Does fMRI neurofeedback in the context of stress influence mood and arousal? A randomised controlled trial with parallel group design

Participants

We recruited 31 subjects and analyzed data of 30 of these (with mood and arousal data lacking from one subject, due to no-show for the main experiment). They were all male students at Korea University, Seoul, Republic of Korea. We allocated 17 of them to the experimental condition and 13 to the control condition, based on a predefined block-randomized scheme (blocks of 8, 10, and 12 with random order). The mean age was 24.6 years (SD=2.1) and 24.5 years (SD=2.4) in the experimental and the control condition, respectively with a mean of education of 14.9 years (SD=1.4) and 15.3 years (1.3), respectively. There were no significant differences between the conditions for these baseline characteristics [age: t(28) = -0.0585, p = 0.954; education years: t(28) = 0.718, p = 0.479].

We based the sample size on previous studies which had shown large effect sizes for rtfMRInf^19,27. Using power analysis, we estimated that with 14 subjects in each group we could detect effects of d = 1.0 with sufficient power (1 − β > .80; given α = 0.05, one-sided). Recruitment was stopped after the intended 30 subjects had participated in the experiment.

A researcher in Switzerland who was not directly involved in conducting the experiment and who had no contact to the participants, generated the randomized allocation sequence. MATLAB was used for the randomization, whose underlying random number generator uses the Mersenne Twister algorithm by default²⁸. This researcher ensured that the allocation sequence was concealed from those who recruited and assigned the participants. Participants were assigned to a condition according to the allocation sequence in the order in which they were included in the study and only after a final decision about inclusion was made, to support concealment. Researchers at Korea University did the enrollment and then assigned participants to the conditions.

Sampling procedure

We recruited participants via ads on the university’s website and a bulletin board on campus. Using the following inclusion and exclusion criteria, we checked all interested students and decided about their eligibility for the study. Inclusion criteria were being i) male, ii) between 18 and 65 years of age, iii) right-handed, iv) familiar with using a smartphone, to take part in the ambulatory training, v) having sufficient English language skills to follow the written instructions in the experiment, vi) no indication of color-blindness, vii) no history of cardiovascular or neurological diseases, and viii) no history of a severe mental disorder. After finishing the whole study procedure, we paid each participant 60,000 KRW to compensate for time and effort related to study participation.

The institutional board of Korea University approved the study and all participants gave written informed consent (approval number: KU-IRB-10-38-A-2(E-A-1)(E-A-1)(E-A-3)).

Materials

We used established tools to assess mood and arousal, applied a well-known cognitive task as a stressor in the fMRI experiment, and instructed our participants in four mental strategies, aimed at reducing their stress response during the experiment.

To assess mood, we used the English version of the established multidimensional mood state questionnaire (MDMQ) (original in German “Mehrdimensionaler Befindlichkeitsfragebogen (MDBF)”), which has good psychometric properties^29,30. The questionnaire measures current mood on three dimensions: good to bad, awake to tired, and calm to nervous. Individual values on each dimension range from 4 to 24 and higher values represent more positive affect, feeling more awake, and calmer, respectively.

We assessed subjective arousal with a non-verbal pictorial rating scale to assess valence, arousal, and dominance, on a 9-point Likert Scale, called Self-Assessment Manikin (SAM)³¹. The arousal rating was labeled with “At the moment, I’m feeling...” and went from “very calm” to “very aroused” in addition to the original pictures. The SAM is an established tool which is used extensively in research. We were only interested in the arousal dimension, because it is clearly linked to a psychological stress response and, thus, have not analyzed the other dimensions of the SAM.

During the rtfMRInf experiment, we induced acute stress using a cognitive task which had previously been used for this purpose and shown to elicit a cardiovascular and neural stress response: the Stroop color-word interference task³², adapted for the use in fMRI experiments and to be more challenging due to implemented adaptive time constraints^33,34. We instructed the participants in four mental strategies: Body attention, contemplative repetition (mantra), emotional imagery, and facial expression (make different emotional faces). More details about these strategies and the exact instructions (text and video clips) were published elsewhere²³.

Overall study procedure

We laid out the whole study as a randomised parallel-group study with rtfMRI neurofeedback as the experimental condition and sham-feedback as the control condition. Participants were blinded about their allocation, while experimenters and those analyzing the data were not. We registered the study before starting recruitment (ClinicalTrials.gov, identifier NCT01921088). Over the course of the study, participants visited the laboratory three times and conducted 13 days of smartphone-based ambulatory mental training between the two main experimental visits. We conducted the study at the Korea University, Seoul, Republic of Korea (RRID:SCR_004095) between August and October of 2013.

