Biology subjects

Wittenberg, G. F.

Publications and source records attributed to Wittenberg, G. F..

8 recordsLinked to original sources

bioRxiv2026

Cervical spinal cord stimulation disrupts proprioception yet improves voluntary arm reaching

Whether proprioception is necessary for upper-limb motor control has been debated for decades. Classic studies in deafferented animals and humans suggested that proprioception may be dispensable for rapid, goal-directed movements. However, chronic sensory loss conflates the absence of proprioceptive input with years of compensatory adaptation. As a result, the field has lacked a strong causal test of proprioceptions contribution to motor control. Here, we leveraged a clinical trial of cervical spinal cord stimulation (SCS) in individuals with chronic post-stroke hemiparesis to study if electrical stimulation of sensory afferents causally perturbs proprioception and affects arm reaching. We found that turning SCS ON causally impaired proprioceptive perception and postural stabilization in response to force perturbations, and enhanced adaptation to visual errors during implicit learning. Yet visually and non-visually rapid, goal-directed reaching improved in smoothness, straightness and spatial accuracy. These findings provide strong causal evidence that proprioception is not required for rapid, goal-directed action, helping resolve a decades-long debate regarding its necessity for effective movement.

bioengineering↗

bioRxiv2026

Adaptive Neural Reorganization Enables Real-Time Finger-Level Robotic Control in BCI-Naïve Stroke Survivors

Restoring hand function remains a major challenge for individuals with motor impairments following stroke. Noninvasive brain-computer interfaces (BCIs) aim to address this problem by translating neural signals into robotic assistance; however, control of individual fingers has not been demonstrated in BCI-naive populations. In this study, we investigated whether individuals with stroke and no prior BCI experience could achieve finger-level robotic control using motor imagery. Nine stroke-affected participants performed real-time BCI tasks to control a robotic hand through imagined finger movements decoded from electroencephalography. On average, participants achieved decoding accuracies of 84% for two-finger tasks and 61% for three-finger tasks, demonstrating reliable control at the level of individual fingers. These results indicate that discriminable neural signals for fine motor control persist after stroke and can be leveraged using data-driven deep learning decoders. Sensor-level and source-level electrophysiological analyses further reveal patterns of stroke-related neural reorganization. Overall, these findings support the potential of noninvasive, finger-level BCIs for post-stroke robotic assistance.

neuroscience↗

bioRxiv2026

CALM-VLM: CALIBRATION AND SELECTIVE PREDICTION IN VISION-LANGUAGE MODELS FOR RELIABLE BRAIN MRI CLASSIFICATION

AO_SCPLOWBSTRACTC_SCPLOWRecent advances in vision-language models (VLMs) have demonstrated strong multimodal capabilities for medical image analysis. However, their confidence in diagnostic predictions is often unclear, limiting adoption in clinical settings. We introduce CALM-VLM (CALibration Mechanism for Vision-Language Models), which integrates confidence calibration and selective prediction into a generative 3D VLM. To create CALM-VLM, we fine-tuned the Med3DVLM architecture for Alzheimers disease (AD) and stroke classification as initial test cases. To improve reliability, we incorporated temperature scaling on the VLMs generative outputs. The calibrated model then selectively abstained from predictions when uncertain; this also improved its diagnostic accuracy. Experiments across multi-site MRI datasets, from 10 countries worldwide, show that CALM-VLM improved confidence relative to uncalibrated VLMs. Coverage-adjusted test receiver-operator characteristic curve-area under the curve (ROC-AUC) increased by 5% to 13% for both diagnostic tasks across independent test sets. Our calibrated VLM achieved a test ROC-AUC of 0.951 for AD classification and 0.905 for stroke classification. These findings highlight the importance of calibrated, uncertainty-aware VLMs for trustworthy neuroimaging AI.

neuroscience↗

bioRxiv2025

Mapping the Causal Roles of Non-Primary Motor Areas in Human Reach Planning and Execution

