ارتباطات عصبی پردازش عاطفی تغییر یافته پس از رفتاردرمانی شناختی با ارائه اینترنت برای اختلال اضطراب اجتماعی
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|30145||2014||9 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Psychiatry Research: Neuroimaging, Psychiatry Research: Neuroimaging
Randomized controlled trials have yielded promising results for internet-delivered cognitive behavior therapy (iCBT) for patients with social anxiety disorder (SAD). The present study investigated anxiety-related neural changes after iCBT for SAD. The amygdala is a critical hub in the neural fear network, receptive to change using emotion regulation strategies and a putative target for iCBT. Twenty-two subjects were included in pre- and post-treatment functional magnetic resonance imaging at 3T assessing neural changes during an affective face processing task. Treatment outcome was assessed using social anxiety self-reports and the Clinical Global Impression-Improvement (CGI-I) scale. ICBT yielded better outcome than ABM (66% vs. 25% CGI-I responders). A significant differential activation of the left amygdala was found with relatively decreased reactivity after iCBT. Changes in the amygdala were related to a behavioral measure of social anxiety. Functional connectivity analysis in the iCBT group showed that the amygdala attenuation was associated with increased activity in the medial orbitofrontal cortex and decreased activity in the right ventrolateral and dorsolateral (dlPFC) cortices. Treatment-induced neural changes with iCBT were consistent with previously reported studies on regular CBT and emotion regulation in general.
Social anxiety disorder (SAD), also referred to as social phobia, is a debilitating psychiatric condition characterized by excessive and persistent fear and concerns about embarrassment and humiliation from others (American Psychiatric Association, 2000). It is a common condition with a lifetime prevalence of around 13% (Fehm et al., 2005 and Kessler et al., 2005). SAD often precedes other complications such as depression (Beesdo et al., 2007), alcohol and drug use disorders (Grant et al., 2005), and it is associated with considerable societal costs (François et al., 2010). Many sufferers do not seek treatment (Baldwin and Buis, 2004) despite that effective pharmacological (Ravindran and Stein, 2010) and psychological (Acarturk et al., 2009) treatment exists. Internet-delivered cognitive behavior therapy (iCBT) has been demonstrated to be efficacious in at least fifteen controlled trials of SAD (Andersson et al., 2012). Effectiveness studies conducted in clinical settings have also provided evidence for this treatment approach (Hedman et al., 2011a). Effect sizes over the short term have been moderate to large (Andersson et al., 2006, Carlbring et al., 2007 and Furmark et al., 2009), and treatment gains have been maintained at long-term follow-ups (Carlbring et al., 2009 and Hedman et al., 2011b). The treatment is evidence-based, standardized and relatively easy to set-up, making it suitable for functional brain imaging research. Moreover, there is an extensive literature on attentional biases in emotional disorders (MacLeod et al., 1986), suggesting that altering this bias reduces anxiety (MacLeod and Mathews, 2012). Faster response towards threat-relevant information in relation to neutral stimuli is regarded as a bias. In attention bias modification (ABM) the participant learns to redirect attention away from threats, such as facial expressions of fear or disgust. ABM have been suggested to share a therapeutic mechanism with CBT (MacLeod and Mathews, 2012). In a study by Schmidt et al. (2009), 72% of the participants in the treatment group as compared to 11% in the control condition, no longer met the criteria for SAD following ABM. These results were maintained at a 4-month follow-up assessment. Two meta-analyses have demonstrated small to medium effect sizes of ABM for anxiety disorders (Hakamata et al., 2010 and Hallion and Ruscio, 2011). However, these promising results have not yet been replicated when the same treatment has been delivered via the internet when comparing to placebo conditions (Boettcher et al., 2011, Carlbring et al., 2012 and Neubauer et al., 2013). Therefore, in the present study, we used the internet-delivered ABM as a control treatment. Studying brain mechanisms and associated behavioral changes after treatment could further enhance knowledge about the maintenance of SAD and improve the specificity of interventions. The most consistent finding in neuroimaging studies of SAD is that the disorder is associated with exaggerated activity in the amygdala (Freitas-Ferrari et al., 