Biology subjects

Sehm, B.

Publications and source records attributed to Sehm, B..

8 recordsLinked to original sources

bioRxiv2025

Patterns of Structural Disconnection Driving Proprioceptive Deficits After Stroke

BackgroundStroke is a leading cause of death and disability worldwide, with proprioceptive impairments affecting up to 64% of survivors. These impairments hinder sensorimotor function and motor recovery, significantly impacting post-stroke disability and quality of life. Proprioception depends on an integrated network of brain regions but remains underexplored due to limitations in clinical assessments, making it difficult to identify precise links between stroke- related damage and functional deficits. To address this, we combined quantitative proprioceptive measurements with Connectome-based Lesion-Symptom Mapping (CLSM) to identify white matter (WM) disconnection patterns underlying proprioceptive deficits following sensorimotor stroke. MethodsIn this observational study, we investigated the relationship between WM disconnection and proprioceptive deficits in 39 chronic stroke survivors with paretic arm function (>6 months post-stroke; 13 females; aged 35-81) using CLSM and kinematic assessments. Lesions were manually delineated from 3T MRI scans, and proprioception was quantified using the Arm Position Matching (APM) task on the KINARM Exoskeleton. Patient-specific voxel-wise WM disconnection maps were generated using the Tractography Lesion Assessment Standard (TractLAS), which quantifies disconnection relative to a healthy WM connectome. Proprioceptive scores were regressed against disconnection maps using voxel-wise linear regressions (family-wise error corrected, controlled for age and sex). ResultsOur disconnectome-based approach identified a network of regions where proprioceptive deficits were significantly associated with WM disconnection (d = 0.55-1, p < .005 FWE, t = 3.48-6.35). These included tracts previously implicated in proprioceptive function (superior longitudinal fasciculus, middle longitudinal fasciculus, and arcuate fasciculus) and beyond (medial lemniscus, spinothalamic tract, posterior thalamic radiation). ConclusionWe provide evidence that post-stroke proprioceptive impairments arise from network- wide WM disconnection in several key tracts that mediate proprioceptive function. This study highlights the benefits of using CLSM to assess stroke-related proprioceptive deficits and offers a framework for network-informed assessments of functional impairments that can be used for targeted therapies post-stroke.

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bioRxiv2024

Motor Imagery Enhances Performance Beyond the Imagined Action

Motor imagery is frequently utilized to improve the performance of specific target movements in sports and rehabilitation. In this study, we show that motor imagery can facilitate learning of not only the imagined target movements but also sequentially linked overt movements. Hybrid sequences comprising imagined and physically executed segments allowed participants to learn specific movement characteristics of the executed segments when they were consistently associated with specific imagined segments. Electrophysiological recordings revealed that the degree of event-related synchronization in the alpha and beta bands during a basic motor imagery task was correlated with imagery-evoked motor learning. Thus, both behavioral and neural evidence indicate that motor imagerys benefits extend beyond the imagined movements, improving performance in linked overt movements. This provides new evidence for the functional equivalence of imagined and overt movements and suggests new applications for imagery in sports and rehabilitation.

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bioRxiv2022

Prior movement of one arm facilitates motor adaptation in the other

Many movements in daily life are embedded in motion sequences that involve more than one limb, demanding the motor system to monitor and control different body parts in quick succession. During such movements, systematic changes in the environment or the body might require motor adaptation of specific segments. However, previous motor adaptation research has focused primarily on motion sequences produced by a single limb, or on simultaneous movements of several limbs. For example, adaptation to opposing force fields is possible in unimanual reaching tasks when the direction of a prior or subsequent movement is predictive of force field direction. It is unclear, however, whether multi-limb sequences can support motor adaptation processes in a similar way. In the present study, we investigated whether reaches can be adapted to different force fields in a bimanual motor sequence when the information about the perturbation is associated with the prior movement direction of the other arm. In addition, we examined whether prior perceptual (visual or proprioceptive) feedback of the opposite arm contributes to force field-specific motor adaptation. Our key finding is that only active participation in the bimanual sequential task supports pronounced adaptation. This result suggests that active segments in bimanual motion sequences are linked across limbs. If there is a consistent association between movement kinematics of the linked and goal movement, the learning process of the goal movement can be facilitated. More generally, if motion sequences are repeated often, prior segments can evoke specific adjustments of subsequent movements. Significance statementMovements in a limbs motion sequence can be adjusted based on linked movements. A prerequisite is that kinematics of the linked movements correctly predict which adjustments are needed. We show that use of kinematic information to improve performance is even possible when a prior linked movement is performed with a different limb. For example, a skilled juggler might have learned how to correctly adjust his catching movement of the left hand when the right hand performed a throwing action in a specific way. Linkage is possibly a key mechanism of the human motor system for learning complex bimanual skills. Our study emphasizes that learning of specific movements should not be studied in isolation but within their motor sequence context.

