Abstract
Researchers generally agree that when upregulating and downregulating emotion, control regions in the prefrontal cortex turn up or down activity in affect-generating brain areas. However, the “affective dial hypothesis” that turning up and down emotions produces opposite effects in the same affect-generating regions is untested. We tested this hypothesis by examining the overlap between the regions activated during upregulation and those deactivated during downregulation in 54 male and 51 female humans. We found that upregulation and downregulation both recruit regulatory regions, such as the inferior frontal gyrus and dorsal anterior cingulate gyrus, but act on distinct affect-generating regions. Upregulation increased activity in regions associated with emotional experience, such as the amygdala, anterior insula, striatum, and anterior cingulate gyrus as well as in regions associated with sympathetic vascular activity, such as periventricular white matter, while downregulation decreased activity in regions receiving interoceptive input, such as the posterior insula and postcentral gyrus. Nevertheless, participants' subjective sense of emotional intensity was associated with activity in overlapping brain regions (dorsal anterior cingulate, insula, thalamus, and frontal pole) across upregulation and downregulation. These findings indicate that upregulation and downregulation rely on overlapping brain regions to control and assess emotions but target different affect-generating brain regions.
SIGNIFICANCE STATEMENT Many contexts require modulating one's own emotions. Identifying the brain areas implementing these regulatory processes should advance understanding emotional disorders and designing potential interventions. The emotion regulation field has an implicit assumption we call the affective dial hypothesis: both emotion upregulation and downregulation modulate the same emotion-generating brain areas. Countering the hypothesis, our findings indicate that up- and down-modulating emotions target different brain areas. Thus, the mechanisms underlying emotion regulation might differ more than previously appreciated for upregulation versus downregulation. In addition to their theoretical importance, these findings are critical for researchers attempting to target activity in particular brain regions during an emotion regulation intervention.
Introduction
As humans, we can strategically modulate our own emotions. Often, this involves diminishing negative emotions and intensifying positive emotions. But there are also situations when one would want to increase the intensity of negative emotions (e.g., when wanting to feel empathy for a friend's grief) or decrease the intensity of positive emotions (e.g., when trying not to laugh at a child's embarrassing mistake). Thus, both diminishing and intensifying processes operate across positive and negative emotions (Gross, 2015).
Prior neuroimaging research indicates that diminishing and intensifying emotion rely on a shared set of affect-controlling regions that modulate activity in affect-generating regions (Ochsner et al., 2012; Buhle et al., 2014). This set of affect-control regions includes the ventrolateral prefrontal cortex (PFC), dorsomedial PFC, and dorsolateral PFC (Ochsner et al., 2012; Kohn et al., 2014; Morawetz et al., 2017b). On the other hand, the amygdala, insula, and striatum have been identified as affect-generating regions (Phelps, 2006; Craig, 2009; Grosse Rueschkamp et al., 2019), which can be up- or down-modulated by the control system (Ochsner et al., 2012; Braunstein et al., 2017).
Despite its wide acceptance, the idea of the control system's dialing up or down activity in affect-generating regions relies on an untested assumption: upregulating (i.e., trying to intensify one's emotions) will increase activity in the same affect-generating brain regions that downregulating (i.e., trying to diminish one's emotions) will decrease activity in. We call this implicit assumption of the emotion regulation field the “affective dial hypothesis” (Fig. 1). Indeed, we initially assumed we would see affective-dial-like effects; however, our findings made us realize we needed to rethink this assumption.
Schematic view of the affective dial hypothesis. The control system (hand) dials down activity in affect-generating brain regions during emotion downregulation and dials up activity in these same target regions during upregulation. Simply viewing emotional images activates affect-generating brain regions without the action of the control system.
There are at least 11 prior studies with young adults that included both upregulation and downregulation trials as well as a nonregulation control and so could provide evidence to support the affective dial hypothesis (Ochsner et al., 2004; Eippert et al., 2007; Kim and Hamann, 2007; Domes et al., 2010; Leiberg et al., 2012; Morawetz et al., 2016a,b, 2017a; Li et al., 2018; Steinfurth et al., 2018; Sokołowski et al., 2021), most of which were reported in a recent meta-analysis (Morawetz et al., 2017b). These studies typically showed increased activity in the ventrolateral PFC, dorsolateral PFC, supplementary motor area, and anterior cingulate gyrus (ACC) during both intensifying and diminishing emotion. Furthermore, five of these studies included an explicit test of which regions were involved in regulation in both conditions by examining where overlap occurred between the upregulation > baseline and downregulation > baseline contrasts (Eippert et al., 2007; Leiberg et al., 2012; Morawetz et al., 2016a, 2017a; Li et al., 2018). All five of these studies showed some overlap between these two contrasts. Thus, these overlapping regions are involved in emotional control regardless of whether people are trying to upregulate or downregulate their emotions. However, the affective dial idea that the same affect-generating regions are targeted by upregulation and downregulation currently lacks support. None of those 11 studies reported an explicit test of the overlap between upregulate > baseline and baseline > downregulate contrasts.
