Modeling functional Magnetic Resonance Imaging (fMRI) experimental variables in the Ontology of Experimental Variables and Values (OoEVV)

Neuroimage. 2013 Nov 15:82:662-70. doi: 10.1016/j.neuroimage.2013.05.024. Epub 2013 May 16.


Neuroimaging data is raw material for cognitive neuroscience experiments, leading to scientific knowledge about human neurological and psychological disease, language, perception, attention and ultimately, cognition. The structure of the variables used in the experimental design defines the structure of the data gathered in the experiments; this in turn structures the interpretative assertions that may be presented as experimental conclusions. Representing these assertions and the experimental data which support them in a computable way means that they could be used in logical reasoning environments, i.e. for automated meta-analyses, or linking hypotheses and results across different levels of neuroscientific experiments. Therefore, a crucial first step in being able to represent neuroimaging results in a clear, computable way is to develop representations for the scientific variables involved in neuroimaging experiments. These representations should be expressive, computable, valid, extensible, and easy-to-use. They should also leverage existing semantic standards to interoperate easily with other systems. We present an ontology design pattern called the Ontology of Experimental Variables and Values (OoEVV). This is designed to provide a lightweight framework to capture mathematical properties of data, with appropriate 'hooks' to permit linkage to other ontology-driven projects (such as the Ontology of Biomedical Investigations, OBI). We instantiate the OoEVV system with a small number of functional Magnetic Resonance Imaging datasets, to demonstrate the system's ability to describe the variables of a neuroimaging experiment. OoEVV is designed to be compatible with the XCEDE neuroimaging data standard for data collection terminology, and with the Cognitive Paradigm Ontology (CogPO) for specific reasoning elements of neuroimaging experimental designs.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Humans
  • Magnetic Resonance Imaging / methods*
  • Neuroimaging*
  • Software*