Biology subjects

Klucharev, V.

Publications and source records attributed to Klucharev, V..

7 recordsLinked to original sources

bioRxiv2025

Voluntary movement initiation is associated with cardiac input in Libet's task.

The relationship between motor intention and initiation of voluntary movement remains a fundamental topic in neuroscience, originating from the B. Libet seminal framework introduced in 1983. Libets paradigm significantly influenced discussions on intentionality, motor control, and free will. However, methodological critiques continue to challenge its interpretations, specifically the accuracy and validity of the urge to move phenomenon. One understudied factor in this debate is the potential influence of interoceptive signals--particularly cardiac activity--in shaping the experience of motor intention and movement initiation. In our study, we addressed this gap by examining whether cardiac signals modulate participants experience of the urge to move, using behavioural and electrophysiological measures in 34 healthy human participants performing Libets task. Crucially, when participants were asked to report the perceived urge to move, their button press timings were predominantly aligned with the diastolic phase of the cardiac cycle, indicating cardiac modulation of motor intention perception. However, analysing heart evoked potential (HEP) amplitudes as a measure of cardiac input perception, we observed no differences in HEP amplitudes associated with changes in introspective demands during the task in both source and sensor spaces. Our results suggest that implicit perception of cardiac signals biases subjective experience of voluntary action initiation, independent from cortical interoceptive markers. These findings have implications for models of motor preparation, intentionality and the bodily basis of voluntary action, challenging conventional interpretations of motor intention and informing debates on volition and interoception. Significance StatementOur study provides evidence that implicit perception of cardiac signals influences the subjective experience of motor intention--the urge to move in Libets experiment. We demonstrate, for the first time, that when reporting urge to move, participants tended to initiate voluntary movements during the diastolic phase of the cardiac cycle. These findings challenge traditional views on factors affecting motor initiation, suggesting relevance of interoceptive processing. By highlighting the role of cardiac input in experiencing motor intention, our findings impact existing debates on volition, agency and free will, further underscoring the importance of integrating bodily signals into these theoretical frameworks.

neuroscience↗

bioRxiv2023

Posterior parietal cortex is causally involved in reward valuation but not probability weighting during risky choice

This study provides evidence that the posterior parietal cortex (PPC) is causally involved in risky decision making via the processing of reward values but not reward probabilities. In the within-group experimental design, participants performed a binary lottery choice task following transcranial magnetic stimulation of the right PPC, left PPC and a right PPC sham (placebo) stimulation. Both, mean-variance and the prospect theory approach to risky choice showed that the PPC stimulation changed participants preferences towards greater risk aversion compared to sham. On the behavioral level, after the PPC stimulation the likelihood of choosing a safer option became more sensitive to the difference in standard deviations between lotteries, compared to sham, indicating greater risk avoidance within the meanvariance framework. We also estimated the shift in prospect theory parameters of risk preferences after PPC stimulation. The hierarchical Bayesian approach showed moderate evidence (BF = 7.44 and 5.41 for right and left PPC respectively) for a credible change in risk aversion parameter towards lower marginal reward value (and, hence, lower risk tolerance), while no credible change in probability weighting was observed. Additionally, we observed anecdotal evidence (BF = 2.9) for a credible increase in the consistency of responses after the left PPC stimulation compared to sham.

neuroscience↗

bioRxiv2021

Resting-state theta oscillations and reward sensitivity in risk taking

Females demonstrate greater risk aversion than males on a variety of tasks, but the underlying neurobiological basis is still unclear. We studied how theta (4-7 Hz) oscillations at rest related to three different measures of risk taking. Thirty-five participants (15 females) completed the Bomb Risk Elicitation Task (BRET), which allowed us to measure risk taking during an economic game. The Domain-Specific Risk-Taking Scale (DOSPERT) was used to measure self-assessed risk attitudes as well as reward and punishment sensitivities. In addition, the Barratt Impulsiveness Scale (BIS11) was included to quantify impulsiveness. To obtain measures of frontal theta asymmetry and frontal theta power, we used magnetoencephalography (MEG) acquired prior to task completion, while participants were at rest. Frontal theta asymmetry correlated with average risk taking during the game but only in the female sample. By contrast, frontal theta power correlated with risk taking as well as with measures of reward and punishment sensitivity in the joint sample. Importantly, we showed that reward sensitivity mediated a correlation between risk taking and the power of theta oscillations localized to the anterior cingulate cortex. In addition, we observed significant sex differences in source- and sensor-space theta power, risk taking during the game, and reward sensitivity. Our findings suggest that sensitivity to rewards, associated with resting-state theta oscillations in the anterior cingulate cortex, is a trait that potentially contributes to sex differences in risk taking.

