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Jérémie Mattout

Affiliations: 
Universite Lyon 1, Villeurbanne, Auvergne-Rhône-Alpes, France 
Area:
Brain-computer interfaces (BCI), Electrophysiology, Perceptual decision-making, Contextual dependent learning, Adaptive design optimization, Hypothesis testing, Generative models, Cognitive neuroscience
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"Jérémie Mattout"
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Gaëtan Sanchez grad student 2014 Universite Lyon 1

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Sapey-Triomphe LA, Sanchez G, Hénaff MA, et al. (2023) Disentangling sensory precision and prior expectation of change in autism during tactile discrimination. Npj Science of Learning. 8: 54
Lecaignard F, Bertrand O, Caclin A, et al. (2021) Neurocomputational underpinnings of expected surprise. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience
Lecaignard F, Bertrand O, Caclin A, et al. (2020) Empirical Bayes evaluation of fused EEG-MEG source reconstruction: Application to auditory mismatch evoked responses. Neuroimage. 117468
Bonaiuto JJ, Afdideh F, Ferez M, et al. (2020) Estimates of cortical column orientation improve MEG source inversion. Neuroimage. 116862
Mladenovic J, Frey J, Joffily M, et al. (2019) Active inference as a unifying, generic and adaptive framework for a P300-based BCI. Journal of Neural Engineering
Medeiros de Freitas A, Sanchez G, Lecaignard F, et al. (2019) EEG artifact correction strategies for online trial-by-trial analysis. Journal of Neural Engineering
Batail JM, Bioulac S, Cabestaing F, et al. (2019) EEG neurofeedback research: A fertile ground for psychiatry? L'Encephale. 45: 245-255
Hincapié AS, Kujala J, Mattout J, et al. (2017) The impact of MEG source reconstruction method on source-space connectivity estimation: A comparison between minimum-norm solution and beamforming. Neuroimage
Sanchez G, Lecaignard F, Otman A, et al. (2016) Active SAmpling Protocol (ASAP) to Optimize Individual Neurocognitive Hypothesis Testing: A BCI-Inspired Dynamic Experimental Design. Frontiers in Human Neuroscience. 10: 347
Hincapié AS, Kujala J, Mattout J, et al. (2016) MEG Connectivity and Power Detections with Minimum Norm Estimates Require Different Regularization Parameters. Computational Intelligence and Neuroscience. 2016: 3979547
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