The current study provides strong power (N = 105) to test the affective dial hypothesis. We included both upregulation and downregulation trials within the same session and contrasted them with viewing trials, allowing us to examine how much the targets of upregulation and downregulation overlap. We then used brain maps from a prior meta-analytic study which investigated the shared and unique brain regions activated by emotion, interoception, and social cognition (Adolfi et al., 2017) to characterize the nature of the regions modulated by upregulation and downregulation. To follow-up on our surprising findings showing mostly different targets of downregulation and upregulation, we conducted exploratory analyses examining whether participants' subjective sense of emotional intensity correlated with activity in the same or different brain regions during downregulation versus upregulation attempts.
Materials and Methods
Participants
The emotion regulation task was conducted as part of a 5-week heart rate variability biofeedback intervention study in which participants were randomly assigned to daily sessions of biofeedback to either increase or decrease their heart rate oscillatory activity (www.ClinicalTrials.gov identifier: NCT03458910). The emotion regulation task was conducted both before and after the interventions, but for this paper we just used the baseline data from young adults before any intervention was conducted. The N was determined to provide power to detect medium effect size differences between the two intervention groups. For the baseline data, the N provides 80% power to detect small-to-medium within-subject effects (i.e., d = 0.28) (Faul et al., 2007). Participants were recruited via University of Southern California's subject pool, University of Southern California's online bulletin board, Facebook, and flyers, and screened out for medical or psychiatric illnesses. However, people taking antidepressant or antianxiety medication were excluded only if they anticipated a change in treatment during the intervention. Participants received $15 per hour for the baseline laboratory visit, which lasted around 2.5 h and included cognitive and emotional tasks and magnetic resonance imaging (MRI) scans. The MRI scans included resting-state blood-oxygenation-level-dependent (BOLD), resting-state arterial spin labeling, emotion regulation task, and structural scans, in that order. Ninety-five participants provided MRI scans for the emotion regulation task for both pre- and post-intervention sessions. As the present analyses focused on the pre-intervention session, we included 19 participants who dropped out after the first emotion regulation task. We excluded 6 participants because they did not respond to ratings for more than half of the trials. We also excluded 3 participants because of failed multiecho independent component analysis (ME-ICA) preprocessing. This yielded 105 participants who ranged in age from 18 to 31 years (Mage = 22.8, SDage = 2.69) and consisted of 54 males and 51 females.
Task
We based our study design on a previously validated emotion regulation task (Kim and Hamann, 2007), which has upregulation and downregulation trials for positive and negative emotions. We used an event-related design. The 10-min emotion regulation task had 42 trials, each of which consisted of a sequence involving a 1-s instruction, a 6-s regulation, and a 4-s rating period (Fig. 2). During the 6-s regulation period, participants were asked to regulate emotion induced by the images according to the presented instruction. The instructions were “intensify,” “diminish,” or “view,” and the presented images were positive, negative, or neutral. Pairing of the instructions and images yielded seven conditions: diminish-negative, diminish-positive, intensify-negative, intensify-positive, view-negative, view-positive, and view-neutral. After regulation, participants were asked to rate their strength of feeling with a scale from 1 (weak) to 4 (strong). Three trials from each condition were nested in a mini-block where the trials were separated by a fixation cross with a jittered interval that ranged from 0 to 4 s. The jittered intervals summed up to 4 s to keep the mini-block length the same, and the mini-blocks were spaced apart by a 5-s-long fixation cross. A total of 14 mini-blocks were arranged in a pseudorandom manner such that no blocks with the same instruction or image valence were shown consecutively. Six sets of images were selected from the International Affective Picture System. Each set consisted of 18 negative (Mvalence = 2.8, Marousal = 5.4), 18 positive (Mvalence = 7.2, Marousal = 5.4), and 6 neutral images (Mvalence = 5.0, Marousal = 2.8), with their average valence and arousal scores the same across the six sets. During the task, each participant was presented with the 42 images in one of the six sets in a randomized order.
