Kudryashova, N. | Search bioRxiv

bioRxiv2025

Noradrenergic-dependent restoration of visual discrimination in a mouse model of SYNGAP1-related disorder

Atypical sensory processing in neurodevelopmental disorders contributes to cognitive, social, and behavioural disruptions, yet underlying neurophysiological mechanisms remain unclear. Using a mouse model of SYNGAP1 haploinsufficiency (HET), a common monogenic cause of intellectual disability and autism, we investigated visual processing deficits. Syngap HET mice exhibited impaired behavioural visual discriminability, associated with reduced coding precision for visual stimuli in the primary visual cortex (V1). Notably, intrinsic properties of V1 neurons and visual responses under anaesthesia were unaltered, suggesting behavioural state-dependent disruptions in awake Syngap HET mice. Supporting this, both mice and individuals with SYNGAP1 haploinsufficiency exhibited larger pupil size during visual stimulation, implicating neuromodulatory dysfunction. Targeting noradrenergic tone systemically with an 2-adrenergic receptor agonist restored V1 coding precision in Syngap HET mice. Our findings reveal neuromodulatory dysregulation as a novel mechanism underlying sensory disruptions in SYNGAP1-related disorder, highlighting potential therapeutic targets for addressing sensory impairments in neurodevelopmental disorders.

neuroscience↗

bioRxiv2025

BAND: Behavior-Aligned Neural Dynamics is all you need to capture motor corrections

Movement is the result of complex, dynamic interaction between cortical and subcortical circuits. These dynamic interactions implement both feedforward motor control, arising from preparatory states, and feedback control, triggered by unexpected sensory events during movement. We show that the neural responses for feedback-driven control can be transient and small in variance, posing difficulties for unsupervised inference methods. We thus propose the Behavior-Aligned Neural Dynamics (BAND) model, which exploits semi-supervised learning to extract latent dynamics that predict both feedforward planned movement and unplanned feedback corrections. Our analysis suggests that motor corrections during movement 1) are encoded on the population level in small neural variability in primary motor (M1), but not dorsal premotor (PMd) cortex; 2) are transient; and 3) are driven by sensory feedback. Our work highlights the importance of targeted closed-loop aware methods to extract and study neural dynamics underlying complex behavioral phenomena.

neuroscience↗

bioRxiv2018

Self-organization of conducting pathways explains electrical wave propagation in cardiac tissues with high fibrosis

Cardiac fibrosis occurs in many forms of heart disease and is considered to be one of the main arrhythmogenic factors. Regions with a high density of fibrosis are likely to cause blocks of wave propagation that give rise to dangerous cardiac arrhythmias. Therefore, studies of the wave propagation through these regions are very important, yet the precise mechanisms leading to arrhythmia formation in fibrotic cardiac tissue remain poorly understood. Particularly, it is not clear how wave propagation is organized at the cellular level, as experiments show that the regions with a high percentage of fibrosis (65-75%) are still conducting electrical signals, whereas geometric analysis of randomly distributed cells predicts connectivity loss at 40% at the most (percolation threshold). To address this question, we used a joint in vitro-in silico approach, which combined experiments in neonatal rat cardiac monolayers with morphological and electrophysiological computer simulations. We have shown that the main reason for sustainable wave propagation in highly fibrotic samples is the formation of a branching network of cardiomyocytes. We have successfully reproduced the morphology of conductive pathways in computer modelling, assuming that cardiomyocytes align their cytoskeletons to fuse into cardiac syncytium. The electrophysiological properties of the monolayers, such as conduction velocity, conduction blocks and wave fractionation, were reproduced as well. In a virtual cardiac tissue, we have also examined the wave propagation at the subcellular level, detected wavebreaks formation and its relation to the structure of fibrosis and, thus, analysed the processes leading to the onset of arrhythmias.\n\nAuthor summaryCardiac arrhythmias are one of the major causes of death in the industrialized world. The most dangerous ones are often caused by the blocks of propagation of electrical signals. One of the common factors that contribute to the likelihood of these blocks, is a condition called cardiac fibrosis. In fibrosis, excitable cardiac tissue is partially replaced with the inexcitable connective tissue. The precise mechanisms leading to arrhythmia formation in fibrotic cardiac tissue remain poorly understood. Therefore, it is important to study wave propagation in fibrosis from cellular to tissue level. In this paper, we study fibrosis of high density in experiments and computer simulations. We have observed a paradoxical ability of the tissue with extremely high fibrosis (up to 75% of fibroblasts) to conduct electrical signals and contract synchronously, whereas geometric analysis of randomly distributed cells predicted connectivity loss at 40% at the most. To explain this phenomenon, we have studied the patterns that cardiac cells form in the tissue and reproduced their self-organisation in a computer model. Our virtual model also took into account the polygonal shapes of the spreading cells and explained high arrhythmogenicity of fibrotic tissue.

systems biology↗