Florent Meyniel

发表

Confidence as Bayesian Probability: From Neural Origins to Behavior

M. Sigman, Z. Mainen, Florent Meyniel, 2015, Neuron.

Neurocomputational account of how the human brain decides when to have a break

J. Daunizeau, M. Pessiglione, C. Sergent, 2013, Proceedings of the National Academy of Sciences.

Behavioural and neural characterization of optimistic reinforcement learning

M. Lebreton, Florent Meyniel, G. Lefebvre, 2017, Nature Human Behaviour.

Biases and Variability from Costly Bayesian Inference

Florent Meyniel, Rava Azeredo da Silveira, Misha Tsodyks, 2021, Entropy.

Brain dynamics for confidence-weighted learning

Florent Meyniel, 2020, PLoS computational biology.

S. Dehaene, L. Cohen, M. Baulac, 2015, Cerebral cortex.

Fast and Automatic Activation of an Abstract Representation of Money in the Human Ventral Visual Pathway

C. Tallon-Baudry, Florent Meyniel, S. Bourgeois-Gironde, 2011, PloS one.

Variability in prior expectations explains biases in confidence reports

M. Sigman, Florent Meyniel, Pablo Tano, 2017, bioRxiv.

Brain networks for confidence weighting and hierarchical inference during probabilistic learning

S. Dehaene, Florent Meyniel, 2017, Proceedings of the National Academy of Sciences.

A specific role for serotonin in overcoming effort cost

M. Pessiglione, G. Goodwin, R. Gaillard, 2016, eLife.

How the human brain allocates physical effort over time : evidence from behavior, neuroimaging and pharmacology

Florent Meyniel, 2013 .

Rational arbitration between statistics and rules in human sequence processing.

S. Dehaene, Florent Meyniel, Maxime Maheu, 2022, Nature human behaviour.

Resource-rational account of sequential effects in human prediction

Florent Meyniel, Arthur Prat-Carrabin, R. A. da Silveira, 2023, bioRxiv.

Brainstem fMRI signaling of surprise across different types of deviant stimuli

T. Donner, Florent Meyniel, A. Amadon, 2022, bioRxiv.

A characterization of the neural representation of confidence during probabilistic learning

E. Eger, Florent Meyniel, Tiffany Bounmy, 2022, NeuroImage.

Studying the neural representations of uncertainty

Rachel N. Denison, Edgar Y. Walker, W. Ma, 2022, 2202.04324.

Studying the neural representations of uncertainty

Rachel N. Denison, Edgar Y. Walker, W. Ma, 2022, 2202.04324.

Gated recurrence enables simple and accurate sequence prediction in stochastic, changing, and structured environments

Florent Meyniel, Cedric Foucault, 2021, bioRxiv.

The Sense of Confidence during Probabilistic Learning: A Normative Account

Florent Meyniel, Stanislas Dehaene, Daniel Schlunegger, 2015, PLoS Comput. Biol..

Large-scale dynamics of perceptual decision information across human cortex

Florent Meyniel, Niklas Wilming, Peter R Murphy, 2020, Nature Communications.

Disentangling Decision-related Feedforward and Feedback Signals in Human Cortex

Florent Meyniel, Niklas Wilming, Peter R Murphy, 2020 .

A theory of memory for binary sequences: Evidence for a mental compression algorithm in humans

M. Sigman, S. Dehaene, Florent Meyniel, 2021, PLoS Comput. Biol..

Brain signatures of a multiscale process of sequence learning in humans

Florent Meyniel, Stanislas Dehaene, Maxime Maheu, 2019, eLife.

The Neural Representation of Sequences: From Transition Probabilities to Algebraic Patterns and Linguistic Trees

Florent Meyniel, Liping Wang, Stanislas Dehaene, 2015, Neuron.

Rational arbitration between statistics and rules in human sequence processing

Florent Meyniel, Stanislas Dehaene, Maxime Maheu, 2020, Nature Human Behaviour.

Bifurcation in brain dynamics reveals a signature of conscious processing independent of report

D. Pressnitzer, J. King, C. Sergent, 2021, Nature Communications.

On-line confidence monitoring during decision making

Florent Meyniel, Stanislas Dehaene, Dror Dotan, 2018, Cognition.

How the Brain Decides When to Work and When to Rest: Dissociation of Implicit-Reactive from Explicit-Predictive Computational Processes

Florent Meyniel, Lou Safra, Mathias Pessiglione, 2014, PLoS Comput. Biol..

Brain dynamics for confidence-weighted learning

Florent Meyniel, Florent Meyniel, 2019, bioRxiv.

Confidence resets reveal hierarchical adaptive learning in humans

Florent Meyniel, Micha Heilbron, Florent Meyniel, 2019, PLoS Comput. Biol..

Better Get Back to Work: A Role for Motor Beta Desynchronization in Incentive Motivation

Florent Meyniel, Mathias Pessiglione, M. Pessiglione, 2014, The Journal of Neuroscience.

Human Inferences about Sequences: A Minimal Transition Probability Model

Florent Meyniel, Stanislas Dehaene, Maxime Maheu, 2016, bioRxiv.

Coupling of Motor Cortical Areas Movement Rate Effect on Activation and Functional

Jessica A. Grahn, K. Linkenkaer-Hansen, W. Fitch, 2015 .

Brainstem fMRI signaling of surprise across different types of deviant stimuli

T. Donner, Florent Meyniel, A. Amadon, 2023, bioRxiv.

Comparison of SMS-EPI and 3D-EPI at 7T in an fMRI localizer study with matched spatiotemporal resolution and homogenized excitation profiles

Florent Meyniel, Stanislas Dehaene, Alexandre Vignaud, 2019, PloS one.

Rational arbitration between statistics 2 and rules in human sequence learning

S. Dehaene, Florent Meyniel, M. Maheu, 2020 .

Subjective confidence reveals the hierarchical nature of learning under uncertainty

Florent Meyniel, Micha Heilbron, Florent Meyniel, 2018, bioRxiv.

Optimistic reinforcement learning: computational and neural bases

M. Lebreton, Florent Meyniel, G. Lefebvre, 2016, bioRxiv.

Let's have a break: Neural substrates of effort management COGMASTER, M2 THESIS, UNDER THE SUPERVISION OF MATHIAS PESSIGLIONE, ICM, PARIS

Florent Meyniel, Florent Meyniel, 2010 .

Brain signatures of a multiscale process of sequence learning in humans

S. Dehaene, Florent Meyniel, M. Maheu, 2019, eLife.

A dissociation between the use of implicit and explicit priors in perceptual inference

Florent Meyniel, Caroline Bévalot, 2023, bioRxiv.

Asymmetric reinforcement learning: computational and neural bases of positive life orientation

M. Lebreton, Florent Meyniel, G. Lefebvre, 2016 .

Studying the neural representations of uncertainty.

Rachel N. Denison, Edgar Y. Walker, W. Ma, 2022, Nature neuroscience.

On-line confidence monitoring during decision making

S. Dehaene, Florent Meyniel, Dror Dotan, 2018, Cognition.

Optimistic reinforcement learning: computational and neural bases

M. Lebreton, Florent Meyniel, G. Lefebvre, 2016, bioRxiv.

Two determinants of dynamic adaptive learning for magnitudes and probabilities

Florent Meyniel, Cedric Foucault, 2023, bioRxiv.

A nonlinear code for event probability in the human brain

Florent Meyniel, Tiffany Bounmy, Cedric Foucault, 2024, bioRxiv.

Multiple and subject-specific roles of uncertainty in reward-guided decision-making

Florent Meyniel, Dalin Guo, Zoe He, 2024, bioRxiv.