Procedure
Participants had a practice session where they came up with their own reappraisal strategies to amplify, moderate, or passively experience the image-induced emotion according to the “intensify,” “diminish,” or “view” instruction. If they had difficulty devising their own method, they were presented with examples, such as reinterpreting the situations or changing the distance between themselves and the scene. We also advised them to adjust their emotional intensity in the moment rather than generating an emotion opposite to the one that they were experiencing. For example, they were not supposed to replace a negative feeling with a positive one to diminish negative emotion. After the scan, participants were asked to report what regulation strategies they used and how successful they were in regulating emotions. For the four emotion-regulating conditions (e.g., diminish positive), 96%-99% of participants used cognitive reappraisal and 92%-98% of participants reported medium to high levels (3-5) of confidence in their emotion regulation success (1: not successful at all; 3: moderately successful; 5: very successful). The reported strategies mainly fell into two categories: reinterpretation and distancing. For example, the participants tended to rationalize the situation or separate themselves from the scene for downregulation and exaggerate the consequences or personalize the scene for upregulation.
MRI data acquisition
MRI scans were conducted at University of Southern California's Dana and David Dornsife Cognitive Neuroimaging Center using a 3T Siemens MAGNETOM Prisma MRI scanner with a 32-channel head coil. We obtained a T1-weighted MPRAGE anatomic image (TR = 2300 ms, TE = 2.26 ms, slice thickness = 1.0 mm, flip angle = 9°, FOV = 256 mm, voxel size = 1.0 mm isotropic). We acquired 250 whole-brain volumes of T2*-weighted functional images using multi-EPI sequence (TR= 2400 mm, TE 18/35/53 ms, slice thickness = 3.0 mm, flip angle = 75°, FOV = 240 mm, voxel size = 3.0 mm isotropic).
Data analysis
The functional MRI (fMRI) data were denoised with ME-ICA, which removed artifact components using the linear echo-time dependence of BOLD signal changes (Kundu et al., 2012). The ME-ICA method allows robust data denoising for motion, physiological, and scanner artifacts via removal of non-BOLD components (Kundu et al., 2017).
The denoised data were entered into FMRI Expert Analysis Tool (FEAT), a tool of FMRIB Software Library (FSL) v6.0 (Jenkinson et al., 2012) for the individual- and group-level analysis. Individual-level analysis (Woolrich et al., 2001) included two steps of affine linear transformation with 12 degrees of freedom where each functional image was registered to the MNI 152 T1 2-mm template via its T1-weighted anatomic image. Individual-level analysis also included a preprocessing of motion correction, spatial smoothing with 5-mm FWHM, and high-pass filtering with 600-s cutoff. Individual whole-brain BOLD time series were modeled with a linear combination of seven emotion-regulation regressors during the 6-s emotion regulation period (diminish-negative, view-negative, intensify-negative, diminish-positive, view-positive, intensify-positive, and view-neutral) along with their temporal derivatives, each convolved with a double-gamma hemodynamic response function. For the group-level analysis, FSL's mixed-effects model (FLAME 1) (Woolrich et al., 2004) was used to test the mean effect of emotion regulation effort, contrasted across the conditions. The final results were corrected for family-wise error at p < 0.05 with the cluster-wise threshold at z > 3.1. We tested for overlapping control regions by taking the intersection of intensify > view and diminish > view and tested the affective dial hypothesis by taking the intersection of intensify > view and view > diminish.
To characterize the nature of the brain areas identified by the view > diminish and intensify > view contrasts, we used emotion-associated and interoception-associated cluster maps from a meta-analytic study (Adolfi et al., 2017). This prior meta-analysis provided cluster maps for interoception, social cognition, and emotion. To help classify the brain regions activated during upregulation and downregulation, we derived three maps from the Adolfi et al. (2017) results: (1) the intersection of the two meta-analytic maps; (2) the emotion-associated map with the intersection regions removed; and (3) the interoception-associated map with the intersection regions removed. We then overlapped these three maps with the thresholded view > diminish and intensify > view contrast maps (after removing the intersection of diminish > view and intensify > view to remove activity likely related to regulation effort rather than its effects), counted the number of voxels overlapping each of the three meta-analytic maps, and divided the number of overlapping voxels with the total number of voxels in each thresholded contrast map.
To assess the BOLD activity changes in the amygdala, we individually segmented the amygdala region from each participant's T1-weighted image using FreeSurfer version 6 (Fischl et al., 2002, 2004) and created the left and right amygdala masks in the native space. We then applied FSL FLIRT (Jenkinson and Smith, 2001; Jenkinson et al., 2002) to transform the masks to the standard MNI space and input them to Featquery to obtain average percent signal change values in the amygdala activity during emotion regulation.
