Biology subjects

Stroganova, T.

Publications and source records attributed to Stroganova, T..

7 recordsLinked to original sources

bioRxiv2025

ABERRANT NEURAL ADAPTATION TO EXPECTED UNCERTAINTY IN ADULTS WITH AUTISM SPECTRUM DISORDER

The ability to adjust brain resources to manage expected uncertainty is hypothesized to be impaired in autism spectrum disorder (ASD), though the evidence remains limited. To investigate this, we studied 29 neurotypical (NT) and 29 high-functioning adults with ASD performing a probabilistic two-alternative value-based task while undergoing magnetoencephalography (MEG) and pupillometry. The task comprised five sequential blocks with stable reward probabilities (70%:30%), but varying stimulus pairs and reward values, enabling assessment of behavioral and neural adaptation to expected uncertainty. We analyzed a hit rate of advantageous choices, response times, and computational measures of prior belief strength and precision. To examine cortical activation during decision-making, we used MEG source reconstruction to quantify -{beta} oscillation suppression in decision-relevant cortical regions within the pre-decision time window. Linear mixed models assessed trial-by-trial effects. Behaviorally, ASD participants exhibited lower overall belief precision but intact probabilistic rule generalization, showing gradual performance improvement and strengthening of prior beliefs across blocks. However, unlike NT individuals, they did not show progressive downscaling of neural activation during decision-making or reduction in neural response to feedback signals as performance improved. Furthermore, on a trial-by-trial basis, increased belief precision in ASD was not associated with reduced cortical activation, a pattern observed in NT individuals. These findings suggest an atypically rigid and enhanced allocation of neural resources to advantageous decisions in individuals with ASD - although they, as NT individuals, rationally judge such decisions as optimal. This pattern may reflect an aversive response to the irreducible uncertainty inherent in probabilistic decision-making.

neuroscience↗

bioRxiv2024

Newly Acquired Word-Action Associations Trigger Auditory Cortex Activation During Movement Preparation: Implications for Hebbian Plasticity in Action Words Learning

Hebbian learning is believed to play a key role in acquisition of action words. However, this biological mechanism requires activation of the neural assemblies representing a word form and a corresponding movement to repeatedly overlap in time. In reality, though, these associated events could be separated by seconds. In the current MEG study, we examined trial-and-error learning of associations between novel auditory pseudowords and movements of specific body parts. We aimed to explore how the brain bridges the temporal gap between the transient activity evoked by auditory input and the preparatory motor activation before the corresponding movement. To address this, we compared learning-induced changes in neuromagnetic responses locked to the onset of the stimulus and to the onset of the movement. As learning progressed, both types of neural responses showed sustained enhancement during the delay period between the auditory pseudoword and the required movement. Cortical sources of this learning-induced increase were localized bilaterally in the lateral and medial temporal cortices. Notably, the learning effect was significantly stronger when measured time-locked to the movement onset, rather than to the pseudoword onset. This suggests that, after the pseudoword-movement associations were reliably acquired, the non-primary auditory cortex was reactivated in sync with the preparation of the upcoming movement. Such reactivation likely served to bring together in time the representations of the correct action and the preceding auditory cue. This temporal alignment could enable Hebbian learning, leading to long-lasting synaptic changes in temporally correlated neural assemblies.

neuroscience↗

bioRxiv2024

Atypical Pupil-Linked Arousal Induced by Low-Risk Probabilistic Choices, and Intolerance of Uncertainty in Adults with ASD

Adults with autism spectrum disorder (ASD) report stress when acting in a familiar probabilistic environment, but the underlying mechanisms are unclear. Their decision-making may be affected by the uncertainty aversion implicated in ASD, and associated with increased autonomic arousal. Previous studies have shown that in neurotypical (NT) people, decisions with predictably better outcomes are less stressful and elicit smaller pupil-linked arousal than those involving random "trial-and-error" searches or self-imposed risk of exploration. Here, in a sample of 46 high-functioning ASD and NT participants, we explored pupil-linked arousal and behavioral performance in a probabilistic reward learning task with a stable advantage of one choice option over the other. Using mixed-effects model analysis, we contrasted pupil dilation response (PDR) between a preferred frequently rewarded exploitative decision and its explorative alternatives. We observed that subjects with ASD learned the advantageous probabilistic choices at the same rate over time and preferred them to the same degree as NT participants both in terms of choice ratio and decision speed. Despite similar reward prediction abilities, outcome predictability modulated decision-related PDR in ASD in the opposite direction than in NT individuals. Moreover, relatively enhanced PDR elicited by exploitative low-risk decisions predicted a greater degree of self-reported intolerance of uncertainty in everyday life. Our results suggest that in a non-volatile probabilistic environment, objectively good predictive abilities in people with ASD are coupled with elevated physiological stress and subjective uncertainty regarding the decisions with the best possible but still uncertain outcome that contributes to their intolerance of uncertainty.

neuroscience↗

bioRxiv2022

Learning of new associations invokes a major change in modulations of cortical beta oscillations in human adults

