
==== Front
Hum Brain Mapp
Hum Brain Mapp
10.1002/(ISSN)1097-0193
HBM
Human Brain Mapping
1065-9471
1097-0193
John Wiley & Sons, Inc. Hoboken, USA

39254109
10.1002/hbm.26812
HBM26812
Research Article
Research Article
The ventromedial prefrontal cortex plays an important role in implicit emotion regulation: A focality‐optimized multichannel tDCS study in anxiety individuals
Gao et al.
Gao Kexiang 1
Wong Aslan B. 1
Li Sijin 1
Zhang Yueyao 1
Zhang Dandan https://orcid.org/0000-0003-1825-7114
1 2 3 zhangdd05@gmail.com

1 Institute of Brain and Psychological Sciences Sichuan Normal University Chengdu China
2 China Center for Behavioral Economics and Finance & School of Economics Southwestern University of Finance and Economics Chengdu China
3 School of Psychology, Chengdu Medical College Chengdu China
* Correspondence
Dandan Zhang, Chengdu Medical College, Jing'an Road #5, Jinjiang District, Chengdu, 610066, China.
Email: zhangdd05@gmail.com

10 9 2024
9 2024
45 13 10.1002/hbm.v45.13 e2681229 6 2024
05 3 2024
23 7 2024
© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

Abstract

The regulation of emotions is a crucial facet of well‐being and social adaptability, with explicit strategies receiving primary attention in prior research. Recent studies, however, emphasize the role of implicit emotion regulation, particularly implicating the ventromedial prefrontal cortex (VMPFC) in association with its implementation. This study delves into the nuanced role of the VMPFC through focality‐optimized multichannel transcranial direct current stimulation (tDCS), shedding light on its causal involvement in implicit reappraisal. The primary goal was to evaluate the effectiveness of VMFPC‐targeted tDCS and elucidate its role in individuals with high trait anxiety. Participants engaged in implicit and explicit emotion regulation tasks during multichannel tDCS targeting the VMPFC. The outcome measures encompassed negative emotion ratings, pupillary diameter, and saccade count, providing a comprehensive evaluation of emotion regulation efficiency. The intervention exhibited a notable impact, resulting in significant reductions in negative emotion ratings and pupillary reactions during implicit reappraisal, highlighting the indispensable role of the VMPFC in modulating emotional responses. Notably, these effects demonstrated sustained efficacy up to 1 day postintervention. This study underscores the potency of VMPFC‐targeted multichannel tDCS in augmenting implicit emotion regulation. This not only contributes insights into the neural mechanisms of emotion regulation but also suggests innovative therapeutic avenues for anxiety disorders. The findings present a promising trajectory for future mood disorder interventions, bridging the gap between implicit emotion regulation and neural stimulation techniques.

This study explores the nuanced role of the ventromedial prefrontal cortex through focality‐optimized multichannel transcranial direct current stimulation, shedding light on its causal involvement implicit reappraisal. The intervention exhibited a notable impact and resulted in significant reductions in negative emotions and pupillary reactions during implicit reappraisal.

implicit emotion regulation
multichannel transcranial direct current stimulation
reappraisal
trait anxiety
ventromedial prefrontal cortex
National Natural Science Foundation of China 10.13039/501100001809 31920103009 32271102 Shenzhen‐Hong Kong Institute of Brain Science2024SHIBS0004 source-schema-version-number2.0
cover-dateSeptember 2024
details-of-publishers-convertorConverter:WILEY_ML3GV2_TO_JATSPMC version:6.4.8 mode:remove_FC converted:10.09.2024
Gao, K. , Wong, A. B. , Li, S. , Zhang, Y. , & Zhang, D. (2024). The ventromedial prefrontal cortex plays an important role in implicit emotion regulation: A focality‐optimized multichannel tDCS study in anxiety individuals. Human Brain Mapping, 45 (13 ), e26812. 10.1002/hbm.26812 39254109
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pmc1 INTRODUCTION

Emotion regulation is integral to well‐being and social adaptation (Jazaieri et al., 2015), and influencing the onset, experience, and expression of emotions through cognitive, behavioural, and environmental modifications (McRae & Gross, 2020). While traditional research has focused on explicit emotion regulation, recent studies have uncovered implicit emotion regulation, which minimally engages cognitive control (Gyurak et al., 2011; Koole et al., 2015; Koole & Rothermund, 2011), proving effective in reducing negative emotional experiences (Mauss et al., 2007; Wyczesany et al., 2021). For instance, under high‐stress conditions that strain cognitive resources, implicit cognitive reappraisal becomes more feasible than explicit cognitive reappraisal (Williams et al., 2009). Similarly, in situations of intense negative emotions, implicit emotion regulation is more effective than explicit regulation (Zhang et al., 2023). Despite its efficacy, our understanding of the cognitive and neural underpinnings of implicit emotion regulation remains limited.

Neuroimaging has identified two primary systems of emotion regulation (Phillips et al., 2008; Rive et al., 2013). While the dorsal system, dominated by the dorsal lateral prefrontal cortex (DLPFC), supports effortful explicit emotion regulation (Diekhof et al., 2011; Ochsner & Gross, 2005), the ventral system, dominated by the ventromedial prefrontal cortex (VMPFC), facilitates implicit emotion regulation (Roy et al., 2012). However, relying on neuroimaging alone has limitations, prompting interest in causal evidence through noninvasive techniques such as transcranial direct current stimulation (tDCS; Jamil & Nitsche, 2017; Woods et al., 2016).