Initially, we screened all interested students in a short telephone interview to check for their history of diseases and mental disorders described in the exclusion criteria above. On a first visit to the laboratory, we then further checked their eligibility based on all additional inclusion and exclusion criteria with a set of questionnaires. There, we also instructed participants about the whole study and the four mental strategies.

After deciding upon the final inclusion in the study, participants then visited the laboratory two more times for the main rtfMRInf experiments. These two visits were 14 days apart and during the 13 days in-between, participants took part in a smartphone-based ambulatory mental training, where they applied the mental strategies they had already used during the experiment in short daily sessions. They were guided through the training with video clips and questionnaires on their smartphones.

We here report data from the first laboratory visit (screening day) and the first experiment day and will, thus, refer to the latter day simply as “experiment day”. More details on the procedures, especially regarding the ambulatory training, have been reported elsewhere²³.

Experimental procedure

With regard to the first experiment day, the experimental procedure contained the following phases: Structural scans, where the previously defined broad regions of interest for the neurofeedback training were localized; Functional localizer phase, where participants did the Stroop task and the individual regions of interest could be pinpointed, to ensure participants get a feedback signal from areas active during the task; resting phase; Neurofeedback-only (i.e., without Stroop) phase, where participants first had to apply the four learned mental strategies in turn, and then continue using the strategy which worked best for them, and also do neurofeedback; resting phase; phase with additional structural scans; Neurofeedback with Stroop, where subjects used both, the mental strategies and the neurofeedback signal to actively modulate their brain activity associated with the stressor; resting phase; Stroop-only phase, where subjects only used the mental strategies to reduce their stress response; resting phase.

The Stroop task runs were made up of 8 blocks each; congruent and incongruent trials were alternated. During the neurofeedback phases, we presented the feedback signal continuously on one side of the screen and (if applicable) the Stroop task on the other side. We assessed current mood (MDMQ questionnaire) once before and once after the whole fMRI experiment and arousal (with the SAMs) after each individual phase of the experiment.

Neurofeedback

We defined a set of regions of interest (ROIs) encompassing the left and right anterior cingulate cortex (ACC) and insular cortex (IC), based on previously found brain activity associated with the Stroop task^33,35. Within this set, a more precise individual ROI was localized during the functional localizer phase for each participant. The recorded and processed brain activity of the individual ROIs was fed back to the participants in near real-time. Participants saw the feedback signal abstracted as a white, moving thermometer-like bar on a black background, which went up and down depending on the signal strength, indicating the divergence from the baseline activity level. We instructed them to modulate the activity of the ROIs using this information, by applying the mental strategies they had learned and the information from the feedback signal. Sham-feedback for the control condition was the recording of the feedback signal from another participant.

We acquired the MRI data with a 3T Siemens Tim Trio scanner with a 12-channel head coil (Erlangen, Germany). To measure the BOLD signal, we applied a standard gradient-echo EPI pulse sequence³⁶ using the following specifications for rtfMRInf: repetition time (TR) = 1500 ms, echo time = 25 ms, field of view 240*240 mm, matrix size 64*64, voxel size = 3.75*3.75*5 mm, flip angle 90, and 30 interleaved slices with 5mm thickness at approximately 30 oblique to the AC-PC line without a gap^37,38.

We calculated individual ROIs for each participant during the functional localizer phase as follows: EPI preprocessing (head motion correction for six parameters, spatial smoothing with an 8 mm full-width at half maximum Gaussian kernel); estimation of beta-value maps for each incongruent and congruent Stroop trial via general linear model (GLM) implemented in SPM to get a contrast map for “incongruent > congruent Stroop trials”; calculating the neurofeedback signal then from the intersection map between ROIs from the GLM and the predefined set of ROIs.

To calculate the neurofeedback signal, we first removed possible artifacts from the raw BOLD signal of the individual ROIs, applying a bandpass-filter (0.008 - 0.1 Hz) using a third-order elliptic digital filter to avoid low-frequency linear drift³⁶. Next, we linearly detrended the median BOLD signals within each of the ROIs as well as the whole-brain area. We then averaged the values between the 10th and 30th percentile during the cross-fixation period, using this as the baseline BOLD intensity (for ROI and whole-brain area). Percentage signal change (PSC) of the ROI relative to the whole-brain area were then estimated voxel-wise, by subtracting the estimated whole-brain PSC from the ROI PSC. This PSC difference was used as the neurofeedback signal. Finally, we averaged the signal over the last three TR periods in order to reduce potential high-frequency fluctuations occurring due to cardiac-and respiratory-related activity.

