Kinematic coding: Measuring information in naturalistic behaviour

Abstract

Recent years have seen an explosion of interest in naturalistic behaviour and in machine learning tools for automatically tracking it. However, questions about what to measure, how to measure it, and how to relate naturalistic behaviour to neural activity and cognitive processes remain unresolved. In this Perspective, we propose a general experimental and computational framework - kinematic coding - for measuring how information about cognitive states is encoded in structured patterns of behaviour and how this information is read out by others during social interactions. This framework enables the design of new experiments and the generation of testable hypotheses that link behaviour, cognition, and neural activity at the single-trial level. Researchers can employ this framework to identify single-subject, single-trial encoding and readout computations and address meaningful questions about how information encoded in bodily motion is transmitted and communicated.