Biology subjects

Mirifar, A.

Publications and source records attributed to Mirifar, A..

3 recordsLinked to original sources

bioRxiv2026

Heightened Distraction under Competition in Obsessive-Compulsive Disorder

The present study examine the extent to which attentional resources are allocated toward distracting affective and disorder-relevant pictures under task-relevant competition in participants with obsessive-compulsive disorder (OCD; N = 33) and controls (N = 31). Competition between cues was examined using a foreground task where participants detected coherent motion in a flickering random dot kinematogram (RDK) overlaid on pictures ranging in emotional content (pleasant, neutral, unpleasant, and OCD-evoking pictures). Steady-state visual evoked potentials (ssVEPs) were measured in response to the flickering RDK and served as an index of visuocortical engagement with task-relevant cues. Data were also fitted to the distraction under competition model (DUC), a computational framework of attention selection. Group differences emerged with stronger visuocortical distraction (attenuated task engagement) in the OCD group, driven largely by the unpleasant pictures, followed by the OCD-evoking and pleasant pictures. Furthermore, the DUC model fit well in both groups and supported the results of the univariate analysis, demonstrating the magnitude of the visuocortical distraction observed in response to the unpleasant pictures, and the presence of substantial distraction in response to the OCD-evoking pictures in the OCD group. The present findings provide visuocortical evidence of heightened distraction in response to unpleasant and OCD-evoking pictures under task-relevant competition in OCD.

neuroscience↗

bioRxiv2025

Concept2Brain: An AI model for predicting subject-level neurophysiological responses to text and pictures

The current growth of artificial intelligence (AI) tools provides an unprecedented opportunity to extract deeper insights from neurophysiological data while also enabling the reproduction and prediction of brain responses to a wide range of events and situations. Here, we introduce the Concept2Brain model, a deep network architecture designed to generate synthetic electrophysiological responses to semantic/emotional information conveyed through pictures or text. Leveraging AI solutions like CLIP from OpenAI, the model generates a representation of pictorial or language input and maps it into an electrophysiological latent space. We demonstrate that this openly available resource generates synthetic neural responses that closely resemble those observed in studies of naturalistic scene perception. The Concept2Brain model is provided as a web service tool for creating open and reproducible EEG datasets, allowing users to predict brain responses to any semantic concept or picture. Beyond its applied functionality, it also paves the way for AI-driven modeling of brain activity, offering new possibilities for studying how the brain represents the world.

neuroscience↗

bioRxiv2022

Effects of Neurofeedback training on performance in laboratory tasks: A systematic review

Neurofeedback procedures are attracting increasing attention in the neuroscience community. Based on the principle that participants, through suitable feedback, may learn to affect specific aspects of their brain activity, neurofeedback has been applied to basic research, translational, and clinical science alike. A large segment of the extant empirical research as well as review articles have focused on the extent to which neurofeedback interventions affect mental health outcomes, cognitive capacity, aging, and other complex behaviors. Another segment has aimed to characterize the extent to which neurofeedback affects the targeted neural processes. At this time, there is no current systematic review of the effects of neurofeedback on healthy participants performance in experimental tasks. Such a review is relevant in this rapidly evolving field because changes in experimental task performance are traditionally considered a hallmark of changing neurocognitive processes, often established in neurotypical individuals. This systematic review addresses this gap in the literature using the PRISMA method, building on earlier reviews on the same topic. Empirical studies using EEG or fMRI to alter brain processes linked to established, well-defined cognitive and affective laboratory tasks were reviewed. Substantial variability was found regarding the nature of the control for placebo effects, the implementation of the feedback, and the neural targets of feedback. Importantly, only a minority of the studies reported statistically meaningful effects of neurofeedback on performance in cognitive and affective tasks. Examining effect sizes and p-values in a subset of studies found no evidence for reporting bias, while also not finding systematic relations between study characteristics such as sample size or experimental control on the one hand and efficacy on the other. Implications for future work are discussed.

neuroscience↗