Ensemble learning and ground-truth validation of synaptic connectivity inferred from spike trains
Fig 2
Reconstruction performance across algorithms, dynamics, cell types, and recording length.
A Example raster plot (upper panel) and traces of binned population activity (lower panel; the number of spikes per second and neuron) of the high-burst rate condition. B Network reconstruction obtained from a subset of the data shown in A, exemplified for the GLMCC method [40]. Red and blue squares correspond to ground-truth excitatory and inhibitory synapses. White and black circles indicate predicted true positives and false positives. C Same as B, for the results obtained with the eANN approach, which generally improved the reconstruction performance. D The mean average precision score (APS, upper panel) and Matthews correlation coefficient (MCC, lower panel), estimated across all connections, obtained from all inference algorithms and the eANN across three different dynamical regimes. Dots depict the performance obtained on three different subnetworks of the same simulation. E Connectivity reconstruction performance (APS, MCC) as a function of recording time. Results indicated an improvement for longer recordings. Results in panel E are depicted for the intermediate dynamical regime. F APS and MCC for each type of connectivity, i.e., either excitatory (E, in red), or inhibitory (I, in blue), or a combination of both types (E+I, in black). Correspondingly, the performance gains achieved by the eANN are plotted in shades of red, blue, and black. G Quality of topological feature reconstruction for the inferred network across the three dynamical regimes. In the upper panel, the relative difference between four global features (network density, average clustering, and efficiency) is shown. The panel in the middle shows average Pearson correlation coefficients for the local/nodal metrics, comparing values obtained for the ground truth and inferred networks. Black stars indicate the method that performed best. The lower panels depict the absolute difference of triplet-motif frequencies between the ground truth and the inferred networks.