We analyzed participants' ratings of their emotional intensity during the task using SPSS 22 (IBM) to conduct an ANOVA with mean emotional intensity as the dependent variable and the regulation goals (diminish, intensify, view) and image valence (negative, positive) as within-subject independent factors.
Emotion regulation trial design.
Finally, we examined how brain activity while implementing different regulation goals relates to subjective sense of emotional intensity. For this, we used the participants' rating scores on emotional intensity, ranging from 1 to 4. However, to compare the strength of the relationship between subjective emotional intensity and regional brain activity for the two regulation goals, we needed to normalize each participant's ratings within each regulation goal condition. In other words, for this question, the overall main effect of condition (intensify vs diminish) on emotional intensity was irrelevant. Instead, we wanted to see which brain regions showed activity that was associated with within-condition variation in emotional intensity and whether the brain regions showing such relationships differed across intensify and diminish conditions. To extract within-subject variations for the two conditions, we normalized the raw rating scores separately within each subject's intensify and diminish conditions by demeaning the rating scores and dividing the demeaned scores by the SD for each condition. The normalized scores for intensify and diminish trials were used as a weight for the two emotion-regulation regressors (diminish, intensify; each aggregated across positive and negative valence) in another individual-level analysis. Data preprocessing methods remained the same as in prior analyses. The subsequent group-level analysis using FSL's FLAME1 tested the mean effect of four contrasts: diminish, intensify, diminish > intensify, and intensify > diminish, and the results were corrected for family-wise error at p < 0.05 with the cluster-wise threshold at z > 3.1. We excluded 9 participants who always responded with the same rating within either condition, which made normalization impossible within that condition for that person.
Results
Self-rated emotional intensity
There was a significant main effect of the three emotion regulation goals (F(2,208) = 228.60, r = 0.83, p < 0.001) and of emotional valence (F(1,104) = 5.58, r = 0.23, p = 0.02) on self-rated emotional intensity. But there was no significant interaction between goals and valence (F(2,208) = 1.73, r = 0.13, p = 0.18). We also conducted Bonferroni-corrected t tests for pairs of regulation and valence types. The corrected p threshold was at 0.007. Subjective intensity ratings were higher for intensifying than for viewing (t(104) = 12.68, r = 0.61, p < 0.001 for negative emotion and t(104) = 16.19, r = 0.63, p < 0.001 for positive emotion), and also higher for viewing than for diminishing (t(104) = 5.44, r = 0.29, p < 0.001 for negative emotion and t(104) = 5.09, r = 0.25, p < 0.001 for positive emotion) (Fig. 3). Ratings did not significantly differ between negative and positive emotion for intensifying (t(104) = 0.60, r = 0.03, p = 0.55), diminishing (t(104) = 2.43, r = 0.09, p = 0.02), or viewing, (t(104) = 2.46, r = 0.10, p = 0.02), although the comparisons were significant at an uncorrected level for diminishing and viewing (Table 1). In addition, we found that participants' average ratings of emotional intensity during the task correlated with their confidence levels for each goal after the task: r(103) = −0.19, p = 0.06 for diminishing negative emotion, r(103) = −0.29, p = 0.003 for diminishing positive emotion, r(103) = 0.41, p < 0.001 for intensifying negative emotion, and r(103) = 0.40, p < 0.001 for intensifying positive emotion. All the correlations appeared to be goal-consistent as they were negative for downregulation and positive for upregulation.
Emotional intensity ratings across regulation and valence
Ratings of emotional intensity. Error bars indicate SE of each condition.
Brain activity associated with regulation effort
Our analyses focused on the general regulatory effect of emotion regulation across positive and negative valence, based on prior findings that the brain's affective workspace varies little across valence (Lindquist et al., 2016). Contrasting the diminish against view condition (diminish > view) revealed brain regions showing increased activation during emotional downregulation (Fig. 4A; Table 2) (Desikan et al., 2006): the anterior insular cortex, lateral frontal orbital cortex, dorsal ACC, paracingulate gyrus, superior frontal gyrus, and inferior frontal gyrus (IFG). Contrasting the intensify against view condition (intensify > view) revealed brain regions showing increased activation during emotional upregulation (Fig. 4B; Table 3): the anterior insular cortex, lateral frontal orbital cortex, frontal medial cortex, ACC, posterior cingulate gyrus, IFG, middle frontal gyrus, superior frontal gyrus, hippocampus, amygdala, putamen, and thalamus. There were a number of brain regions activated during both upregulation and downregulation (intensify > view ∩ diminish > view), consistent with regulatory regions shared by the two opposing regulation goals. These regions were the insular cortex, IFG, middle frontal gyrus, superior frontal gyrus, dorsal ACC, and angular gyrus (Fig. 5A).
