The Filter Detection Task for measurement of breathing-related interoception and metacognition
AbstractThe study of the brain’s processing of sensory inputs from within the body (‘interoception’) has been gaining rapid popularity in neuroscience, where interoceptive disturbances have been postulated to exist across a wide range of chronic physiological and psychological conditions. Here we present a task and analysis procedure to quantify specific dimensions of breathing-related interoception, including interoceptive sensitivity (accuracy), decision bias, metacognitive bias, and metacognitive performance. We describe a task that is tailored to methods for assessing respiratory interoceptive accuracy and metacognition, and pair this with an established hierarchical statistical model of metacognition (HMeta-d) to overcome significant challenges associated with the low trial numbers often present in interoceptive experiments. Two major new developments have been incorporated into this task analysis by pairing: (i) a novel adaptive algorithm to maintain task performance at 70-75% accuracy, and (ii) an extended metacognitive model developed to hierarchically estimate multiple regression parameters linking metacognitive performance to relevant (e.g. clinical) variables. We demonstrate the utility of both developments, using both simulated and empirical data from three separate studies. This methodology represents an important step towards accurately quantifying interoceptive dimensions from a simple experimental procedure that is compatible with the practical constraints in clinical settings. Both the task and analysis code are publicly available.