Non-primary motor areas, including the dorsal premotor cortex (PMd), ventral premotor cortex (PMv), and posterior parietal cortex (PPC), are involved in movement planning, but their precise contributions remain unclear. We used functional magnetic resonance imaging (fMRI), transcranial magnetic stimulation (TMS), and kinematic assessments to explore how these areas influence reaching performance in neurologically intact adults. Participants performed a reaching task using the KINARM exoskeleton robot. Brief TMS pulse trains were initiated before movement onset to perturb cortical activity at subthreshold and suprathreshold intensities targeting bilateral PMd, PMv, and PPC. Subthreshold stimulation of contralateral PMd and PMv reduced reach efficiency and smoothness, while suprathreshold stimulation of contralateral PPC increased deviation error and reduced smoothness. Among ipsilateral targets, PMd showed consistent TMS-induced effects, and was the only target where resting-state connectivity predicted behavioral response. Stronger interhemispheric connectivity in the primary motor cortex and weaker interhemispheric PPC connectivity were associated with greater reductions in straightness and smoothness during subthreshold ipsilateral PMd stimulation. These findings show that perturbation of premotor and parietal areas during early movement execution alters reach trajectories, and differences in network organization explain variability in behavioral response. Identifying contributions of cortical areas and connectivity patterns may help personalize interventions after stroke. This study was registered at ClinicalTrials.gov under ID NCT04286516.

bioengineering↗

bioRxiv2023

Data-driven biomarkers outperform theory-based biomarkers in predicting stroke motor outcomes

Chronic motor impairments are a leading cause of disability after stroke. Previous studies have predicted motor outcomes based on the degree of damage to predefined structures in the motor system, such as the corticospinal tract. However, such theory-based approaches may not take full advantage of the information contained in clinical imaging data. The present study uses data-driven approaches to predict chronic motor outcomes after stroke and compares the accuracy of these predictions to previously-identified theory-based biomarkers. Using a cross-validation framework, regression models were trained using lesion masks and motor outcomes data from 789 stroke patients (293 female/496 male) from the ENIGMA Stroke Recovery Working Group (age 64.9{+/-}18.0 years; time since stroke 12.2{+/-}0.2 months; normalised motor score 0.7{+/-}0.5 (range [0,1]). The out-of-sample prediction accuracy of two theory-based biomarkers was assessed: lesion load of the corticospinal tract, and lesion load of multiple descending motor tracts. These theory-based prediction accuracies were compared to the prediction accuracy from three data-driven biomarkers: lesion load of lesion-behaviour maps, lesion load of structural networks associated with lesion-behaviour maps, and measures of regional structural disconnection. In general, data-driven biomarkers had better prediction accuracy - as measured by higher explained variance in chronic motor outcomes - than theory-based biomarkers. Data-driven models of regional structural disconnection performed the best of all models tested (R2 = 0.210, p < 0.001), performing significantly better than predictions using the theory-based biomarkers of lesion load of the corticospinal tract (R2 = 0.132, p< 0.001) and of multiple descending motor tracts (R2 = 0.180, p < 0.001). They also performed slightly, but significantly, better than other data-driven biomarkers including lesion load of lesion-behaviour maps (R2 =0.200, p < 0.001) and lesion load of structural networks associated with lesion-behaviour maps (R2 =0.167, p < 0.001). Ensemble models - combining basic demographic variables like age, sex, and time since stroke - improved prediction accuracy for theory-based and data-driven biomarkers. Finally, combining both theory-based and data-driven biomarkers with demographic variables improved predictions, and the best ensemble model achieved R2 = 0.241, p < 0.001. Overall, these results demonstrate that models that predict chronic motor outcomes using data-driven features, particularly when lesion data is represented in terms of structural disconnection, perform better than models that predict chronic motor outcomes using theory-based features from the motor system. However, combining both theory-based and data-driven models provides the best predictions.

neuroscience↗

bioRxiv2023

Representation and Retrieval of Brain Connectivity Information derived from TMS Experiments

BackgroundTranscranial magnetic stimulation (TMS) is a painless non-invasive method that allows focal activation or deactivation of a human brain region in order to assess effects on other brain regions. As such, it has a unique role in elucidating brain connectivity during behavior and at rest. Information regarding brain connectivity derived from TMS experiments has been published in hundreds of papers but is not accessible in aggregate. ObjectiveOur objective was to identify, extract, and represent TMS-connectivity data in a graph database. This approach uses nodes connected by edges to capture the directed nature of interregional communication in the brain while also being flexible enough to contain other information about the connections, such as the source of information and details about the experiments that produced them. MethodsData related to interregional brain connectivity is first extracted from full-text publications, with creation of a table-like structure that list data of multiple types, principally the source and target brain regions, sign (excitatory/inhibitory) and latency. While machine-reading methods were explored, so far human experts have had to extract and verify data. These data are used to populate a neo4j graph database. A graphical user interface coupled with a query system allows users to search for networks and display information about connections between any two brain regions of interest. ResultsExperiments involving two TMS stimulating coils, in which one is over a putative source region and the other is over another region with a measurable effect in the body (such as the primary motor cortex) are the most straightforward to represent in the database. Even in those experiments, differing conventions for naming regions, and differing experimental parameters such as stimulation intensity and coil position, create issues for representing data from multiple studies in the same database. Other types of experiments, such a neuromodulatory stimulation such as rTMS, can provide information regarding connectivity, but are harder to represent. But we have, thus far, stored information about 100 connections in the database and demonstrated its utility in exploring direct and indirect connections between brain regions. We have also explored adding a causal inference method to those connections, allowing information about latency to shape the connections retrieved given latency limits. ConclusionA graph database can flexibly store information about interregional brain connectivity and is particularly useful for exploring the temporal aspects of brain networks.

