Biology subjects

Klibaite, U.

Publications and source records attributed to Klibaite, U..

8 recordsLinked to original sources

bioRxiv2026

FGF signaling induces disease-associated oligodendrocyte states and drives myelin pathology

Myelin integrity is essential for normal central nervous system (CNS) function and is disrupted in neuroinflammatory and neurodegenerative disorders, including multiple sclerosis and Alzheimer's disease. In these settings, myelin-forming oligodendrocytes adopt a conserved disease-associated transcriptional state, termed disease-associated oligodendrocytes (DAOs). How DAOs arise, the signals that drive their induction, and whether they actively contribute to pathology remain poorly understood. Here we show that FGF signaling instructs mature oligodendrocytes to enter disease-associated states that are sufficient to trigger myelin pathology. By screening disease-linked secreted factors, we identify FGF1 and FGF2 as potent inducers of a DAO-like state in purified oligodendrocyte cultures, characterized by transcriptional reprogramming and myelin-membrane shedding. In vivo, activating oligodendrocyte FGF signaling is sufficient to elicit DAO programs and myelin disruption, whereas inhibiting FGF signaling suppresses DAO induction in a mouse model of multiple sclerosis. Finally, analysis of post-mortem multiple sclerosis tissue reveals a concordant DAO-like state associated with increased engagement of the FGF/FGFR axis. Collectively, these studies define a regulated mechanism of DAO formation linked to myelin disruption and position mature oligodendrocytes as active contributors to myelin pathology in CNS disease.

neuroscience↗

bioRxiv2025

VQ-MAP: a flexible, versatile framework for animal behavior understanding

The brain generates behaviors that reflect configurations and computations of neural systems. Animal pose analysis can comprehensively profile behaviors in terms of stereotyped action expression, but the absence of common tracking standards makes it difficult to relate measurements across labs and experiments, hindering data exchange and collective knowledge building. Here, we present VQ-MAP, a versatile approach capable of mapping 2D or 3D keypoint sequences with divergent pose formats into a common set of discrete behavioral motifs. VQ-MAP utilizes permutation-invariant attention blocks for keypoint-agnostic processing and a quantized latent space for fast, interpretable delineation of motifs organized into type-subtype hierarchies. We deployed VQ-MAP to align and harmonize heterogeneous pose datasets, co-profiling rodent behaviors in multiple species and models of autism. In longitudinal recordings of rat behavioral maturation, VQ-MAP revealed developmental trajectories connecting specific behaviors across periods of substantial bodily growth and change. By unifying heterogeneous behavioral measurements, our framework will accelerate neurobiological discovery and help the community exercise the full potential of large-scale behavioral datasets.

neuroscience↗

bioRxiv2024

Mapping the landscape of social behavior

Social interaction is integral to animal behavior. However, we lack tools to describe it with quantitative rigor, limiting our understanding of its principles and neuropsychiatric disorders, like autism, that perturb it. Here, we present a technique for high-resolution 3D tracking of postural dynamics and social touch in freely interacting animals, solving the challenging subject occlusion and part assignment problems using 3D geometric reasoning, graph neural networks, and semi-supervised learning. We collected over 140 million 3D postures in interacting rodents, featuring new monogenic autism rat lines lacking reports of social behavioral phenotypes. Using a novel multi-scale embedding approach, we identified a rich landscape of stereotyped actions, interactions, synchrony, and body contact. This enhanced phenotyping revealed a spectrum of changes in autism models and in response to amphetamine that were inaccessible to conventional measurements. Our framework and large library of interactions will greatly facilitate studies of social behaviors and their neurobiological underpinnings.

animal behavior and cognition↗

bioRxiv2023

Differential kinematic coding in sensorimotor striatum across species-typical and learned behaviors reflects a difference in control

The sensorimotor arm of the basal ganglia is a major part of the mammalian motor control network, yet whether it is essential for generating natural behaviors or specialized for learning and controlling motor skills is unclear. We examine this by contrasting contributions of the sensorimotor striatum (rodent dorsolateral striatum, DLS) to spontaneously expressed species-typical behaviors versus those adapted for a task. In stark contrast to earlier work implicating DLS in the control of acquired skills, bilateral lesions had no discernable effects on the expression or detailed kinematics of species-typical behaviors, such as grooming, rearing, or walking. To probe the neural correlates underlying this dissociation, we compared DLS activity across the behavioral domains. While neural activity reflected the kinematics of both learned and species-typical behaviors, the coding schemes were very different. Taken together, we did not find evidence for the basal ganglia circuit being required for species-typical behaviors; rather, our results suggest that it monitors ongoing movement and learns to alter its output to shape skilled behaviors in adaptive and task-specific ways.