Despite tDCS showing promise, its efficacy, particularly in emotion regulation, varies across studies (Horvath et al., 2015; Vergallito et al., 2022; Zhang et al., 2022). Challenges with traditional bipolar (single‐channel) tDCS include reduced focality (Guler et al., 2016; Masina et al., 2021; Mikkonen et al., 2020) and limited impact on implicit emotion regulation (Qiu et al., 2023). This may be because explicit emotion regulation typically stimulates superficial cortical areas, such as the DLPFC, whereas implicit emotion regulation involves deeper brain areas, which are more challenging for traditional noninvasive neuromodulation techniques to effectively reach. Therefore, the development of optimized tDCS methods for VMPFC is crucial. Multichannel tDCS utilizing optimization techniques has emerged as a solution (Dmochowski et al., 2011; Fernández‐Corazza et al., 2020; Guler et al., 2016). This study employed a multichannel tDCS optimization algorithm (Saturnino et al., 2021) to enhance focality, providing valuable causal evidence for the VMPFC's role in implicit emotion regulation and its clinical applications for mood disorders.

To investigate this, we employed multichannel tDCS during explicit and implicit cognitive reappraisal tasks. Explicit reappraisal was guided by the introduction, prompting participants to rethink the picture from a positive perspective (Gross, 2015). Implicit reappraisal was induced through a sentence unscrambling task, tapping into unconscious goal pursuit (Williams et al., 2009; Yuan et al., 2022). We specifically recruited participants with high trait anxiety, a group known to have impaired explicit emotion regulation (Buckner et al., 2010; Kenwood et al., 2022). Given the cognitive resource depletion in anxiety and stress (Heatherton & Wagner, 2011; Raio et al., 2013), understanding implicit emotion regulation becomes crucial (Hopp et al., 2011). This study utilized self‐reported emotion rating as the primary measure (Mauss & Robinson, 2009; Zhao et al., 2021), complemented by subjective valence ratings and eye movement analyses, to explore both the immediate and prolonged effects of stimulation. Previous studies have shown that variations in pupil size correspond to emotional arousal, with successful downregulation leading to decreased pupil diameter (Turonova et al., 2016; Yu et al., 2023). Concurrently, saccadic eye movements serve as markers of cognitive effort (Zagermann et al., 2018). We hypothesized that multichannel tDCS of the VMPFC might affect the effectiveness of emotion regulation and emotional responses. We also anticipated that implicit emotion regulation, which is effective in downregulating negative emotions in anxious populations and is less dependent on cognitive effort, would result in reduced pupil dilation and fewer saccades.

2 METHODS

2.1 Participants

This study was approved by the Ethics Committee of Sichuan Normal University. To attain a statistical power of 0.95 for a within‐between interaction effect in a repeated measures ANOVA with the effect size ηp2=0.039(Abend et al., 2019; Gilam et al., 2018), we utilized G*Power 3.0 to determine a necessary sample size of 66. To account for potential attrition, we initially recruited 75 undergraduate students exhibiting high trait anxiety (STAI‐T scores >48) three days before the experiment. The selection criteria were based on Spielberger's State–Trait Anxiety Inventory trait form (STAI‐T; Spielberger et al., 1983). Participants with normal or corrected‐to‐normal vision and without underlying medical conditions or a history of neurological or psychiatric disorders were eligible. Following the exclusion of five participants who did not return for the second day's valence ratings, the final sample consisted of 70 participants (see Table 1).

TABLE 1 Demographic characteristics of participants (mean and standard errors).

Items	Vertex (n = 35)	VMPFC (n = 35)	Statistics	p	
Gender (male/female)	14/21	10/25	χ 2  = 1.00	.317	
Age (years)	19.9 (0.32)	20.3 (0.31)	t = 0.96	.342	
Handedness (right/left)	35/0	35/0			
BDI‐II	8.5 (0.68)	8.4 (0.66)	t = 0.90	.928	
STAI‐T	53.5 (1.42)	53.6 (1.23)	t = 0.05	.964	
ERQ‐R	29.7 (0.77)	28.5 (0.54)	t = −1.22	.228	
Abbreviations: BDI‐II, Beck Depression Inventory Second Edition; STAI‐T, Trait Form of Spielberger's State–Trait Anxiety Inventory; ERQ‐R, the Cognitive Reappraisal Dimension of the Emotion Regulation Questionnaire. Two‐tailed t‐tests.

2.2 Experimental design and stimuli

A within–between interaction design was employed, with the tDCS target (VMPFC/vertex) as the between‐subjects factor and the type of emotion regulation (passive viewing/implicit reappraisal/explicit reappraisal) as the within‐subjects factor. Participants were randomly assigned to either the VMPFC or vertex stimulation group to ensure group comparability.

