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In the rate model, the LNc spiking rate averaged over the duration of each stimulus presentation replaces the spike density function in the response matrix (see below).
The high spiking rate generated by these compound ORNs results in a significant probability of multiple spikes occurring within a single time step Δt.
These include (1) the inherently high response variability of cortical neurons, (2) either very high or very low selectivity levels (intermediate selectivity provides the most robust CSI), and (3) low spiking rate.
When the limit circle intersects with the threshold (Fig. 5, middle column), the output spiking rate decreases until the input frequency F increases to the critical frequency F* (see Appendix S1, Eq. 4), when the firing rate becomes zero.
To test whether an increase in cAMP levels in the sensory neurons would lead to an increased spiking rate in OR83b knock-out flies (Or83b-/), we generated a mutant fly expressing PACα in the neurons on a OR83b knock-out background.
However, in order to make the spiking rate an increasing function of input frequency, the minimal addition to the model is to include an intrinsic oscillation, where firing increases up to a peak value when the external frequency resonates with the intrinsic oscillatory frequency.
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Light induced increases in spiking rates were detected in several types of sensilla (Figure 6B).
In Figure 3 some spiking rates show negative values, which indicates that the values shown represent spiking rates relative to baseline.
In most neurons that received positive timing inductions sensory-evoked spiking rates increased after the pairing protocol.
Therefore, depending on the conditions, the BOLD signal may actually reflect both LFPs and neuronal spiking rates [Ekstrom, 2010].
Figure 10 Spike rate per sample before and after training.
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