2010). The amygdala is part of a fear circuit involved in detecting threat signals and coordinating autonomic responses (LeDoux, 2000). In addition, the prefrontal cortex acts in concert with subcortical regions involved in emotional expressions (Barbas et al., 2003), and is crucial for emotion regulation (Hartley and Phelps, 2009 and Ochsner and Gross, 2005), extinction learning (Phelps et al., 2004) and resolving emotional conflicts (Etkin et al., 2006). Prior studies have highlighted the orbitofrontal (OFC), ventromedial (vmPFC) and rostral anterior cingulate (rACC) cortices to be involved in regulation of emotional responses (Etkin et al., 2011, Hartley and Phelps, 2009, Milad et al., 2007 and Milad and Rauch, 2007). Prefrontal regions may be directly or indirectly connected to the amygdala, and are able to exert inhibitory influences. Regions within the OFC and ACC have the densest connections to the amygdala, accounting for about half of all the prefrontal projecting neurons (Ghashghaei et al., 2007). Hence, it is of particular interest to study if these regions are involved in therapeutic change by psychological interventions. Viewing emotionally valenced faces has been shown to reliably activate the amygdala in patients with SAD (Lira Yoon et al., 2007, Stein et al., 2002 and Straube et al., 2004), and severity of symptoms predicts the amygdala activation to negative faces (Evans et al., 2008, Goldin et al., 2009a and Phan et al., 2013). Affective face processing tasks have also been used as predictors for outcome of CBT for SAD (Doehrmann et al., 2013 and Klumpp et al., 2013), and the pharmacological treatment of anxiety (Whalen et al., 2008). A neuroimaging study of SAD by Furmark et al. (2002) reported that responders to CBT delivered in group, and to selective serotonin reuptake inhibitors (SSRIs) both resulted in decreased anxiety-related reactivity in the amygdala after treatment. Phan et al. (2013) also noted reduced amygdala reactivity to fearful faces after SSRI treatment although this was not related to social anxiety symptom improvement. The present study aimed to investigate neural changes, measured during an emotional face processing task (Hariri et al., 2002), following internet-delivered CBT for SAD in comparison to an active control condition using ABM. We used functional magnetic resonance imaging (fMRI) before and after the treatments to explore therapeutic effects on functional neural responses. We hypothesized that a positive treatment outcome would be associated with attenuated amygdala reactivity. Within iCBT we also investigated concomitant activation changes of the prefrontal cortex that might exert regulatory effects on the amygdala. We expected to find increased activity in prefrontal regions (e.g. dlPFC, mOFC, rACC, vmPFC) in relation to decreases in amygdala.
نتیجه گیری انگلیسی
3. Results 3.1. Behavioral results Pretreatment differences: there were no statistically significant differences between the two treatment groups with regards to demographics or pretreatment self-report measures (all p's>0.15); see also Supplementary Table S1. No differences were found in pretreatment LSAS-SR scores between subjects who completed the study and excluded participants (n=4; t(24)=0.95, p>0.35). Treatment outcome: repeated measurement ANOVA of LSAS-SR data revealed a significant main effect of time (F(2,22)=37.33, p<0.001), but no significant time × group interaction, F(2,22)=0.84, p=0.37 (see also Supplementary Table S1). Moderate to large within-group effect sizes (Cohen's d) were observed on LSAS-SR, d=0.91 (CI 95% 0.44–1.37) for iCBT, and d=1.08 (CI 95% 0.43–1.74) for ABM. A repeated measure MANOVA including all social anxiety self-reports (LSAS-SR, SIAS, SPS and SPSQ) revealed a significant multivariate time × group interaction effect, Wilks's λ=0.535, F(4,19)=4.13, p=0.01 (see also Supplementary Table S1), suggesting a differential treatment outcome in favor of iCBT. Also, the number of CGI-I responders was significantly higher (χ2(1)=4.20, p=0.04) in the iCBT group, having eight (66%) responders as compared to three (25%) in the ABM control group. Response times and subjective ratings: regarding reaction times to the emotional face processing task, there were no significant interaction effects (time × group) for the different facial expressions (F(1,20)=1.16–3.44, all p's>0.08). Analyses of all faces combined revealed a trend-level interaction effect (F(1,20)=3.82, p=0.065) suggesting faster responses when matching faces after ABM (Mpost=1 174.19 ms, S.D.=219.12) compared to iCBT (Mpost=1 250.34 ms, S.D.