This program aims to promote interdisciplinary Neuro-AI research by supporting pilot projects at the crossroads between neuroscience AND artificial intelligence. The program also aims to foster the creation of new synergies within the UNIQUE community, and to increase the success rate of its researchers when applying for funding from major granting agencies.

The budget available for this program will enable 7 projects to be funded, up to a maximum of $40,000 per project, for one year. Two of the 7 projects will be financed under the UNIQUE-STRATEGIA  subprogram (see details in the Eligibility criteria section). These funds are non-renewable.

For more information on the eligibility criteria , the application and evaluation procedures, please refer to the program description and application form above. 

Funded projects
2025-2026 Competition

Active, embodied visual learning in humans and ANNs using virtual reality
Principal investigator: Shahab Bakhtiari, Université de Montréal
Co-aplicants: Christopher Pack (McGill University), Blake Richards (McGill University)

Developing Personalized Encoding Models of fMRI data for Psychotic Disorders via Transfer Learning
Principal investigator: Lune Bellec, Université de Montréal
Co-aplicants: Pouya Bashivan (McGill University), Ian Charest (Université de Montréal), Vincent Taschereau-Dumouchel (Université de Montréal)

Unsupervised Inference of Functional Brain States and Transition Mechanisms in Zebrafish
Principal investigator: Paul DeKoninck, Université Laval
Co-aplicants: Patrick Desrosiers (Université Laval), Bratislav Misic (McGill University)

Vers une Neuro-IA Quantique? Évaluation des algorithmes de simulation et d’apprentissage machine quantiques pour la simulation et l’analyse du cerveau
Principal investigator: Dumas, Guillaume, Université de Montréal
Co-aplicants: Benjamin De Leener (Polytechnique), Karim Jerbi (Université de Montréal), Irina Rish (Université de Montréal)
Collaborator: Annemarie Wolff (Université de Montréal)

Arbitrating between timescales in biological and computational reinforcement learning
Principal investigator: Paul Masset, McGill University
Co-aplicants: Matthew G. Perich (Université de Montréal), Doina Precup (McGill University)

Modeling and calibrating the causal functional connections between cortical layers using laminar-resolved neurophysiology and machine learning
Principal investigator: Amir Shmuel, McGill University
Co-aplicants: Habib Benali (Université Concordia) Paul Masset (McGill University)

Closing the Loop: Causal Modulation of Perception with AI-Guided Brain Stimulation
Principal investigator: Vincent Taschereau-Dumouchel, Université de Montréal
Co-aplicants: Marco Bonizzato (Polytechnique), Ian Charest (Université de Montréal), Frédéric Gosselin (Université de Montréal)
Collaborator: Charles Dupras (Université de Montréal)