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The unbiased estimation of the fraction of variance explained by a model

Fig 12

A comparison of our data quality metric, the signal-to-noise ratio estimator (Eq 16), across several datasets.

(A) The cumulative distribution of under the original experimental protocols. Traces with the same line thickness have similar numbers of n and m. Thick line (blue): MT data has n ≈ 10, m = 8. Medium lines (green, orange, red): V4 data has n ≈ 5, m ≈ 350. Thin lines: Allen Inst. data has n ≈ 50, m ≈ 120. The Allen Inst. data has two recording modalities: extracellular action potentials (spikes) on Neuropixel probes (NP) and two-photon calcium imaging (Ca). Both were recorded for the same stimuli: natural scenes and gratings (see Methods, “Electrophysiological data”). (B) Distribution of after normalization with respect to the duration of the spike counting window (traces for calcium signal are not included). The normalization assumes that the original average spike rate can be applied to a 1 s counting window. But, if firing rates tend to decay over time, this will produce overestimates for recordings shorter than 1 s and underestimates for recordings longer than 1 s.

doi: https://doi.org/10.1371/journal.pcbi.1009212.g012