Florent is the team leader. He has been a CEA researcher since 2016 with a joint appointment at the GHU in 2023. He was trained as a biologist and then cognitive neuroscientist at ENS Paris. He specialized in human functional brain imaging and obtained his PhD at the Paris Brain institute in 2013. He started developing an interest for computational approaches, notably Bayesian inference, during a postdoc at Neurospin.

I’m interested in how the brain supports flexible and adaptive behavior in changing and uncertain environments. More specifically, I currently focus on the study of how the human brain identifies the most adaptive behavioral strategy, sets the balance between exploiting and actively exploring its environment, while monitoring its alternatives.

To tackle these issues, I use tools from computational neurosciences and machine learning, combined with neurophysiological/imaging recordings (MRI, EEG/MEG, intracranial EEG) of human brain activity while it’s engaged in dynamically controlling decision-making processes. We are currently developing ML-augmented voltammetric recordings in humans with the overarching goal to clarify the computational role of key monoamines in the algorithmic models we developed to account for strategic inference.

I trained as a biologist at ENS Lyon, then defended in 2011 a PhD in computational cognitive neuroscience at ISC Marc Jannerod focusing on models of perceptual decision-making and how it applied to the field of neuroeconomy. I became interested in coupling algorithmic models of choices with intracranial recordings in humans during my postdoc at ENS (DEC-LNC2). From 2014 to 2022, I continued and developed this line of research at ICM. Since 2022, I have been the medical and scientific director of the neuromodulation institute. As a psychiatrist specializing in treatment-resistant OCD/depression and neuromodulation, I’m also interested in using the same approach to study the computational underpinning of neuropsychiatric diseases.

I have a background in computer science, a degree I pursued in Braga (U. Minho, Portugal) and in Amsterdam (UvA, Netherlands). This was later combined with a masters in bioinformatics in Bologna (UNIBO, Italy). During my masters I got fascinated by neurobiology and, after a gap year traveling through Central America, I decided to pursue a PhD in computational neuroscience. Under the supervision of Albert Compte (UB, Spain), I got interested in biophysical models of working memory bridging data across all scales (synaptic dynamics, spiking activity, EEG and behavior). During my postdoc under the supervision of Srdjan Ostojic (ENS, Paris) I shifted my interest towards flexible decision-making, and in particular how this cognitive feat engages a distributed network of interacting brain regions. I tackled these questions using normative and data-driven recurrent neural network models.

I have joined the team in the summer of 2024.

I study how people represent and manipulate abstract mental objects and their structures in geometry, numbers, language and sequences. I want to build models of these abilities that make specific predictions about neural activity. A guiding idea is the Language of Thought hypothesis: that a small set of mental operations can be combined to generate an open-ended range of structured representations, much as grammatical rules let us form new sentences from few words. I approach this from two ends: top-down, designing behavioural and neuroimaging experiments to test what these operations are and how we combine them, and bottom-up, using neural recordings and mechanistic analyses of neural networks to understand how they could be implemented in the brain. I trained in computer science before moving into cognitive and computational neuroscience. I like thinking about theories, building models, programming experiments and analysing data. I work with symbolic, neural network and neurosymbolic models, and with behavioural, neuroimaging and electrophysiological data. I received funding from the FYSSEN Foundation for my postdoc and an ANR grant to join the team.

I am a psychiatrist and neuroscientist specialized in the study of consciousness and its alterations in psychiatric disorders or by the use of substances. After completing my PhD in 2018 under the supervision of Professors Stanislas Dehaene and Raphaël Gaillard (Neurospin Unicog), I worked at Hospitalo-Universitary department of Sainte Anne Hospital in Paris as the head of a unit for patients with treatment-resistant psychiatric disorders and did a postdoctorate at Yale University in the Anticevic Lab. Currently, I lead research on psychedelics at the Institut de Neuromodulation and serve as the principal investigator of France’s first psilocybin trial for depression. I also co-founded the Psychedelic Medicine section of AFPBN. I joined the Computational Brain team in the summer of 2024.

I am a research engineer dedicated to electrophysiology at the INM and in the computational brain team since 2024. I obtained a phd in cognitive neuroscience at the Paris Brain institute, during which I worked with patients treated with deep brain stimulation. I then worked in different labs in France and abroad (Salzman lab, Columbia University, NYC; Tallon-Baudry’s team, LNC2, ENS, Paris; Burguière team, ICM, Paris), in which I acquired additional experience in recording signals from the peripheral nervous system, from the scalp (such as MEG and EEG) and from intracranial electrodes. I have a strong interest in “listening” to healthy and diseased brains and bodies using electrophysiology, and assisting researchers and clinicians with experiment setup and data analysis.