Large-scale cortical beta ({beta}) oscillations have been implicated in the learning processes but their exact role is debated. We explored the dynamics of {beta}-oscillations while 25 adult participants learned, through trial and error, novel associations between four auditory pseudowords and movements of four body extremities. We used MEG to evaluate learninginduced changes in beta modulation accompanying cue-triggered movements. Our findings showed that spatial-temporal characteristics of movement-related {beta}-oscillations underwent a major transition as learning proceeded. Early in learning, suppression of {beta}-power in multiple cortical areas occurred long before movement initiation and sustained throughout the whole behavioral trial. As learning advanced and task performance reached asymptote, {beta}suppression was replaced by a widespread and prolonged rise in {beta}-power. The {beta}-power rise started shortly after the initiation of correct motor response and mainly comprised the prefrontal and medial temporal regions of the left hemisphere. This post-decision {beta}-power predicted trial-by-trial response times (RT) at both stages of learning (before and after the rules become familiar) but in opposite ways. When a subject started to acquire associative rules and gradually improved task performance, a decrease in RT was correlated with the increase in the post-decision {beta}-band power. Repeatedly correct implementation of the learned rules reversed this correlation in the opposite direction with faster (more confident) responses associated with the weaker post-decision {beta}-band synchronization. Our findings suggest that maximal beta activity is pertinent to a distinct stage of learning and may serve to strengthen the newly learned association in a distributed memory network.

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bioRxiv2021

Pupil Dilation and Response Slowing Distinguish Deliberate Explorative Choices in the Probabilistic Learning Task

This study examined whether pupil size and response time would distinguish directed exploration from random exploration and exploitation. Eighty-nine participants performed the two-choice probabilistic learning task while their pupil size and response time were continuously recorded. Using LMM analysis, we estimated differences in the pupil size and response time between the advantageous and disadvantageous choices as a function of learning success, i.e., whether or not a participant has learned the probabilistic contingency between choices and their outcomes. We proposed that before a true value of each choice became known to a decision-maker, both advantageous and disadvantageous choices represented a random exploration of the two options with an equally uncertain outcome, whereas the same choices after learning manifested exploitation and direct exploration strategies, respectively. We found that disadvantageous choices were associated with increases both in response time and pupil size, but only after the participants had learned the choice-reward contingencies. For the pupil size, this effect was strongly amplified for those disadvantageous choices that immediately followed gains as compared to losses in the preceding choice. Pupil size modulations were evident during the behavioral choice rather than during the pretrial baseline. These findings suggest that occasional disadvantageous choices, which violate the acquired internal utility model, represent directed exploration. This exploratory strategy shifts choice priorities in favor of information seeking and its autonomic and behavioral concomitants are mainly driven by the conflict between the behavioral plan of the intended exploratory choice and its strong alternative, which has already proven to be more rewarding.

neuroscience↗

bioRxiv2018

Additive effect of contrast and velocity proves the role of strong excitatory drive in suppression of visual gamma response.

Visual gamma oscillations are generated through interactions of excitatory and inhibitory neurons and are strongly modulated by sensory input. A moderate increase in excitatory drive to the visual cortex via increasing contrast or motion velocity of drifting gratings results in strengthening of the gamma response (GR). However, increasing the velocity beyond some transition point leads to the suppression of the GR. There are two theoretical models that can explain such suppression. The excitatory drive model infers that, at high drifting rates, GR suppression is caused by excessive excitation of inhibitory neurons. Since contrast and velocity have an additive effect on excitatory drive, this model predicts that the GR transition point for low-contrast gratings would be reached at a higher velocity, as compared to high-contrast gratings. The alternative velocity tuning model implies that the GR is maximal when the drifting rate of the grating corresponds to the preferable velocity of the motion-sensitive V1 neurons. This model predicts that lowering contrast either will not affect the transition point or will shift it to a lower drifting rate. We tested these models with magnetoencephalography-based recordings of the GR during presentation of low (50%) and high (100%) contrast gratings drifting at four velocities. We found that lowering contrast led to a highly reliable shift of the GR suppression transition point to higher velocities, thus supporting the excitatory drive model. No effects of contrast or velocity were found for the alpha-beta response power. The results have important implications for the understanding of the neural mechanisms underlying gamma oscillations and the development of gamma-based biomarkers of brain disorders.

neuroscience↗

bioRxiv2017

Modulation of visual gamma oscillation by excitatory drive and the excitation/inhibition balance in the visual cortex

Gamma-band oscillations arise from the interplay between neural excitation (E) and inhibition (I) and may provide a non-invasive window into the state of cortical circuitry. A bell-shaped modulation of gamma response power by increasing the intensity of sensory input was observed in animals and is thought to reflect neural gain control. Here we sought to find a similar input-output relationship in humans with MEG via modulating the intensity of a visual stimulation by changing the velocity/temporal-frequency of visual motion.\n\nIn the first experiment, adult participants observed static and moving gratings. The frequency of the MEG gamma response monotonically increased with motion velocity whereas power followed a bell-shape. In the second experiment, on a large group of children and adults, we found that despite drastic developmental changes in frequency and power of gamma oscillations, the relative suppression at high motion velocities was scaled to the same range of values across the life-span.\n\nIn light of animal and modeling studies, the modulation of gamma power and frequency at high stimulation intensities characterizes the capacity of inhibitory neurons to counterbalance increasing excitation in visual networks. Gamma suppression may thus provide a non-invasive measure of inhibitory-based gain control in the healthy and diseased brain.

neuroscience↗