Topic: common input

Cortical circuits exhibit complex activity patterns, both spontaneously and evoked by external stimuli. Information encoding and learning in neural circuits depend on how well time-varying stimuli can control network activity. We show that in firing-rate networks in the balanced state, external control of recurrent dynamics, i.e., the suppression of the internally-generated chaotic variability, strongly depends on correlations in the input: One might expect that driving all neurons with a common input helps to control network dynamics. Surprisingly, we find that the network is far easier to co

Populations of cortical neurons can respond to changes in their common input within about a millisecond. However, that response speed has a pronounced dependence on the temporal statistics of the neuron's input (Tchumatchenko etal.2011, Merino etal. 2021, Revah etal. 2024). Slowly fluctuating inputs allow for much more rapid responses. In the dynamic gain function of the individual neuron, this corresponds to a wider bandwidth under slower input correlations. Fourcaud etal. (2003) demonstrated that a wide bandwidth requires a strong voltage dependence of the action potential initiating current