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bioRxiv2021

Distributed networks for auditory memory contribute differentially to recall precision

Re-directing attention to objects in working memory can enhance their representational fidelity. However, how this attentional enhancement of memory representations is implemented across distinct, sensory and cognitive-control brain network is unspecified. The present fMRI experiment leverages psychophysical modelling and multivariate auditory- pattern decoding as behavioral and neural proxies of mnemonic fidelity. Listeners performed an auditory syllable pitch-discrimination task and received retro-active cues to selectively attend to a to-be-probed syllable in memory. Accompanied by increased neural activation in fronto-parietal and cingulo-opercular networks, valid retro-cues yielded faster and more perceptually sensitive responses in recalling acoustic detail of memorized syllables. Information about the cued auditory object was decodable from hemodynamic response patterns in superior temporal sulcus (STS), fronto-parietal, and sensorimotor regions. However, among these regions retaining auditory memory objects, neural fidelity in the left STS and its enhancement through attention-to-memory best predicted individuals gain in auditory memory recall precision. Our results demonstrate how functionally discrete brain regions differentially contribute to the attentional enhancement of memory representations.

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bioRxiv2020

Modulation of neural activity in frontopolar cortex drives reward-based motor learning

Decision-making is increasingly being recognised to play a role in learning motor skills. Understanding the neural processes regulating motor decision-making is therefore essential to identify mechanisms that contribute to motor skill learning. In decision-making tasks, the frontopolar cortex (FPC) is involved in tracking the reward of different alternative choices, as well as their reliability. Whether this FPC function extends to reward landscapes associated with a continuous movement dimension remains unknown. Here we used anodal transcranial direct current stimulation (tDCS) over the right FPC to investigate its role in reward-based motor learning. Nineteen healthy human participants completed a motor sequence learning task using trial-wise reward feedback to discover a hidden performance goal along a continuous dimension: timing. As a control condition, we modulated contralateral motor cortex (left M1) activity with tDCS, which has been shown to benefit motor skill learning but less consistently reward-based motor learning. Each active tDCS condition was contrasted to sham stimulation. Right FPC-tDCS led to faster learning primarily through a regulation of exploration, without concurrent modulation of motor noise. A Bayesian computational model revealed that following rFPC-tDCS, participants had a higher expectation of reward, consistent with their faster learning. These higher reward estimates were inferred to be less volatile, and thus participants under rFPC-tDCS deemed the mapping between movement and reward to be more stable. Relative to sham, lM1-tDCS did not significantly modulate main behavioral outcomes. The results indicate that brain regions previously linked to decision-making, such as the FPC, are relevant for motor skill learning.

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bioRxiv2020

A flexible workflow for simulating transcranial electric stimulation in healthy and lesioned brains

