Dr Lefebvre’s research lies at the interface of computational and mathematical neuroscience, addressing questions that relate to nonlinear dynamics and biomathematics. His lab develops and analyzes models of neural circuits to better understand the brain, and the dynamics of neurodegenerative diseases. A significant part of his work has been devoted to the characterization of synchronous dynamics in recurrent neural networks, and to the investigation of driven nonlinear systems. He also works in close collaborations with clinicians and experimentalists.
Modeling gene-environment interactions in longitudinal family studies: a comparison of methods and their application to the association between the IGF pathway and childhood obesity.
BMC Med Genet. 2019 Jan 11;20(1):9
Sorting of Semiconducting Single-Walled Carbon Nanotubes in Polar Solvents with an Amphiphilic Conjugated Polymer Provides General Guidelines for Enrichment.
ACS Nano. 2018 Jan 16;:
High-Purity Semiconducting Single-Walled Carbon Nanotubes: A Key Enabling Material in Emerging Electronics.
Acc Chem Res. 2017 Sep 13;:
Can proportional ventilation modes facilitate exercise in critically ill patients? A physiological cross-over study : Pressure support versus proportional ventilation during lower limb exercise in ventilated critically ill patients.
Ann Intensive Care. 2017 Dec;7(1):64
ACS Nano. 2016 Sep 21;
J Neurosci. 2016 May 11;36(19):5328-37
Neuroimage. 2016 Apr 01;129:335-44
A Comparison of Statistical Methods for the Discovery of Genetic Risk Factors Using Longitudinal Family Study Designs.
Front Immunol. 2015;6:589
A hybrid enrichment process combining conjugated polymer extraction and silica gel adsorption for high purity semiconducting single-walled carbon nanotubes (SWCNT).
Nanoscale. 2015 Oct 14;7(38):15741-7
BMC Bioinformatics. 2015;16:160
Scientist, Krembil Research Institute (Krembil)
Assistant Professor, Department of Mathematics, University of Toronto