ePoster · Computational Neuroscience
Synaptic modulation facilitates adaptation in cortical networks
Ivan Bulygin, James Ferguson, Nicoleta Condruz, Tim Vogels · Bernstein Conference 2024
The human brain quickly adapts to a changing environment, often faster than can be explained by synaptic plasticity. One of the main candidates to account for such rapid changes is neuromodulation. We explore how modulation can assist a recurrent neural network to accommodate a range of variations of the tasks it is initially trained on. There are a number of approaches allowing for rapid acquisition of new tasks, for example, the neuronal gain modulation model [1]. However, we found that by affecting the input-output function of a neuron such an approach can neither address the variation of a