Steeve Laquitaine is a postdoctoral scientist in the Connectomics group within the Simulation Neuroscience Division.
At Blue Brain, Steeve creates experimental and computational approaches and tools to explain how decision-making arises from human and animal neocortical synaptic connectivity.
Before joining the Blue Brain Project, Steeve worked with Prof. Justin Gardner at Stanford University, where he used psychophysics, fMRI, and Bayesian modeling to link human visual choice with cortical activity.
Steeve studied Computational Neuroscience at the University of Bordeaux, France, where he obtained his Masters inMedical and Biological Sciences, and his PhD under the supervision of Prof. Thomas Boraud. He specialized in developing statistical approaches and reinforcement learning models to link animal choices with multi-unit multi-site sensorimotor spiking activity. He found that these are not always motivated by reward but are sometimes entirely driven by contextual cues. He pursued this research first at the Riken Brain Science Institute in Japan, then at Stanford University. During this time, 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 spent a brief period in industry working as a Lead Data Scientist where he perfected his machine learning engineering skills. 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.
Laquitaine, S., & Gardner, J. L. (2018). A switching observer for human perceptual estimation. Neuron, 97(2), 462-474.
Laquitaine, S., Piron, C., Abellanas, D., Loewenstein, Y., & Boraud, T. (2013). Complex population response of dorsal putamen neurons predicts the ability to learn. PLoS One, 8(11), e80683.
Rentzeperis, I., Laquitaine, S., & van Leeuwen,C. (2022). Adaptive rewiring of random neural networks generates convergent–divergent units. Communications in Nonlinear Science and Numerical Simulation, 107, 106135.
Chetrit, J., Ballion, B., Laquitaine, S., Belujon, P., Morin, S., Taupignon, A., … & Benazzouz, A. (2009). Involvement of Basal Ganglia network in motor disabilities induced by typical antipsychotics. PLoS One, 4(7), e6208.