bioRxiv Science⌕ Search

bioRxiv · 10.1101/2023.07.08.548191

Artificial Tactile Stimulation Provides Haptic Cuing in Force Field Adaptation

Abstract

When interacting with objects with unfamiliar dynamics, the sensorimotor system uses haptic information to develop internal representations of the new dynamics. These representations are subsequently used to manipulate the objects by applying predictive forces that comply with the mechanical properties of the objects. In a recent study (Farajian et al. 2020), we showed that when participants evaluated the stiffness of elastic objects, adding artificial tactile stimulation created an illusion of higher stiffness, increasing the grip force control used to interact with the object. Here, we took a step further in understanding how kinesthetic and tactile information is integrated into the control of objects. Specifically, we examined how added skin stretch influenced the learning of novel forces. We found that the extent of force compensation that the participants exhibited depended on the direction of the artificial skin stretch applied simultaneously with the force; learning was enhanced when the skin was stretched in the opposite direction to the external force and diminished when the skin was stretched in the same direction. Strikingly, when the skin stretch stimulation was delivered during probe trials in which the force perturbation was absent, the behavior pattern was flipped, with an increase in force compensation for the same-direction skin stretch stimulation and vice versa. Modeling suggests that these results reflect a unique effect of tactile stimulation during the learning of novel forces; rather than becoming integrated with the dynamic information, it is used by the sensorimotor system as a guidance cue, possibly through explicit mechanisms, providing information on the way to compensate for the forces and optimize movements. We believe that these findings propose a novel instructive role of tactile stimulation during interaction with a dynamic object. This provides a significant potential to leverage these effects in the development of devices aiming to assist and guide users in many human-in-the-loop applications, such as rehabilitation and surgical robotics.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Avraham, C., Avraham, G., Nisky, I.. 2023-07-10. Artificial Tactile Stimulation Provides Haptic Cuing in Force Field Adaptation. https://doi.org/10.1101/2023.07.08.548191

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↗