I’m a research engineer at the NeuroModulation Institute, focusing on MRI and fMRI methodologies for both clinical and fundamental research. In 2024, I joined the Computational Brain Team, following my Ph.D. at NeuroSpin/CEA Saclay, where I specialized in non-Cartesian fMRI methods. With a strong passion for advancing MRI and fMRI techniques, I aim to bridge methodological developments with meaningful applications in cognitive neuroscience and clinical practice. 

 I’m a psychiatrist and researcher, currently working in the University Hospital department of Sainte Anne Hospital in Paris. I obtained a PhD in cognitive neuroscience under the co-supervision of Philippe Domenech and Mehdi Khamassi (ISIR), on adaptive behavior in uncertain and changing environments. I am mainly interested in inference processes under uncertainty in healthy subjects as well as in patients with psychiatric pathologies. My approach combines experimental psychology, computational modeling and Bayesian statistics. 

I am a postdoctoral researcher with a background in psychophysiology. I earned my PhD from the University of Brighton in 2022, where I studied the behavioral and neurophysiological causes and consequences of the acute subjective experience of fatigue. During my PhD, I developed research interests that include body-brain interactions, particularly interoceptive (predictive) inference and its links to perception and emotion. In 2024, I joined the Computational Brain Team. In my current role, I investigate how noradrenaline influences adjustments in evidence weighting during probabilistic learning within dynamically changing environments. I hold a strong interest in Bayesian inference as a computational framework for understanding various conditions across both health and disease.

I have a background in Psychology and obtained a PhD in cognitive neuroscience at the University of Potsdam (Germany) in 2024, where I mainly used EEG to look at prediction (-errors) and implicit learning in language comprehension. After developing an interest in computational approaches and the intricacies of (probabilistic) learning, I joined the Computational Brain Team to work on learning under uncertainty. Currently, my work is focused on the neuromodulation, domain generality of uncertainty, and perceptual decision making.

I have a background in Physics and completed a PhD in Behavioral Neuroscience at “Sapienza” University of Rome. During my PhD, I used recurrent neural networks to model serial learning tasks and analyzed intracortical recordings from non-human primates during decision-making. I joined the team in March 2025 to investigate how the brain represents uncertainty during learning and decision-making. More broadly, I am interested in how the representational structure of task variables evolves during learning and how internal world models shape individual decision strategies.

I am a psychologist with a PhD in Neuroscience from the University of Florence and a Master’s in Neuropsychological Rehabilitation from the University of Bologna. My PhD research focused on neurophysiological markers of psychiatric disorders, combining EEG and non-invasive brain stimulation techniques (TMS, tACS). I conducted my research at the Siena Brain Investigation and Neuromodulation Lab and the Plasticity Lab at CUNY School of Medicine. I joined the team in April 2025 to work with Philippe Domenech on detecting auditory-verbal hallucinations (AVHs) in schizophrenia using MEG.

I hold a Bachelor's and Master's degree in Bioengineering from the University of Porto. During my studies, I interned at the Champalimaud Foundation, where I became interested in the neurobiological underpinnings of repetitive behaviours in psychiatric conditions. I then pursued a PhD in Neuroscience at Sorbonne University, conducting my research at the Paris Brain Institute. My work focused on understanding pathological repetitive behaviours—such as compulsions and tics—particularly in the context of obsessive-compulsive disorder (OCD), with a strong emphasis on learning mechanisms. After completing my PhD, I undertook additional training in data science and artificial intelligence. I joined the INM and the Computational Brain Team in 2025 as a postdoctoral researcher, where I am currently investigating the role of monoamines in OCD.

I am a postdoctoral researcher who joined the Computational Brain Team in 2026, after obtaining my PhD in Cognitive Science at Sorbonne Université the same year. My PhD focused on computational models of information-seeking and change detection using reinforcement learning, with applications in robotics and modeling of human behavior. Before this PhD, I studied cognitive science, mathematics, and physics. My research interests broadly comprise the development of computational models to explain human behavior and its associated neural mechanisms in uncertain or volatile tasks.