neuroscience↗

bioRxiv2020

Adaptive learning under strategic and structural uncertainty: the case of auction games

In games of incomplete information individual players make decisions facing a combination of structural uncertainty about the underlying parameters of the environment, and strategic uncertainty about the actions undertaken by their partners. How well are human actors able to cope with these uncertainties, and what models best describe their learning in such environments? We use a double auction task with different competitive and informational environments to characterize learning abilities of the single human participants (buyers) in a range of adaptive learning models covering reinforcement learning, directional learning and belief learning. Results show that real behaviour is best described using simple models of directional learning type with minimal knowledge assumptions about information efficiency of prices. This behavior is consistent with bounded rationality and risk aversion: human subjects try to maximize their chance for transaction, and do so using the simplest learning rule.

animal behavior and cognition↗

bioRxiv2020

Neural basis of common-pool resources exploitation

Why do people often exhaust unregulated common (shared) natural resources but manage to preserve similar private resources? To answer this question, in the present work we combine a neurobiological, economic, and cognitive modeling approach. Using functional magnetic resonance imaging on 50 participants, we show that sharp depletion of common and private resources is associated with deactivation of the ventral striatum, a brain region involved in the valuation of outcomes. Across individuals, when facing a common resource, ventral striatal activity is anti-correlated with resource preservation (less harvesting), whereas with private resources the opposite pattern is observed. This indicates that neural value signals distinctly modulate behavior in response to the depletion of common versus private resources. Computational modeling suggest that over-harvesting of common resources is facilitated by the modulatory effect of social comparison on value signals. In sum, the results provide an explanation of peoples tendency to over-exploit unregulated common natural resources.

neuroscience↗

bioRxiv2018

Action in auctions: neural and computational mechanisms of bidding behavior

Competition for resources is a fundamental characteristic of evolution. Auctions have been widely used to model competition of individuals for resources, and bidding behavior plays a major role in social competition. Yet how humans learn to bid efficiently remains an open question. We used model-based neuroimaging to investigate the neural mechanisms of bidding behavior under different types of competition. Twenty-seven subjects (nine male) played a prototypical bidding game: a double action, with three \"market\" types, which differed in the number of competitors. We compared different computational learning models of bidding: directional learning models (DL), where the model bid is \"nudged\" depending on whether it was accepted or rejected, along with standard reinforcement learning models (RL). We found that DL fit the behavior best and resulted in higher payoffs. We found the binary learning signal associated with DL to be represented by neural activity in the striatum distinctly posterior to a weaker reward prediction error signal. We posited that DL is an efficient heuristic for valuation when the action (bid) space is continuous. Indeed, we found that the posterior parietal cortex represents the continuous action-space of the task, and the frontopolar prefrontal cortex distinguishes among conditions of social competition. Based on our findings we proposed a conceptual model that accounts for a sequence of processes that are required to perform successful and flexible bidding under different types of competition.

neuroscience↗

bioRxiv2016

RL mechanisms of short-term plasticity of auditory cortex

The decision-making process is exposed to modulatory factors, and, according to the expected value (EV) concept the two most influential factors are magnitude of prospective behavioural outcome and probability of receiving this outcome. The discrepancy between received and predicted outcomes is reflected by the reward prediction error (RPE), which is believed to play a crucial role in learning in dynamic environment. Feedback related negativity (FRN), a frontocentral negative component registered in EEG during feedback presentation, has been suggested as a neural signature of RPE. In modern neurobiological models of decision-making the primary sensory input is assumed to be constant over the time and independent of the evaluation of the option associated to it. In this study we investigated whether the electrophysiological changes in auditory cues perception is modulated by the strengths of reinforcement signal, represented in the EEG as FRN.\n\nWe quantified the changes in sensory processing through a classical passive oddball paradigm before and after performance a neuroeconomic monetary incentive delay (MID) task. Outcome magnitude and probability were encoded in the physical characteristics of auditory incentive cues. We evaluated the association between individual biomarkers of reinforcement signal (FRN) and the degree of perceptual learning, reflected by changes in auditory ERP components (mismatch negativity and P3a). We observed a significant correlation of MMN and valence - dFRN, reflecting differential processing of gains and omission of gains. Changes in P3a were correlated to probability - dFRN, including information on salience of the outcome, in addition to its valence.\n\nMID task performance evokes plastic changes associated with more fine-grained discrimination of auditory anticipatory cues and enhanced involuntary attention switch towards these cues. Observed signatures of neuro-plasticity of the auditory cortex may play an important role in learning and decision-making processes through facilitation of perceptual discrimination of valuable external stimuli. Thus, the sensory processing of options and the evaluation of options are not independent as implicitly assumed by the modern neuroeconomics models of decision-making.

neuroscience↗