On the first day, participants completed the Beck Depression Inventory Second Edition (BDI‐II; Beck et al., 1996) and the cognitive reappraisal dimension of the Emotion Regulation Questionnaire (ERQ‐R; Gross & John, 2003). These questionnaires assessed depression levels and the propensity for cognitive reappraisal, respectively. No significant differences were observed between groups in demographic variables, BDI‐II scores, STAI‐T scores, or ERQ‐R scores, ensuring baseline comparability (see Table 1).

Before the main task, participants engaged in a practice session for explicit cognitive reappraisal using a separate set of images. The online tDCS session commenced with a two‐minute warm‐up period, followed by the primary task involving baseline (passive viewing), implicit, and explicit reappraisal blocks (see Figure 1a). The sequence of the three blocks was counterbalanced within each group. Within each block, participants first completed a sentence unscrambling task comprising four trials, followed by a picture viewing task also consisting of four trials. This sequence was repeated four times, resulting in a total of 16 sentence unscrambling trials and 16 picture viewing trials within each block. A 10‐second transition cue appeared between blocks, indicating the type of emotion regulation for the upcoming block.

FIGURE 1 Experimental procedure. (a) Block procedure and task order in each block. The sequence of the three blocks was counterbalanced within each group; in this instance, the block sequence was baseline, implicit, and then explicit. (b) An example of the sentence unscrambling task. In the implicit reappraisal block, “change” was the reappraisal‐related word. In the explicit reappraisal and baseline blocks, the sentence was unrelated to reappraisal. (c) Trial Procedure and emotion ratings. The requirement for emotion rating appears following the picture presentation, and participants reported their current emotions on a scale of 0–1 (ranging from negative to positive).

The sentence unscrambling task (see Figure 1b) required participants to construct a grammatically correct 4‐word sentence from a 5‐word jumble within 30 seconds (Mauss et al., 2007). In the implicit reappraisal block, the jumbles contained reappraisal‐related words or phrases, whereas in the baseline and explicit reappraisal sessions, the words were unrelated to emotion regulation. The reappraisal‐related and irrelevant sentences were drawn from our previous studies (Yuan et al., 2022; Zhang et al., 2023). No significant differences in valence and familiarity were observed between the two types of sentences. The reappraisal‐relevant sentences featured a priming word associated with cognitive reappraisal. For example, in the sentence “旅行可以改变心情” (Travel can change mood), “改变” (change) served as a reappraisal‐related word. The reappraisal‐irrelevant sentences had no connection to emotion regulation. For instance, “树木可以制造氧气” (Trees can make oxygen). Each sentence was randomly rescrambled and supplemented with novel noise words to ensure fresh parsing before use. Previous research has shown that unscrambling sentences containing regulation‐related words can prime the unconscious, mainly automatic, pursuit of regulating subsequent emotional responses (Hopp et al., 2011; Yang et al., 2015; Zhang et al., 2023), whereas unscrambling emotion regulation‐irrelevant sentences do not influence emotion regulation (Mauss et al., 2007; Williams et al., 2009; Wyczesany et al., 2021; Yuan et al., 2019).

Following the sentence unscrambling task, participants engaged in a picture‐viewing task (see Figure 1c), during which their eye movements were recorded. Negative pictures were presented, and participants continuously reported their emotions by clicking the mouse on a scale ranging from “extremely negative” (score = 0) to “extremely positive” (score = 1), with “emotional neutrality” marked at the midpoint (score = 0.5). The trial interval was set to 1 second. In the passive viewing and implicit reappraisal blocks, participants were instructed to closely observe the pictures and experience their emotions. In the explicit reappraisal block, participants were required to consciously reinterpret the pictures positively (e.g., believing that the victims in the picture had been rescued and would recover soon).

One day following the stimulation session, participants rated the valence of the previously viewed pictures on a scale ranging from “extremely unpleasant” (0) to “extremely pleasant” (1), with 0.5 indicating neutrality. This step aimed to explore the sustained effects of multichannel tDCS on emotional responses.

A total of 48 negative pictures were selected from the International Affective Picture System (Lang et al., 1997) and the Chinese Affective Picture System (Bai et al., 2005). The valence (rated from 1 = very unhappy to 9 = very happy) and arousal (rated from 1 = very relaxed to 9 = very alert) of these 48 pictures were assessed by another 20 undergraduate students. These pictures represented emotions such as fear, sadness, disgust, shock, and mutilation and were evenly distributed across the three blocks, with each block containing 16 pictures. One‐way ANOVA revealed no significant differences in valence (baseline: 3.37 ± 0.16, implicit: 3.40 ± 0.19, explicit: 3.43 ± 0.17, F(2, 45) = 0.03, p = .972) or arousal (baseline: 5.45 ± 0.13, implicit: 5.48 ± 0.13, explicit: 5.52 ± 0.01, F(2, 45) = 0.08, p = .926) across the three blocks.

2.3 Multichannel tDCS

For the VMPFC stimulation, the electrodes were positioned at Fp2 (0.375 mA), FT7 (0.375 mA), F10 (0.625 mA), Fp1 (−0.375 mA), FT8 (−0.250 mA), and F9 (−0.750 mA). This electrode montage was optimized using the multichannel algorithm proposed by Saturnino et al. (2021). This algorithm aimed to maximize the focusing of the electric field in the bilateral VMPFC, considering constraint conditions such as the number of electrodes (up to 6), maximum total current (up to 2 mA), maximum individual current (up to 1 mA), and target intensity (both 0.1 V/m). The application of this multichannel tDCS approach remains exploratory, as it does not fully account for individual brain variations or intricate interactions between electrical currents and brain tissue.

