ePoster · Computational Neuroscience
Correcting cortical output: a distributed learning framework for motor adaptation
Leonardo Agueci, N Alex Cayco Gajic · Bernstein Conference 2024
Learning is fundamental for interacting with a changing environment. Critical to this process is the ability to rapidly adapt previously acquired skills to external perturbations while avoiding catastrophic forgetting of previous tasks. For the learning system, this corresponds to a trade-off between being able to maintain stable memories of learned tasks, and the ability to swiftly adapt such memories to changes. We hypothesize that such a problem can be addressed by using a two-timescale [1,2] strategy, where memorization and adaptation are performed by two separate modules. This structure a