Poster No:
1343
Submission Type:
Abstract Submission
Authors:
Jiyoung Park1, Euisun Kim2, Woo Yong Lee2, Bohyun Lee3, Dawon Park3, Sole Yoo1, Jinseok Eo4, Hae-Jeong Park5
Institutions:
1Department Cognitive Science, Yonsei University, Seoul, Republic of Korea, 2Graduate School of Medical Science, Brain Korea 21 Project, Yonsei University College of Medicine, Seoul, Republic of Korea, 3Department of Psychology, Yonsei University, Seoul, Republic of Korea, 4Center for Systems and Translational Brain Sciences, Yonsei University, Seoul, Republic of Korea, 5Department of Nuclear Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
First Author:
Jiyoung Park
Department Cognitive Science, Yonsei University
Seoul, Republic of Korea
Co-Author(s):
Euisun Kim
Graduate School of Medical Science, Brain Korea 21 Project, Yonsei University College of Medicine
Seoul, Republic of Korea
Woo Yong Lee
Graduate School of Medical Science, Brain Korea 21 Project, Yonsei University College of Medicine
Seoul, Republic of Korea
Bohyun Lee
Department of Psychology, Yonsei University
Seoul, Republic of Korea
Dawon Park
Department of Psychology, Yonsei University
Seoul, Republic of Korea
Sole Yoo
Department Cognitive Science, Yonsei University
Seoul, Republic of Korea
Jinseok Eo
Center for Systems and Translational Brain Sciences, Yonsei University
Seoul, Republic of Korea
Hae-Jeong Park
Department of Nuclear Medicine, Severance Hospital, Yonsei University College of Medicine
Seoul, Republic of Korea
Introduction:
In this study, we aimed to investigate the effects of perceiving vibration stimuli synchronized with or slower than one's heartbeat on anxiety modulation, assessed via EEG. By introducing bodily sensations at a slower pace than the actual heartbeat, we sought to disrupt internal cardiac signals and observe changes in anxiety perception. Previous research has shown that presenting a slower heart rate can help alleviate performance anxiety and stress (Zhou, Murata, & Watanabe, 2020; Sakuragi et al., 2023). Therefore, we explored heartbeat-related brain responses to slower pace sensations by analyzing frequency-domain changes in heartbeat-related EEG signals using Heartbeat-Related Spectral Perturbation (HRSP) analysis (Lee, W et al. 2024)
Methods:
The study involved two conditions where participants perceived either vibrations matching their heartbeat or vibrations slower than their heartbeat while observing a balloon that either burst or did not burst. A total of 40 balloons were shown, with an equal number bursting and not bursting. Eighteen non-diagnosed participants rated their anxiety on a scale from 1 to 9 after each trial. Preprocessing of EEG and ECG data was carried out using MATLAB-based EEGLAB, applying high-pass filtering and common average referencing. Subsequently, EEG data were extracted, and Independent Component Analysis (ICA) was performed to separate independent signal components. Following preprocessing, R-peaks were detected in the ECG data, and the corresponding time points in EEG channels and common components were grouped to generate Heartbeat-related Spectral Perturbation (HRSP) for each R-peak. During HRSP analysis, cluster-based permutation tests were used to identify statistically significant differences between the four conditions in clusters and time-frequency bands based on HRSP data.
Results:
The statistical analysis revealed that across the four conditions, the channel-based analysis showed a tendency for clusters to activate in the frontal and central regions within the alpha, beta, and theta frequency bands. This activation was particularly prominent within the 0.2 to 0.6-second window following the R-peak. Notably, in the theta band, a significant negative cluster was observed in the right inferior parietal lobe and temporo-parietal junction when participants perceived slower vibrations while watching a non-bursting balloon, compared to when watching a bursting balloon.
Conclusions:
This study demonstrated that the perception of vibration stimuli synchronized with or slower than one's heartbeat influences anxiety modulation, as reflected in EEG-based Heartbeat-Related Spectral Perturbation (HRSP). These findings suggest that the brain's processing of interoceptive signals varies depending on the interaction between external vibration stimuli and anxiety-inducing conditions. This highlights the potential of HRSP analysis as a useful biomarker for understanding the complex interactions between anxiety, interoception, and neural processing.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 2
Modeling and Analysis Methods:
EEG/MEG Modeling and Analysis 1
Keywords:
Anxiety
Electroencephaolography (EEG)
Emotions
Other - Heartbeat-Related Spectral Perturbation analysis, Anxiety-reducing device, Interoception, Anxiety-inducing stimuli, Heart rate
1|2Indicates the priority used for review
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Please indicate below if your study was a "resting state" or "task-activation” study.
Task-activation
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Healthy subjects
Was this research conducted in the United States?
No
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel?
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Were any animal research approved by the relevant IACUC or other animal research panel?
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Please indicate which methods were used in your research:
EEG/ERP
Behavior
Neuropsychological testing
Which processing packages did you use for your study?
Other, Please list
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EEGLAB, Fieldtrip
Provide references using APA citation style.
Sakuragi, M., Shinagawa, K., Terasawa, Y., & Umeda, S. (2023). Effect of subconscious changes in bodily response on thought shifting in people with accurate interoception. Scientific reports, 13(1), 16651.
Zhou, Y., Murata, A., & Watanabe, J. (2020, March). The calming effect of heartbeat vibration. In 2020 IEEE Haptics Symposium (HAPTICS) (pp. 677-683). IEEE.
Lee, W., Kim, E., Park, J., Eo, J., Jeong, B., & Park, H. J. (2024). Heartbeat-related spectral perturbation of electroencephalogram reflects dynamic interoceptive attention states in the trial-by-trial classification analysis. NeuroImage, 299, 120797.
No