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Dr. Romain Brasselet (Research Engineer Sorbonne University)
CNRS – INSERM – Sorbonne University
17, rue Moreau F-75012 Paris, France email:
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Research statement: As a mathematical neuroscientist, I am in general interested in applying statistical and mathematical methods to various fields of neuroscience and psychology (as well as other fields, opportunity pending). I nod thoughtfully at John Tukey’s famous quote: “the best thing about being a statistician is that you get to play in everyone’s backyard”. A former advisor of mine wrote that I try to teach that particular branch of statistics called How-Psychology-and-Neuroscience-Mistreat-Statistics. He might be onto something. When I am not nurturing/torturing my colleagues with stats, I dedicate myself to various topics in neuroscience. I currently work on the cohort data recorded at the AVA. One of my primary goals is to try to find the underlying dimensionality of the manifold the data lives on, using cutting-edge dimensionality reduction techniques. This would provide insight the deeper structure of the data and allow me to carry further statistical techniques to understand how the various measurements interact with each other. I am also, among others, interested in spatio-temporal neural coding, or how populations of neurons manage to encode temporally-resolved signals. More precisely, I try to understand how the mathematical relations betweens neural signals can map relations between external stimulations, and how these relations are altered or preserved as the signals are hierarchically processed. I also study complex networks. On a technical side, I make an extensive use of information theory and machine learning techniques. I give lectures on these topics as well as on statistical inference.
Short-bio: After a degree in Theoretical Physics from University Aix-Marseille 2, I obtained a PhD in Computational Neuroscience from Université Pierre et Marie Curie (under the supervision of Angelo Arleo). I proceeded with postdocs at the Max-Planck-Institute for Biological Cybernetics in Tübingen (with Christoph Kayser and Stefano Panzeri), and Universitat Pompeu Fabra in Barcelona (with Gustavo Deco). I was then awarded the Excellence Grant at SISSA (working with Mathew Diamond, Alessandro Treves, Valentina Parma and others) and continued working there in the Language, Learning and Reading Lab (with Davide Crepaldi) and the Time Perception Lab (with Domenica Bueti). I joined the Aging in Vision and Action team in January 2022. This is the least tortuous and convoluted way I found to get back to the starting place.
Keywords: statistics, information theory, mixed-effect models, modeling, neural coding, complex networks.
CV and Publication List (pdf): [ download ]
Publications
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2011
- (2011) Isometric coding of spiking haptic signals by peripheral somatosensory neurons. In Cabestany, J. et al., editors, LNCS - Advances on Computational Intelligence, vol. 6691, pages 528-536, Springer.
2010
- (2010) Local metrical information: application to the perceptual magnet effect. In Gervais, R. et al., editors, Proceedings of the Fifth french conference on computational neuroscience (Neurocomp), pages 132-136.
- (2010) Effective encoding/decoding of spiking signals from an artificial touch sensor. In Gervais, R. et al., editors, Proceedings of the Fifth french conference on computational neuroscience (Neurocomp), pages 120-125.
- (2010) Neuromimetic encoding/decoding of spatiotemporal spiking from an artificial touch sensor. In Proceedings of the International Joint Conference on Neural Networks (IJCNN) (in press).
2009
- (2009) Optimal context separation of spiking haptic signals by second-order somatosensory neurons. In Bengio, Y. et al., editors, Advances in Neural Information Processing Systems 22, vol. 22, pages 180-188.