Heartbeat-Related Bodily Processing Shapes Transition Patterns in Self-Related Spontaneous Thought
Sakuragi, M.; Shinagawa, K.; Terasawa, Y.; Tanaka, Y.; Umeda, S.
Show abstract
Spontaneous thought changes over time, yet the moment-to-moment factors shaping these changes remain poorly understood. We examined whether heartbeat-related bodily processing, operating largely outside explicit awareness, is associated with the organization of ongoing thought. Forty adults performed an auditory attention task with intermittent thought probes in which auditory events were scheduled either 200 ms after each detected R peak (synch condition) or independently of ongoing cardiac timing (asynch condition), with occasional omissions in both conditions. Heartbeat-synchronous omissions in this paradigm have been shown to induce cardiac deceleration and modulate heartbeat-evoked potentials (HEPs). The score of the heartbeat counting task (HCT) served as a behavioral index related to cardiac interoceptive accuracy. The results showed that higher HCT score was associated with a stronger synch-asynch shift toward more self-related and less task/self-unrelated thought. HEPs showed a synch-related negative shift across several thought groups, although the magnitude of this condition effect did not reliably differ among thought groups. Overall thought-group distributions were similar across conditions, while transition analyses suggested a tendency in the synch condition toward more frequent transitions linking predominantly interoceptive stimulus-dependent thought with both on-task and self-related thought. Together, these findings suggest that heartbeat-related bodily processing may influence the organization of spontaneous thought, particularly in individuals with greater cardiac interoceptive accuracy. Bodily signals may therefore act as an automatic constraint on the ongoing stream of thought, biasing which thought contents and transitions become more likely over time.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Alpha and theta activity during reward anticipation are modulated by implicit expectations about sequential risk 93%
- Sensory suppression and increased neuromodulation during actions disrupt memory encoding of unpredictable self-initiated stimuli 93%
- Electrophysiological indices reflect switches between Bayesian and heuristic strategies in perceptual learning 93%
Similar papers in this journal
- Dimension-Selective Attention and Dimensional Salience Modulate Cortical Tracking of Acoustic Dimensions 93%
- Neural responses to sensory novelty with and without conscious access 92%
- Conscious and unconscious perception of pitch shifts in auditory feedback during vocalization: Behavioral functions and event-related potential correlates 92%
Similar papers in this journal
- The Relation between Alpha/Beta Oscillations and the Encoding of Sentence induced Contextual Information 93%
- Rapid Brain Responses to Familiar vs. Unfamiliar Music - an EEG and Pupillometry study 93%
- From computing transition probabilities to word recognition in sleeping neonates, a two-step neural tale 92%
Similar papers in this journal
- A hierarchical Bayesian model reveals increased precision weighting for afferent cardiac signals, and reduced anxiety, as a function of interoceptive training 92%
- Decoding the dynamics of cognitive control: Insights from reach movements and electroencephalography 91%
- Alpha and Beta Oscillations Mediate the Effect of Motivation on Neural Coding of Cognitive Flexibility 91%
Similar papers in this journal
- Human and AI voice identities evoke shared neural signatures during speaker recognition across changes in speech content and prosody 93%
- Spontaneous Visual Imagery During Extended Music Listening Is Associated With Reliable Alpha Suppression 93%
- Hierarchical syntax models of music predict theta power during music listening 92%
"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.