Simulating transcranial electric stimulation is actively researched as knowledge about the distribution of the electrical field is decisive for understanding the variability in the elicited stimulation effect. Several software pipelines comprehensively solve this task in an automated manner for standard use-cases. However, simulations for non-standard applications such as uncommon electrode shapes or the creation of head models from non-optimized T1-weighted imaging data and the inclusion of irregular structures are more difficult to accomplish. We address these limitations and suggest a comprehensive workflow to simulate transcranial electric stimulation based on open-source tools. The workflow covers the head model creation from MRI data, the electrode modeling, the modeling of anisotropic conductivity behavior of the white matter, the numerical simulation and visualization. Skin, skull, air cavities, cerebrospinal fluid, white matter, and gray matter are segmented semi-automatically from T1-weighted MR images. Electrodes of arbitrary number and shape can be modeled. The meshing of the head model is implemented in a way to preserve feature edges of the electrodes and is free of topological restrictions of the considered structures of the head model. White matter anisotropy can be computed from diffusion-tensor imaging data. Our solver application was verified analytically and by contrasting tDCS simulation results with another simulation pipeline (SimNIBS 3.0). An agreement in both cases underlines the validity of our workflow. Our suggested solutions facilitate investigations of irregular structures in patients (e.g. lesions, implants) or of new electrode types. For a coupled use of the described workflow, we provide documentation and disclose the full source code of the developed tools.

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bioRxiv2019

Multimodal DTI-TMS assessment of the motor system in patients with chronic ischemic stroke

Background and PurposeDespite the continuing efforts in multimodal assessment of the motor system after stroke, conclusive findings on the complementarity of functional and structural metrics of the corticospinal tract (CST) integrity and the role of the contralesional hemisphere are still missing. The aim of this work was to find the best combination of the motor system parameters, allowing classification of patients into three predefined groups of upper limb motor recovery. Methods35 chronic ischemic stroke patients (47 [26-66] y.o., 29 [6-58] months post-stroke) with only supratentorial lesion and unilateral upper extremity weakness were enrolled. Patients were divided into three groups depending on the upper limb motor recovery. Non-parametric statistical tests and regression analysis were used to investigate the relationships among structural and functional motor system parameters, probed by diffusion tensor imaging (DTI) and transcranial magnetic stimulation (TMS). In addition, stratification rules were tested, using a decision tree classifier to identify parameters explaining motor recovery. ResultsFractional anisotropy (FA) ratio in the internal capsule (IC) and absence/presence of motor evoked potentials (MEPs), were equally discriminative of the worst motor outcome group (96% accuracy). MEP presence diverged for two investigated hand muscles. Concurrently, for the three recovery groups classification, the best parameter combination was: IC FA ratio and Frechet distance between the contralesional and ipsilesional CST FA profiles (91% accuracy). No other metrics had any additional value for patients classification. ConclusionsThis study demonstrates that IC FA ratio and MEPs absence are equally important markers for poor recovery. Importantly, we found that MEPs should be controlled in more than one hand muscle. Finally, we show that better separation between different motor recovery groups may be achieved when considering the whole CST FA profile.

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bioRxiv2017

Dopaminergic Modulation Of Brain Signal Variability And The Functional Connectome During Cognitive Performance

Dopamine underlies important aspects of cognition, and has been suggested to boost cognitive performance. However, how dopamine modulates the large-scale cortical dynamics during cognitive performance has remained elusive. Using functional MRI during a working memory task in healthy young human listeners (N=22), we investigated the effect of levodopa (L-dopa) on two aspects of cortical dynamics, blood oxygen-level-dependent (BOLD) signal variability and the functional connectome of large-scale cortical networks. We here show that enhanced dopaminergic signaling modulates the two potentially interrelated aspects of large-scale cortical dynamics during cognitive performance, and the degree of these modulations is able to explain inter-individual differences in L-dopa-induced behavioral benefits. Relative to placebo, L-dopa increased BOLD signal variability in task-relevant temporal, inferior frontal, parietal and cingulate regions. On the connectome level, however, L-dopa diminished functional integration across temporal and cingulo-opercular regions. This hypo-integration was expressed as a reduction in network efficiency and modularity in more than two thirds of the participants and to different degrees. Hypo-integration co-occurred with relative hyper-connectivity in paracentral lobule and precuneus, as well as posterior putamen. Both, L-dopa-induced BOLD signal variability modulation and functional connectome modulations proved predictive of an individuals L-dopa-induced gain in behavioral performance, namely response speed and perceptual sensitivity. Lastly, L-dopa-induced modulations of BOLD signal variability were correlated with L-dopa-induced modulation of nodal connectivity and network efficiency. Our findings underline the role of dopamine in maintaining the dynamic range of, and communication between, cortical systems, and their explanatory power for inter-individual differences in benefits from dopamine during cognitive performance.

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