Regions (Fig. 4A) that increased activity during downregulation (diminish > view)
Regions (Fig. 4B) that increased activity during upregulation (intensify > view)
Regions showing activation differences between view and regulation conditions. A, Areas (blue) that increased activity during downregulation. B, Areas (red) that increased activity during upregulation. C, Areas (green) in which activity was decreased during downregulation. D, Areas (yellow) in which activity was decreased during upregulation.
Brain activity consistent with regulatory effort versus with emotional outcome across regulation conditions. A, Common regions (purple) activated during both upregulation and downregulation. B, Regions (green) deactivated during both upregulation and downregulation. C, Regions (turquoise) that increased activity during upregulation and decreased activity during downregulation. D, Regions (orange) that decreased activity during upregulation and increased activity during downregulation.
To test the affective dial hypothesis, we examined the intersection of the two contrasts (intensify > view and view > diminish) that should show significant emotion-related activity if emotion regulation modulates affect-generating brain regions in the expected linear fashion (intensify > view > diminish). If emotion regulation processes act on the same affect-generating brain regions when upregulating and downregulating, the intensify > view and view > diminish contrasts should show overlapping areas. Despite our robust power, however, there were only seven voxels that were significant for both the intensify > view and view > diminish contrasts. They were in the central opercular cortex (five voxels), the parietal operculum cortex (one voxel), and the insular cortex (one voxel). Besides these seven voxels (Fig. 5C), there was no overlap between the significant clusters in the two contrasts, suggesting that upregulation and downregulation act on two distinct emotion-generating regions. The intensify > view contrast (Fig. 4B; Table 3) revealed the amygdala, striatum, anterior insular cortex, and cingulate gyrus, which are associated with emotional experience (Lindquist et al., 2016), as well as white matter and ventricular regions, which are associated with vascular activity during sympathetic arousal (Özbay et al., 2019). The view > diminish contrast (Fig. 4C; Table 4) showed the posterior insular cortex and postcentral gyrus, which receive visceral and sensory input and represent the physiological states of the body (Craig, 2002). The regions with lowered activity during intensifying emotion (view > intensify) included the frontal pole, middle frontal gyrus, and angular gyrus (Fig. 4D; Table 5). Similarly, examining the diminish > view and view > intensify intersection revealed only 4 voxels in the paracingulate gyrus, consistent with a linear diminish > view > intensify affective dial suppression pattern (Fig. 5D).
Regions (Fig. 4C) which decreased activity during down-regulation (view > diminish)
Regions (Fig. 4D) which decreased activity during up-regulation (view > intensify)
In addition, we tested whether the view > diminish and intensify > view contrasts differed between positive and negative valence conditions. We found no significant clusters except for one in the left angular gyrus (Zmax = 4.13; xmax = −48, ymax = −58, zmax = 44; 151 voxels) during view > diminish for negative compared with positive emotion. We also checked whether an affective dial pattern would emerge within either positive or negative trials analyzed separately. Neither the intersection of intensify > view and view > diminish contrasts nor the intersection of diminish > view and view > intensify contrasts yielded any significant voxels that overlapped when we analyzed positive and negative trials separately.
The lack of much activity consistent with either an intensify > view > diminish or a diminish > view > intensify pattern suggests that intensifying and diminishing emotions target different brain networks to modulate emotion. To help characterize the nature of the brain regions which emotion upregulation versus downregulation act on, we counted how many voxels activated during intensify > view versus view > diminish overlapped with emotion- versus interoception-associated cluster maps generated from a prior meta-analysis (Adolfi et al., 2017) (for maps, see Fig. 6). We found that 21.5% of activated voxels during view > diminish overlapped with interoception-related areas, while only 6.0% overlapped with emotion-related areas. During intensify > view, 15.9% overlapped emotion-related areas, while 5.7% overlapped interoception-related areas.
Emotion-related and interoception-related areas identified in the Adolfi et al. (2017) meta-analysis. While clusters (red) in A are related to emotion, clusters (blue) in B are related to interoception. C, Intersection (purple) of A and B. D, Percentage of the voxels during downregulation and upregulation (Fig. 4B, C), which overlap with A, B, and C.
In our follow-up ROI analysis, although the amygdala numerically showed the affective-dial-like diminish < view < intensify pattern (Fig. 7), neither the right or left amygdala showed both significant diminish < view and view < intensify effects as predicted by the affective dial hypothesis. A post hoc t test with Bonferroni-corrected p threshold at 0.01 showed that activity in the left amygdala differed between intensify and view (t(104) = 4.12, r = 0.20, p < 0.001) but did not differ significantly between view and diminish (t(104) = 1.20, r = 0.05, p = 0.23). Activity in the right amygdala did not differ significantly between intensify and view (t(104) = 2.04, r = 0.10, p = 0.04), nor between view and diminish (t(104) = 1.67, r = 0.08, p = 0.10), but differed between intensify and view at an uncorrected p threshold (Table 6).