To ensure blinding and control for placebo effects, the vertex region was chosen as the control stimulation site. This choice was based on the characteristics of comparable scalp sensations and minimal impact on emotion regulation and placebo effects (Zhao et al., 2021). The electrodes were relocated to the vertex region without altering the current strengths, ensuring comparable sensations: Cz (0.375 mA), CP1 (0.375 mA), C2 (0.625 mA), CP2 (−0.250 mA), CPz (−0.375 mA), and C1 (−0.750 mA).

The electrical field distributions of the two target regions (see Figure 2) were visualized using SimNIBS 3.2.6 software (Thielscher et al., 2015), acknowledging potential variations in skull thickness between the frontal and parietal regions (Mikkonen et al., 2020; Opitz et al., 2015).

FIGURE 2 Electric field distribution of multichannel tDCS. (a) Electrode montage of the VMPFC group and its electric field distribution are illustrated by normE. (b) Electrode montage and its electric field distribution of the vertex group represented using normE. For A and B, the normE reflects the currents intensity. A shift toward red indicates a greater current intensity flowing through that region.

Poststimulation, participants completed debriefing questionnaires to assess the tolerability and sensation of online tDCS. This served as the primary indicator to ensure the integrity of blinding control in this study.

The tDCS was administered using a wireless DC stimulator (NeuStim NSS18, Neuracle, Changzhou, China) equipped with six silver chloride (AgCl) electrodes, each with a surface area of 84.78mm2, coated with a 3‐mm layer of conductive gel. The stimulator delivered a constant current individually to each electrode, with a 30‐second ramp‐up and ramp‐down to minimize the sensation of an electric shock. The total duration of the stimulation was 20 min, aligned with the intended task duration. The actual average task duration observed was 15.81 ± 1.98 minutes (ranging from 12.9 to 25.4 min), with the online tDCS session concluding before the task completion for one participant, representing a small percentage (1.43%) of the total participants.

2.4 Eye‐tracking device

Eye movements were recorded using the Eyelink 1000 Plus infrared tracker (SR Research Ltd., Ottawa, Canada) operating at a frequency of 500 Hz. Calibration and validation were performed using the standard 9‐point Eyelink procedure. Participants were seated with their heads securely positioned in a chinrest, approximately 60 cm from the eye tracker, and were instructed to maintain stillness throughout the recording.

Saccade count and pupil dilation were analyzed using the Data Viewer software (SR Research Ltd., Ottawa, Canada) and Pupillometry Pipeliner (PUPI) in MATLAB (Kinley & Levy, 2022), respectively. Saccade count was determined using velocity and acceleration thresholds of 30°/s and 8000°/s2, respectively. Blinks were detected using the pupillometric noise method (Hershman et al., 2018), and data from 50 ms before blinking to 150 ms after blinking were excluded from the analysis. The starting time for pictures was designated as 0, and the data were subjected to filtering using the moving median method (150 ms Hann window), linear interpolation, and segmentation into epochs spanning from 0 to 5 seconds. Individual baseline pupil size, calculated as the mean from the −200 to 0 ms window of each trial, served as a reference. Pupil dilation was determined as the percentage change from baseline, averaged over the entire duration of picture presentation.

2.5 Statistics

SPSS Statistics 22.0 (IBM, Somers, USA) was used for statistical analyses. Descriptive data were presented as mean ± standard error. A significance threshold of p < .05 was established, with the Bonferroni method applied for correction of multiple comparisons unless specified otherwise. Repeated‐measures ANOVAs were conducted for subjective emotional ratings, pupil dilation, and saccade counts, with tDCS target (VMPFC/vertex) and type of emotion regulation (passive viewing/implicit reappraisal/explicit reappraisal) as factors. The Greenhouse–Geisser correction was applied when appropriate. Two‐tailed t‐tests were used for questionnaire ratings and postvalence ratings. Pearson's r was calculated to examine relationships between emotion ratings, postvalence ratings, and ERQ‐R scores. Bayesian analysis using JASP software (Version 0.17.1, JASP Team, 2023; Wagenmakers et al., 2018) provided an alternative to traditional hypothesis testing.

3 RESULTS

3.1 Self‐reported ratings

All participants believed they were receiving active stimulation, indicating successful blinding. The 20‐minute multichannel tDCS was well‐tolerated across both groups, with participants reporting mild to no negative experiences related to electrical stimulation. No significant differences in tolerability were observed between the two groups (refer to Table 2).

TABLE 2 Simulation debriefing questionnaire (mean and standard error).

