Steeve Laquitaine
EPFL BBP-CORE
Campus Biotech
Bâtiment B1
Ch. des Mines 9
1202 Genève
+41 21 693 73 08
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B1 5 284.045
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Web site: Site web: https://www.epfl.ch/research/domains/bluebrain/
Biographie
Steeve Laquitaine is a postdoctoral scientist for Connectomics within the Simulation Neuroscience Division. Steeve creates experimental and computational approaches and tools to explain how decision-making arises from human and animal neocortical synaptic connectivity.Before he joined the Blue Brain Project, he worked with Prof. Justin Gardner at Stanford University, where he used psychophysics, fMRI, and Bayesian modeling to link human visual choice with cortical activity. He found that a frugal heuristic model of motion direction and location estimation that does not integrate current sensory evidence with prior experience but switches between the two efficiently approximates Bayesian inference. The model also better accounted for human choice estimates than standard Bayesian models. Steeve studied Computational Neuroscience at the University of Bordeaux, France, where he obtained his PhD under the supervision of Prof. Thomas Boraud. He specialized in developing statistical approaches and reinforcement learning models to link rodents’ and monkeys’ choices with multi-unit multi-site sensorimotor spiking activity. He found that animal choices are not always motivated by reward but are sometimes entirely driven by contextual cues irrelevant to reward.
To understand how context shapes decision-making, he initiated a postdoc at the Riken Brain Science Institute in Japan, which he pursued at Stanford University. During his time at Riken and Stanford he honed his skills in machine learning and statistical decision modeling and acquired new skills in fMRI to link human decision-making, prior experience, and cortical activity. He then decided to spend a brief period in industry working as a Tech Lead / Lead Data Scientist where he perfected his machine learning engineering skills and learned tools to build reproducible and maintainable production software. As a lead instructor he also designed and taught courses on the best practices of machine learning engineering to teams of data scientists. He also pursued research as a visiting scholar at KU Leuven, where he continues to investigate efficient and adaptive self-organizing artificial neural networks in collaboration with Prof. Cees Van Leeuwen.
In his free time, Steeve likes to read, run, and go on road trips.
Formation
Ph.D
Computational Neurosciences
University of Bordeaux
2007-2010
M.S
Medical and Biological Sciences
University of Bordeaux
2005-2007
B.S
Biochemistry, Cell Biology and Physiology
University of Bordeaux
2002-2005
Récompenses
Stanford University Center for Cognitive and Neurobiological Imaging innovation grant
2014, 2015
Japan Society for the Promotion of Science fellowship (JSPS, I declined it)
2010
France Parkinson Doctoral Fellowship
2009-2010
Publications
Sélection de publications
Laquitaine S, Gardner J L. Neuron (2018) |
A switching observer for human perceptual estimation |
Laquitaine S., Piron C., Abellanas D., Loewenstein Y., Boraud T. PLoS ONE (2013) |
Complex population response of dorsal putamen neurons predicts the ability to learn |
Rentzeperis, I., Laquitaine, S., & van Leeuwen, C. Communications in Nonlinear Science and Numerical Simulation (2022) |
Adaptive rewiring of random neural networks generates convergent–divergent units |
Chetrit, J., Ballion, B., Laquitaine, S., Belujon, P., Morin, S., Taupignon, A., Bioulac B., Gros. C.E. & Benazzouz, A PLoS One (2009) |
Involvement of Basal Ganglia network in motor disabilities induced by typical antipsychotics |