Biology subjects

Vlasov, Y.

Publications and source records attributed to Vlasov, Y..

5 recordsLinked to original sources

bioRxiv2025

Neural correlates of perceptual decision making in primary somatosensory cortex

The brain is thought to produce decisions by gradual accumulation of sensory evidence through a hierarchically organized feedforward cascade of neuronal activities that transforms early stimulus representations in the primary somatosensory cortex (S1) to a perceptual decision processed in pre-motor areas. Recently, this prevailing view has been challenged by observation of choice- correlated neural activity as early in the hierarchy as S1. Here, to reconcile these seemingly controversial observations, we employ ethological whisker-guided navigation of mice in a tactile virtual reality paradigm combined with dense electrophysiological recordings in whisker-related wS1. Leaving only a pair of C2 whiskers for mice to navigate with, we effectively designed an information bottleneck for sensory input to decision making. We show that neural activity during sensory evidence accumulation exhibits dramatic collapse of the high-dimensional spiking activity to just a single latent variable followed by a slower and almost synchronous ramping up across the whole cortical column. We show that this variable is consistent with models of gradual accumulation of noisy sensory evidence to a decision bound. These observations indicate that S1 may directly participate in a categorical coding of all-or-none decision variable via cortico-cortical feedback loops through which sensory information reverberates to be transformed into perception and action. Significance StatementBy employing ethological whisker-guided navigation of mice in a tactile virtual reality paradigm combined with dense electrophysiological recordings in whisker-related wS1, we show that neural activity during sensory evidence accumulation exhibits dramatic collapse of the high-dimensional spiking activity to just a single latent variable followed by a slower and almost synchronous ramping up across the whole cortical column. We show that this variable is consistent with models of gradual accumulation of noisy sensory evidence to a decision bound. These observations indicate that wS1 may directly participate in a categorical coding of all-or-none decision variable. Naturalistic perceptual decisions during active whisker-guided navigation High-dimensional activity in S1 collapses to a single variable prior to decision This ramping spiking activity is consistent with drift-diffusion decision models Indicates direct involvement of S1 in evidence accumulation

neuroscience↗

bioRxiv2025

Perceptual decision-making during whisker-guided navigation causally depends on a single cortical barrel column

Perceptually driven behavioral choices are thought to develop gradually from sensation to perception in the somatosensory cortex to guide decision-making in higher order cortical areas. Primary somatosensory cortex (wS1) of rodents related to their mystacial whiskers has been a model system to study this information flow. However, the role of wS1 in this process is often debated based on controversial results of loss-of-function behavioral experiments that often require prolonged training and movement restraints. Here, to elucidate the role of wS1 in decision-making, we developed an ethological whisker-guided virtual reality (VR) paradigm that closely mimics natural navigation in underground burrows. Untrained mice navigate left and right turns at high speed by sensing VR walls with just a pair of their C2 whiskers. Inactivating layer 4 of C2 barrel results in loss of ability to produce turns contralateral to the lesion. Using probabilistic model of collision avoidance in the presence of noise and uncertainties we hypothesize that wS1 is involved in a feedback control loop that requires continuous updates and predictions to infer the optimal path for collision avoidance. SignificancePerceptual decisions driven by sensing salient changes in the environment are thought to develop from sensation in primary cortex (S1) to decisions in pre-motor cortical areas. However, the role of S1 in this process is debated based on controversial results of loss-of-function behavioral experiments that often require prolonged training and movement restraints. Here, by utilizing an ethological whisker-guided virtual reality, we show that perceptual decisions causally depend on small subpopulation of neurons in layer 4 of a single cortical barrel. Whisker-guided navigation requires continuous updates and predictions of relative positions of the body and obstacles to infer the optimal path for collision avoidance. These complex computations are likely to rely on nested feedback loops that directly involve wS1 hence making it indispensable.

neuroscience↗

bioRxiv2023

Highly localized chemical sampling at sub-second temporal resolution enabled with a silicon nanodialysis platform at exceedingly slow flows.

