Sylvain Baillet's lab contributes advances to understand human brain activity: from milliseconds to the life span.
Our broad objective is to comprehend the mechanisms of large-scale brain rhythms (a.k.a. oscillatory neural dynamics): how they enable functions and behavior by shaping communication in brain networks, and how the earliest detection of their alterations in disease can contribute to improved healthcare prevention and interventions. To achieve this goal, our group has strong expertise in imaging methods and experimental neuroscience, complemented with collaborations in computational and disease models, neuromodulation techniques, and translational arms to the clinic and industry.
Our rationale is that so far, the ubiquitous polyrhythmic activity of the brain has been approached empirically, with underlying mechanisms that remain not understood. This hinders our comprehension of how 1) perception, behavior and consciousness emerge from distributed brain network activity, and 2) the pathophysiology of brain and mental-health disorders affect large-scale neural communication.
Our vision is that these difficult questions require a principled, mechanistic approach: We need to understand how basic physiological factors of neural integrity and function shape the dynamical structure of oscillatory brain rhythms, manifesting interdependence and coupling across multiple frequencies. These phenomena represent a deep source of uncharted markers of neural integrity, excitability, activity and connectivity.
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Read more about our latest research just published in Nature Neuroscience, Neuron and PNAS.
To address our scientific questions, we develop innovative approaches in structural and time-resolved functional neuroimaging. Our preferred technique is electromagnetic imaging with MEG, complemented with other modalities such as magnetic resonance imaging (MRI), basic electrophysiology and neurostimulation techniques.
Our network of collaborators brings together multidisciplinary expertise in: computational models in biology (François, McGill Physics), rodent e-phys (Avoli, de Villers-Sidani, MNI; Williams, Douglas), congenital amusia (Peretz, U of Montreal), epilepsy (Dudley, Montreal Children's Hospital), Alzheimer disease (Breitner, Gauthier, Rosa-Neto, Villeneuve, Williams, McGill/Douglas Institute; Dang-Vu, Concordia University), auditory perception and cognition (Zatorre, MNI), autism & schizophrenia (Jacquemont, U of Montreal; Forgeot d'Arc, Rivière-des-Prairies), ADHD (Brisebois, Szabo; College Montmorency), motor & decision systems (Kalaska, U of Montreal), nanoprobes (Kinsella, McGill/Bioengineering), multimodal imaging (Boudrias, Hoge, Mitsis, McGill), software developments (Leahy, USC; Mosher, U Texas; Hämälainen, Harvard Medical School).
Our lab also provides continuous support and expertise to investigators interested in using MEG for their cognitive and clinical neuroscience research. The MEG core unit at McGill’s Montreal Neurological Institute is part of the McConnell Brain Imaging Centre, and is an open platform for academic researchers and industrial partners.
We are funded by (inter)national public – including CIHR, NSERC, SSHRC, NIH, Brain Canada, Compute Canada, CFI – and private sources (gross total obtained: $30M; 21 presently active grants).
We are advocates of open science, as a vector of research productivity and reproducibility: in 2014-15, our group drove a Quebec Bioimaging Network strategic initiative for open data (the Open MEG Archive), and we host with RO1 NIH support since 2009, the international developments of Brainstorm, a widely used open-source software application for multimodal functional brain imaging (approaching 20,000 registered users).