Biology subjects

Ramawat, S.

Publications and source records attributed to Ramawat, S..

6 recordsLinked to original sources

bioRxiv2025

Individual differences in learning and decision-making: the role of COMT Val158Met polymorphism in transitive inference

Understanding the ordinal relationships between items requires constructing a rank order supporting decision-making between options. This process depends on the ability to learn reciprocal relationships and to select the best option available when making a choice. In such forms of decision-making, the prefrontal cortex (PFC) plays a crucial role in encoding the relative value of alternatives as a decision is formed. Higher-order cognitive abilities are influenced by genetic factors that affect dopamine availability in the PFC, potentially contributing to individual differences. Here, we examined the performance of 83 participants in a transitive inference task (TI), grouped by genotype based on the Val158Met single-nucleotide polymorphism in the Catechol-O-Methyltransferase (COMT) gene. The task included a learning phase in which participants acquired the reciprocal relationships among a set of hierarchically ranked items (A>B>C>D>E>F), followed by a test phase in which they were required to compare all possible item pairs and select the higher-ranked one. While genotype did not significantly influence test-phase performance, it did affect learning efficiency. Specifically, Val homozygotes took a longer learning procedure than both heterozygotes and Met homozygotes during the learning phase. Drift diffusion modelling (DDM) revealed that task performance was explained by the efficiency of evidence accumulation, which was lower in Val homozygotes, accounting for their poorer performance not only during initial learning but also when required to switch to a reversed hierarchical structure (A<B<C<D<E<F). These findings suggest that individual differences in inferential decision-making and cognitive flexibility may be partially driven by genetically determined variations in prefrontal dopamine availability.

neuroscience↗

bioRxiv2025

Dynamics of oscillatory power subtends multiplexing of perceptual and mnemonic information within the premotor cortex

Flexible behaviour requires decision-making that integrates both perceptual and mnemonic-related information. While the dorsal premotor cortex (PMd) is known to support decision-making based on perceptual computations, its contributions to decisions based on mnemonic information for motor planning are underexplored. Here, investigating local field potential (LFP) oscillations in PMd of monkeys performing a transitive inference task required the formation and retrieval of mnemonic representations of an arbitrarily defined rank order among perceptual items. Our results highlight that a dynamic interplay between lower frequencies (Theta, Alpha, Beta) and high-Gamma oscillatory activity of LFP reflects a mechanism for accessing and manipulating memory-related information underlying decision-making. These findings provide evidence that the PMd plays a role in multiplexing both perceptual and mnemonic information, extending its competence beyond the association of perceptual input with motor decisions.

neuroscience↗

bioRxiv2024

The biomechanical state of the effector affects motor control and provides measures of single trial inhibition in a stop signal task

The Stop Signal Task (SST) has been the benchmark for studying the behavioral and physiological basis of movement generation and inhibition. In our study, we extended the scope beyond physiological findings related to muscle activity, focusing our analysis on the initial biomechanical state of the effector. By incorporating a force sensitive resistor (FSR), we continuously monitored the force applied by the effector (here the index finger) during a button release version of the SST. This modified task design allowed us to examine both the baseline force before the relevant Go signal was presented and during the covert state of movement preparation. Notably, variations in force over time in response to the Go signal revealed differences across trials where movement was either generated or successfully inhibited, depending on the amount of force during the baseline period. Specifically, higher baseline force was associated with a delayed movement generation, which simultaneously slowed down the force release, facilitating successful inhibition when requested. Our results highlight the influence of biomechanical variables in movement control, which should be accounted for by the models developed for investigating the physiology of this ability. NEW & NOTEWORTHYMovement involves changing the position of anatomical effectors, like a finger. The initial biomechanical state of an effector impacts movement generation and inhibition. Using the Stop-Signal task, we studied these factors by measuring the force applied to a mouse button before movement onset. Higher initial force delayed movement generation and slowed force release, aiding movement inhibition. This research links behavioral models of action-stopping with movement biomechanics, highlighting the effectors initial state importance.

neuroscience↗

bioRxiv2024

Balancing postural control and motor inhibition during gait initiation

This study examines the relationship between stopping a planned gait initiation due to sudden environmental changes and maintaining body stability. Using a gait initiation version of the Stop Signal Task (SST), we studied changes in anticipatory postural adjustments (APA) during gait initiation and suppression. We found that trial-level variables, such as the time to start or stop stepping, interacted with biomechanical factors like the center of mass displacement relative to the base of support, affecting performance. A critical biomechanical threshold was identified, beyond which stopping movement was unlikely. These findings highlight the strong link between limb action control and body equilibrium, offering a framework within a motor control paradigm. By integrating biomechanical elements, the model effectively simulates real-life scenarios, identifying key variables for studying neural correlations between action and postural control, and aiding in the development of injury prevention and rehabilitation tools for individuals with movement and posture impairments.

neuroscience↗

bioRxiv2023

A Theoretical Formalization of Consequence-Based Decision-Making

Learning to make adaptive decisions depends on exploring options, experiencing their consequence, and reassessing ones strategy for the future. Although several studies have analyzed various aspects of value-based decision-making, most of them have focused on decisions in which gratification is cued and immediate. By contrast, how the brain gauges delayed consequence for decision-making remains poorly understood. To investigate this, we designed a decision-making task in which each decision altered future options. The task was organized in groups of consecutively dependent trials, and the participants were instructed to maximize the cumulative reward value within each group. In the absence of any explicit performance feedback, the participants had to test and internally assess specific criteria to make decisions. This task was designed to specifically study how the assessment of consequence forms and influences decisions as learning progresses. We analyzed behavior results to characterize individual differences in reaction times, decision strategies, and learning rates. We formalized this operation mathematically by means of a multi-layered decision-making model. By using a mean-field approximation, the first layer of the model described the dynamics of two populations of neurons which characterized the binary decision-making process. The other two layers modulated the decision-making policy by dynamically adapting an oversight learning mechanism. The model was validated by fitting each individual participants behavior and it faithfully predicted non-trivial patterns of decision-making, regardless of performance level. These findings provided an explanation to how delayed consequence may be computed and incorporated into the neural dynamics of decision-making, and to how learning occurs in the absence of explicit feedback.

neuroscience↗

bioRxiv2021

Different contribution of the monkey prefrontal and premotor dorsal cortex in decision-making supported by inferential reasoning

Several studies have reported similar neural modulations between brain areas of the frontal cortex, such as the dorsolateral prefrontal (DLPFC) and the premotor dorsal (PMd) cortex, in tasks requiring encoding of the abstract rules for selecting the proper action. Here we compared the neuronal modulation of the DLPFC and PMd of monkeys trained to choose the higher rank from a pair of abstract images (target item), selected from an arbitrarily rank-ordered set (A>B>C>D>E>F) in the context of a transitive inference task. Once acquired by trial-and-error, the ordinal relationship between pairs of adjacent images (i.e., A>B; B>C; C>D; D>E; E>F), monkeys were tested in indicating the ordinal relation between items of the list not paired during learning. During these decisions, we observed that the choice accuracy increased and the reaction time decreased as the rank difference between the compared items enhanced. This result is in line with the hypothesis that after learning, the monkeys built an abstract mental representation of the ranked items, where rank comparisons correspond to the items position comparison on this representation. In both brain areas, we observed higher neuronal activity when the target item appeared in a specific location on the screen with respect to the opposite position and that this difference was particularly enhanced at lower degrees of difficulty. By comparing the time evolution of the activity of the two areas, we observed that the neural encoding of target item spatial position occurred earlier in the DLPFC than in the PMd.

animal behavior and cognition↗