closed-loop neurostimulation therapies.

neuroscience↗

bioRxiv2023

Dopamine and neuromodulation shorten the latency from motor intention to execution in Parkinson's disease

The ability to initiate volitional action is fundamental to human behaviour. Loss of dopaminergic neurons in Parkinsons 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 Parkinsons 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 Parkinsons 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.

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bioRxiv2022

Subthalamic beta bursts correlate with dopamine-dependent motor symptoms in 106 Parkinson's patients

Pathologically increased beta power has been described as a biomarker for Parkinsons disease (PD) and related to prolonged bursts of subthalamic beta synchronization. Here, we investigate the association between subthalamic beta dynamics and motor impairment in a cohort of 106 Parkinsons patients in the ON- and OFF-medication state, suing two different methods of beta burst determination. We report a frequency-specific correlation of low beta power and burst duration with motor impairment OFF dopaminergic medication. Furthermore, reduction of power and burst duration correlated significantly with symptom alleviation through dopaminergic medication. Importantly, qualitatively similar results were yielded with two different methods of beta burst definition. Our findings validate the robustness of previous results on pathological changes in subcortical oscillations both in the frequency-as well as in the time-domain in the largest cohort of PD patients to date with important implications for next-generation adaptive deep brain stimulation control algorithms.

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bioRxiv2021

The sensitivity of ECG contamination to surgical implantation site in adaptive closed-loop neurostimulation systems

BackgroundBrain sensing devices are approved today for Parkinsons, essential tremor, and epilepsy therapies. Clinical decisions for implants are often influenced by the premise that patients will benefit from using sensing technology. However, artifacts, such as ECG contamination, can render such treatments unreliable. Therefore, clinicians need to understand how surgical decisions may affect artifact probability. ObjectivesInvestigate neural signal contamination with ECG activity in sensing enabled neurostimulation systems, and in particular clinical choices such as implant location that impact signal fidelity. MethodsElectric field modelling and empirical signals from 85 patients were used to investigate the relationship between implant location and ECG contamination.a ResultsThe impact on neural recordings depends on the difference between ECG signal and noise floor of the electrophysiological recording. Empirically, we demonstrate that severe ECG contamination was more than 3.2x higher in left-sided subclavicular implants (48.3%), when compared to right-sided implants (15.3%). Cranial implants did not show ECG contamination. ConclusionsGiven the relative frequency of corrupted neural signals, we conclude that implant location will impact the ability of brain sensing devices to be used for "closed-loop" algorithms. Clinical adjustments such as implant location can significantly affect signal integrity and need consideration. HighlightsO_LIChronic embedded brain sensing promises algorithm-based neurostimulation C_LIO_LIAlgorithms for closed-loop stimulation can be impaired by artifacts C_LIO_LIThe relationship of implant location to cardiac dipole has relevant impact on neural signal fidelity; simple models can provide guidance on the sensitivity C_LIO_LIECG artifacts are present in up to 50% of neural signals from left subclavicular DBS systems C_LIO_LIImplanting DBS in a right subclavicular location significantly reduces frequency of ECG artifacts C_LIO_LICranial-mounted implants are relatively immune to artifacts C_LI

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bioRxiv2019

Left prefrontal connectivity links subthalamic stimulation with depressive symptoms in Parkinson’s disease

ObjectiveSubthalamic nucleus deep brain stimulation (STN-DBS) in Parkinsons Disease (PD) not only stimulates focal target structures but also affects distributed brain networks. The impact this network modulation has on non-motor DBS effects is not well characterized. By focusing on the affective domain, we systematically investigate the impact of electrode placement and associated structural connectivity on changes in depressive symptoms following STN-DBS which have been reported to improve, worsen or remain unchanged. MethodsDepressive symptoms before and after STN-DBS surgery were documented in 116 PD patients from three DBS centers (Berlin, Queensland, Cologne). Based on individual electrode reconstructions, the volumes of tissue activated (VTA) were estimated and combined with normative connectome data to identify structural connections passing through VTAs. Berlin and Queensland cohorts formed a training and cross-validation dataset used to identify structural connectivity explaining change in depressive symptoms. The Cologne data served as test-set for which depressive symptom change was predicted. ResultsStructural connectivity was linked to depressive symptom change under STN-DBS. An optimal connectivity map trained on the Berlin cohort could predict changes in depressive symptoms in Queensland patients and vice versa. Furthermore, the joint training-set map predicted changes in depressive symptoms in the independent test-set. Worsening of depressive symptoms was associated with left prefrontal connectivity. InterpretationFibers linking the STN electrode with left prefrontal areas predicted worsening of depressive symptoms. Our results suggest that for the left STN-DBS lead, placement impacting fibers to left prefrontal areas should be avoided to maximize improvement of depressive symptoms.

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