bioRxiv Science⌕ Search

bioRxiv · 10.1101/2025.10.16.682851

Evolutionary expansion of the corticospinal system is linked to dexterity in Peromyscus mice

Abstract

While the central nervous system is perpetually reshaped by evolution, the principles governing how such changes promote ecologically relevant behaviors without breaking established functions are poorly understood. The expansion of neuron number is a potential mechanism by which the nervous system evolves to support changes in behavior without disrupting existing circuit function. Corticospinal neurons (CSNs) are a classic example: an expansion in the corticospinal system in the primate lineage has been hypothesized to underlie their exceptional dexterity. However, the role of CSN number in behavior has been difficult to assess due to the lack of a tractable model system. We compared two closely related subspecies of deer mice (Peromyscus maniculatus): forest mice, which evolved the ability to adeptly climb, presumably to support a semi-arboreal lifestyle, and prairie mice, which are less proficient climbers. We find that forest mice have about two-fold larger corticospinal tracts (CSTs) driven by an increase in CSN number in secondary motor and sensory cortical areas (M2 and S2). Furthermore, forest mice display greater manual dexterity than their prairie counterparts in a reach-to-grasp task, consistent with the idea that an increase in CSN number supports more dexterous behavior. High-throughput neural recordings during this task revealed a difference in the timing of neural activity between forest and prairie mice, specifically in M2: in forest mice, the peak of activity was shifted towards the grasping phase of the behavior. Forest mice also outperform their prairie counterparts on an ecologically relevant climbing task, where they spend more time upright crossing a thin rod, move faster, and right themselves more quickly when they fall, suggesting a general difference in motor dexterity not restricted to hand use. Finally, we use F2 hybrid animals to show that CST size is correlated with climbing dexterity, providing support for the long-standing hypothesis that corticospinal system expansion supports the evolution of dexterity. Together, our work establishes the forest-prairie deer mouse system as a model to investigate the role of neuron number expansion, and CSNs in particular, in dexterous movement.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Tyssowski, K. M., Cohen, J. D., Guo, J.-Z., Richardson, P. R., Cortina, K. E., Smith, I. H., Eijogu, D. C., Hantman, A. W., Hoekstra, H. E.. 2025-10-17. Evolutionary expansion of the corticospinal system is linked to dexterity in Peromyscus mice. https://doi.org/10.1101/2025.10.16.682851

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↗