Models in Neuroscience

Models are present at all levels of neuroscience from the study of brain cell to the study of human behavior. Each discipline has its own conceptualization and epistemological considerations of models. In particular, conceptual and theoretical models (which aim to understand and represent something in the real world) should be distinguished from predictive models (which aim to predict something in the real world). Despite philosophical and practical differences across disciplines, some general important principles for models can be found across disciplines, such as usefulness, applicability, refutability and the trade-off between accuracy and simplicity.
Within psychological sciences, many different conceptual models have been proposed. All these models rely on many concepts that do not come from an unique common ontology across fields, despite showing semantic overlap. Following the developments of neuroimaging technics in the last decades, many of these concepts have been mapped to the brain. Thousands of fMRI and PET studies show the neural correlates of various concepts derived from the study of human behavior. An overview of those model-based data reveals a many-to-many mapping on both brain-behavior directions: one single brain region can be related to many behavioral concepts and conversely, one single behavioral concept can be assigned to many brain regions. We will discuss how the aggregation of these behavioral model-based data could be harnessed to switch the perspective in order to generate a new brain-based model and ontology.