Input-driven circuit reconfiguration in critical recurrent neural networks.

ABSTRACT: Changing a circuit dynamically, without actually changing the hardware itself, is called reconfiguration, and is of great importance due to its manifold technological applications. Circuit reconfiguration appears to be a feature of the cerebral cortex, so understanding the dynamical principles underlying self-reconfiguration may prove of import to elucidate brain function. We present a very simple example of dynamical reconfiguration: a family of networks whose signal pathways can be switched on the fly, only through use of their inputs, with no changes to their synaptic weights. These are single-layer convolutional recurrent network with local unitary synaptic weights and a smooth sigmoidal activation function. We generate traveling waves using the high spatiotemporal frequencies of the i

SUBMITTER: Magnasco MO 

PROVIDER: S-EPMC11912373 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature