Biology subjects

Petton, M.

Publications and source records attributed to Petton, M..

5 recordsLinked to original sources

bioRxiv2025

Multi-task Intracranial EEG recordings reveal a Comprehensive Role of the Human Dorsal Anterior Insula in High-Level Cognition

The dorsal anterior insula (dAI) is widely recognized as a cornerstone of human cognition. However, its functional characterization remains the subject of considerable debate and competing theories. Embracing a "shift in viewpoint" approach--defining a brain regions function through the observation of the same neural population across diverse experimental contexts--this study used intracranial EEG (iEEG) recordings from a large cohort of patients to investigate the sub-second neural response dynamics of the human dAI across a broad range of cognitive tasks, spanning visual category discrimination, phonological and semantic processing, attentive visual search, and verbal and visuospatial working memory. This within-subject, multi-task iEEG framework offered a robust basis for decoding the structure-function relationship of the dAI and for empirically testing key predictions of prevailing theoretical models concerning its role. Our findings confirmed the dAIs involvement in the Action-Mode Network and shed new light on the large-scale spatiotemporal organization of that network, while providing novel insights into the interplay between cognitive effort and efficiency.

neuroscience↗

bioRxiv2025

The Inferior Frontal Sulcus, not the Anterior Insula, acts as a late-stage attentional gate for the fast rejection of salient but irrelevant sensory inputs during cognitive tasks

The ability to prioritize behaviorally relevant stimuli is essential for efficient cognition, particularly in distracting environments. The anterior insula (AI), a key node of the salience network, has been proposed to support this selection process by detecting salient events. A similar function, however, has also been attributed to the inferior frontal sulcus (IFS), located at the intersection of the ventral and dorsal attention networks. Here, we directly compared the respective contributions of these regions to attentional gatekeeping--the identification and rejection of attention-grabbing yet task-irrelevant "false positives" to preserve cognitive resources. We recorded intracranial EEG from 63 patients performing an attentive reading task designed to dissociate salience from task relevance. High-Frequency Activity (HFA) responses between 50 Hz and 150 Hz revealed that the IFS was the only region--across an extensive sampling of the frontal and insular cortices--to exhibit consistent, subsecond response dynamics compatible with the filtering of false positives. In contrast, the AI did not participate in the analysis or rejection of distractors and showed only sparse, delayed responses to targets, suggesting a role in coordinating or energizing downstream cognitive or motor processes rather than in salience detection per se. These findings indicate that the IFS--rather than the AI--is the primary late-stage node for attentional gatekeeping during cognitive tasks performed under distracting conditions.

neuroscience↗

bioRxiv2020

THE DUAL-TASK COST IS DUE TO NEURAL INTERFERENCES DISRUPTING THE OPTIMAL SPATIO-TEMPORAL DYNAMICS OF THE COMPETING TASKS

Dual-tasking is extremely prominent nowadays, despite ample evidence that it comes with a performance cost: the Dual-Task (DT) cost. Neuroimaging studies have established that tasks are more likely to interfere if they rely on common brain regions, but the precise neural origin of the DT cost has proven elusive so far, mostly because fMRI does not record neural activity directly and cannot reveal the key effect of timing, and how the spatio-temporal neural dynamics of the tasks coincide. Recently, DT electrophysiological studies in monkeys have recorded neural populations shared by the two tasks with millisecond precision to provide a much finer understanding of the origin of the DT cost. We used a similar approach in humans, with intracranial EEG, to assess the neural origin of the DT cost in a particularly challenging naturalistic paradigm which required accurate motor responses to frequent visual stimuli (task T1) and the retrieval of information from long-term memory (task T2), as when answering passengers questions while driving. We found that T2 elicited neuroelectric interferences in the gamma-band (>40 Hz), in key regions of the T1 network including the Multiple Demand Network. They reproduced the effect of disruptive electrocortical stimulations to create a situation of dynamical incompatibility, which might explain the DT cost. Yet, participants were able to flexibly adapt their strategy to minimize interference, and most surprisingly, reduce the reliance of T1 on key regions of the executive control network - the anterior insula and the dorsal anterior cingulate cortex - with no performance decrement. HIGHLIGHTS- First direct evidence in humans of neural interferences between two tasks. - First explanation of the Dual-Task cost at the neural level in humans. - First Dual-Tasking study with intracranial EEG in naturalistic conditions.

neuroscience↗

bioRxiv2018

BLAST : a short computerized test to measure the ability to stay on task. Normative behavioral data and detailed cortical dynamics.

1.This article provides an exhaustive description of a new short computerized test to assess on a second-to-second basis the ability of individuals to << stay on task >>, that is, to apply selectively and repeatedly task-relevant cognitive processes. The task (Bron/Lyon Attention Stability Test, or BLAST) lasts around one minute, and measures repeatedly the time to find a target letter in a two-by-two letter array, with an update of all letters every new trial across thirty trials. Several innovative psychometric measures of attention stability are proposed based on the instantaneous fluctuations of reaction times throughout the task, and normative data stratified over a wide range of age are provided by a large (>6000) dataset of participants aged 8 to 70. We also detail the large-scale brain dynamics supporting the task from an in-depth study of 32 participants with direct electrophysiological cortical recordings (intracranial EEG) to prove that BLAST involves critically large-scale executive attention networks, with a marked activation of the dorsal attention network and a deactivation of the default-mode network. Accordingly, we show that BLAST performance correlates with scores established by ADHD-questionnaires.

neuroscience↗

bioRxiv2017

Frequency-Resolved Correlates Of Visual Object Recognition In Human Brain Revealed By Deep Convolutional Neural Networks

Previous work demonstrated a direct correspondence between the hierarchy of the human visual areas and layers of deep convolutional neural networks (DCNN) trained on visual object recognition. We used DCNNs to investigate which frequency bands correlate with feature transformations of increasing complexity along the ventral visual pathway. By capitalizing on intracranial depth recordings from 100 patients and 11293 electrodes we assessed the alignment between the DCNN and signals at different frequency bands in different time windows. We found that gamma activity, especially in the low gamma-band (30 - 70 Hz), matched the increasing complexity of visual feature representations in the DCNN. These findings show that the activity of the DCNN captures the essential characteristics of biological object recognition not only in space and time, but also in the frequency domain. These results also demonstrate the potential that modern artificial intelligence algorithms have in advancing our understanding of the brain.\n\nSignificance StatementRecent advances in the field of artificial intelligence have revealed principles about neural processing, in particular about vision. Previous works have demonstrated a direct correspondence between the hierarchy of human visual areas and layers of deep convolutional neural networks (DCNNs), suggesting that DCNN is a good model of visual object recognition in primate brain. Studying intracranial depth recordings allowed us to extend previous works by assessing when and at which frequency bands the activity of the visual system corresponds to the DCNN. Our key finding is that signals in gamma frequencies along the ventral visual pathway are aligned with the layers of DCNN. Gamma frequencies play a major role in transforming visual input to coherent object representations.

neuroscience↗