=208.29). We also analyzed self-reported fear and distress during brain image acquisition and found no interaction (time×group), nor main effects (F(2,20)=0.00–2.60, all p's>0.12) before or after treatment. 3.2. fMRI results Pretreatment effects: as expected, we found that the fMRI task robustly activated the amygdala in a full sample analysis before treatment (left amygdala xyz [–30,–4,–20], Z=3.32, pFWE=0.009, 513 mm3; right amygdala xyz [24,–7,–14], Z=3.39, pFWE=0.008, 837 mm3). We found no significant pretreatment differences in bilateral amygdala reactivity between iCBT and ABM; t(20)=−0.17 to 0.32, all p's>0.75. Within-group treatment effects: changes in LSAS-SR-related amygdala reactivity were nonsignificant at the corrected level within both treatment modalities. At a more lenient statistical threshold, activity in the left amygdala decreased (pre>post) with iCBT while the reverse pattern (preTable 2). Whole-brain analyses revealed decreases in the caudate, cerebellum, dlPFC, putamen and rACC with iCBT whereas the ABM group increased in the postcentral gyrus, putamen, supplementary motor area (SMA) and superior temporal lobe ( Table 2). Table 2. Anxiety-related neural changes within and between-groups. Contrast and brain regions MNI Coordinates MaximumZvalue Volume (mm3) pvalue x y z iCBT (pre>post) L Amygdala (ROI) –21 –1 –11 2.68 189 0.07# L Caudate –18 8 19 3.25 27 0.001 L Cerebellum –42 –76 –29 3.31 27 <0.001 R Cerebellum 39 –64 –29 3.26 108 0.001 L dlPFC, BA 9 –27 38 34 3.59 243 <0.001 L Putamen –18 23 –5 5.16 513 <0.001 R Putamen 18 14 –11 3.46 162 <0.001 R rACC, BA 32 3 35 –2 3.11 27 0.001 iCBT (pre<post) ns ABM (pre>post) ns ABM (pre<post) L Amygdala (ROI) –27 –7 –11 2.26 216 0.13# R Amygdala (ROI) 24 –7 –14 2.23 324 0.15# R Postcentral gyrus, BA 4 45 –16 40 3.09 27 0.001 L Putamen –24 –1 10 3.14 135 0.001 R Putamen 24 8 10 3.84 486 <0.001 L SMA, BA 6 –12 20 61 3.13 27 0.001 L Temporal superior, BA 13 –54 –40 16 3.78 216 <0.001 ABM>iCBT L Amygdala (ROI) –27 –7 –11 2.98 378 0.03# R Amygdala (ROI) 27 –1 –11 2.08 351 0.20# L Cerebellum –24 –61 –47 3.41 216 <0.001 R Cerebellum 45 –58 –29 3.24 27 0.001 R Corpus callosum/Cingulate cortex 9 –13 28 3.29 27 0.001 L Postcentral gyrus, BA 4 –42 –19 43 3.18 54 <0.001 L Putamen –24 2 7 3.91 5 022 <0.001 R Putamen 27 8 10 4.12 837 <0.001 R Thalamus 18 –13 10 3.28 162 0.001 Abbreviations: ABM, attention bias modification; BA, Brodmann Area; dlPFC, dorsolateral prefrontal cortex; FWE, family wise error corrected; iCBT, internet-delivered cognitive behavior therapy; L, left; MNI, Montreal Neurological Institute; ns, non significance; R, right; rACC, rostral anterior cingulate cortex; ROI, region of interest; SMA, supplementary motor area; #, Family-wise error corrected (FWE) p-value Table options Differential treatment effects: between-group analysis indicated a significant time × group interaction, i.e. a different neural change (post compared to pre), in the left amygdala with decreased reactivity in iCBT in relation to ABM subjects ( Table 2, Fig. 2). Whole-brain analyses further showed that activity in the cerebellum, postcentral gyrus, putamen and thalamus decreased with iCBT, relative to increases with ABM, yielding significant interaction (group by time) effects, see Table 2. Full-size image (32 K) Fig. 2. Differential treatment response in the left amygdala (p<0.05, FWE corrected) with decreased reactivity after iCBT in relation to the active control ABM. Plots show amygdala change scores in relation to corresponding symptom changes according to the Liebowitz Social Anxiety Scale, self-report version (LSAS-SR). Figure options Functional connectivity: multiple regression analyses indicated that changes within the mOFC were significantly negatively correlated with left amygdala changes in the iCBT group (Supplementary Figure S1). Thus, increased activity in mOFC after treatment was linked to reduced amygdala reactivity. Activity within the right ventrolateral (vlPFC; Supplementary Figure S2) and dlPFC decreased in concert with attenuated left amygdala responses, i.e. a positive correlation ( Table 3). Table 3. Left amygdala functional connectivity within iCBT. Contrast and brain regions MNI Coordinates MaximumZvalue Volume (mm3) pvalue x y z iCBT L Amygdala, negative correlations R mOFC, BA 11 3 56 –11 3.39 27 <0.001 L Amygdala, positive correlations R dlPFC, BA 9/10 36 41 28 3.69 783 <0.001 R vlPFC, BA 10 42 53 −2 3.41 162 <0.001 Mean activity in the left amygdala seed was used as regressor within iCBT. Abbreviations: BA, Brodmann Area; dlPFC, dorsolateral prefrontal cortex; iCBT, internet-delivered cognitive behavior therapy; L, left; MNI, Montreal Neurological Institute; mOFC, medial orbitofrontal cortex; R, right; vlPFC, ventrolateral prefrontal cortex.