Portrait of Karim Jerbi

Karim Jerbi

Associate Academic Member
Associate Professor, Université de Montréal, Department of Psychology
Research Topics
Computational Neuroscience
Data Mining
Dynamical Systems
Natural Language Processing

Biography

Karim Jerbi is a professor in the Department of Psychology at Université de Montréal. He holds the Canada Research Chair in Computational Neuroscience and Cognitive Neuroimaging, and is the director of UNIQUE (Unifying Neuroscience and Artificial Intelligence in Quebec). A member of the Royal Society of Canada’s College of New Scholars, Artists and Scientists, Jerbi obtained a PhD in cognitive neuroscience and brain imaging from the Pierre & Marie Curie University in Paris and a biomedical engineering degree from the University of Karlsruhe (Germany).

Jerbi’s research lies at the crossroads of cognitive, computational and clinical neuroscience. The goal of his research is to probe the role of large-scale brain dynamics in higher-order cognition and to investigate brain network alterations in the case of psychiatric and neurological disorders. The multidisciplinary research conducted in his laboratory combines magnetoencephalography (MEG), scalp- and intracranial electroencephalography (EEG) with advanced signal processing and data analytics, including machine learning. Ongoing projects in his lab use electrophysiological brain recordings to examine large-scale brain network dynamics in a range of cognitive processes (e.g., decision-making and creativity) and across different states of consciousness (resting wakefulness, sleep, dreaming, anesthesia, meditation and psychedelic states). Jerbi is also strongly committed to the promotion of social justice, equity, diversity and inclusion in academia, and he has a keen interest in the convergence between brain science, AI, creativity and art.

Current Students

Master's Research - Université de Montréal
Professional Master's - Université de Montréal

Publications

Good Scientific Practice in MEEG Research: Progress and Perspectives
Guiomar Niso
Laurens R. Krol
Etienne Combrisson
A.-Sophie Dubarry
Madison A. Elliott
Clément François
Yseult Héjja-Brichard
Sophie K. Herbst
Vanja Kovic
Katia Lehongre
Steven J. Luck
Manuel Mercier
John C. Mosher
Yuri G. Pavlov
Aina Puce
Antonio Schettino
Daniele Schön
Walter Sinnott-Armstrong
Bertille Somon … (see 6 more)
Anđela Šoškić
Suzy J. Styles
Roni Tibon
Martina G. Vilas
Marijn van Vliet
Maximilien Chaumon
Good scientific practice (GSP) refers to both explicit and implicit rules, recommendations, and guidelines that help scientists to produce w… (see more)ork that is of the highest quality at any given time, and to efficiently share that work with the community for further scrutiny or utilization. For experimental research using magneto- and electroencephalography (MEEG), GSP includes specific standards and guidelines for technical competence, which are periodically updated and adapted to new findings. However, GSP also needs to be regularly revisited in a broader light. At the LiveMEEG 2020 conference, a reflection on GSP was fostered that included explicitly documented guidelines and technical advances, but also emphasized intangible GSP: a general awareness of personal, organizational, and societal realities and how they can influence MEEG research. This article provides an extensive report on most of the LiveMEEG contributions and new literature, with the additional aim to synthesize ongoing cultural changes in GSP. It first covers GSP with respect to cognitive biases and logical fallacies, pre-registration as a tool to avoid those and other early pitfalls, and a number of resources to enable collaborative and reproducible research as a general approach to minimize misconceptions. Second, it covers GSP with respect to data acquisition, analysis, reporting, and sharing, including new tools and frameworks to support collaborative work. Finally, GSP is considered in light of ethical implications of MEEG research and the resulting responsibility that scientists have to engage with societal challenges. Considering among other things the benefits of peer review and open access at all stages, the need to coordinate larger international projects, the complexity of MEEG subject matter, and today’s prioritization of fairness, privacy, and the environment, we find that current GSP tends to favor collective and cooperative work, for both scientific and for societal reasons.