Biology subjects

Vahabie, A.-H.

Publications and source records attributed to Vahabie, A.-H..

8 recordsLinked to original sources

bioRxiv2025

Risky Choices After Frontal Brain Injury: Differential Effects in Self vs Other-Decision Contexts

Frontal lobe integrity is crucial for assessing risk and making informed decisions. This study investigated how frontal lobe lesions affect the computational mechanisms underlying risky choice, particularly when decisions impact oneself versus another person. A Patient Group of 20 individuals with frontal cortex damage and a Control Group of 20 matched individuals performed a gambling task, making accept/reject decisions on mixed-outcome gambles for themselves ("Self") or an anonymous other ("Other"). We provide a mechanistic account of choice behavior using Prospect Theory, the leading behavioral model of decision-making under risk, to quantify parameters for utility curvature, loss aversion, and probability weighting. Behaviorally, the Patient Group accepted significantly more disadvantageous gambles for themselves than did the Control Group yet showed a trend toward greater caution when choosing for others. Prospect Theory modeling revealed a specific computational phenotype for this behavior. Compared to the Control Group, the Patient Group exhibited significantly more pronounced utility curvature (lower , {beta}) and more linear, less distorted probability weighting (higher {gamma}). While patients also showed a trend toward lower loss aversion ({lambda}), this difference was not statistically significant. This combination of altered utility and probability processing explains their paradoxical risk-seeking. These findings suggest that frontal cortex damage disrupts the computation of subjective value, leading to a distinctive decision-making profile marked by altered utility curvature and reduced sensitivity to outcome magnitudes. This computational characterization deepens our understanding of frontal lobe contributions to decision-making and can inform targeted rehabilitation strategies.

neuroscience↗

bioRxiv2025

Short-Term Arcade-Action Video Gaming Enhances Working Memory Precision

Working-memory (WM) precision depends on top-down control by dorsolateral prefrontal cortex (dlPFC). Whether a brief session of action video-game play can sharpen this control, and which neural processes mediate any benefit, remains unknown. Thirty-four adults were randomly assigned to 30 min of fast-paced gaming (Snail Mail; Experiment) or time-matched cartoon viewing (Control). Delayed continuous-report precision and 128-channel resting EEG were collected before and after the intervention. Absolute recall error fell in the Experiment group (p < .001) but rose in Controls (p = .005); the groups did not differ at baseline (p = .164) yet the Experiment group outperformed Control at post-test (p < .001). In the EEG subset (N = 30), gaming selectively increased high-alpha (10-13 Hz) power over left dlPFC (AFF7h; p = .041), an effect absents in Controls and significant between groups (p = .010). Across participants, the magnitude of this prefrontal alpha gain predicted the improvement in WM precision (r = .53, p = .0025), whereas concurrent flattening of the global 1/f slope was unrelated (|r| < .24, p > .21). A single, ecologically realistic gaming session therefore yields measurable enhancement of mnemonic precision together with local up-regulation of dlPFC-centered alpha oscillations, identifying a plausible cortical mechanism for rapid, low-cost cognitive plasticity.

neuroscience↗

bioRxiv2024

Emotional content effects the precision of visual working memory

ObjectivesOur working memory (WM) is susceptible to errors influenced by various sources. Recent research has illuminated the intricate relationship between emotional valence and working memory performance. This study aims to comprehensively investigate memory recall biases across different emotional categories. MethodTo explore this relationship, we designed and implemented a delayed-reproduction facial emotion n-back task. Participants were tasked with recalling the emotional valence of target faces across various n-back conditions, selecting their responses from a continuum of 19 morphed faces ranging from sad to happy. ResultsOur findings indicate that participants generally exhibit a negativity bias, struggling more with happy faces. Interestingly, they also perceive happy faces as less happy and sad faces as less sad, suggesting both positive and negative reappraisal in their emotional valence perception. This underscores the complex interplay between emotional valence and cognitive performance. Notably, recall of neutral images remained stable and was unaffected by preceding emotional contexts. ConclusionThese findings demonstrate that emotional content in working memory significantly impacts errors during WM tasks, with more emotionally charged faces leading to a greater drift toward the lower valence axis. This highlights the need for further exploration of how emotional factors influence cognitive processes in working memory.

neuroscience↗

bioRxiv2024

Investigating the Effects of Synbiotic Intervention on Working Memory performance in Healthy Young Women

The gut-brain axis plays a key role in the bidirectional communication between the gastrointestinal system and the brain, with gut microbiota significantly influencing cognitive function. While synbiotic and probiotic interventions have shown potential cognitive benefits, results across studies remain mixed. This randomized, controlled, repeated-measures study investigated the effects of a 15-day synbiotic intervention on cognitive performance in 28 healthy women (aged 18-32), assigned to either a synbiotic or no-treatment control group. Cognitive performance was assessed before and after the intervention using the Parametric Auditory Working Memory Task and the Integrated Visual and Auditory Continuous Performance Test (IVA-CPT). Compared to the control group, participants in the synbiotic group demonstrated selective improvements in attention, particularly in overall visual attention and visual sustained attention, as indicated by significant group-by-time interactions (ps < .05). No significant changes were observed in auditory working memory or inhibitory control. These results suggest that short-term synbiotic supplementation may selectively enhance visual attention without broadly affecting executive functions.

