Jean‐Paul Noel

This study uses a virtual reality task and Inverse Rational Control to identify sensory and motor differences in ASD compared to neurotypical individuals.

This study identifies how peripersonal space is represented in the mouse rostro-lateral visual cortex using dense neural recordings and reveals multisensory integration and dynamic network properties.

This study examines age-related changes in neural and behavioural variability during a decision-making task in mice, finding increased neural variability and reduced variability quenching in specific brain regions.

The paper identifies a neural marker of peripersonal space (PPS) integration in EEG data and shows its presence correlates with conscious states in sleep and disorders of consciousness.

This study shows that active locomotion predictsively rescues head direction attractor dynamics in head-fixed mice by stabilizing the network through prospective motor signals.

Mice infer stimulus-side priors from recent choices; prior signals are decodable pre-stimulus in 24.0% to 30.2% of 242 brain regions, including early visual and motor areas.

The paper presents a brain-wide neural activity map from 621,733 neurons across 139 mice performing a decision-making task, showing how neural activity encodes task variables across brain regions.

The paper shows that mice with ASD-related mutations exhibit similar computational and neural anomalies in prior updating during decision-making.

This study evaluates the reproducibility of electrophysiological measurements across ten labs using standardized protocols and finds that variability in electrode targeting and statistical methods affects reproducibility.

The paper shows macaques strategically abort rewards in a VR task to maximize long-term gains, with dlPFC activity reflecting this behavior.

The paper introduces two public websites for exploring large-scale electrophysiology data from the International Brain Laboratory, enabling cross-platform access to behavioral trials and neuronal data.

The paper introduces an infinite hidden semi-Markov model to analyze learning curves in mice, finding three major learning stages and behavior changes after rest periods.

The paper investigates causal inference during closed-loop navigation by examining how humans disambiguate self- and object-motion, showing misattribution patterns and their dependence on motion conditions and target location.

The paper shows that dynamic reconfiguration of functional connectivity in prefrontal cortex supports context-invariant beliefs during natural behavior.

The paper examines neural dynamics in human primary motor cortex during brain-machine-interface mediated actions, showing that M1 encodes the onset of subjective intention.

The paper describes a modular data architecture for a neuroscience collaboration, enabling data contribution, access, and analysis across multiple labs.

The paper investigates how neural circuits in sensory, parietal, and frontal cortices encode latent variables during virtual navigation tasks in monkeys.

This study shows that humans and macaques rely on optic flow for decision-making in a naturalistic navigation task, demonstrating sensory evidence accumulation during action-perception loops.

This paper introduces a video analysis tool that combines supervised pose estimation with unsupervised dimensionality reduction to extract interpretable behavioral features from animal videos, improving downstream analyses.

This paper develops a standardized task for measuring decision-making in mice, showing reproducible results across multiple laboratories and providing a public dataset and tools.

This study shows that individuals with ASD have reduced sensory encoding capacity and limited adaptability to changing visual stimuli compared to controls.

This study investigates PPS remapping in ASD using psychophysical, EEG, and neural network models, finding reduced flexibility due to E/I imbalances.

This study investigates visual navigation in ASD using a computational task, finding increased variability but intact integration, with reduced variance through feedback.

The paper demonstrates that peri-personal space encoding adapts rapidly to sensory history, supported by psychophysical, electrophysiological, and neural network modeling evidence.

This study investigates how the brain represents stimulus presence and modal identity using neural recordings from non-human primates, finding distinct spatiotemporal dynamics in S1 and PMv cortices.

The paper analyzes neuronal activity in non-human primates under anesthesia to compare consciousness theories, finding convergent neurons show greater consciousness-related properties than integrative neurons.

This study uses intracranial EEG to show that peripersonal space processing around the trunk in humans involves multisensory integration and spatial modulation in specific brain regions.