neuroscience↗

bioRxiv2021

Cerebellar contributions to a brainwide network for flexible behavior

The cerebellum regulates nonmotor behavior, but the routes by which it exerts its influence are not well characterized. Here we report a necessary role for the posterior cerebellum in guiding a reversal learning task, acting through a network of diencephalic and neocortical structures. After chemogenetic inhibition of Purkinje cells in lobule VI or crus I, mice could learn a water Y-maze task but were impaired in their ability to reverse their initial choice. To map targets of perturbation, we imaged c-Fos activation in cleared whole brains using light-sheet microscopy. Reversal learning activated diencephalic regions and associative neocortical regions. Distinctive subsets of structures were altered by perturbation of lobule VI (including thalamus and habenula) and crus I (including hypothalamus and prelimbic/orbital cortex), and both perturbations influenced anterior cingulate and infralimbic cortex. To identify functional networks, we used correlated variation in c-Fos activation within each test group. Lobule VI inactivation weakened within-thalamus correlations, while crus I inactivation divided neocortical activity into well-separated sensorimotor and associative subnetworks. In both groups, high-throughput automated analysis of complex whole-body movement revealed deficiencies in across-day adaptation to an open field environment. Neither perturbation affected gait, within-day open-field adaptation, or location preference. Taken together, these experiments reveal brainwide systems for cerebellar influence that can affect multiple flexible responses. Significance statementThe cerebellum, a part of all vertebrate brains, provides feedback to the rest of the brain on a split-second basis in response to unexpected events. The consequent changes can range from minute adjustments in movement to broad changes in behavior. In mice, we investigated cerebellar regions that help guide flexible behavior. Inactivation of these regions prevented mice from responding flexibly to a changing Y-shaped maze. We used light-sheet microscopy of c-fos protein expression to map brainwide effects of different stages of learning and cerebellar inactivation. Inactivation caused changes in thalamocortical activity that were similar in pattern, but opposite in sign, from normal learning. Lobule VI inactivation weakened thalamic functional networks, while crus I inactivation divided sensorimotor from associative neocortical networks. The same inactivation also impaired multiday adaptation to an open arena, as tracked using machine vision. Our work shows how the cerebellums influence over flexible response can be mediated by a widespread brain network.

neuroscience↗

bioRxiv2021

The PAIR-R24M Dataset for Multi-animal 3D Pose Estimation

Understanding the biological basis of social and collective behaviors in animals is a key goal of the life sciences, and may yield important insights for engineering intelligent multi-agent systems. A critical step in interrogating the mechanisms underlying social behaviors is a precise readout of the 3D pose of interacting animals. While approaches for multi-animal pose estimation are beginning to emerge, they remain challenging to compare due to the lack of standardized training and benchmark datasets. Here we introduce the PAIR-R24M (Paired Acquisition of Interacting oRganisms - Rat) dataset for multi-animal 3D pose estimation, which contains 24.3 million frames of RGB video and 3D ground-truth motion capture of dyadic interactions in laboratory rats. PAIR-R24M contains data from 18 distinct pairs of rats and 24 different viewpoints. We annotated the data with 11 behavioral labels and 3 interaction categories to facilitate benchmarking in rare but challenging behaviors. To establish a baseline for markerless multi-animal 3D pose estimation, we developed a multi-animal extension of DANNCE, a recently published network for 3D pose estimation in freely behaving laboratory animals. As the first large multi-animal 3D pose estimation dataset, PAIR-R24M will help advance 3D animal tracking approaches and aid in elucidating the neural basis of social behaviors.

animal behavior and cognition↗

bioRxiv2021

Deep behavioral phenotyping of mouse autism models using open-field behavior

AO_SCPLOWBSTRACTC_SCPLOWAutism is noted for both its genotypic and phenotypic diversity. Repetitive action, resistance to environmental change, and motor disruptions vary from individual to individual. In animal models, conventional behavioral phenotyping captures such fine-scale variations incompletely. Here we use advances in computer vision and deep learning to develop a framework for characterizing mouse behavior on multiple time scales using a single popular behavioral assay, the open field test. We observed male and female C57BL/6J mice to develop a dynamic baseline of adaptive behavior over multiple days. We then examined two rodent models of autism, a cerebellum-specific model, L7-Tsc1, and a whole-brain knockout model, Cntnap2. Both Cntnap2 knockout and L7-Tsc1 mutants showed forelimb lag during gait. L7-Tsc1 mutants showed complex defects in multi-day adaptation, lacking the tendency of wild-type mice to spend progressively more time in corners of the arena. In L7-Tsc1 mutant mice, failure-to-adapt took the form of maintained ambling, turning, and locomotion, and an overall decrease in grooming. Adaptation in Cntnap2 knockout mice more broadly resembled that of wild-type. L7-Tsc1 mutant and Cntnap2 knockout mouse models showed different patterns of behavioral state occupancy. Our automated pipeline for deep phenotyping successfully captures model-specific deviations in adaptation and movement as well as differences in the detailed structure of behavioral dynamics.

neuroscience↗

bioRxiv2019

Interacting fruit flies synchronize behavior

Social behaviors are ubiquitous and crucial to an animals survival and success. The behaviors an animal performs in a social setting are affected by internal factors, inputs from the environment, and interaction with others. To quantify social behaviors, we need to measure both the stochastic nature of behavior of isolated individuals and how these behaviors change as a function of the environment and features of social interaction. We probed the behavior of male and female fruit flies in a circular arena as individuals and within all possible pairings. By combining measurements of the animals position in the arena with an unsupervised analysis of their behaviors, we fully define the effects of position in the environment and the presence of a partner on locomotion, grooming, singing, and other behaviors that make up an animals repertoire. We find that geometric context tunes behavioral preference, pairs of animals synchronize their behavioral preferences across trials, and paired individuals display signatures of behavioral mimicry.

animal behavior and cognition↗