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The relationship between the mean spike latency and its standard deviation is illustrated in Fig. 7C.
Voltage deflections which exceeded 50% of the maximum amplitude, and which fell within 1 standard deviation (1 SD) of the mean spike latency, were counted as generating reliable spiking.
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As was the case with simple spike suppression, neither average CS-complex spike occurrence nor its average latency showed between-cell correlations to average CR properties (each p > 0.25), except for a small correlation between mean CS-complex spike latency and mean CR onset (n = 14, r = 0.567, p = 0.0346).
These slightly longer latencies could simply reflect lower firing rates of the neurons showing strong adaptation for a given condition, as the mean first-spike latency can be affected by the response strength, or it could be due to additional neuronal processing, for example cortical modulation of these neurons [10].
To analyze the relationship between SSA and response latency, we plotted the mean first-spike latencies to the standard and deviant stimuli for all neurons under all conditions tested to determine whether their means differed (Fig. 12A).
Figure 12A shows that the latencies of the MGB neurons were distributed over a broad range; to determine whether the latency of the neurons was related to the amount of adaptation that they exhibited, we plotted their mean first-spike latencies to the deviant versus their CSI (Fig. 12B).
(C ) Mean and SD of the light-evoked spike latency for identified serotonergic neurons.
The average changes induced by serotonin on spike latency and the first inter-spike interval for each neuron tested are illustrated in Fig. 3C.
Also, in a similar mixed model, CR amplitude related inversely to CS-complex spike latency, with an average decrease in percentage eyelid closure of 0.26 percentage points per millisecond increase of CS-complex spike latency (p = 0.0034; Table S1E).
By comparing with spike trains measured from the glabrous skin of macaque monkeys, it was found that this approach can mimic FA-I afferent spiking activities in terms of both the average inter-spike interval and the first spike latency.
The modified Rulkov map can mimic a wide variety of spiking patterns, such as spike-frequency adaptation, postinhibitory rebound, phasic spiking, spike accommodation, spike latency and inhibition-induced spiking (Fig. 2).
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