Items	Vertex (n = 35)	VMPFC (n = 35)	Statistics	p	
Overall uncomfortable	2.71 (0.18)	3.00 (0.28)	t = 0.86	.392	
Overall mood impact	2.89 (0.30)	2.31 (0.30)	t = 0.86	.392	
Agitation level	1.86 (0.21)	1.94 (0.26)	t = 0.26	.795	
Burning pain	3.11 (0.30)	2.60 (0.33)	t = −1.15	.256	
Stinging pain	3.46 (0.21)	3.66 (0.33)	t = 0.51	.609	
Dizziness level	1.89 (0.21)	1.97 (0.18)	t = 0.31	.757	
Itching level	3.29 (0.36)	3.11 (0.35)	t = −0.34	.732	
Sleepiness level	2.89 (0.40)	2.34 (0.32)	t = −1.07	.289	
Flashing level	1.57 (0.14)	2.03 (0.22)	t = 1.73	.089	
Note: Scores of the items ranged from 1 (indicating no such feelings) to 9 (indicating extreme feelings). Two‐tailed t‐tests.

In terms of emotion rating, a significant interaction between the type of emotion regulation and the tDCS target was identified, F(2, 136) = 4.67, p = .024, ηp2=0.064, BF10 = 11.48. Simple effect analyses revealed significant differences between the tDCS groups. Specifically, the VMPFC group reported more positive ratings compared to the vertex group in the implicit reappraisal condition (F (1,68) = 14.60, p < .001, ηp2=0.177, BF10 = 88.19; VMPFC group: 0.37 ± 0.01, 95% CI = [0.34, 0.40]; vertex group: 0.30 ± 0.01, 95% CI = [0.27, 0.33]) and the baseline condition (F (1,68) = 5.61, p = .021, ηp2=0.076, BF10 = 2.58; VMPFC group: 0.32 ± 0.01, 95% CI = [0.29, 0.34]; vertex group: 0.27 ± 0.01, 95% CI = [0.24, 0.30]). However, no significant group differences were observed under the explicit reappraisal condition (F (1,68) = 0.04, p = .843, ηp2=0.001, BF10 = 0.25; VMPFC group: 0.51 ± 0.02, 95% CI = [0.48, 0.54]; vertex group 0.51 ± 0.02, 95% CI = [0.48, 0.55]) (refer to Figure 3a).

FIGURE 3 Self‐reported results. (a) Emotion ratings. (b) Valence ratings 1 day after the main experiment. The data were depicted using raincloud plots, which combine a violin plot and a box plot. On the left side of each plot, there was a half violin that reflected the data density and had been adjusted to 0.7 for aesthetic purposes. On the right side, there was a box plot that displayed the quartile range and median values. Individual data points were represented by small dots, whereas outliers were indicated by black diamonds. For both A and B, the scores ranged from 0 (indicating extreme negativity or unhappiness) to 1 (indicating extreme positivity or happiness), with 0.5 denoting emotional neutrality. Significance levels were indicated as follows: ***p < .001, * p < .05.

To further explore the effect of implicit emotion regulation, a 2 × 2 ANOVA was conducted by removing the explicit reappraisal condition. Results indicated a trend in the interaction between the type of emotion regulation and the tDCS target (F (1,68) = 2.83, p = .097, ηp2=0.040, BF10 = 3.51). Simple effect analyses, conducted in a different direction from those in the 2 × 3 ANOVA to provide a comprehensive interpretation, revealed that although emotion ratings were higher under the implicit reappraisal condition than at baseline for both groups, this improvement was more pronounced in the VMPFC group (F (1,34) = 28.44, p <.001, ηp2=0.456, BF10 >100) compared to the vertex group (F (1,34) = 7.26, p = .011, ηp2=0.176, BF10 = 4.02).

Additionally, a highly significant main effect of the type of emotion regulation emerged in emotion ratings (F (2,136) = 166.06, p <.001, ηp2=0.709, BF10 = ∞). Explicit reappraisal garnered significantly higher positive ratings (0.51 ± 0.01, 95% CI = [0.49, 0.54]) compared to both implicit reappraisal (0.33 ± 0.01, 95% CI = [0.31, 0.35], pairwise p <.001, Cohen's d = 2.43, BF10 >100) and baseline conditions (0.30 ± 0.01, 95% CI = [0.28, 0.32]; pairwise p <.001, Cohen's d = 2.01, BF10 >100). Implicit reappraisal also received higher positive ratings than did the baseline condition (pairwise p <.001, Cohen's d = 0.42, BF10 >100). Moreover, a significant main effect of the tDCS target was observed (F (1,68) = 6.01, p = .017, ηp2=0.081, BF10 = 8.83). The VMPFC group (0.40 ± 0.01, 95% CI = [0.38, 0.42]) reported significantly higher positive ratings than the vertex group (0.36 ± 0.01, 95% CI = [0.34, 0.38]).

Postvalence ratings 1 day after the main experiment revealed a significant difference between the two groups (t(68) = 3.11, p = .003, Cohen's d = 0.74, BF10 = 13.04), with the VMPFC group (0.39 ± 0.01, 95% CI = [0.37, 0.42]) reporting more positive ratings than the vertex group (0.33 ± 0.01, 95% CI = [0.31, 0.36]; Figure 3b).

3.2 Eye movement results

Ten participants were excluded from the eye‐tracking data due to equipment issues.

