Training the emotional brain: improving affective control through emotional working memory training - PubMed (original) (raw)

Controlled Clinical Trial

Training the emotional brain: improving affective control through emotional working memory training

Susanne Schweizer et al. J Neurosci. 2013.

Abstract

Affective cognitive control capacity (e.g., the ability to regulate emotions or manipulate emotional material in the service of task goals) is associated with professional and interpersonal success. Impoverished affective control, by contrast, characterizes many neuropsychiatric disorders. Insights from neuroscience indicate that affective cognitive control relies on the same frontoparietal neural circuitry as working memory (WM) tasks, which suggests that systematic WM training, performed in an emotional context, has the potential to augment affective control. Here we show, using behavioral and fMRI measures, that 20 d of training on a novel emotional WM protocol successfully enhanced the efficiency of this frontoparietal demand network. Critically, compared with placebo training, emotional WM training also accrued transfer benefits to a "gold standard" measure of affective cognitive control-emotion regulation. These emotion regulation gains were associated with greater activity in the targeted frontoparietal demand network along with other brain regions implicated in affective control, notably the subgenual anterior cingulate cortex. The results have important implications for the utility of WM training in clinical, prevention, and occupational settings.

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Figures

Figure 1.

Figure 1.

A, Task design of the eWM training (dual _n_-back) task for a sample training block where _n_-back = 1. Stimuli with a bold pink border represent target stimuli for the current block. Participants respond with a button press if the target stimulus in either or both modalities matches the stimulus n positions back. In this _n_-back = 1 example, there is a match because, for the visuospatial modality, the current face appears in the same location as the face 1-position back; and for the auditory target, the word (RAPE) is the same as the word one-back. B, C, Task-demand-related BOLD activation that was observed comparing conditions of lower task-demand (_n_-back = 1) and higher task-demand (_n_-back = 3) at pre-training. All reported BOLD activation was significantly different across these conditions at the whole-brain level, with significance levels corrected for false discovery rates at PFDR < 0.05. Activation increases (B) and activation decreases (C) in condition _n_-back = 3 compared with _n_-back = 1. For a full overview of differential activation, see Table 1. Error bars indicate SEM.

Figure 2.

Figure 2.

A, The graph represents mean performance accuracy on target trials at the levels of _n_-back = 1, 2, 3, and 5 in the emotional and neutral blocks during the eWM task in the scanner at pre-training. Error bars indicate SE. B, The graph reports emotionality ratings across ER task conditions at pre-training. Emotionality (experienced distress) while viewing the film clips was rated on a Likert scale ranging from 1 (extremely positive) to 10 (extremely negative), with 5 (neutral). The conditions were as follows: Neutral, neutral film clips were presented with the instruction to attend to the films without effortful ER; Attend, aversive film clips were presented with the instruction to attend to the films without effortful ER; Regulate, aversive film clips were presented with the instruction to downregulate negative emotions elicited by the films. Error bars indicate SEM.

Figure 3.

Figure 3.

A, The graphs represent the eWM training (top graph) and placebo training (bottom graph) groups' performance on their respective tasks across training days. For the eWM training, the graph reports average level of _n_-back achieved across 20 blocks per day; and for the placebo training, a composite score (including raw score, number of attempts, and reaction time) on the feature match task is reported. Error bars indicate SD. B, The behavioral gains in eWM across training plotted as mean peak level of _n_-back achieved. A mixed-model ANOVA with time (pre-training and post-training) as the within-subjects factor and training (placebo, eWM) as the between-subjects factor yielded a significant interaction, which showed that the augmentation of eWM observed in the eWM training group was significantly greater than the change in the placebo training group (F(1,30) = 16.61, p < 0.001, longer dotted line). Repeated-measures analyses with time (pre-training, post-training) as the within-subjects factor were then conducted in the two groups separately. These revealed that the placebo training did not lead to any significant changes in eWM performance (Δ mean, −0.59; SD, 1.6; p = 0.18). In contrast, eWM training led to a significant pre-training to post-training increase in eWM performance (Δ mean, 1.59; SD, 1.2; p < 0.001, shorter dotted line). Moreover, eWM performance was significantly greater in the eWM training group compared with the placebo training group at post-training (t = −2.79 p = 0.009). ***p < 0.001, two-tailed significance level. Error bars indicate SDs. C, BOLD activation changes during the eWM task from pre-training to post-training conflated across all levels of _n_-back for the training groups. Significant interactions of training (placebo, eWM) × time (pre-training, post-training) are described in the main text. The absence of behavioral change after placebo training was mirrored by the absence of brain activation changes (left). In contrast, the behavioral gain in eWM after eWM training (right) was associated with decreased neural activation in the (I) left ventrolateral to dorsolateral PFC (Z = 4.10, −42/42/6), (II) bilateral inferior parietal cortex (Z = 4.87, −57/−48/39) and right precuneus (Z = 3.54, 12/−63/36), (III) inferior/middle temporal gyrus (Z = 5.76, 63/−33/−9), (IV) bilateral middle and posterior cingulum (Z = 3.74, −3/−24/33), and (V) left ACC (Z = 2.53, −1/10/25). All regions were significant at the whole brain with significance set at PFDR < 0.05.

Figure 4.

Figure 4.

A, The graph reports mean changes (post-training − pre-training) in emotion ratings for each condition; lower change scores indicate reduced negative affect after training in that condition. B, The graph represents the association between pre-training and post-training changes in ER capacity and changes in eWM. The association is negative because the ER measure represents the pre-training to post-training reduction in reported emotional distress, whereas eWM reports increases in maximum level of _n_-back achieved at the offline post-training assessment. C, The figure shows the differential effects of eWM training compared with placebo training across time for the Regulate versus Attend conditions in the left superior temporal gyrus. The figure is represented at Puncorrected < 0.001. Error bars indicate SEM. D, The graphs depict the effect of eWM training compared with placebo training across time (pre-training, post-training) for the Regulate versus Attend conditions on BOLD activation in the ROI. Error bars indicate SEM.

Figure 5.

Figure 5.

A, The figure shows brain areas that showed greater BOLD activation increases (a contrast of post-training − pre-training) in the Regulate relative to the Attend condition for the eWM training group only at the whole-brain level of analysis. The figure was thresholded at Puncorrected < 0.001. For a full list of activation details, see Table 8. B, The histograms depict mean BOLD activation during the ER task at pre-training and post-training in the regions reported in Figure 5_A_, which showed an interactive effect of time (pre-training, post-training) and condition (Regulate, Attend) in the eWM training group. Error bars indicate SEM.

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