Topic: attentional mechanisms

Humans and animals can quickly adapt to new task demands while retaining previously-developed capabilities, but the neural mechanisms of such flexibility remain unclear. While neural computations are governed by synaptic interactions, adjusting the strength of all synapses to allow this behavioral adaptation would likely be slow and not easily reversible. Here we use intrinsic, structured gain fluctuations to rapidly and transiently fine-tune hierarchical neural networks for a particular task. This mechanism takes inspiration from well documented low-dimensional covariability in visual areas o