Search bioRxiv⌕ Search

bioRxiv · 10.1101/2022.12.23.521816

Tactile Stimulation Designs Adapted to Clinical Settings Result in Reliable fMRI-based Somatosensory Digit Maps

Abstract

A wide range of neurological diseases with impaired motor functioning of the upper extremities are accompanied by impairments of somatosensory functioning, which are often undescribed but can provide crucial information for diagnostics, treatment selection, and follow-up. Therefore, a reliable description of the functional representation of the digits in the somatosensory cortex would be a highly valuable, but currently lacking, tool in the clinical context. Task-based functional Magnetic Resonance Imaging of passive tactile stimulation provides an indirect, but valid description of the layout of the digit map in the primary somatosensory cortex. However, to fulfill the specific requirements for clinical application, the presently established approaches need to be adapted and subsequently assessed for feasibility and retest reliability, in order to provide informative parameters for the description of the evoked digit activations. Accordingly, the present high-field 3T fMRI study compares the performance of two established digit mapping designs - travelling wave (TW) and blocked design (BD) - for passive tactile stimulation of the five digits, adapted to reduce the time requirements to just below 15 minutes. To be able to assess the retest reliability unaffected by any clinical conditions, the study was performed on neurotypical participants. The results show that both stimulation designs evoke significant and distinct activation clusters in the primary somatosensory cortex of all participants for all five digits. The average spatial locations of the center of gravities across participants show the common succession of distinct digit representation along the central sulcus. The cortical extent elicited activation, which is generally larger for the thumb and the index finger, also shows comparable average values across the two approaches. Less overlap of activation between neighboring digits was obtained in BD, consistent with the distinct single digit neuronal representations. A high retest reliability was obtained for the location of the digit activation, displaying stable center of gravity locations across sessions for both stimulation designs. This is contrasted by only medium to low retest reliability for the extent and overlap of the digit activations, indicating discrepancies across sessions. These results demonstrate the capacity of shortened fMRI digit mapping approaches (both TW and BD) to obtain the full layout of single digit cortical activations on the level of the individual, which together with the high reliability of the location of the digit representation over time indicates both approaches are clinically applicable.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Steinbach, T., Eck, J., Timmers, I., Biggs, E., Goebel, R., Schweizer, R., Kaas, A.. 2022-12-23. Tactile Stimulation Designs Adapted to Clinical Settings Result in Reliable fMRI-based Somatosensory Digit Maps. https://doi.org/10.1101/2022.12.23.521816

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↗