Heart Rate Discrimination Task (HRDT)

Introduced by Legrand et al. (2022), The heart rate discrimination task: A psychophysical method to estimate the accuracy and precision of interoceptive beliefs — the Aarhus group’s cardiac instrument, and the wiki’s first cardiac task built to psychophysical rather than clinical specifications. Met first-hand through Banellis et al. (2026); the methods paper itself is not in raw/.

What problem it was built for

The wiki’s cardiac evidence rests almost entirely on two 1980s instruments — Schandry counting and Katkin/Whitehead discrimination — both catalogued with their defects on heartbeat-detection-task. The structural complaint, made by the validity debate and independently by signal detection theory, is that a single accuracy number confounds sensitivity with response bias, and reports neither.

The HRDT’s design response is to make the judgment comparative and the scale continuous. Instead of “how many beats,” it asks “faster or slower than yours” against a stimulus the experimenter controls in known units. That converts the measurement into a standard psychophysical estimation problem, with the familiar apparatus: adaptive staircase, fitted psychometric function, threshold and slope estimated separately, lapse rate absorbing inattention.

Note the subtitle’s honesty: the accuracy and precision of interoceptive beliefs. The task does not claim to measure the afferent signal. It measures what the person’s estimate of their heart rate is, and how tightly held.

Why it matters to this wiki beyond the cardiac literature

It makes cardiac and respiratory interoception comparable for the first time. Paired with the RRST, it yields the same four parameters from the same estimation pipeline in a second organ — which is the precondition for is-interoception-domain-general being answerable at all. Every earlier cross-modal null could be blamed on instrument mismatch; this pairing removes that defence.

It measures the quantity the theory pages are about. interoceptive-precision appears throughout predictive-coding, interoceptive-inference, active-inference and computational-psychiatry as the load-bearing term — precision-weighting is what the models manipulate — while the wiki’s empirical pages had no measure of it. The slope parameter is a first, partial answer.

What it does not fix

The task solves a response problem, not a signal problem. Everything on heartbeat-detection-task that turns on cardiodynamics — stroke volume predicting performance, exercise transiently manufacturing accurate perceivers, an older heart being a quieter one — applies here unchanged, because a bigger beat is easier to judge as well as easier to count. Nothing in the psychophysical apparatus addresses signal amplitude.

Nor does it settle whether the minority-validity thesis (Van der Does et al. 2000) survives. That claim is that the counting distribution is a mixture of one perceiving subpopulation and one confabulating majority. The HRDT’s continuous threshold in physical units is the right instrument to test it — a formal mixture analysis on HRDT thresholds in a large unselected sample is now feasible, and is the single missing analysis that debate has been asking for. The Banellis dataset (N = 513 for cardiac) is public and large enough.