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The maximal firing rate (Fmax) and the current that induced 63% of Fmax were extracted from each fit.
A common way to estimate the spatial tuning of a neuron is to measure the width of its SRF at half maximal firing rate [7].
The current required to reach 63% of the maximal firing rate was extracted from each fit and used for comparison with other experimental conditions.
Under control conditions the current required to induce a firing rate of 63% of the maximal firing rate was 0.65±0.06 nA (n = 20).
However, since the maximal firing rate increased, there was no significant change in the current required to reach 63% of the maximal firing frequency (from 0.55±0.06 nA (n = 14) under control conditions to 0.52±0.08 nA (n = 4) after application of 8 µM NMDA and 0.8 µM AMPA).
Maximal firing rate for each row is indicated to the right.
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The maximum firing rate decreased from 79 to 17 spikes/s.
Noisy limit cycles and quasi-cycles are mechanisms of emergent oscillations in neural networks, both of which allow the maximal firing rates of individual neurons to be lower than the network oscillation frequency.
Optimal spatial and temporal frequencies were set within the 0.2 0.4 cycles·deg−1 and 1.0 2.0 Hz range respectively, where V1 neurons are known to respond well to sine-wave drifting gratings [39], all of the parameters were selected with the aim to evoke maximal firing rates.
DSIs and preferred directions of individual cells were calculated using the maximal firing rates elicited by moving visual stimuli in 8 directions (θ = 0o:45o:315o) and vector sums were calculated as in Kim et al. (2008).
It appears that the units shown in Figures 5b,c did indeed have a certain disconnect between threshold and half-maximal firing rate, in that firing appeared to increase at a lower level (threshold) than expected from the main ascending arm of the RLF.
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