Inhibition-stabilized networks (ISNs) are neural architectures with strong positive feedback among pyramidal neurons balanced by strong negative feedback from inhibitory interneurons, a circuit element found in the hippocampus and the primary visual cortex. In their working regime, ISNs produce damped oscillations in the gamma-range in response to inputs to the inhibitory population. In order to understand the properties of interconnected ISNs, we investigated periodic forcing of ISNs. We show that ISNs can be excited over a range of frequencies and derive properties of the resonance peaks. In particular, we studied the phase-locked solutions, the torus solutions, and the resonance peaks. Periodically forced ISNs respond with (possibly multistable) phase-locked activity, whereas networks with sustained intrinsic oscillations respond more dynamically to periodic inputs with tori. Hence, the dynamics are surprisingly rich, and phase effects alone do not adequately describe the network response. This strengthens the importance of phase-amplitude coupling as opposed to phase-phase coupling in providing multiple frequencies for multiplexing and routing information.
author = "R. Veltz and T. J. Sejnowski",
title = "Periodic Forcing of Inhibition-Stabilized Networks: Nonlinear Resonances and Phase-Amplitude Coupling",
year = 2015,
journal = "Neural Computation",
publisher = "MIT Press",
volume = 27,
institution = "INRIA Sophia Antipolis",
number = 12,
pages = "2477-2509",
month = "Dec",
keywords = "oscillation, gamma band, theta band",
doi = "doi:10.1162/NECO_a_00786",
url = "http://www.mitpressjournals.org/doi/10.1162/NECO_a_00786"