Back

Oscillatory markers of interoceptive attention: beta suppression as a neural signature of heartbeat processing

Pultsina, K.; Karjalainen, S.; Parviainen, T.

2025-07-21 neuroscience
10.1101/2025.06.24.660939 bioRxiv
Show abstract

Interoceptive attention--the ability to selectively focus on internal bodily signals--has been linked to distinct neural responses, yet the contribution of oscillatory dynamics to this process remains underexplored. This study investigates the neural mechanisms underlying interoceptive attention by examining beta-band power suppression during heartbeat and auditory discrimination tasks. Fifty-one healthy participants engaged in interoceptive (heartbeat detection) and exteroceptive (auditory discrimination) tasks while their brain activity was measured using magnetoencephalography (MEG). The results revealed significant beta suppression time-locked to the R-peak in the somatosensory cortex, anterior cingulate cortex, mid-cingulate cortex, and dorsolateral prefrontal cortex from 310 to 530 ms post-R-peak. Beta suppression was more pronounced during interoceptive attention, correlating positively with interoceptive accuracy. The findings support the notion that beta suppression in fronto-cingulo-somatosensory network may serve as a neural marker of interoceptive processing, contributing to predictive coding models of interoception. This study highlights the potential for using beta suppression as an objective measure of interoceptive accuracy and suggests that neural oscillations play a critical role in the brains regulation of heartbeat-related information. Furthermore, the study proposes that interoceptive attention involves a top-down mechanism that dynamically adjusts the brains response to cardiac afferent signals, enhancing the precision of interoceptive processing. These findings have implications for understanding how the brain integrates interoceptive signals and may provide insights into clinical applications targeting interoceptive dysfunctions.

Published in Psychophysiology (predicted rank #2) · training set

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.