Model of gap junction plasticity: Bursting induces gLTD, spiking gLTP.

(A) Bursting protocol replicated from Haas et al. [16]. A current (red line, top panel) of 300 pA for 50 ms at 2 Hz and of -80 pA otherwise is injected into a pair of coupled neurons induces repeated bursting (blue line, middle panel, voltage trace). To quantify the amount of bursting, we low-pass filtered (b_i) the voltage trace, threshold it at θ_burst = 1.3 (discontinued dark line), and integrate. Light blue areas represent the periods during which bursts are detected and therefore gap junctions are depressed. (B) When neurons N1 and N2 spike sparsely (top panel, dark blue, first part of the stimulus), gap junctions are potentiated (bottom panel, green line, first part of the simulation), whereas when they are bursting, gap junctions are depressed (second part of the simulation). (C) Green dots show steady-state values of the mean gap junction coupling for the gLTP with soft bounds, for different values of the network drive along the y-axis. For slow gLTP, the steady-state can be found in the AI regime, where the power of the oscillations of the population spiking activity is low (blue area). (D) Network architecture: A step excitatory drive is fed to the network of E and I neurons (same network detailed on Fig 1, with plastic gap junctions) inducing gamma oscillations. The activity of the network is read out by a downstream population of 200 regular spiking cells. (E) Top panel, step excitatory drive fed to the networks. Second panel, evolution of the mean gap junction coupling. As the excitatory drive is delivered, a gamma oscillation appears, leading to an increase in bursting activity which is followed by a depression of the gap junctions, until the new fixed point is reached. Bottom panels, raster plots of the inhibitory neurons (blue, I1), excitatory neurons (red, E1) and read-out neurons (red, RON). 6 s of data is represented. (F) Top panel, step excitatory drive. Other panels, population activity of the read-out neurons in red, evolution of the mean gap junction coupling in light blue. Second panel, simulation with plastic gap junctions. The read-out neurons are the most active during the transient oscillations. Third panel, static gap junction coupling. The read-out neurons are active as long as the excitatory drive is high. Bottom panel, no gap junction coupling. The read-out neurons are not active. 10 s of data is represented.