Levels of pattern separation and convergence through burstiness and firing rate codes differ between hippocampal celltypes.

(A) Assessment of burstiness in different celltypes (binless analysis). Left: Cumulative frequency distributions of interspike intervals (ISI) observed in the output spike trains of different hippocampal celltypes and their associated input trains. ISI of all recordings of a given celltype or input set type were pooled. The ISIs were normalized to their median for a given celltype or input type, such that their cumulative distribution would cross at frequency = 0.5, and that all exponential cumulative distributions characteristic of a Poisson process (as both type of input sets are) would be super-imposed or very close to each other. Thus, GCs are visually close to an exponential distribution, suggesting their output is close to a Poisson process, i.e. not bursty. Distributions falling away from their corresponding input distribution suggest that spikes are organized in a non-Poisson manner, suggestive of a bursty behavior. In this sense, HMCs, CA3 PCs and their GC controls seem to exhibit a similar bursty behavior, and FSs an even more bursty one. Right: Quantification of the burstiness of each recording set (102 for GCs, 20 for FSs, 18 for HMCs, 15 for CA3 PCs+gzn and 22 for GCs+gzn). Burstiness was assessed as the Kullback-Leibler divergence from P to M, with M the frequency distribution of normalized ISI in an output set (50 output trains), and P the frequency distribution of normalized ISI in the associated input set type (either Poisson 10Hz or Poisson 30 Hz input sets were combined, as in A). The higher the divergence, the burstier a cell is. This analysis confirms that GCs outputs are close to a Poisson process, and that all other celltypes and conditions are significantly burstier (Kruskal-Wallis one-way ANOVA: p (B) Average levels of pattern separation via binwise Compactness, binwise Occupancy or FR codes were measured for each recording set of every celltype, as in Fig 6B (negative values indicate pattern convergence). Levels were different between celltypes (Kruskal-Wallis one-way ANOVA: p Table 4).