Imaging NeuroscienceNeurosciencePeer-reviewed journal article
Validating genuine changes in Heartbeat Evoked Potentials using Pseudotrials and Surrogate Procedures
Tim Paul SteinfathiD, Nadine HerzogiD, Antonin FourcadeiD, Christian SanderiD, Vadim V. NikuliniD, Arno VillringeriD
Abstract
The brain continuously receives interoceptive information about the state and function of our internal organs. For instance, each time the heart beats, the brain responds by generating time-locked activity, known as heartbeat evoked potentials (HEP). When investigating HEPs, it is essential to adequately control for heartbeat-independent confounding activity to avoid false interpretation. In the present study, we highlight the pitfalls of uncontrolled analyses and advocate for the use of surrogate heartbeat analysis and pseudotrial correction, which are promising tools to control for spurious results. Surrogate heartbeat analysis involves shuffling the timing of heartbeats to verify the time-locking of HEP effects. Pseudotrial correction works by subtracting heartbeat-independent activity from HEPs. In this study we employ both procedures, validate them in simulations and apply them to real EEG data. Using EEG recordings obtained during the performance of an auditory novelty oddball task in a large population, we show that, without control analyses, pre-stimulus HEPs appear inversely related to task-related measures such as P300 event-related potential amplitudes and reaction time speed. However, these effects disappear after carefully controlling for heartbeat-unrelated EEG activity. Additionally, in real and simulated data, we show that pseudotrial correction has the potential to remove task-related confounds from HEPs, thereby uncovering real heartbeat-related effects that otherwise could be missed. This study therefore highlights issues that can arise when analyzing HEPs during tasks, provides solutions to overcome them, and gives recommendations for future studies to avoid pitfalls when analyzing and designing behavioral paradigms with HEPs.
- organism: human
- assay: electronic health records
- research focus: benchmarking
- approach: statistical model
- approach: simulation
- Citations
- 14
- FWCI
- 9.03
- Field percentile
- top 2%
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