BMC Neuroscience 2020: 29th Annual Computational Neuroscience Meeting: CNS*2020 - Studying neural mechanisms in recurrent neural network trained for multitasking depending on a context signal.

Congreso

Summary *

Most biological brains, as well as artificial neural networks, are capable of performing multiple tasks **[1].** The mechanisms through which simultaneous tasks are performed by the same set of units are not yet entirely clear. Such systems can be modular or mixed selective through some variable such as sensory stimulus **[2,3]**. Based on simple tasks studied in our previous work **[4]** , where tasks consist of the processing of temporal stimuli, we build and analyze a simple model that can perform multiple tasks using a contextual signal. We study various properties of our trained recurrent networks, as well as the response of the network to the damage done in connectivity. In this way, we are trying to illuminate those mechanisms similar to those that could occur in biological brains associated withmultiple tasks. Information provided by the agent in SIGEVA