We are a NeuroAI laboratory in the Department of Psychology at the Université de Montréal.

We aim to understand the algorithmic and neuronal principles underlying animals' visual processing and learning. By leveraging these principles, we aspire to develop more brain-like artificial intelligence.

Our Approach

We use a multi-faceted approach, leveraging various data sources and methodologies:

• Neuronal and Behavioral data from different species (via collaborations and publicly available data)

• Physics engines (simulating different species' ecological environment)

• Artificial Neural Networks and Deep learning

Our Objectives

• Discover the computational principles underlying learning and development in the visual system

• Develop brain-like, life-long learning algorithms for AI that can continuously improve and adapt, similar to how the brain learns over time.

• Train the next generation of NeuroAI scientists who will bridge the gap between AI and systems neuroscience.

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