Figure 5. Tuning the olfactory network by reference to GGN’s olfactory responses required heterogeneous synaptic strengths onto KCs and structured patterns of activity in PNs.
(a) Schematic of mushroom body network model. Each of the 50,000 KCs receives input from 50% of the 830 PNs, which are modeled as spike trains. All KCs excite GGN in its α lobe branch and receive inhibition from a random calyceal branch of GGN. (b–d) Model with simplified, homogenous firing patterns in PNs and uniform synaptic strengths generates unrealistic membrane potential in GGN. (b) Raster plot of model PN spike trains (67 shown); dots in each row mark spike times in a PN. (c) Raster plot of spike trains evoked in the KCs (397 shown) when all of them receive identically strong inhibitory connections from GGN. (d) Unrealistic membrane potential in GGN features a few peaks corresponding to highly synchronized bouts of activity in KCs. Light gray bar: 1 s odor stimulation. (e–g) Model in which subpopulations of PNs have different temporal patterns of spiking during and after odor stimulation generates unrealistic membrane potential in GGN. (e) Rasters show different firing patterns in different PNs. (f) Simulation of model with PN activity pattern in panel e) along with uniform synaptic strengths onto KCs generate synchronized spiking in KCs and (g) unrealistic membrane potential in GGN. Simulation of a model with both structured PN activity patterns in panel e) and heterogeneous synaptic strengths gives rise to (h) temporally diffuse spiking in KC population and (i) sustained depolarization of GGN similar to that observed in vivo (e.g. Figure 4 animal 1). Dark gray bar: 1 s odor stimulation; light gray bar: 0.5 s ‘off response’ period.
Figure 5—figure supplement 1. Introducing diverse delays in PN to KC synapses does not alleviate the unrealistic extent of synchronization of KC firing.
Figure 5—figure supplement 2. Model with steady activity in a fixed set of PNs (as in Figure 5b) can produce sustained depolarization of GGN when the synaptic strengths are lognormally distributed.
