The first one has been stated above; if in the case of leaky integrate-and-fire populations, the firing rate was taking into account only the "jumping" part of the flux, we have here the opposite case, since only the drift flux influences the rate of neurons at the firing phase.
Here, depolarizing stimuli produce switching independently of the time of delivery (Type X″) (upper panel, Fig. 10C), the impact of hyperpolarizing stimuli is again restricted to the firing phases of neurons (Type Y″) (middle panel, Fig. 10C) and mixed stimuli provide switching if delivered anywhere in the cycle except during firing phases (Type X″ Y″) (upper line, bottom panel Fig. 10C).
The experiments allowed the estimation of carbon emission in the different fire phases.
Here, θ(t) = 2 πf θ t is the local field potential (LFP) theta phase at time t and ϕ(x) is the preferred firing phase associated with the animal's location x, termed the encoded phase.
We estimated the preferred firing phase at each location from the simulated data using the methods stated in Harris et al. (2003), using either single-direction data or data consisting of runs in both directions to generate nondirectional or directional phase fields.
We find conditions for a network to be able to keep a fixed firing period but vary the relative firing phase between its neurons, and vice versa.
First, assuming that only cells belonging to one of these groups are stimulated, a transition from AP to IP occurs if a depolarizing signal arrives within a large mid-cycle window (type X') (upper panel Fig. 10B), or if a hyperpolarizing signal is applied in a very narrow window restricted to the cell firing phase (type Y') (middle panel Fig. 10B).
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In Georgia, another team found emissions of most volatile organic compounds were much higher during the smoldering phase of prescribed fires in pine forests compared with the flaming phase.
Importantly however, during these firing phases the network switches from a given AP to a new AP pattern.
