Figure 1
Workflow for the generation of network simulation of CA1 hippocampus. Gray boxes represent the adopted procedural blocks. Red boxes represent computational functions. Green box represents non elaborated data obtained from public repositories (external sources). (1) Neuronal placement: Cell coordinates have been downloaded from the BBP atlas and landmarks have been obtained as meshes from Allen database. 3D coordinates have been assigned to excitatory (2) and inhibitory (11) classes according to their position in CA1 layers (see Fig. 2) and have been aligned with meshes in the CCF to generate the first 2 outputs (OUT1-a,b). (2) Neuronal morphologies: Geometrical shapes have been generated by analyzing morphological databases providing dendritic and axonal features. Neurons have been oriented according to their relative position within the hippocampus and by using CA3, Subiculum and CA1 layers as landmarks to generate axonal convex hulls (OUT2a) and dendritic point clouds (OUT2b). (3) Network connectivity; Bounding boxes for axons and dendrites were generated to calculate the potential intersections of every axon with all dendrites. An iterative algorithm calculated the intersections of every axonal hull only with neurons with overlapping dendritic bounding boxes. Connection pairs (OUT3) were generated when at least one dendritic point was included into the axonal hull. (4) Network simulation. Neuronal placement and connection pairs were loaded into the BSB python module which generated the adapter for the NEST simulator to run the simulation. The PMA algorithm is represented by blocks 2 and 3.
