Biology subjects

Rostami, F.

Publications and source records attributed to Rostami, F..

3 recordsLinked to original sources

bioRxiv2026

Hard-to-beat animacy perception: EEG evidence of accurate animate-inanimate distinction for ambiguous objects

Human recognition of objects as animate or inanimate is fast and accurate. However, this task may be challenging for objects with animal-like properties (e.g., presence of eyes/face), albeit being inanimate (e.g., a cow-mug). Lookalike objects provide an opportunity to examine how visual perception resolves categorical ambiguities and whether it exhibits an intrinsic bias to see animacy. During electroencephalography (EEG), we presented healthy humans with images of objects at a regular, rapid frequency (6 Hz), where every five exemplars of a standard category (animate or inanimate), an exemplar of the other oddball category was shown (1.2 Hz). In some conditions, oddball-stimuli were replaced by lookalikes. Periodic visual stimulation should give rise to a distinctive EEG response at 6 Hz. Moreover, if the oddball category elicits a different neural response than the standard category, a distinct response should be observed at 1.2 Hz. This categorization response was found for animate-oddballs among inanimate objects, and vice versa. It was also found for lookalike-oddballs presented among animate or inanimate objects, but it was significantly higher in the first case, implying that lookalike objects were perceived as more similar to inanimate than animate objects. The degree of animal resemblance modulated the amplitude of neural response to lookalikes, without however changing the category boundary. These results--also replicated in an artificial model of human vision--demonstrate that animal resemblance of objects is registered in visual perception, but it does not alter the critical ability to distinguish between what is truly alive and what is not.

neuroscience↗

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

Animate-inanimate object categorization from minimal visual information in the human brain, human behavior, and deep neural networks

The distinction between animate and inanimate things is a main organizing principle of information in perception and cognition. Yet, animacy, as a visual property, has so far eluded operationalization. Which visual features are necessary and sufficient to see animacy? At which level of the visual hierarchy does the animate-inanimate distinction emerge? Here, we show that the animate-inanimate distinction is preserved even among images of objects that are made unrecognizable and only retain low- and mid-level visual features of their natural version. In particular, in three experiments, healthy human adults saw rapid sequences of images (6 Hz) where every five exemplars of a category (i.e., animate), an exemplar of another category (i.e., inanimate) was shown (1.2 Hz). Using frequency-tagging electroencephalography (ftEEG), we found significant neural responses at 1.2 Hz, indicating rapid and automatic detection of the periodic categorical change. Moreover, such effect was found -although increasingly weaker- for impoverished stimulus-sets that retained only certain (high-, mid-or low-level) features of the original colorful images (i.e., grayscale, texform and phase-scrambled images), and even if the images were unrecognizable. Similar effects were found with two Deep Neural networks (DNNs) presented with the same stimulus-sets. In sum, reliable categorization effects for dramatically impoverished and unrecognizable images, in humans EEG and DNN data, demonstrate that animacy representation emerges early in the visual hierarchy and is remarkably resilient to the loss of visual information.

neuroscience↗