Biology subjects

Yargholi, E.

Publications and source records attributed to Yargholi, E..

4 recordsLinked to original sources

bioRxiv2025

Alignment of human behavior, brain, and AI models in the high-level valence processing of complex social scenes

Humans can evaluate the emotional meaning of complex social scenes in real-life settings. Recent evidence from the human brain and AI models pointed to visual processing as a core substrate for representing emotional valence of natural images, but this conclusion may not generalize to complex social scenes. We implemented experiments with social scenes in which emotional valence is partially dissociated from visual characteristics, objects, and scene settings. Human behavior, neuroimaging, and visual AI models confirm that visual processing captures basic emotional associations of objects and scene elements. However, when the valence of social scenes is incongruent with these basic properties, higher levels of processing are needed in the human association cortex and AI models. Our results show how and when valence processing demands advanced cognitive, neural, and computational processes that extend beyond the encoding of visual features.

neuroscience↗

bioRxiv2025

A network of face patches in human prefrontal cortex for social processing of faces

The human cerebral cortex contains localized regions for processing faces. These regions or patches, which are classically found in the occipito-temporal cortex, encode visual properties of faces. Using naturalistic movie-watching fMRI data from 176 human subjects and multivariate functional connectivity analysis, here we comprehensively characterize a novel network of four frontal face patches (FFPs) arranged dorsoventrally in the lateral prefrontal cortex. FFPs are strongly coupled with a face-selective region in the middle superior temporal sulcus, appear to be primarily involved in processing high-level social aspects of faces during movie-watching, and show partial correlations of activity with distinct cognitive networks. Activations in FFPs are correlated with the performance of subjects in a social cognition task. We further identify two groups of subjects who showed a remarkable difference in the topographical organization of FFPs. The discovery of FFPs provides new insights into the understanding of social processing in the brain.

neuroscience↗

bioRxiv2022

Category trumps shape as an organizational principle of object space in the human occipitotemporal cortex

The organizational principles of the object space represented in human ventral visual cortex are debated. Here we contrast two prominent proposals that, in addition to an organization in terms of animacy, propose either a representation related to aspect ratio or to the distinction between faces and bodies. We designed a critical test that dissociates the latter two categories from aspect ratio and investigated responses from human fMRI and deep neural networks (BigBiGAN). Representational similarity and decoding analyses showed that the object space in occipitotemporal cortex (OTC) and BigBiGAN was partially explained by animacy but not by aspect ratio. Data-driven approaches showed clusters for face and body stimuli and animate-inanimate separation in the representational space of OTC and BigBiGAN, but no arrangement related to aspect ratio. In sum, the findings go in favor of a model in terms of an animacy representation combined with strong selectivity for faces and bodies.

neuroscience↗

bioRxiv2021

Two distinct networks containing position-tolerant representations of actions in the human brain

Humans can recognize other peoples actions in the social environment. This action recognition ability is rarely hindered by the movement of people in the environment. The neural basis of this tolerance to changes in the position of observed actions is not fully understood. Here, we aimed to identify brain regions capable of generalizing representations of actions across different positions and investigate the representational content of these regions. fMRI data were recorded from twenty-two subjects while they were watching video clips of ten different human actions in Point Light Display format. Each stimulus was presented in either the upper or the lower visual fields. Multivoxel pattern analysis and a searchlight technique were employed to identify brain regions that contain position-tolerant action representation: linear support vector machine classifiers were trained with fMRI patterns in response to stimuli presented in one position and tested with stimuli presented in another position. Results of this generalization test showed above-chance classification in the left and right lateral occipitotemporal cortex, right intraparietal sulcus, and right post-central gyrus. To explore the representational content of these regions, we constructed models based on the objective measures of movements and human subjective judgments about actions. We then evaluated the brain similarity matrix from the cross-position classification analysis based on these models. Results showed cross-position classifications in the lateral occipito-temporal ROIs were more strongly related to the subjective judgments, while those in the dorsal parietal ROIs were more strongly related to the objective movements. An ROI representational similarity analysis further confirmed the separation of the dorsal and lateral regions. These results provide evidence for two networks that contain abstract representations of human actions with distinct representational content.

neuroscience↗