Activity difference in amygdala ROI between regulation and view conditionsa
Activity in the amygdala ROIs during downregulation, viewing, and upregulation. Error bars indicate SE of each condition.
Brain activity associated with the subjective sense of regulation outcome
Our findings that upregulation and downregulation effort modulated mostly nonoverlapping affect-generating regions (Fig. 4B,C) raised the question of whether brain regions contributing to participants' sense of emotional intensity differ during upregulation and downregulation. The normalized rating scores within subjects for the diminish or intensify condition weighted each trial based on how extreme each participant's intensity rating was on that trial compared with the average rating for diminishing or intensifying trials. The SD of raw rating scores did not significantly differ between intensifying and diminishing trials (t(95) = 1.125, r = 0.06, p = 0.26), indicating similar variability in emotional intensity in the two conditions.
We first examined brain regions where activity during the 6-s task period (Fig. 2) was positively associated with subjective sense of emotional intensity separately for each condition. While higher subjective emotional intensity after diminishing was associated with the ACC and paracingulate gyrus (Fig. 8A; Table 7), subjective emotional intensity after intensifying was associated with broader areas, including the dorsal ACC, supplementary motor cortex, lingual gyrus, thalamus, and cerebellum (Fig. 8B; Table 8). The dorsal ACC, insula, thalamus, and frontal pole were overlapping areas that were associated with greater subjective emotional intensity across both intensifying and diminishing conditions (Fig. 9A). We then examined whether there were any brain regions in which activity was negatively associated with subjective emotional intensity. There were no significant regions for the diminish condition (Fig. 8C); but in the intensify condition, there was less activity in right frontoparietal regions during trials with higher subjective emotional intensity (Fig. 8D; Table 9).
Regions (Fig. 8A) that increased activity as subjective emotional intensity increased during diminish trials
Regions (Fig. 8B) that increased activity as subjective emotional intensity increased during intensify trials
Regions (Fig. 8D) that decreased activity as subjective emotional intensity increased during intensify trials
Regions correlated with subjective emotional intensity during diminish or intensify trials. A, Regions (blue) that increased activity as subjective emotional intensity increased during diminish trials. B, Regions (red) that increased activity as subjective emotional intensity increased during intensify trials. C, Regions (null) that increased activity as subjective emotional intensity decreased during diminish trials. D, Regions (orange) that decreased activity as subjective emotional intensity increased during intensify trials.
Similarities and differences between regulation conditions in the regions correlated with subjective emotional intensity. A, The intersection (red) of regions positively correlated with subjective emotional intensity during diminish trials (see Fig. 8A) and during intensify trials (see Fig. 8B). B, The intersection (mint) of regions positively correlated with subjective emotional intensity during diminish trials (see Fig. 8A) and regions negatively correlated with subjective emotional intensity during intensify trials (see Fig. 8D). C, Regions (green) correlated with subjective emotional intensity more positively during diminish than intensify trials or more negatively during intensify than diminish trials. D, Regions (orange) correlated with subjective emotional intensity more positively during intensify than diminish trials or more negatively during diminish than intensify trials.
The intersection of Figure 8A and 8B revealed that, during both upregulation and downregulation, participants reported greater feeling intensity when activation in the insula, ACC, and thalamus was higher (Fig. 9A). In contrast, the intersection of Figure 8A and 8D reflects goal-inconsistent subjective emotional intensity in both conditions (i.e., higher feeling intensity during diminish trials and lower feeling intensity during intensify trials) and revealed a separate ACC region (Fig. 9B). There also were some significant differences across regulation conditions in how subjective emotional intensity was associated with brain activity. The diminish > intensify contrast revealed significant condition differences in the angular gyrus, supramarginal gyrus, dorsal ACC, paracingulate gyrus, and middle frontal gyrus (Fig. 9C). The intensify > diminish contrast revealed significant differences in the postcentral gyrus and superior parietal lobule (Fig. 9D). However, it is important to note that, in the diminish > intensify contrast, the differences across regulation conditions were driven by effects within the intensify condition, as the regions in Figure 9C overlap with those in Figure 8D, which indicates greater negative associations between frontoparietal regions and subjective emotional intensity during intensify than diminish trials. Thus, we did not find any evidence of regions that are more associated with subjective intensity during diminishing than during intensifying emotions.
