bioRxiv Science⌕ Search

bioRxiv · 10.1101/2022.12.13.520353

A complex reach direction rule that delays reaction time causes alternating excitation and inhibition in express muscle responses and corticospinal excitability

Abstract

The dynamics of muscle activation during fast visually guided reaching are suggestive of two neural control signals; an early signal that acts at "express" latencies in response to the visual stimulus, and a longer latency signal that executes a strategic reach plan. Here we developed a task designed to temporally isolate the express visuomotor response from the longer latency muscle response, and to characterize the time course of corticospinal excitability changes in the express response time window when the late voluntary response is delayed. We tested this by measuring electromyograms (EMG) and changes in Motor Evoked Potential (MEP) amplitudes following Transcranial Magnetic Stimulation (TMS) of the motor cortex, as participants reached either towards or away from visual targets. Crucially, the information about the task rule was provided by the luminance of the target itself, and so was unknown to the subject until the instant of target presentation. This feature delayed reaction times, likely because additional (presumably cortical) processing was required to interpret and apply the rule before formation of a goal directed reach plan. The earliest EMG responses to target presentation occurred with a 70-105 ms time window, and were oriented to bring the hand toward the location of the target. However, there was also a slightly later response that was also time-locked to target appearance in a 105-140 ms time window. This second response was "reciprocal" to the first, such that it was oriented to take the hand in the direction opposite from the target. In some participants, additional oscillating cycles were apparent after the first two target-related responses. These multiphasic express visuomotor responses were nearly identical in both pro- and anti-reach conditions. These muscle activity responses were generally reflected in the temporal pattern of corticospinal excitability modulations in experiment two. Indeed, the MEP and background EMG responses showed an alternating pattern similar to that in experiment one, although the effect was clearer in the anti-reach than the pro-reach condition. Overall, the data show that the express and voluntary responses are indeed distinct neural control signals, which supports the hypothesis that at least two separate neural pathways (one slow and one fast) contribute to the control of visually guided reaching. The properties of the fast pathway are consistent with a tecto-reticulospinal pathway, while those of the slow pathway are consistent with a transcortical loop.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Divakar, R., Loeb, G. E., Corneil, B. D., Wallis, G., Carroll, T. J.. 2022-12-15. A complex reach direction rule that delays reaction time causes alternating excitation and inhibition in express muscle responses and corticospinal excitability. https://doi.org/10.1101/2022.12.13.520353

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↗