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By manipulating the integration constant and computing the specificity of patterns, one can identify the optimal timescale on which information is best encoded, i.e., the optimal timescale for a given set of stimuli.
Peer prediction was performed at a timescale of 25 ms (the optimal timescale in Harris et al. (2003)).
In experimental data the optimal timescale for peer prediction is approximately 20 ms, which corresponds to the gamma rhythm and the membrane time constant of CA1 neurons (Harris et al., 2003).
The quality of this prediction is dependent on the timescale at which peer activity is included in the analysis, so that the optimal timescale for peer prediction provides a measure of the temporal resolution of assembly formation.
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To display the peer prediction performance shown in Figure 4C, the optimal prediction timescale for each phase locking value was chosen.
The optimal peer prediction timescale depends on the amount of phase locking.
We find that in the independent coding model the optimal peer prediction timescale depends strongly on phase locking.
In the example considered in the Results section (Sect. 3), this timescale is chosen to match the timescale associated with the optimal metric-based clustering of the responses.
Our model demonstrates advantageous population dynamics where the optimal percentage of asexual reproduction depends on selection strength, on the number of selected loci and on the timescale of environmental fluctuations.
Larger timescale fluctuations would increasingly be experienced as constant conditions, and would allow the population to become fixed for the optimal phenotypes that are insensitive to mutations ('genetic robustness') (Meyers et al. 2005).
The optimal solution then?
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com