Discussion
The field of emotion regulation has an unexamined assumption we call the affective dial hypothesis. According to this hypothesis, exerting emotional control increases affect-generating brain regions' activity during emotion upregulation and decreases these regions' activity during emotion downregulation. However, our well-powered (N = 105) study demonstrated that upregulation and downregulation target separate brain regions. Most of the brain regions downregulated by diminishing did not overlap with those upregulated by intensifying emotions, as indicated by the minimal intersection between the intensify > view and view > diminish contrasts (Fig. 5C).
Compared with viewing pictures, upregulating emotion increased activity in many brain regions (Fig. 4B) previously associated with affective experience, including the amygdala, anterior insular cortex, ACC, thalamus, and nucleus accumbens as well as in regions associated with sympathetic vascular activity, such as periventricular white matter (Özbay et al., 2018). Instead of decreasing activity in these same brain regions as predicted by the affective dial hypothesis, downregulating emotion decreased activity in the posterior insular cortex and postcentral gyrus (Fig. 4C). These areas receive visceral information through the afferent vagus nerve and are involved in interoceptive awareness (Craig, 2002; Khalsa et al., 2009). Indeed, downregulating activated more brain regions linked by a previous meta-analysis (Adolfi et al., 2017) with interoception than brain regions associated with emotion experience, recognition, or perception, whereas upregulating showed the reverse pattern (Fig. 6D).
It is possible that different strategy preferences across upregulation and downregulation activated different affective circuits. When upregulating, participants may have engaged more with emotional images; previous studies indicate that personalizing stimuli activate emotional arousal pathways, such as the amygdala and hippocampus (Kim and Hamann, 2007; Sokołowski et al., 2021). On the other hand, during downregulating, participants may have disengaged emotions by rationalizing the external situation, thereby reducing activity in interoceptive processing pathways involving the insula and inferior parietal lobule (Ochsner et al., 2004). Consistent with differential strategy selection for intensifying versus diminishing, post hoc review of the strategies and examples reported by the participants revealed that, to diminish emotion, 74% of participants reported reframing the situation, whereas to intensify emotion, 70% of them reported minimizing the distance from the scene. However, future research is needed to test the effects of personalizing versus rationalizing as the post-study questions were not tailored to distinguish one subtype of reappraisal strategy from another and the answers did not indicate exclusive use of those strategies. Aggregating across positive and negative valence did not appear to play a role because we found few significant differences across valence in the two contrasts (view > diminish, intensify > view), suggesting similar effects across valence. However, we note that including both upregulation and downregulation conditions within subjects in our study might have led to different baseline brain activity compared with a between-subject design comparing these two regulatory goals.
Although the brain regions targeted by upregulation and downregulation barely overlapped (Fig. 5C, D), these regulatory modes activated an overlapping set of brain regions (Fig. 5A), including the IFG, dorsal ACC, and anterior insular cortex, regions associated with various aspects of emotion regulation (Ochsner et al., 2004; Eippert et al., 2007; Kim and Hamann, 2007; Domes et al., 2010; Li et al., 2018). Our participants used cognitive reappraisal strategies; the IFG, within the ventrolateral PFC, is involved in strategies that require modifying interpretations of emotional situations to attenuate negative emotion (Ochsner and Gross, 2005). The dorsal ACC detects conflicts and signals adjustments in cognitive tasks (Bush et al., 2000; Botvinick et al., 2004) and emotion regulation (McRae et al., 2008; Ichikawa et al., 2011; Etkin et al., 2015). Anterior insula activation is associated with subjective feelings of emotion and their autonomic representation (Craig, 2009; Critchley and Harrison, 2013).
The amygdala showed a linear pattern; its BOLD activity was highest during upregulation, mid-range during viewing, and lowest during downregulation (Fig. 7). This seemed to support prior work on how emotion regulation modulates amygdala activity (e.g., Ochsner et al., 2004; Kim and Hamann, 2007; Goldin et al., 2008; McRae et al., 2010; Steinfurth et al., 2018). However, to our knowledge, there are no prior findings of overlapping upregulation > baseline and baseline > downregulation effects in the amygdala at a whole-brain threshold level as prior findings were based on ROI or small-volume-corrected analyses. Likewise, we found no significant amygdala voxels in the affective-dial intensify > view ∩ view > diminish contrast at the whole-brain level with our conservative threshold (cluster size Z > 3.1). Participants' self-reported greater use of reframing during downregulation than upregulation may be relevant as reinterpretation does not tend to lower amygdala activity (Dörfel et al., 2014). Further examination of our whole-brain results showed that the view > diminish contrast activated amygdalar laterobasal subregions receiving sensory information, whereas the intensify > view contrast activated mostly the superficial and centromedial subregions, related to emotional arousal and responses (Kerestes et al., 2017). Future research should investigate whether upregulation and downregulation reliably target different amygdala subregions.
