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.