NeuroAI Lab

Brains and Artificial Intelligence (AI) both engage in computation. They share similarities and differences in their underlying mechanisms. These include features such as having multiple processing units and being heavily interconnected through learned weights derived from data. However, apart from these commonalities, AI and brains differ significantly in other aspects.

What lessons can we draw from these shared traits and unique characteristics that drive computational processes in brains and AI? What important scientific questions can be answered with AI-pioneering technologies to open the NeuroAI field?

The laboratory works where Artificial Intelligence meets Neuroscience to study principles of neural circuit function, including studies of malfunction during disease states. Our current focus is on understanding the biological mechanisms for cognitive behavior 'in-silico', and neural abnormalities manifesting in some neurological diseases, primarily associated with Alzheimer's. A key interest is in developing an algorithmic understanding of cognitive and memory processes, especially those related to spatiotemporal location.

Our tools are mainly related to modeling in Computational Neuroscience and Cognitive Robotics/AI. Still, the lab examines neuronal processes in the light of new neuroscientific discoveries. Additionally, some members possess expertise in Neural Data Science and machine learning within System Neuroscience, and have used techniques such as 2-photon imaging, optogenetics, and electrophysiology.

Our work has received support from IBRO (International), CONICET, and Programa Raices-MinCyT (Argentina).