bioRxiv Science⌕ Search

bioRxiv · 10.1101/2025.07.08.663774

Somatosensory Realignment Following Single and Dual Force Field Adaptation

Abstract

Evidence that adaptive motor learning coincides with a realignment of somatosensory perception has led to hypotheses that a shared mechanism underlies both processes. This implies that these two phenomena should exhibit similar properties. However, studies of somatosensory realignment with visuomotor adaptation have shown mixed support, possibly due to a confounding coactivation of sensory prediction errors and multisensory integration. While the former is thought to drive adaptation, both processes may contribute to somatosensory realignment. Here, we examined somatosensory realignment following force field adaptation, which is not confounded by multisensory integration. Across two experiments, we tested whether somatosensory realignment mimics three canonical properties of adaptation in this paradigm. Our first experiment examined whether sensory realignment (for the perception of movement or static position) correlated with adaptation across individuals, and generalized beyond the trained reach direction. The results showed that force field adaptation coincided with a selective realignment of somatosensory perception of movement in the direction of the perturbing force, but this realignment did not correlate with the magnitude of adaptation or generalize beyond the reach direction of the adaptation task. In a second experiment, we tested whether context-dependent dual adaptation to opposing force field perturbations coincides with a context-dependent dual realignment of somatosensory perception. The results showed no evidence of context-dependent somatosensory realignment after dual adaptation. Overall, our results indicate that somatosensory realignment and adaptation exhibit different properties and are therefore unlikely to rely on the same underlying mechanism, although realignment does display some coherence with the nature of the perturbation. NEW AND NOTEWORTHYThis study is the first to demonstrate a dissociation in the realignment of somatosensory perceptions of static position and movement following adaptation to novel forces in the upper limb. By assessing whether perceptual realignment following force field adaptation exhibits two canonical properties of this type of motor learning - i.e., generalization to nearby movement directions and context dependence - this study constitutes a key test of theories positing a shared mechanism underlying the motor and perceptual processes.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Zangakis, D., Wong, A. L., Therrien, A. S.. 2025-07-12. Somatosensory Realignment Following Single and Dual Force Field Adaptation. https://doi.org/10.1101/2025.07.08.663774

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience↗

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience↗

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience↗