CoTOn: A Cognitive Theory Ontology for Representing Diverging Conceptualizations of Cognitive Concepts

Cognitive neuroscience is a data-intensive and theory-driven discipline that seeks to explain how human experience and behavior is related to physiological, behavioral, and neural measurements. The investigated cognitive concepts (e.g., memory or attention) are, however, latent, unobservable constructs that are assessed via observable and objectifiable measurements obtained in carefully designed experimental settings. Because their definitions and assumed interrelations may vary depending on the underlying cognitive theories, cognitive concepts must be defined and interpreted in the context of those theories. For communication, however, the cognitive neuroscience community is accustomed to use the same linguistic terms for denoting cognitive concepts that have varying definitions in different theories, effectively introducing terminological ambiguity. An ontology for the domain of cognitive neuroscience thus needs to be capable of representing these varying definitions of cognitive concepts that depend on different theories while preserving the relation to their linguistic terms to meet the communication needs of the community. To address this problem, we propose a Cognitive Theory Ontology (CoTOn) that provides the means to represent and relate 1. the objectifiable knowledge about observable entities of the experimental setting, 2. the theory-dependent conceptualizations of latent cognitive concepts, and 3. the community-specific use of the same linguistic terms for differently defined cognitive concepts. In this paper, we ontologically analyse the relevant entities in the cognitive neuroscience domain and derive a reference model and an operational version of CoTOn on the level of general types. We implement this initial version of CoTOn in Protégé and show its applicability for retrieving objectifiable as well as theory-dependent knowledge.