For pupil size, a significant interaction effect was observed between the type of emotion regulation and the tDCS target, F(2,116) = 5.48, p = .007, ηp2=0.086, BF10 = 18.96. However, simple effect analyses between tDCS groups revealed nonsignificant differences under the baseline condition (F (1,58) < 1), the implicit reappraisal condition (F (1,58) = 2.24, p = .14, ηp2=0.037, BF10 = 0.67), and the explicit reappraisal condition (F (1,58) = 1.35, p = .250, ηp2=0.023, BF10 = 0.46).

To further explore the two‐way interaction, simple effect analyses were conducted in another direction (refer to Figure 4a). The results showed a significant effect of emotion regulation within the VMPFC group (F (2,58) = 5.68, p = .006, ηp2=0.164, BF10 = 6.89). Pupil size under implicit reappraisal (−26.15% ± 1.05%, 95% CI = [−28.58%, −24.01%]) was significantly smaller than in the explicit reappraisal (−24.36% ± 1.05%, 95% CI = [−26.50%, −22.22%]; pairwise p = .01, Cohen's d = 0.31, BF10 = 4.24) and baseline conditions (−24.53% ± 1.05%, 95% CI = [−26.67%, −22.40%]; pairwise p = .023, Cohen's d = −0.28, BF10 = 12.19). In contrast, the vertex group showed significant pupil size differences only between the explicit reappraisal (−22.46% ± 1.30%, 95% CI = [−25.01%, −19.91%]) and baseline conditions (−24.62% ± 1.08%, 95% CI = [−26.73%, −22.50%]; pairwise p < .001, Cohen's d = 0.33, BF10 = 21.88), with pupil size in the implicit reappraisal condition falling in between (−23.74% ± 1.2%, 95% CI = [−26.09%, −21.38%]), F (2,58) = 8.06, p = .002, ηp2=0.218, BF10 = 35.85).

FIGURE 4 Eye movement results. a. Percentage change in pupil size from baseline pupil size. b. Saccade count. *** p < .001, ** p < .01, * p < .05.

A significant main effect of the type of emotion regulation was observed (F(2,118) = 8.07, p < .001, ηp2=0.122, BF10 = 30.29). The pupil size is smaller during implicit reappraisal (−25.19% ± 0.78%, 95% CI = [−26.72%, −23.65%]) compared to explicit reappraisal (−23.95% ± 0.79%, 95% CI = [−25.51%, −22.40%]; pairwise p < .001, Cohen's d = −0.25, BF10 = 33.93). Pupil size during explicit reappraisal was significantly larger than during the baseline condition (−24.46% ± 0.75%, 95% CI = [−25.92%, −22.99%]; pairwise p = .012, Cohen's d = 0.19, BF10 = 3.42). No significant differences were observed between implicit reappraisal and baseline conditions. The main effect of the tDCS target was not significant (F (1,58) = 0.85, p = .360, ηp2= 0.014, BF10 = 0.52).

Saccade count analysis revealed no significant interaction between the type of emotion regulation and the tDCS target (F (2,122) = 0.75, p = .477, ηp2=0.012, BF10 = 0.07). The main effect (refer to Figure 4b) of the type of emotion regulation is significant (F (2,122) = 8.93, p < .001, ηp2=0.131, BF10 = 72.71). Explicit emotion regulation (15.26 ± 0.26, 95% CI = [14.75, 15.76]) displayed significantly more saccades than implicit emotion regulation (14.53 ± 0.26, 95% CI = [14.08, 14.98], pairwise p = .002, Cohen's d = 0.330, BF10 = 80.6) and the baseline condition (14.47 ± 0.26, 95% CI = [13.93, 14.96], pairwise p < .001, Cohen's d = 0.365, BF10 = 33.2). No significant differences in the saccade count were observed between baseline and implicit reappraisal conditions. The main effect of the tDCS target was not significant (F (1,60) = 0.05, p = .821, ηp2=0.001, BF10 < 0.01).

3.3 Correlations

Significant positive associations between emotion ratings and postvalence ratings were observed in both the baseline condition (Pearson's r = 0.56, p uncorrected <.001, p < .001, BF10 >100, see Figure 5a) and the implicit reappraisal condition (Pearson's r = 0.64, p uncorrected <.001, p < .001, BF10 >100, see Figure 5b). However, in the explicit reappraisal condition, this correlation appeared less pronounced, presenting only as a trend (Pearson's r = 0.21, p uncorrected = .084, BF10 = 0.65, see Figure 5c).

FIGURE 5 Correlation results. (a) Correlation between emotion ratings in the implicit reappraisal condition and postvalence ratings across all groups. (b) Correlation between emotion ratings in the baseline condition and postvalence ratings across all groups. (c) Correlation between emotion ratings in the explicit reappraisal condition and postvalence ratings across all groups. D Correlation between emotion ratings in the implicit reappraisal condition and scores on the cognitive reappraisal dimension of the Emotion Regulation Questionnaire across all groups. ***p uncorrected <.001, * p uncorrected <.05.

No significant correlation was found between emotion ratings and pupil dilation under the baseline (Pearson's r = 0.10, p = .441, BF10 = 0.22), implicit emotion regulation (r = 0.085, p = .521, BF10 = 0.20), or explicit emotion regulation conditions (r = 0.144, p = .271, BF10 = 0.29).

