Search bioRxiv⌕ Search

bioRxiv · 10.1101/2023.10.13.562210

Transformation of neural coding for vibrotactile stimuli along the ascending somatosensory pathway

Abstract

Perceiving substrate vibrations is a fundamental component of somatosensation. In mammals, action potentials fired by rapidly adapting mechanosensitive afferents are known to reliably time lock to the cycles of a vibration. This stands in contrast to coding in the higher-order somatosensory cortices, where neurons generally encode vibrations in their firing rates, which are tuned to a preferred vibration frequency. How and where along the ascending neuraxis is the peripheral afferent temporal code of cyclically entrained action potentials transformed into a rate code is currently not clear. To answer this question, we probed the encoding of vibrotactile stimuli with electrophysiological recordings along major stages of the ascending somatosensory pathway in mice. Recordings from individual primary sensory neurons in lightly anesthetized mice revealed that rapidly adapting mechanosensitive afferents innervating Pacinian corpuscles display phase-locked spiking for vibrations up to 2000 Hz. This precise temporal code was reliably preserved through the brainstem dorsal column nuclei. The main transformation step was identified at the level of the thalamus, where we observed a significant loss of phase-locked spike timing information accompanied by a further narrowing of tuning curve widths. Using optogenetic manipulation of thalamic inhibitory circuits, we found that parvalbumin-positive interneurons in thalamic reticular nucleus participate in sharpening frequency selectivity and disrupting the precise spike timing of ascending neural signals encoding vibrotactile stimuli. To test the functional implications of these different neural coding mechanisms, we applied frequency-specific microstimulation within the brainstem, which generated frequency selectivity reminiscent of real vibration responses in the somatosensory cortex, whereas microstimulation within thalamus did not. Finally, we applied microstimulation in the brainstem of behaving mice and demonstrated that frequency-specific stimulation could provide informative and robust signals for learning. Taken together, these findings not only reveal novel features of the computational circuits underlying vibrotactile sensation, but could also guide biomimetic stimulus strategies to activate specific nuclei along the ascending somatosensory pathway for sensory neural prostheses.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Lee, K.-S., Loutit, A., de Thomas Wagner, D., Sanders, M., Prsa, M., Huber, D.. 2023-10-17. Transformation of neural coding for vibrotactile stimuli along the ascending somatosensory pathway. https://doi.org/10.1101/2023.10.13.562210

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↗