Heart Rate Variability and Emotion Regulation (HRV-ER)

Previous research suggests that heart rate variability (HRV) biofeedback aimed at increasing HRV can reduce anxiety and stress. The current project investigated the brain mechanisms underlying these effects, with the primary hypothesis being that inducing high amplitude heart rate oscillations via slow paced breathing and HRV biofeedback would increase functional connectivity within brain emotion-related networks, including between amygdala and mPFC. The effects of two 5-weeks interventions were compared: 1) Increase-Oscillations (Osc+), in which participants completed two daily sessions involving slow paced breathing and HRV biofeedback aimed at increasing heart rate oscillation; 2) Decrease-Oscillations (Osc-), in which participants completed two daily sessions involving individualized strategies and HRV biofeedback aimed at decreasing heart rate oscillation.

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Study design:
Study Type  : Interventional  (Clinical Trial)
Actual Enrollment  : 193 participants
Sessions: 2 MRI sessions and 2 HRV data (lab biofeedback calibration data as the third "session" and home practice data as the forth session). The study also involved multiple lab visits.
Allocation: Randomized
Intervention Model: Parallel Assignment
Intervention Model Description: Participants were randomly assigned to either the HRV-increase group or the HRV-decrease group.
Masking:	Single (Participant)
Primary Purpose:	Basic Science
Official Title: Why Does Heart Rate Variability Matter for Emotion Regulation
Actual Study Start Date: February 14, 2018
Actual Primary Completion Date :	March 13, 2020
Actual Study Completion Date : May 5, 2020

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Publications using this dataset:

Min, J., Nashiro, K., Yoo, H. J., Cho, C., Nasseri, P., Bachman, S. L., Porat, S., Thayer, J. F., Chang, C., Lee, T. H. & Mather, M. (2022). Emotion down-regulation targets interoceptive brain regions while emotion up-regulation targets other affective brain regions. Journal of Neuroscience.

Nashiro, K., Min, J., Yoo, H. J., Cho, C., Bachman, S., Dutt, S., Thayer, J. F., Lehrer, P., Feng, T., Mercer, N., Nasseri, P., Wang, D., Chang, C., Marmarelis, V., Narayanan, S., Nation, D., and Mather, M. (in press). Increasing coordination and responsivity of emotion-related brain regions with a heart rate variability biofeedback randomized trial. Cognitive, Affective, & Behavioral Neuroscience.

Nashiro, K., Yoo, H. J., Min, J., Cho, C., Nasseri, P., Zhang, Y., Lehrer, P., Thayer, J. F., and Mather, M. (in press). Effects of a randomised trial of 5-week heart rate variability biofeedback intervention on mind wandering and associated brain function. Cognitive, Affective, & Behavioral Neuroscience. PDF

Nashiro, K., Yoo, H. J., Cho, C., Min, J., Feng, T., Nasseri, P., Bachman, S., Lehrer, P., Thayer, J. F., and Mather, M. (in press). Effects of a Randomised Trial of 5-Week Heart Rate Variability Biofeedback Intervention on Cognitive Function: Possible Benefits for Inhibitory Control. Applied Psychophysiology and Biofeedback.

Bachman, S. L., Cole, S., Yoo, H. J., Nashiro, K. N., Min, J., Mercer, N., Nasseri, P., Thayer, J. F., Lehrer, P. & Mather, M. (2022). Daily heart rate variability biofeedback training decreases locus coeruleus MRI contrast in younger adults. medRxiv.

Bachman, S. L., Nashiro, K., Yoo, H. J., Wang, D., Thayer, J. F. & Mather, M. (in press). Associations between locus coeruleus MRI contrast and physiological responses to acute stress in younger and older adults. Brain Research.

Yoo, H. J., Nashiro, K., Min, J., Cho, C., Bachman, S., Nasseri, P., Porat, S., Dutt, S., Grigoryan, V., Choi, P., Thayer, J. F., Lehrer, P., Chang, C., and Mather, M. (in press). Heart rate variability (HRV) changes and cortical volume changes in a randomized trial of five weeks of daily HRV biofeedback in younger and older adults. International Journal of Psychophysiology.

Min, J., Rouanet, J., Martini, A. C., Nashiro, K., Yoo, H. J., Porat, S., ... & Mather, M. (2023). Modulating heart rate oscillation affects plasma amyloid beta and tau levels in younger and older adults. Scientific Reports, 13(1), 3967.