I am a child psychiatrist by training and currently a research psychiatrist at Inserm (Inserm hosting position) for a three-year period to pursue a PhD in computational psychiatry under the supervision of Professor Philippe Domenech and Valentin Wyart. I am expected to take up a position as a clinical chief assistant (CCA) at the GHU of Sainte-Anne in 2026. In my free time, I enjoy sports and run a small YouTube channel where I share insights on psychiatry and (occasionally) cognitive science

I am a PhD student at GHU Paris and the Learning Planet Institute, with an interdisciplinary background in neuroscience, physics, and science communication. My previous work includes contributions to projects on decision-making, episodic inference modeling, and reinforcement learning. My current PhD research focuses on understanding the neural mechanisms underlying cognitive flexibility, particularly in schizophrenia, through computational models and cross-species studies. I am eager to contribute to impactful research that advances both scientific understanding and therapeutic approaches. In addition to my research, I am dedicated to science communication, working to make complex scientific concepts accessible to the public through outreach and educational initiatives that promote scientific literacy.

I am a second-year PhD student in the computational brain team (INM) and with the MIND team at INRIA Saclay, France. My research focuses on enhancing fMRI functional alignment techniques to improve brain decoding performance, leveraging machine learning models and optimal transport methods. Prior to this, I completed a Master’s degree in applied mathematics at Université Paris-Saclay, a Master’s degree in computer science at Sorbonne Université, and an engineering degree in statistics and economics at ENSAE Paris, France.

I am currently pursuing a PhD under the supervision of Professor Domenech, focusing on decision-making in uncertain and volatile environments. My research is conducted in the context of patients implanted with stereo-electroencephalography (sEEG) electrodes as part of treatment for drug-resistant epilepsy. This work integrates behavioural modelling, brain dynamics, and circuit-level analysis. Broadly, my research aims to elucidate the mechanisms by which the human brain integrates and transforms information to produce behaviour. I am particularly interested in the multiscale organisation and interaction of neural systems, from cellular processes to algorithmic computations, that underpin cognitive function.

I am a PhD student at Université Paris-Saclay, supervised by Lucie Berkovitch and Florent Meyniel in the Computational Brain Team. I come from a background of Psychology (Bristol, UK) and Neurosciences (Dual Masters UCL/ENS/Sorbonne). My research focuses on the neurobehavioural mechanisms underlying the psychedelic, psychotomimetic, and antidepressant effects of psychedelics. In particular, I am interested in how psychedelics may alter the way predictions shape perception. Ultimately, our goal is to shed light on the neurobehavioural mechanisms underlying psychedelics’ action to better understand their antidepressant effects and to shed light on models of psychosis.

I'm a computer scientist with background in AI and signal processing, but I am particularly interested in working with neural data and for neuroscience applications. I am currently a CIFRE PhD student with Joao Barbosa and YNeuro, working with simultaneous EEG and fMRI data and foundation models for aligning and distilling from different modalities.

I am a PhD student under the supervision of Joao Barbosa and Srdjan Ostojic. My research focuses on understanding how interactions between brain regions support decision-making, and more broadly, how networks of relatively simple neurons give rise to complex computations and behaviors.ith a background in physics and strong interest in human cognition. Currently I am working as a research engineer with Joao Barbosa, training RNNs to reproduce brain dynamics to gain insight into how different brain areas contribute to decision making.

I am a PhD student supervised by Florent Meyniel and Zaineb Amor. I have a background in cognitive and computational neuroscience (Dual MSc in Brain and Mind Sciences UCL/Sorbonne/ENS). My research focuses on understanding the mechanisms underlying learning and decision-making under uncertainty. I combine computational modeling with high-precision fMRI to identify and characterize latent strategies in decision-making, with a particular focus on single-trial dynamics and inter-individual differences.

I am a research engineer at the INM and a member of the Computational Brain Team, which I returned to in September 2026 after completing my Master's in Biomedical Engineering at PSL/ESPCI Paris, specialising in digital mental health and neuromodulation for treatment-resistant psychiatric disorders. My path to the INM started during my M1, where I worked on intracranial EEG biomarker detection in OCD patients to inform closed-loop DBS approaches. My M2 then took me to the Brain Plasticity Laboratory at ESPCI, where I investigated location-dependent effects of medial forebrain bundle DBS in a mouse model, in collaboration with Philippe Domenech and the INM, to derive translational insights for treatment-resistant depression. At the INM, I am developing a generalised iEEG preprocessing pipeline with a focus on epilepsy recordings, and contributing to ongoing projects in the lab.

I have a background in neuroscience and computer science (University of British Columbia, Canada) and am particularly interested in machine learning approaches for analyzing and modelling neural activity. As a research engineer with Joao Barbosa, I will be using recurrent neural networks to study how neuromodulation shapes neural dynamics.