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Updated: Mar 30, 2026

Optogenetic Entrainment of Hippocampal Theta Oscillations in Behaving Mice
Published on: June 29, 2018
Slow fluctuations in recurrent networks of spiking neurons
Stefan Wieland1,2, Davide Bernardi1,2, Tilo Schwalger3
1Bernstein Center for Computational Neuroscience Berlin, Philippstrasse 13, Haus 2, 10115 Berlin, Germany.
Abstract:
Networks of fast nonlinear elements may display slow fluctuations if interactions are strong. We find a transition in the long-term variability of a sparse recurrent network of perfect integrate-and-fire neurons at which the Fano factor switches from zero to infinity and the correlation time is minimized. This corresponds to a bifurcation in a linear map arising from the self-consistency of temporal input and output statistics. More realistic neural dynamics with a leak current and refractory period lead to smoothed transitions and modified critical couplings that can be theoretically predicted.
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