Ensemble learning and ground-truth validation of synaptic connectivity inferred from spike trains
Fig 5
Characterizing the connectivity of in vitro neuronal networks.
A Firing rate cumulative density function (CDF) of 600 spike-sorted units from HD-MEA recordings obtained from primary cortical cultures (top panel; n = 6 cultures; 100 units per network; recording duration: 1 h; culture age: DIV 14); and CDF of inter-spike interval coefficients of variation (ISI CV) for the same cultures (lower panel). B Overall distribution of eANN weights of empirical networks (in gray; values are depicted in logarithmic space) and overlaid with the corresponding distribution of eANN values inferred from surrogate networks (in yellow). The distribution of experimentally inferred values demonstrates a clear peak in the eANN weight distribution that distinguishes putative synaptic connections from unconnected pairs. C Significant eANN edges cannot exclusively be explained by the overlap across all inference methods. Panel E depicts the consensus distribution, i.e., the overlap across the six inference methods for all significant eANN edges; most eANN edges were found by five of the other methods. About 20% of edges were found by the eANN, but not by the other methods at the selected threshold (see zero bin). D Network density as a function of threshold values (corresponding to α: 0.05, 0.01, 0.005, and 0.001) across all inference methods. α threshold values were derived from surrogate connectivity estimates (temporally jittered spike trains). Network density decreased with smaller α-values, and varied significantly across methods. E Intersection of significant eANN connections with those of all other connectivity inference methods. F Inferred connectivity decayed with interneuronal distance (α = 0.01), and the likelihood of long-range connections (> 1 mm) was very low. G Example connectivity matrices for one culture inferred with all seven inference methods. H Topology of inferred in vitro networks differed significantly across inference methods (α = 0.01; filled circles: empirical data; empty circles: randomized surrogate networks). I All inference methods yielded an over-representation of triplet motifs (see Fig 2 for motif ID legend), but with slight differences across methods. Dots depict motif IDs that occurred significantly more frequently than re-wired surrogate networks (FDR corrected α of 0.001); the color indicates the relative mean difference in their occurrence. J Lower triangle (red color scale): Topological similarity, calculated by pairwise Pearson correlation coefficients across the topological metrics shown in H and I across all inference methods. Upper triangle (blue color scale): Network similarity, quantified by pairwise MCCs across all inferred adjacency matrices. Panels D-J depict network graphs thresholded with α = 0.01.