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Data type


1.	Questionnaire: self reported behavior and emotion
2.	Sleep data: Sleep time measured by whoop
3.	Cognitive task: NIH toolbox-Cognition, SART
4.	Picture memory task
5.	HRV data-: lab calibration, Home training
6.	Stress task: Physiological data, Behavioral data
7.	Blood plasma Aβ42, Aβ40, pTau, and tTau
8.	MRI data: 
     a.	Anatomical-T1
     b.	Anatomical-TSE
     c.	Anatomical-MRS
     d.	Functional-resting
     e.	Functional-Emotion regulation
     f.	Functional-training mimicking
     g.	Functional-UG
     h.	Functional-ASL resting-state scan
     i.	Functional-ASL training mimicking
     j. magnetic resonance spectroscopy (MRS)

Data description

At the root level of the dataset, participant demographic information, including sex, and handedness, and age group is provided in the participants.tsv file and these variables are further described in the accompanying data dictionary, participants.json. The file also indicates which of the different tasks, physiological data, and MRI scans are available for each participant at each time point. This information is organized into 33 columns containing “1” (data exist) or “0” (missing data) for all measures at each session (i.e. ses-pre_task-emotionRegulation; ses-post_task-emotionRegulation). Also, we organized the information about data quality in 15 columns containing “1” (recommend excluding) or “0” (recommend including) for MRI or physiological measures at each session.
We organized the rest of the participants’ data in three ways: phenotype, subject folders, and derivatives folder
1) “Phenotype”: This folder includes files that list all participants’ scores on standardized tests at each time point and participants’ responses to emotion questionnaires at each time-point (with one row per participant)

2) “Sub- < ID > ”: This folder contains participants’ MRI scan data, physiological measures, and behavioral measures. Inside the folder of each participant with longitudinal data available (i.e. n = 193), there are two subfolders, named “ses-pre”, “ses-post” including MRI scan data, physiological measures, and behavioral measures and another two subfolders for heart rate measures, named “ses-calibration”, “ses-home”. The last subfolder, named “beh” has individual data of picture memory tasks, which was measured at one time-point.
Inside “ses-pre” and “ses-post” subfolders, there are four subfolders named “anat”, “func”, “perf”, and “beh”. “Anat” folder contains T1-weighted structural images, “func” folder contains multi-echo BOLD scan data, “perf” folder contains pCASL scan data, and “beh” folder contains behavioral and physiological measures outside the scanner. Inside the “func” subfolder, there are files containing participant’s performance on the task (i.e. event file), and physiological data for each task (i.e. physio file) in addition to brain image data. The event file includes response per trial, as well as onset time of each trial, duration of the event and the presented stimulus. Inside the “perf” subfolder, there are files containing (1) 10 tag & control acquisitions from the pCASL scan in a 4D file (“*_asl.nii”) and (2) an M0 calibration image from the pCASL scan in a 3D file (“*_m0scan.nii”). Figure 3 provides an example of the BIDS data structure for one subject. Table 2 provides detailed information about the file name and the location for each measure at each time point.

3)“derivatives”: This folder contains MRS, mriqc, and freesurferQC folders.  Inside the MRS folder, there is a “MRS_summary.tsv” file and individual subject folders. “MRS_summary.tsv” includes the individual metabolite concentration levels and quality metrics for all scans for all participants. Inside each subject folder, there are two subfolders, named “ses-pre”, “ses-post” including raw MRS data as IMA file format. The pre session included one MRS scan, which produced three ‘.IMA’ files. During the post session, some participants had two MRS scans; the first MRS scan occurred at the same point in the scan sequence as the pre MRS scan. The second, optional, MRS scan was completed after all other task scans were done. Inside the mriqc folder, there are multiple files for scan types; “group_T1w_mriqc.tsv” and “group_BOLD_mriqc_<task-name>.tsv” include the quality control metrics for the T1-weighted and functional (BOLD) MRI scans, respectively. Inside the freesurferQC folder, there is a freesurfer_QC.tsv file including Freesurfer quality metrics and outlier participants on these metrics flagged.

Note that data dictionaries are the same across participants and are provided at the root level rather than duplicating them within each subject folder.

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If you have any questions, please contact:
- Mara Mather [email protected]
- Kaoru Nashiro [email protected]
- Hyun Joo Yoo [email protected]