During each trial, participants rated the intensity of their feelings (Fig. 2). As expected, they rated intensity as lower on diminish than on intensify trials (Fig. 3). But does variation in subjective emotional intensity relate to activity in the same brain regions during upregulating versus downregulating emotion? Indeed, we found several brain regions where increased activity both during diminishing and intensifying emotions was associated with relatively greater subjective emotional intensity (Fig. 9A). These included the left insula (Fig. 9A) and a small cluster in the right insula (not shown). The insula's activity level may help signal emotional intensity as it is associated with both interoception and emotion (Fig. 6C) (Adolfi et al., 2017). Other regions whose activity was correlated with subjective emotional intensity included the dorsal ACC and the frontal pole, which, as part of the medial PFC, activate during self-referencing tasks involving emotional stimuli (Northoff et al., 2006).
There were also interesting differences across conditions. When the goal was to intensify emotions, higher subjective emotional intensity was associated with lower activity in the right frontoparietal attention network (e.g., Laird et al., 2011), suggesting that intensifying emotions suppresses activity in this attention network (Fig. 8D). Directly contrasting the correlations with subjective emotional intensity in the two conditions revealed that this suppression of frontoparietal activity was more associated with subjective emotional intensity during intensifying than during diminishing emotion (Fig. 9C, D). Thus, whereas amping up emotion during upregulation suppresses frontoparietal activity (Fig. 8D), tamping down emotion during downregulation does not increase frontoparietal activity (Fig. 8C). This suggests that subjective emotional intensity affects cognitive control abilities associated with the frontoparietal attention network more during upregulation than downregulation.
In contrast, activity in a dorsal ACC region (Fig. 9B) was associated with lower subjective intensity during intensify trials (i.e., a failure to achieve the instructed higher arousal state; Fig. 8D) and with higher subjective intensity ratings on diminish trials (i.e., again, a failure to achieve the instructed lower arousal state; Fig. 8A). This region appears to be providing a task-failure signal (or reflecting compensatory effort in response to failure), consistent with the role of the dorsal ACC in error monitoring (Taylor et al., 2007; Gilbertson et al., 2021). Thus, upregulation and downregulation appear to rely on some overlapping brain regions (Fig. 9A-B) to integrate arousal signals and to monitor the gap between the goal and actual states, despite the differences we identified in affect-generating brain regions targeted by these two regulatory goals.
We observed broad activation in the white matter surrounding the ventricles during intensifying emotion compared with viewing emotional images (Fig. 4B). Although we could not find prior papers mentioning white matter activation during emotion regulation, we observed it in figures depicting the fMRI results of emotion upregulation (e.g., Arbuckle and Shane, 2017, their Fig. 1; Grosse Rueschkamp et al., 2019, their Fig. 4). Increased white matter BOLD signal during upregulation may be caused by emotional arousal and sympathetic activity increasing vascular tone (Özbay et al., 2018). White matter veins converge to subependymal veins that run around the edge of the lateral ventricles (Okudera et al., 1999), and so periventricular white matter is especially susceptible to systemic changes in vascular tone (Özbay et al., 2018). Future studies should examine how autonomic nervous system activity affects the vascular aspect of BOLD signals during emotion regulation.
In conclusion, in the current study, cognitive reappraisal during upregulation versus downregulation activated an overlapping set of control regions and relied on an overlapping set of regions to inform subjective sense of emotional intensity but modulated distinct affect-generating brain regions. The regions targeted by upregulation were more likely to be involved in emotional arousal, whereas regions targeted by downregulation were more likely to be involved in interoception. These findings suggest that upregulating and downregulating our emotions using cognitive reappraisal target different affective circuits in the brain rather than exerting opposing effects on the same emotion-generating brain regions. This dissociation between targeted brain regions raises the possibility that some individuals may excel at upregulating but not at downregulating their own emotions, or vice versa.
Footnotes
This work was supported by National Institutes of Health R01AG057184 to M.M. We thank our research assistants for help with data collection: Linette Bagtas, Akanksha Jain, Divya Suri, Sophia Ling, Michelle Wong, Yong Zhang, Vardui Grigoryan, and Gabriel Shih.
The authors declare no competing financial interests.
- Correspondence should be addressed to Mara Mather at mara.mather{at}usc.edu
