bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2022.06.07.495172

Age-related learning and working memory impairment in the common marmoset

Glavis-Bloom, C.·Vanderlip, C. R.·Reynolds, J. H.
View original source ↗Export metadata ↓

Abstract

Aging is the greatest risk factor for the development of neurodegenerative diseases, yet we still do not understand how the aging process leads to pathological vulnerability. The research community has relied heavily on mouse models, but the considerable anatomical, physiological, and cognitive differences between mice and humans limit their translational relevance. Ultimately, these barriers necessitate the development of novel aging models. As a non-human primate, the common marmoset (Callithrix jacchus) shares many features in common with humans and yet has a significantly shorter lifespan (10 years) than other primates, making it ideally suited to longitudinal studies of aging. Our objective was to evaluate the marmoset as a model of age-related cognitive impairment. To do this, we utilized the Delayed Recognition Span Task (DRST) to characterize age-related changes in working memory capacity in a cohort of sixteen marmosets varying in age from young adult to geriatric. These monkeys performed thousands of trials over periods of time ranging up to 50 percent of their adult lifespan. To our knowledge, this represents the most thorough cognitive profiling of any marmoset aging study conducted to-date. By analyzing individual learning curves, we found that aged animals exhibited delayed onset of learning, slowed learning rate after onset, and decreased asymptotic working memory performance. These findings are not accounted for by age-related impairments in motor speed and motivation. This work firmly establishes the marmoset as a model of age-related cognitive impairment. Significance StatementUnderstanding the normal aging process is fundamental to identifying therapeutics for neurodegenerative diseases for which aging is the biggest risk factor. Historically, the aging field has relied on animal models that differ markedly from humans, constraining translatability. Here, we firmly establish a short-lived non-human primate, the common marmoset, as a key model of age-related cognitive impairment. We demonstrate, through continuous testing over a substantial portion of the adult marmoset lifespan, that aging is associated with both impaired learning and working memory capacity, unaccounted for by age-related changes in motor speed and motivation. Characterizing individual cognitive aging trajectories reveals inherent heterogeneity, which could lead to earlier identification of the onset of impairment, and extended timelines during which therapeutics are effective.

Source connections

Explore related subjects

neurosciencePreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Glavis-Bloom, C., Vanderlip, C. R., Reynolds, J. H.. 2022-06-09. Age-related learning and working memory impairment in the common marmoset. https://doi.org/10.1101/2022.06.07.495172

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

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↗
bioRxiv2026

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↗
bioRxiv2026

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↗