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Patrick Desrosiers

Ph.D. (doctor),  Regular member
Expertise
Neuroscience
Principal Interest
Optogenetics & sensory systems
Secondary Interest
Low back pain
Primary Affiliation

Université Laval

Secondary Affiliation
Centre de recherche CERVO (CERVO)

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Publications

Biography

After completing studies in physics (B.Sc., 1998) and theoretical physics (M.Sc., 2001; Ph.D., 2004) at Université Laval, Patrick Desrosiers pursued postdoctoral research in mathematics at The University of Melbourne (Australia, 2005–2006) and in mathematical physics at CEA-Saclay (France, 2006–2007). He later served as Associate Professor of Mathematics at Universidad de Talca (Chile) until 2013. Since 2014, he has been a Senior Scientist at the CERVO Brain Research Center and Adjunct Professor in the Department of Physics, Engineering Physics & Optics at Université Laval. He co-leads the Dynamica Research Lab, affiliated with CIMMUL, where he conducts multidisciplinary research at the intersection of physics, mathematics, neuroscience, and machine learning. A member of the UNIQUE and IVADO networks, his work focuses on the resilience of neuronal networks, the influence of brain geometry on activity dynamics, and modeling chronic pain factors to identify targets for intervention.

ORCID: https://orcid.org/0000-0001-7528-697X
Google Scholar: https://scholar.google.ca/citations?user=YAqE0O0AAAAJ&hl=en
Semantic Scholar: https://www.semanticscholar.org/author/Patrick-Desrosiers/2096311

What excites you most about your research program or field?
What I find the most exciting is seeing how the tools of mathematics and physics can shed light on the complexity of living organisms. By applying dynamic systems theory, network theory, and artificial intelligence to neuroscience, we can reveal hidden patterns within systems as vast as the neural networks of the brain and spinal cord. In the context of pain, this approach helps us investigate how interactions between different structures of the nervous system, as well as between biological, psychological, and social factors, shape the perception and persistence of pain. It paves the way for identifying key determinants that can guide more targeted and personalized interventions.