neuroscience↗

bioRxiv2020

Regional and age-dependent Effects of Cortical Magnetic Stimulation on Unconstrained Reaching Behavior

BackgroundThe specific and dynamic contributions of premotor and supplementary motor areas to reaching movements in aging humans are not well understood. ObjectiveTo better understand the role of cortical motor regions and age on the control of unconstrained reaches against gravity by neurologically intact, younger and older adults. MethodsDouble pulse transcranial magnetic stimulation (TMS) was applied at locations targeting primary motor cortex (M1), dorsal premotor area (PMA), supplementary motor area (SMA), or dorsolateral prefrontal cortex (DLPFC). Paired stimuli were delivered before or after a visual cue was presented to initiate self-paced right-handed reaches to one of three, vertically oriented target locations. ResultsRegional stimulation effects on movement amplitude were observed both early and late in the reach. PMA stimulation increased reach distance to a greater extent than M1, SMA, and DLPFC stimulation. M1 and PMA stimulation increased deviation from the straight-line path around the time of peak velocity to an extent that was greater than SMA and DLPFC stimulation. Cortical stimulation increased the time that elapsed after, but not before, peak velocity. Despite stronger effects of stimulation on reaches in the younger group, this group had shorter times to reach the target after reaching peak velocity. ConclusionThese results provide support for a role of PMA in visually guided movement after movement initiation. For older subjects, the increased time to arrive at the target after peak velocity despite weaker stimulation effects suggests an age-related reduction in sensorimotor processing flexibility for online control of unconstrained reaching. HighlightsO_LIDorsal premotor area stimulation at any time during the reaction-time period and early reaching affected early reach kinematics at least as much as stimulation of primary motor cortex. C_LIO_LIOlder individuals had more stimulation-related interference in the late components of reaching despite having less early effect of stimulation, suggesting a reduction in flexibility of dynamic motor control due to aging. C_LIO_LIThe antigravity component of unconstrained reaching did not have special aspects for regional cortical effects of stimulation. C_LI

neuroscience↗

bioRxiv2020

Normal aging affects unconstrained three-dimensional reaching against gravity with reduced vertical precision and increased co-contraction

Reaching for an object in space forms the basis for many activities of daily living and is important in rehabilitation after stroke and in other neurological and orthopedic conditions. It has been the object of motor control and neuroscience research for over a century, but studies often constrain movement to eliminate the effect of gravity or reduce the degrees of freedom. In some studies, aging has been shown to reduce target accuracy, with a mechanism suggested to be impaired corrective movements. We sought first to explore the changes in control of shoulder and elbow joint movements that occur with aging during performance of reaching movements to different target heights with the normal effects of gravity, unconstrained hand movement, and stable target locations. Three-dimensional kinematic data and electromyography were collected in 14 young (25{+/-}6 years) and 10 older adults (68{+/-}3 years) during second-long reaches to three targets aligned vertically in front of the participants. Older adults took longer to initiate a movement than the young adults and were more variable and inaccurate in their initial and final movements. Target height had greater effect on trajectory curvature variability in older than young adults, with angle variability relative to target position being greater in older adults around the time of peak speed. There were significant age-related differences in use of the multiple degrees of freedom of the upper extremity, with less variability in shoulder abduction in the older group. Muscle activation patterns were similar, except for a higher biceps-triceps co-contraction and tonic levels of some proximal muscle activation. The path length of movements was not affected by age. These results show an age-related deficit in the motor planning and online correction of reaching movements against a predictable force (i.e., gravity). These results will facilitate interpretation of our forthcoming study of transcranial magnetic stimulation effects on the same task in these two populations, and is relevant to any study that seeks to measure the effect of pathological processes on upper extremity motor performance in the elderly.

neuroscience↗