Data analysis

All offline data analysis was conducted using the software package R (version 3.5.1 and later; RRID:SCR_001905)³⁹ and specific further packages for R as follows: “lme4” (RRID:SCR_015654) and “lmerTest” (RRID:SCR_015656)⁴⁰, to conduct the mixed effects models, “dplyr” (RRID:SCR_016708) and “tidyr” (RRID:SCR_017102)⁴¹ for data preparation, and “ggplot2” (RRID:SCR_014601)⁴² and “ggpubr”⁴³ to create and export data visualizations. For online fMRI data preparation, analysis, feedback signal calculation, and neurofeedback presentation as described above, we used MATLAB (The MathWorks, Inc., Natick, MA, USA; RRID:SCR_001622) with SPM8 (RRID:SCR_007037).

To take into account the longitudinal nature of the mood data (two measurements, before and after the fMRI session), we used linear mixed effects models. Our models included the following factors: fixed effects Time (prescan, postscan), Condition (experimental, control), and the interaction Time*Condition, and random intercept for each participant. We estimated three models, one for each of the mood dimensions as dependent variable. Together with beta values, we report 95% confidence intervals of two-sided tests using an alpha-level of 0.05 to determine statistical significance.

Participant flow

The flow of participants, from enrollment to allocation and analysis, is given in Figure 1 in a flow diagram consistent with the Consolidated Standards of Reporting Trials (CONSORT).

Figure 1. CONSORT flow diagram.

Mood

Mood scores were assessed with the MDMQ once before and once after the fMRI session. Results of individual mixed models for the three mood dimensions are presented in Table 1, and descriptive statistics can be found in the interaction plots in Figure 2. In the mood dimensions good/bad and awake/tired, we saw lower values after the fMRI session than before in both conditions, leading to a significant main effect of time. In the calm/nervous dimension, a slight drop in values was present only in the experimental condition, but neither the time effect nor the interaction with condition was significant in this model. None of these models, to determine effects on mood, showed a significant main effect for condition or an interaction between time and condition.

Figure 2. Mood values reported before and after fMRI session for experimental and control condition.

Lighter empty symbols in the background are individual data points (jittered on the x-axis to avoid overplotting), while filled symbols with error bars are condition group values (means and standard errors).

Arousal

We calculated Welch two sample t-tests for unequal variances to assess differences in SAM arousal values between the experimental and control conditions. To account for heteroscedasticity, these tests model different variances for both levels of the factor condition. Descriptive values for subjective arousal can be found in Figure 3. In the “Neurofeedback-only” phase, we found SAM arousal to be significantly higher for participants in the experimental condition [t(26.6)=-2.216, 95%CI[-2.188, -0.083], p=0.035, (two-tailed test)], as compared to those in the control condition. In the phase “Neurofeedback with Stroop”, SAM arousal was also significantly higher in the experimental condition [t(27.9)=-3.252, 95%CI[-2.685, -0.609], p=0.003, (two-tailed test)]. This difference was not present in the “Functional localizer” phase, before the neurofeedback intervention started [t(24.1)=-1.429, 95%CI[-1.869, 0.339], p=0.166, (two-tailed test)].

Figure 3. Subjective arousal by condition and experiment phase.

Combination of dot plot with individual data points and a boxplot for each condition group. The boxplot’s lower and upper hinges mark the 25th and 75th percentiles. Whiskers extend from the hinges to the largest/smallest value up to 1.5 * the inter-quartile range. Black X shapes mark the condition group means. There was one missing value in the experimental condition during the functional localizer phase.

Underlying data

Full underlying (non-aggregated) data cannot be made publicly available since the ethics approval of this study does not cover openly publishing non-aggregated data.

In order to access this data, it must be requested from the corresponding author. Data requestors will have to provide: i) written description and legally binding confirmation that their data use is within the scope of the study; ii) detailed written description and legally binding confirmation of their actions to be taken to protect the data (e.g., with regard to transfer, storage, back-up, destruction, misuse, and use by other parties), as legally required and to current national and international standards (data protection concept); and iii) legally binding and written confirmation and description that their use of this data is in line with all applicable national and international laws (e.g., the General Data Protection Regulation of the EU).

Reporting guidelines

Open Science Framework: CONSORT checklist for “Does fMRI neurofeedback in the context of stress influence mood and arousal? A randomised controlled trial with parallel group design”. https://doi.org/10.17605/OSF.IO/XFQHZ⁴⁴.

The completed CONSORT checklist is available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).