Furthermore, a negative correlation was observed between the ERQ‐R score, measuring the intention to explicitly use reappraisal in everyday life, and emotion ratings under the implicit reappraisal condition (Pearson's r = −0.25, p uncorrected = .041, BF10 = 1.15, see Figure 5d).

4 DISCUSSION

This study harnessed the power of focality‐optimized multichannel tDCS to target the VMPFC in individuals with high trait anxiety, aiming to unravel its impact on implicit emotion regulation. The results align with our hypotheses, showcasing that precise VMPFC stimulation significantly influenced implicit reappraisal, leading to a substantial reduction in self‐reported negative emotions and alterations in pupillary reactions associated with emotional arousal. Beyond this, our findings emphasize the efficacy of implicit reappraisal in individuals with high trait anxiety, signaling its potential as a therapeutic avenue. The direct causal evidence presented here underscores the pivotal role of the VMPFC in implicit reappraisal and highlights the therapeutic potential of multichannel tDCS for enhancing implicit emotion regulation in anxiety disorders.

4.1 Central findings and implications

At the core of our findings is the elucidation of the critical role played by the VMPFC in implicit emotion regulation. The positive modulation of the VMPFC significantly influenced emotional ratings during implicit reappraisal, accompanied by a reduction in pupillary size indicative of diminished emotional arousal. This aligns with existing research supporting the idea that effective emotion regulation correlates with reduced pupil diameter (Bradley et al., 2008). For example, He et al. (2018) demonstrated that explicit cognitive reappraisal significantly reduced emotional arousal and pupil diameter in individuals exposed to social exclusion. However, it is crucial to acknowledge that pupil diameter is also modulated by effortful control (Kinner et al., 2017; Urry et al., 2009). Maier and Grueschow (2021) suggested that greater pupil diameter during explicit emotion regulation is associated with higher cognitive control and can predict the success of explicit reappraisal. In studies such as Yu et al. (2023), both effortful emotion regulation and reduced emotional arousal altered the pupil diameter. Therefore, the observed increase in pupil size under the explicit reappraisal condition reflects the need to recruit more cognitive resources during effortful emotion regulation. Moreover, we found that implicit reappraisal not only improved emotional ratings but also elicited fewer saccadic movements compared to explicit reappraisal, suggesting that implicit reappraisal achieves emotional benefits without significantly increasing cognitive demand (Leigh & Kennard, 2004).

4.2 Nuanced role of the VMPFC in emotion regulation

Our study contributes to the nuanced understanding of the role of the VMPFC in emotion regulation. While anodal stimulation of the VMPFC has previously been associated with enhanced processing of positive emotions (Abend et al., 2019; Gilam et al., 2018), our study, using priming techniques, directly substantiated the pivotal role of the VMPFC in implicit emotion regulation. Notably, VMPFC stimulation did not affect the number of saccades, indicating that its influence on implicit emotion regulation was independent of explicit reappraisal.

In contrast to its role in implicit regulation, VMPFC stimulation did not enhance explicit reappraisal in individuals with high trait anxiety. This finding contradicts previous research that positions the VMPFC as an important hub during the downregulation of negative emotions using explicit reappraisal, because the VMPFC typically synergizes with archaic emotion‐processing structures (Diekhof et al., 2011). One possible explanation for our finding is that while both implicit and explicit emotion regulation involve the VMPFC, they engage different cognitive processes and neural pathways. Our recent research (He et al., 2023) indicates that explicit emotion regulation involves the activation of the DLPFC and ventrolateral prefrontal cortex (VLPFC), which then engage the VMPFC. The VMPFC subsequently modulates activity in the amygdala and other emotion‐related regions. Thus, the fact that direct VMPFC stimulation did not significantly impact explicit regulation compared to vertex stimulation in the current study might be due to the need for initial activation of the DLPFC and VLPFC in explicit regulation, which our VMPFC‐targeted tDCS protocol did not address.

Another possible explanation is that individuals with high trait anxiety have deficits in the lateral prefrontal cortex, which is crucial for explicit regulation (Babaev et al., 2018; Berggren & Derakshan, 2014; Eden et al., 2015; Li et al., 2022). Thus, enhancing explicit regulation in these individuals may require additional strategies to bolster the lateral prefrontal cortex function.

Our findings clarify the role of the VMPFC in different emotion regulation methods and suggest that interventions targeting implicit and explicit emotion regulation may need to be tailored to specific neural pathways and cognitive processes. Implicit regulation operates through automatic processes, whereas explicit regulation requires deliberate cognitive control supported by the lateral prefrontal cortex. The distinct mechanisms underlying emotion regulation methods necessitate further exploration, particularly in studies directly comparing these processes within the same experimental framework. Further research is essential to understand these neural interactions and their implications for the clinical treatment of mood disorders.

4.3 Advancements in multichannel tDCS methodology

Furthermore, our study pioneers the use of multichannel tDCS for enhancing implicit emotion regulation, addressing limitations associated with single‐channel tDCS methods (Abend et al., 2019; Dittert et al., 2018; Gilam et al., 2018). Prior studies employing single‐channel tDCS (Abend et al., 2019; Gilam et al., 2018) demonstrated regulatory effects of VMPFC activation on emotion experiences and anger processing but inadvertently activated other brain regions (such as the subgenual anterior cingulate cortex, ventral striatum, and occipital areas), complicating the isolation of VMPFC‐specific effects. By utilizing a multichannel tDCS method, our study accurately targets the VMPFC, offering valuable insights into the neural mechanisms of emotion regulation and opening new avenues for more effective therapeutic interventions in mood disorders.

