title: Feedback-induced gain control in stochastic spiking networks.
abstract: The joint influence of recurrent feedback and noise on gain control in a network of globally coupled spiking leaky integrate-and-fire neurons is studied theoretically and numerically. The context of our work is the origin of divisive versus subtractive gain control, as mixtures of these effects are seen in a variety of experimental systems. We focus on changes in the slope of the mean firing frequency-versus-input bias (f-I) curve when the gain control signal to the cells comes from the cells' output spikes. Feedback spikes are modeled as alpha functions that produce an additive current in the current balance equation. For generality, they occur after a fixed minimum delay. We show that purely divisive gain control, i.e. changes in the slope of the f-I curve, arises naturally with this additive negative or positive feedback, due to a linearizing actions of feedback. Negative feedback alone lowers the gain, accounting in particular for gain changes in weakly electric fish upon pharmacological opening of the feedback loop as reported by Bastian (J Neurosci 6:553-562, 1986). When negative feedback is sufficiently strong it further causes oscillatory firing patterns which produce irregularities in the f-I curve. Small positive feedback alone increases the gain, but larger amounts cause abrupt jumps to higher firing frequencies. On the other hand, noise alone in open loop linearizes the f-I curve around threshold, and produces mixtures of divisive and subtractive gain control. With both noise and feedback, the combined gain control schemes produce a primarily divisive gain control shift, indicating the robustness of feedback gain control in stochastic networks. Similar results are found when the "input" parameter is the contrast of a time-varying signal rather than the bias current. Theoretical results are derived relating the slope of the f-I curve to feedback gain and noise strength. Good agreement with simulation results are found for inhibitory and excitatory feedback. Finally, divisive feedback is also found for conductance-based feedback (shunting or excitatory) with and without noise.
authors.affiliation: Center for Neural Dynamics, University of Ottawa, 150 Louis Pasteur, Ottawa, K1N 6N5, Canada.
authors.forename: Connie
authors.initials: C
authors.lastname: Sutherland
authors.forename: Brent
authors.initials: B
authors.lastname: Doiron
authors.forename: André
authors.initials: A
authors.lastname: Longtin
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D004555:Electric Fish / Q000502:physiology; D005246:Feedback / Q000502:physiology*; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009474:Neurons / Q000502:physiology*; D013269:Stochastic Processes