The effects of population tuning and trial-by-trial variability on information encoding and behavior

Identifying the features of population responses that are relevant to the amount of information encoded by neuronal populations is a crucial step toward understanding population coding. Statistical features, such as tuning properties, individual and shared response variability, and global activity modulations, could all affect the amount of information encoded and modulate behavioral performance. We show that two features in particular affect information: the modulation of population responses across conditions (population signal) and the inverse population covariability along the modulation axis (projected precision). We demonstrate that fluctuations of these two quantities are correlated with fluctuations of behavioral performance in various tasks and brain regions consistently across 4 monkeys (1 female and 1 male Macaca mulatta; and 2 male Macaca fascicularis). In contrast, fluctuations in mean correlations among neurons and global activity have negligible or inconsistent effects on the amount of information encoded and behavioral performance. We also show that differential correlations reduce the amount of information encoded in finite populations by reducing projected precision. Our results are consistent with predictions of a model that optimally decodes population responses to produce behavior.R.N. was supported by National Science Foundation’s NeuroNex Program DBI-1707398 and Gatsby Charitable Foundation GAT3419. R.M.-B. was supported by Ministry of Economy (MINECO) (Spain) BFU2017-85936-P and FLAGERA-PCIN-2015-162-C02-02 and Howard Hughes Medical Institute 55008742. G.C.D., N.E.P., and A.A., as well as experiments in the G.C.D. laboratory, were supported by National Eye Institute (NEI) Grants EY013644 and EY016178. J.M.-T. was supported by the Canadian Institutes of Health Research (CIHR) and Natural Sciences and Engineering Research Council (NSERC)