Biology subjects

Loued-Khenissi, L.

Publications and source records attributed to Loued-Khenissi, L..

3 recordsLinked to original sources

bioRxiv2025

Mid-level visual features engage V4 to support sparse object recognition under uncertainty

Cortical visual prostheses aim to restore sight by stimulating the visual cortex, yet current approaches remain limited. Implants targeting V1 typically evoke isolated phosphenes that do not support coherent object recognition. We asked whether mid-level visual features, specifically curve segments associated with area V4, could provide a more efficient substrate for artificial vision. Using fMRI, 24 participants performed an object recognition task with stimuli fragmented into either phosphene-like dots or curve segments at varying densities. Behaviorally, curve segments enabled recognition at lower density thresholds and produced steeper psychometric slopes. Neurally, both fragment types engaged V1, but only curve segments recruited V4, and correct recognition of segments relative to phosphenes evoked broader occipito-temporo-parietal responses. Multivariate decoding showed that successful recognition of phosphenes was predicted by early visual and cingulate activity, whereas recognition of segments was predicted only by V4, indicating a shift toward mid-level representational support. Mediation analyses further showed that phosphene-based recognition relied on anterior cingulate cortex under conditions of higher uncertainty, while segment-based recognition depended primarily on visual cortex. Together, these results show that mid-level fragments confer perceptual and neural advantages, reducing reliance on both dense stimulation and downstream uncertainty resolution, and identify V4 as a promising target for next-generation cortical prostheses.

neuroscience↗

bioRxiv2025

Pain Expectations: the neural representations of predicted pain in self and others

Inferring another persons pain is a challenging computational problem: unlike self-related pain, individuals have no access to others nociceptive input and must instead rely only on indirect cues under substantial uncertainty. Using a predictive-processing framework, we modeled how expectation, uncertainty (variance-based risk), prediction error (PE) and surprise jointly shape pain-related decisions for oneself and for a stranger. During fMRI, participants received cues signaling the intensity and probability of possible painful events, then made decisions to mitigate the anticipated pain via a lottery and a wager. Behaviorally, participants were more risk-averse toward others pain than their own, prioritizing pain reduction over economic gain. Neurally, anticipatory risk signals in anterior insula (AI) and dorsal striatum were selectively amplified when pain concerned another person, as opposed to self-pain. By contrast, PE and surprise were reliably represented in AIns for both targets following pain delivery. However, representational similarity analysis suggest that error-signal in AIns is represented through reliable, but dissociated, patterns for self and others. Together, these findings show that expectation, uncertainty and error processing are differentially affected by the identity of the pain recipient, and underscore how models of prediction under uncertainty are powerful tools for explaining how we assess pain in other people. Significance StatementWhen we make decisions about another persons pain, we cannot directly access what they feel: we must infer it under uncertainty. Through a rigorous computational framework of prediction under uncertainty, we assessed the joint role played by expectancy, uncertainty and error-signal to model peoples decisions about their own and others pain. Deciding on anothers behalf increased brain and behavioral sensitivity to uncertainty; likewise error signals following a painful event were represented in a specific code, distinct from self-related pain. These findings offer a computational account of how humans navigate the inherent uncertainty of inferring others internal states, with direct relevance to clinical settings where surrogate decision-makers must estimate a patients pain despite lacking direct access to it.

neuroscience↗

bioRxiv2019

Anterior Insula Reflects Inferential Errors in Value-Based Decision-making and Perception

The process of inference is theorized to underlie neural processes, including value-based decision-making and perception. Value-based decision-making commonly involves deliberation, a time-consuming process that requires conscious consideration of decision variables. Perception, by contrast, is thought to be automatic and effortless. To determine if inference characterizes both perception and value-based decision-making, we directly compared uncertainty signals in visual perception and an economic task using fMRI. We presented the same individuals with different versions of a bi-stable figure (Neckers cube) and with a gambling task during fMRI acquisition. To track the inferential process assumed in both tasks, we experimentally varied uncertainty, either on perceptual state or financial outcome. We found that inferential errors captured by surprise in the gambling task yielded BOLD responses in the anterior insula, in line with earlier findings. Moreover, we found perceptual risk and surprise in the Necker Cube task yielded similar responses in the anterior insula. These results suggest that uncertainty, irrespective of domain, correlates to a common brain region, the anterior insula. These findings provide empirical evidence that the brain interacts with its environment through inferential processes.

neuroscience↗