Catherine Duclos, Ph.D.

Associate Professor of research (2022- )
Department of anesthesiology and pain medicine, Université de Montréal
catherine.duclos@umontreal.ca

Training

Postdoctoral fellowship in computational neurosciences computationnelles and consciousness (McGill University)
Ph.D. in biomedical sciences (Université de Montréal)

Research interests

To characterize the functional neural networks of different states of consciousness (e.g. anesthesia, sleep, coma, delirium, disorders of consciousness) and to understand how these networks can be modulated in order to improve the cognitive and functional health of patients in surgical and critical care.

Methodological approaches

Electroencephalography, functional connectivity, graph theory, pharmacological neuromodulation, closed-loop neuromodulation.

Fundings

International Anesthesia Research Society Mentored Research Award
Amount: 175 000 USD
Role: Principal investigator
Title: Using anesthesia to predict recovery from disorders of consciousness
Years: 2021-2023

CRSNG Découverte / NSERC Discovery
Amount: 195 000 CAD
Role: Principal investigator
Title: Developing neurocomputational tools for the prediction and modulation of consciousness
Years: 2022-2027

Healthy Brains for Healthy Lives Neuro Commercialization Grant – IGNITE
Amount: 50 000 CAD
Role: Co-principal investigator
Title: The Adaptive Reconfiguration Index: A Novel Tool for Prognosticating Recovery in Unresponsive Patients
Years: 2022

CRSNG Nouvelles Frontières Exploration / NSERC New Frontiers Exploration
Amount: 250 000 CAD
Role: Co-investigator
Title: Reconnecting the severely injured brain using an individually-tailored, non-invasive stimulation protocol targeting preserved brain networks
Years: 2022-2024

My team

Karine Lacourse, Ing., M.Sc.

Software Developer

David Lévesque, Ing.

Software Developer

Hanieh Barzegarzadeh, M.Sc.

Engineer

Guillermo Martinez-Villar

M.Sc. candidate

Charles Gervais

B.Sc. Candidate

Rosalie Girard-Pépin

B.Sc. candidate

Maya de Sulzer Wart

B.Sc. candidate

Selected publications

Duclos C, Mahdid Y, Nadin D, Maschke C, Rokos A, Abour C, Badawy M, Létourneau J, Owen AM, Plourde G, Moraes S. Brain’s response to anesthesia predicts recovery in coma and disorders of consciousness. American Journal of Respiratory and Critical Care Medicine. Accepted.

Duclos C, Maschke C, Mahdid Y, Berkun K, Castanheira JDS, Tarnal V, et al. Differential classification of states of consciousness using envelope- and phase-based functional connectivity. Neuroimage. 2021:118171.

Duclos C*, Nadin D*, Mahdid Y, Tarnal V, Picton P, Vanini G, Golmirzaie G, Janke E, Avidan MS, Kelz MB, Mashour GA, Blain-Moraes S. Brain network motifs are markers of loss and recovery of consciousness. Scientific Reports. 2021;11(1):3892.

Duclos C, Norton L, Laforge G, Frantz A, Maschke C, Badawy M, Letourneau J, Slessarev M, Gofton T, Debicki D, Owen AM, Blain-Moraes S. Protocol for the prognostication of consciousness recovery following a brain injury. Frontiers in Human Neuroscience. 2020;14:582125.

Nadin D, Duclos C, Mahdid Y, Rokos A, Badawy M, Letourneau J, Arbour C, Plourde G, Blain-Moraes S. Brain Network Motif and Hub Topology Predicts Emergence from Disorders of Consciousness. Neuroscience of Consciousness. 2020;2020(1):niaa017.

Duclos C, Dumont M, Paquet J, Blais H, Van der Maren S, Menon DK, Bernard F, Gosselin N. Sleep-wake disturbances in hospitalized patients with traumatic brain injury: association with brain trauma but not with an abnormal melatonin circadian rhythm. SLEEP. 2020;43(1):1-8. doi:10.1093/sleep/zsz191

Duclos C, Dumont M, Arbour C, Paquet J, Blais H, Menon DK, De Beaumont L, Bernard F, Gosselin N. Parallel recovery of consciousness and sleep in acute traumatic brain injury. Neurology. 2017;88(3):268-275.

Projects

Use of anesthesia to detect the potential for consciousness recovery in non-communicative patients

Development of prognostic markers of consciousness recovery following brain injury

Closed-loop stimulation of slow oscillations in anesthesia

Exploration of the criticality of neural networks in different states of consciousness