4.4 Insights into emotion recovery and sustained effects

The findings extend to the realm of emotional recovery, revealing that individuals in the VMPFC stimulation group exhibited less negative reactivity 1 day post‐treatment. This aligns with research demonstrating that tDCS can produce enduring effects (Nitsche et al., 2003; Nitsche & Paulus, 2001), with repeated applications holding promise for longer‐lasting benefits (Jafari et al., 2021; Jamil & Nitsche, 2017; Ljubisavljevic et al., 2016). Additionally, our analysis revealed that emotional valence scores in the post‐test were significantly correlated with emotion ratings under both implicit reappraisal and baseline conditions. However, only a correlation trend was observed under the explicit reappraisal condition, suggesting that self‐reported emotions under explicit emotion regulation might be influenced by speculative intentions. This highlights the potential of implicit emotion regulation as a clinical tool for the monitoring and quality control, especially for those struggling with explicit emotion regulation.

4.5 Implications for clinical treatments

Our findings indicate that individuals who less frequently employed explicit cognitive reappraisal in everyday lives benefit more from implicit emotion regulation. This is evidenced by the significant negative correlation between ERQ scores and emotion ratings under the implicit emotion regulation condition. This result aligns with prior research (Hopp et al., 2011), suggesting the advantages of implicit emotion regulation for those who struggle with explicit regulation. Additionally, our previous studies have shown that the effectiveness of implicit emotion regulation can be maintained over time with training (Zhang et al., 2023). This suggest that combining multiple tDCS sessions with implicit training could become a promising method for future clinical treatments, offering a novel approach for interventions targeting mood disorders.

Emotion regulation is a complex process that may not be fully captured by a single measurement. Eye‐tracking measures and subjective ratings examined in the current study may capture different aspects of emotion regulation. While pupil size can reflect emotional arousal, it is also affected by physical characteristics of stimuli such as brightness and contrast, complicating the interpretation of its changes (Joshi & Gold, 2020; Mathôt & Vilotijević, 2023). Similarly, emotion ratings can be influenced by various factors, such as memory bias and emotional self‐awareness (Dolcos et al., 2020; Smith et al., 2018), beyond the immediate physiological response reflected by pupil size. As a result, we suggest employing multimodal emotional measurements to monitor the emotional states of clinical individuals, thus obtaining a comprehensive understanding and management of their emotional responses.

4.6 Conclusion and future research directions

In conclusion, our exploratory study not only establishes the efficacy of optimized multichannel tDCS in enhancing implicit emotion regulation but also provides crucial insights into the role of the VMPFC in emotion regulation among individuals with high trait anxiety. The sustained emotional benefits observed a day after the intervention suggest potential long‐term applications in the treatment of mood disorders. However, previous literature indicates that the efficacy of tDCS varies across studies, potentially due to individual differences in cortical anatomy (Vergallito et al., 2022). Future studies should consider personalize the stimulation montage according to individual anatomy.

Additionally, the physiological mechanisms underlying electrical stimulation remain elusive. Various factors, such as individual anatomical variations, current intensity, direction, duration, and the subject's psychological state during stimulation, can influence outcomes (Woods et al., 2016). Future research should include a deeper investigation into the underlying physiological mechanisms of electrical brain stimulation, complemented by neuroimaging evidence to further elucidate the neural substrates involved and refine tDCS protocol designs.

Moreover, emotion regulation, a complex high‐level cognitive process, involves multiple brain areas and networks, making it challenging to find a completely unrelated control site for emotion regulation studies. Future studies might consider diverse control setups, integrating sham, active, and inhibitory stimulations, or employing double dissociation designs as used by Zhao et al. (2021) to provide more compelling evidence.

Furthermore, exploring the sustained effects of repeated tDCS sessions combined with implicit emotion regulation training could significantly advance our understanding of the long‐term impacts and therapeutic potential of tDCS in mood disorders. Finally, validation of our findings in larger sample sizes is necessary to enhance the generalizability and reliability of the results. Overall, our study contributes significantly to the field of emotional neuroscience, highlighting the therapeutic potential of multichannel tDCS in modulating specific neural circuits associated with emotion regulation.

AUTHOR CONTRIBUTIONS

D. Zhang and K. Gao conceptualized and designed the research. K. Gao conducted the experiments and performed data analysis. K. Gao, Aslan B. Wong, S. Li, and Y. Zhang contributed to the writing of the paper. D. Zhang provided critical revisions to the paper.

FUNDING INFORMATION

This research was supported by the National Natural Science Foundation of China (32271102; 31920103009), the Major Project of National Social Science Foundation (20&ZD153), and Shenzhen‐Hong Kong Institute of Brain Science (2024SHIBS0004).

CONFLICT OF INTEREST STATEMENT

The authors declare that there are no conflicts of interest in relation to this study.

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.
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