BraiNets is a research team in computational neuroscience working at the interface between system/cognitive neuroscience and artificial intelligence. Our vision is that computational neuroscience will lead to ground-breaking applications by formalising how brain functions emerge from the interaction between neural populations and brain networks. The BraiNets team exploits most advanced theoretical approaches and computational tools from artificial intelligence and statistics to study how brain interactions support neural computations underlying cognitive functions.
The main research axes of BraiNets are:
- Brain interactions and neurocomputational bases of goal-directed learning (A Brovelli)
- Machine learning and artificial intelligence aplied to computational neuroscience (E Daucé)
- Whole-brain anatomo-functional modelling of healthy and pathological brain networks (M Gilson)
- Brain networks for auditory perception (B Giordano)