Extended Data Fig. 1: Consistent decoding accuracy in delay and reactivation links these two representations at the neural ensemble level. | Nature Neuroscience

Extended Data Fig. 1: Consistent decoding accuracy in delay and reactivation links these two representations at the neural ensemble level.

From: Interplay between persistent activity and activity-silent dynamics in the prefrontal cortex underlies serial biases in working memory

Extended Data Fig. 1

a, The size of n=94 independent ensembles of simultaneously recorded neurons varies between 1-6. b, Fraction of neural ensembles with significant previous stimulus decoding accuracy (z > 1.96, see Methods) computed for all ensembles (dashed line) and only for those ensembles with strongest previous stimulus code averaged across the whole delay (see Methods). The incidence of stimulus decoding was significant in delay and reactivation, but not at ITI (two-sided binomial test at p=0.05, with n=94 and n=27 ensembles, for ‘all ensembles’ and ‘highest delay code’, respectively). Error bars are bootstrapped ±s.e.m. c, across-ensemble Pearson correlation between delay decoding accuracy (averaged in the entire delay) and decoding accuracy at different time points (two-sided p-values: 6.5e-30, 0.87, 0.035, n=94 ensembles). The ensembles with strongest delay code also had stronger decoding during reactivation, demonstrating the neural association between delay representations and reactivations despite absent code in the ITI. Error bars denote ±s.e.m. computed with a bootstrap procedure. d, Individual ensemble values from c, orange (Pearson correlation, two-sided p=0.035, n=94 ensembles).

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