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The output of the population is quantified by the sum of the individual spike trains.
For vanishing independent noise, the individual spike trains of the population are identical for a fixed realization of the signal and the common noise.
The question arises how the specific choice of the output, which is taken to be the sum of individual spike trains, affects the findings discussed above.
While current approaches are mostly model-based, and designed for capturing the temporal evolution of the underlying stochastic processes, we focus on a data-driven approach where statistics are defined and computed in function spaces where individual spike trains are viewed as points.
However, note that the accurate exponential relationship is observed for individual spike events where the synaptic strength is gradually increased.
Nevertheless, careful visual inspection of the individual spike trains revealed clear patterns of regular firing (Figure 2A).
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Focusing on these factors allows us to identify the key features of individual spike-evoking epochs (SEEs) that drive reliable spike timing, even though these SEEs show great variety in amplitude and time profile.
We modify this model for neurons that have broader action potentials or those for which the burst envelope instead of individual spikes are modeled.
For each variety, three biological samples, each represented by the mixed samples at the same phonological growth stage from at least three individual spikes, were used for qRT-PCR.
The syndrome of short-acting unilateral neuralgiform headache attacks with conjunctival injection and tearing (SUNCT) is characterized by three different types of pain: single stabs, groups of stabs, and a saw-tooth pattern in which repetitive spike-like paroxysms occur without reaching the pain-free baseline between the individual spikes.
If the synaptic time scales are slow compared to the time scale of the individual spikes, then the full conductance based model can be reduced systematically to an approximate rate model [11], equations (13,14 ]: τ d s i d t = ( r i − s i 2 ) S max − s i S max τ d r i d t = x 0 F ( I − ∑ j = 1 N g i j s j ) τ − r i, (18).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com