Insite: A Pipeline Enabling In-Transit Visualization and Analysis for Neuronal Network Simulations.

Neuronal network simulators are central to computational neuroscience, enabling the study of the nervous system through in-silico experiments. Through the utilization of high-performance computing resources, these simulators are capable of simulating increasingly complex and large networks of neurons today. Yet, the increased capabilities introduce a challenge to the analysis and visualization of the simulation results. In this work, we propose a pipeline for in-transit analysis and visualization of data produced by neuronal network simulators. The pipeline is able to couple with simulators, enabling querying, filtering, and merging data from multiple simulation instances. Additionally, the architecture allows user-defined plugins that perform analysis tasks in the pipeline. The pipeline applies traditional REST API paradigms and utilizes data formats such as JSON to provide easy access to the generated data for visualization and further processing. We present and assess the proposed architecture in the context of neuronal network simulations generated by the NEST simulator.