The goal of cognitive neuroscience is to identify the mapping between brain function and mental processing. In this article, I examine the strategies that have been used to identify such mappings and argue that they may be fundamentally unable to identify selective structure-function mappings. To understand the functional anatomy of mental processes, it will be necessary for researchers to move from the brain-mapping strategies that the field has employed toward a search for selective associations. This will require a greater focus on the structure of cognitive processes, which can be achieved through the development of formal ontologies that describe the structure of mental processes. In this article, I outline the Cognitive Atlas Project, which is developing such ontologies, and show how this knowledge could be used in conjunction with data-mining approaches to more directly relate mental processes and brain function.
Keywords: machine learning; neuroimaging; ontology; prediction.
© The Author(s) 2010.