Search bioRxiv⌕ Search

bioRxiv · 10.1101/2023.03.23.532745

Autistic kinematics diverge from the power laws that typically govern movement

Abstract

Extant work reliably demonstrates that autistic individuals move with increased jerk (where jerk concerns change in acceleration). Although it follows that autistic movement may therefore diverge from fundamental power laws that govern movement, this hypothesis has not been directly tested to date. This lack of insight holds back progress in understanding the mechanisms underpinning differences in autism in motor control particularly with respect to movement jerkiness. Here we investigated whether movements executed by autistic adults diverged from the typical power law relationship that links movement speed and curvature. x and y position of the stylus tip was recorded at 133 Hz while 21 autistic and 19 non-autistic age-, intelligence quotient- and sex-matched adults traced, on a tablet device, a range of shapes that varied in angular frequency from 2/33 (spiral-like shapes) to 4 (square-like shapes). The gradient of the relationship between speed and curvature for each angular frequency-defined shape is reliably predicted by a set of mathematical equations often referred to as fundamental power laws thus, to assess deviations from power laws, we compared autistic and non-autistic participants in terms of speed-curvature gradients. To gain insight into potential mechanisms underpinning any differences we also used fast Fourier transform to explore amplitude spectral density across all angular frequencies. Compared to non-autistic adults, autistic adults exhibited significantly steeper speed-curvature gradients. Fast Fourier transform further revealed that non-autistic participants exhibited highly precise modulation of speed oscillations around the target frequency. For example, when drawing an ellipse their speed profile was dominated by speed changes in a band centred around the angular frequency 2 with minimal changes in other bands. Autistic adults, in contrast, exhibited less precise modulation of speed oscillations around the target frequency, a result that is reminiscent of a literature reporting broader auditory filters in autistic individuals. These results evidence, in autistic adults, a deviation from the power laws that typically govern movement and suggest differences in motor cortical control policies and/or biomechanical constraints.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Cook, J. L., Fraser, D. S., Hickman, L. J., Brewer, R., Huh, D.. 2023-03-23. Autistic kinematics diverge from the power laws that typically govern movement. https://doi.org/10.1101/2023.03.23.532745

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↗