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NeuroML: A Language for Describing Data Driven Models of Neurons and Networks with a High Degree of Biological Detail

Figure 2

Relationship between experimental data and model components expressed in NeuroML.

Experimental neuroscience data is measured at different scales describing subcellular, cellular and network properties and NeuroML provides a framework to describe models developed using this data at all of these levels. Once models are defined in NeuroML they can either be directly imported into a simulator or translated via a metasimulator like neuroConstruct. Optimization of such data-driven models involves an iterative process of experimentation, creation of models, comparison with data and refinement of models, and suggestions for new experiments based on modeling results.

Figure 2

doi: https://doi.org/10.1371/journal.pcbi.1000815.g002