neuroscience↗

bioRxiv2024

Conscious and Unconscious Emotional Processing: Insights from Behavioral and Pupillary Responses

Emotions are crucial in social interactions, influencing communication and relationships. Distinguishing the perceived emotion in conscious and unconscious emotional processing is a key research area with cognitive and physiological implications. This study investigates conscious and unconscious emotional processing through behavioral and pupillary responses. Participants completed emotion recognition tasks under varying states, revealing higher accuracy in conscious emotion identification. Emotions like anger, happiness, fear, surprise, and neutral elicited distinct response patterns. Pupillometry data showed pupil size suppression in the conscious state and enhancement in the unconscious state, with differences in peak pupil size across emotions. Task-related components, amplitude, and latency parameters differed between conscious and unconscious states, highlighting the role of awareness in emotional regulation. These findings emphasize the complex interplay of cognitive and physiological processes in emotional responses, providing insights into emotional recognition mechanisms. This study contributes to understanding emotional processing dynamics and has implications for psychology and neuroscience research.

neuroscience↗

bioRxiv2023

The Spatial Frequency Representation Predicts Category Coding in the Inferior Temporal Cortex

Understanding the neural representation of spatial frequency (SF) in the primate cortex is vital for unraveling visual processing mechanisms in object recognition. While numerous studies concentrate on the representation of SF in the primary visual cortex, the characteristics of SF representation and its interaction with category representation remain inadequately understood. To explore SF representation in the inferior temporal (IT) cortex of macaque monkeys, we conducted extracellular recordings with complex stimuli systematically filtered by SF. Our findings disclose an explicit SF coding at single-neuron and population levels in the IT cortex. Moreover, the coding of SF content exhibits a coarse-to-fine pattern, declining as the SF increases. Temporal dynamics analysis of SF representation reveals that low SF (LSF) is decoded faster than high SF (HSF), and the SF preference dynamically shifts from LSF to HSF over time. Additionally, the SF representation for each neuron forms a profile that predicts category selectivity at the population level. IT neurons can be clustered into four groups based on SF preference, each exhibiting different category coding behaviors. Particularly, HSF-preferred neurons demonstrate the highest category decoding performance for face stimuli. Despite the existing connection between SF and category coding, we have identified uncorrelated representations of SF and category. In contrast to the category coding, SF is more sparse and places greater reliance on the representations of individual neurons. Comparing SF representation in the IT cortex to deep neural networks, we observed no relationship between SF representation and category coding. However, SF coding, as a category-orthogonal property, is evident across various ventral stream models. These results dissociate the separate representations of SF and object category, underscoring the pivotal role of SF in object recognition.

neuroscience↗

bioRxiv2019

Higher Meta-cognitive Ability Predicts Less Reliance on Over Confident Habitual Learning System

Many studies on human and animals have provided evidence for the contribution of goal-directed and habitual valuation systems in learning and decision-making. These two systems can be modeled using model-based (MB) and model-free (MF) algorithms in Reinforcement Learning (RL) framework. Here, we study the link between the contribution of these two learning systems to behavior and meta-cognitive capabilities. Using computational modeling we showed that in a highly variable environment, where both learning strategies have chance level performances, model-free learning predicts higher confidence in decisions compared to model-based strategy. Our experimental results showed that the subjects meta-cognitive ability is negatively correlated with the contribution of model-free system to their behavior while having no correlation with the contribution of model-based system. Over-confidence of the model-free system justifies this counter-intuitive result. This is a new explanation for individual difference in learning style.

neuroscience↗

bioRxiv2018

Better than maximum likelihood estimation of model-based and model-free learning style

Multiple decision making systems work together to shape the final choices in human behavior. Habitual and goal-directed systems are the two most important systems that are studied in the reinforcement learning (RL) literature by model-free and model-based learning methods. Human behavior resembles the weighted combination of these systems and such a combination is modeled by weighted summation of actions value from the model based and model free systems. Extraction of this weighted parameter, which is important for many applications and computational modeling, has been mostly based on the maximum likelihood or maximum a posteriori methods. We show these methods bring many challenges and their respective extracted values are less reliable especially in the proximity of extremes values. We propose that using a free format learning method (k-nearest neighbor) which uses more information besides the fitted values e.g. global information like stay probability instead of trial by trial information can ameliorate the estimation error. The proposed method is examined by simulation and results show the advantage of the proposed method. In addition, investigation of the human behavior data from previous researchers proved the proposed method to result in more statistically robust results in predicting other behavioral indices such as the number of gaze directions toward each target. In brief, the proposed method increases the reliability of the estimated parameters and enhances the applicability of reinforcement learning paradigms in clinical trials.

neuroscience↗