Philippe Kahane

This study investigates whether stimulus detection and confidence evaluation in the human cortex use shared or modality-specific circuits, finding evidence for supramodal coding in detection and partial supramodal coding in confidence.

This study shows that neural representational geometry in ventral temporal cortex adapts gradually to task demands, supporting behavioral flexibility within sensory cortex.

This study uses multi-task intracranial EEG recordings to investigate the role of the human dorsal anterior insula in various cognitive tasks, revealing its involvement in the Action-Mode Network and the interplay between cognitive effort and efficiency.

The paper investigates how the brain encodes value signals for pleasant and unpleasant scenarios, showing distinct neural systems in vmPFC and aIns that guide decision-making.

This study uses intracranial EEG to show that reading sensation-related sentences activates the posterior insula earlier and more intensely than other semantic categories.

This study uses intracerebral stimulation to show that different locations in ventromedial prefrontal cortex and anterior insula have opposing effects on economic choices.

This study identifies overlapping neural mechanisms for evidence accumulation, confidence, and changes of mind in specific brain regions using intracranial recordings and computational modeling.

The paper shows evidence accumulation in brain regions explains perceptual experience and confidence, using neural data from 29 participants.

This study investigates the optimal level of theta activity in the subthalamo-medio-prefrontal circuit for rule-switching, finding a Goldilocks effect where moderate theta power supports successful switching while excessive or delayed theta leads to errors.

The paper identifies distinct neural interaction subsystems in the human frontal cortex for reward and punishment learning using intracranial recordings.

This study uses intracerebral EEG to show that motor cortex activity encodes hand movement direction during both planning and execution, with different frequency features involved in each phase.

This study investigates the role of the thalamus in human reinforcement learning using intra-thalamic electrophysiological recordings and identifies temporally structured oscillations as encoding key learning signals.

The paper investigates how mood fluctuations, influenced by incidental feedback, affect choice behavior through neural activity in the vmPFC and daIns.

The paper investigates the neural origin of dual-task cost in humans using intracranial EEG, finding gamma-band interferences in task-relevant brain regions and showing adaptive strategies to minimize interference.

The paper investigates reward and punishment prediction errors in humans using intracerebral recordings, finding distinct brain regions sensitive to each type of error.

The paper introduces a new protocol called GE2REC to interactively map language and memory networks using MRI in healthy participants, showing robust activation of relevant brain regions.

This study uses intracerebral EEG recordings in humans to show that sustained high gamma activity in fronto-parietal cortex distinguishes free choice from instructed saccades during a delayed oculomotor decision task.

This study uses machine learning to identify spectral signatures in human brain activity that correlate with perceptual categorization of visual stimuli.

This study identifies acoustic contamination in neural recordings during speech and sound processing, showing it can artificially improve speech decoding performance.

The paper introduces a new computerized test, BLAST, to measure attention stability and provides normative data and cortical dynamics from EEG recordings.

The paper investigates the alignment between gamma band activity in the human visual cortex and feature transformations in deep convolutional neural networks (DCNNs) along the ventral visual pathway.