Neuro-Inspired Artificial Intelligence

Can insights from neural circuits bridge critical gaps in artificial intelligence?

We are developing neuro-AI approaches to integrate biologically-inspired confidence assessments into AI architectures, addressing limitations in current systems. By applying computational models to decode complex neural data and understand behavior, we aim to enhance AI systems with capabilities reflecting cognitive processes found in the brain.

Selected Publications

R-learning in actor-critic model offers a biologically relevant mechanism for sequential decision-making
Shuvaev, S., Starosta, S., Kvitsiani, D., Kepecs, A., & Koulakov, A.. Advances in neural information processing systems (2020) 33, 18872-18882