Biology subjects

Bareyre, F. M.

Publications and source records attributed to Bareyre, F. M..

4 recordsLinked to original sources

bioRxiv2026

Axonal Branch Points of Parvalbumin Interneurons are Focal Sites of Tau-Induced Degeneration

Tau aggregation, a defining feature of tauopathies, commonly appears as neuropil threads within neurites including axons. However, the affected neuronal populations and the spatial organization of axonal vulnerability remain poorly defined. Here, following identification of Tau accumulation in parvalbumin (PV) interneuron axons in primary tauopathy patients, we generated a P301S Tau model targeted to PV interneurons to track the structural integrity of their neurites and somas. We observed neuronal loss alongside axonal dystrophy, with focal swellings forming preferentially at axonal bifurcations. This spatial enrichment exceeded chance levels, and local axonal geometry predicted swelling localization. Longitudinal in vivo imaging revealed that bifurcation-associated swellings progressed to axonal severing. Analogous bifurcation-associated dystrophies were present in PV axons in human primary tauopathy tissue. These findings indicate that axonal branch geometry shapes the spatial pattern of Tau-induced neurodegeneration and identify PV axonal branch points as sites of pathology in mouse and human tauopathy.

neuroscience↗

bioRxiv2026

SingleBehavior Lab: behavioral sequencing and phenotyping with lightweight task specific adaptation

Understanding behavioral differences between experimental groups and quantifying action structure in behavioral experiments remains challenging. Currently, most approaches rely on pose estimation followed by downstream classification, resulting in assay specific pipelines with substantial annotation requirements. Here we present SingleBehavior Lab (SBL), a framework for modeling behavior across experimental contexts using a standardized graphical interface. SBL leverages spatiotemporal embeddings from large video foundation models and combines them with lightweight contrastive adapters, a multi-head attention pooling (MAP) module and a temporal decoder to enable behavior sequencing and task-specific refinement. The framework supports few-shot learning, allowing small models trained on pretrained embeddings to improve action segmentation and classification with limited labeled data, without fine-tuning the underlying video model. In parallel, a large segmentation model with motion-aware memory is used to extract object-centered representations that, together with shared spatiotemporal embeddings, enable unsupervised clustering of behavioral states and analysis of their structure, including cluster prioritization, transition dynamics and attention-based interpretability. Across multiple assays and species, SBL supports identification of group-level differences and rare behaviors, and provides a basis for integrating behavioral representations across experimental contexts.

neuroscience↗

bioRxiv2023

Targeting the TCA cycle can ameliorate widespread axonal energy deficiency in neuroinflammatory lesions

Inflammation in the central nervous system (CNS) can impair the function of neuronal mitochondria and contributes to axon degeneration in the common neuroinflammatory disease multiple sclerosis (MS). Here we combine cell type-specific mitochondrial proteomics with in vivo biosensor imaging to dissect how inflammation alters the molecular composition and functional capacity of neuronal mitochondria. We show that neuroinflammatory lesions in the mouse spinal cord cause widespread and persisting axonal ATP deficiency, which precedes mitochondrial oxidation and calcium overload. This axonal energy deficiency is associated with impaired electron transport chain function, but also an upstream imbalance of tricarboxylic acid (TCA) cycle enzymes, with several, including key rate-limiting, enzymes being depleted in neuronal mitochondria in experimental models and in MS lesions. Notably, viral overexpression of individual TCA enzymes can ameliorate the axonal energy deficits in neuroinflammatory lesions, suggesting that TCA cycle dysfunction in MS may be amendable to therapy.

neuroscience↗

bioRxiv2021

A deep-learning-based toolbox for Automated Limb Motion Analysis (ALMA) in murine models of neurological disorders

In neuroscience research, the refined analysis of rodent locomotion is complex and cumbersome, and access to the technique is limited because of the necessity for expensive equipment. In this study, we implemented a new deep-learning-based toolbox for Automated Limb Motion Analysis (ALMA) that requires only basic behavioral equipment and an inexpensive camera. The ALMA toolbox enables the unbiased and comprehensive analyses of locomotor kinematics and paw placement and can be applied to neurological conditions affecting the brain and spinal cord. We demonstrated that the ALMA toolbox can (1) robustly track the evolution of locomotor deficits after spinal cord injury, (2) sensitively detect locomotor abnormalities after traumatic brain injury, and (3) correctly predict disease onset in a multiple sclerosis model. We, therefore, established a broadly applicable automated and standardized approach that requires minimal financial and time commitments to facilitate the comprehensive analysis of locomotion in rodent disease models.

neuroscience↗