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.