Microdialysis (MD) is a versatile and powerful technique for chemical profiling of biological tissues and is widely used for quantification of neurotransmitters, neuropeptides, metabolites, biomarkers, and drugs in the central nervous system as well as in dermatology, ophthalmology, and in pain research. However, MD performance is severely limited by fundamental tradeoffs between chemical sensitivity, spatial resolution, and temporal response. Here, by using wafer-scale silicon microfabrication, we develop and demonstrate a nanodialysis (ND) sampling probe that enables highly localized chemical sampling with 100m spatial resolution and sub-second temporal resolution at high recovery rates. These performance metrics, which are 100X-1000X superior to existing MD approaches, are enabled by a 100X reduction of the microfluidic channel cross-section, a corresponding drastic 100X reduction of flow rates to exceedingly slow few nL/min flows, and integration of a nanometer-thin nanoporous membrane with high transport flux into the probe sampling area. Miniaturized ND probes may allow for the minimally invasive and highly localized sampling and chemical profiling in live biological tissues with unprecedented spatio-temporal resolution for clinical, biomedical, and pharmaceutical applications.

bioengineering↗

bioRxiv2023

Discovery of latent dynamic connectivity in brain cortical networks from massive spiking data

Complex cognitive functions in a mammalian brain are distributed across many anatomically and functionally distinct areas and rely on highly dynamic routing of neural activity across the network. While modern electrophysiology methods enable recording of spiking activity from increasingly large neuronal populations at a cellular level, development of probabilistic methods to extract these dynamic inter-area interactions is lagging. Here, we introduce an unsupervised machine learning model that infers dynamic connectivity across the recorded neuronal population from a synchrony of their spiking activity. As opposed to traditional population decoding models that reveal dynamics of the whole population, the model produces cellular-level cell-type specific dynamic functional interactions that are otherwise omitted from analysis. The model is evaluated on ground truth synthetic data and compared to alternative methods to ensure quality and quantification of model predictions. Our strategy incorporates two sequential stages - extraction of static connectivity structure of the network followed by inference of temporal changes of the connection strength. This two-stage architecture enables detailed statistical criteria to be developed to evaluate confidence of the model predictions in comparison with traditional descriptive statistical methods. We applied the model to analyze large-scale in-vivo recordings of spiking activity across mammalian visual cortices. The model enables the discovery of cellular-level dynamic connectivity patterns in local and long-range circuits across the whole visual cortex with temporally varying strength of feedforward and feedback drives during sensory stimulation. Our approach provides a conceptual link between slow brain-wide network dynamics studied with neuroimaging and fast cellular-level dynamics enabled by modern electrophysiology that may help to uncover often overlooked dimensions of the brain code.

neuroscience↗

bioRxiv2022

Pre-neuronal processing of haptic sensory cues via dispersive high-frequency vibrational modes

Sense of touch is one of the major perception channels. Neural coding of object textures conveyed by rodents whiskers has been a model to study early stages of haptic information uptake. While high-precision spike timing has been observed during whisker sweeping across textured surfaces, the exact nature of whisker micromotions that spikes encode remains elusive. Here, we discovered that a single micro-collision of a whisker with surface features generates vibrational eigenmodes spanning frequencies up to 10KHz. While propagating along the whisker, these high-frequency modes can carry up to 80% of shockwave energy, exhibit 100X smaller damping ratio, and arrive at the follicle 10X faster than low frequency components. The mechano-transduction of these energy bursts into a time-sequenced population spike trains may generate temporally unique "bar code" with ultra-high information capacity. This hypothesis of pre-neuronal processing of haptic signals based on dispersive temporal separation of the vibrational modal frequencies can shed light on neural coding of haptic signals in many whisker-like sensory organs across the animal world as well as in texture perception in primates glabrous skin. Significance StatementUnderstanding how the outside world is encoded in neurons spikes in sensory organs and how these neural codes contribute to perception remains elusive. Using a model system - a whisker of a mouse - we discovered that tiny whisker vibrations induced at the whisker tip by collisions with external objects generate a time series of energy bursts. This creates a temporally unique "bar code" of a time-sequenced population spike trains with ultra-high information capacity. We hypothesize that such a "pre-neuronal processing" of touch events into time-coded spikes can provide a conceptual link to understand neural coding in many whisker-like sensory organs across the animal world as well as in texture perception in primates glabrous skin.

neuroscience↗