The choice-wide behavioral association study: data-driven identification of interpretable behavioral components.

Behavior contains rich structure across many timescales, but there is a dearth of methods to identify relevant components, especially over the longer periods required for learning and decision-making. Inspired by the goals and techniques of genome-wide association studies, we present a data-driven method-the choice-wide behavioral association study: CBAS-that systematically identifies such behavioral features. CBAS uses powerful, resampling-based, methods of multiple comparisons correction

Déclaration de conflit d'intérêts

Declaration of interests. The authors declare no competing interests.