Using an experimental medicine model to explore combination effects of pharmacological and cognitive interventions for depression and anxiety

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ABSTRACT Selective serotonergic reuptake inhibitors (SSRIs) and cognitive therapies are effective in the treatment of anxiety and depression. Previous research suggests that both forms of


treatments may work by altering cognitive biases in the processing of affective information. The current study assessed the effects of combining an SSRI with a cognitive intervention on


measures of affective processing bias and resilience to external challenge. A total of 62 healthy participants were randomly assigned to receive either 7 days of citalopram (20 mg) or


placebo capsules while also completing either an active or a control version of a computerized cognitive bias training task. After treatment, standard measures of affective processing bias


were collected. Participants’ resilience to external stress was also tested by measuring the increase in negative symptoms induced by a negative mood induction. Participants who received


both citalopram and the active cognitive bias training task showed a smaller alteration in emotional memory and categorization bias than did those who received either active intervention


singly. The degree to which memory for negative information was altered by citalopram predicted participants’ resistance to the negative mood induction. These results suggest that


co-administration of an SSRI and a cognitive training intervention can reduce the effectiveness of either treatment alone in terms of anxiety- and depression-relevant emotional processing.


More generally, the findings suggest that pinpointing the cognitive actions of treatments may inform future development of combination strategies in mental health. SIMILAR CONTENT BEING


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depression highlight the role of affective information-processing biases, such as the tendency to focus selectively on negative at the expense of positive information, in the etiology and


maintenance of disorders (Beck et al, 1985; Mathews and MacLeod, 2005). These models predict that interventions that reduce negative processing biases will improve symptoms of emotional


disorders by increasing resilience to challenging external events. Consistent with this proposal, antidepressant medications, which are effective in the treatment of anxiety and depression


(NICE, 2007, 2009), have been demonstrated to reduce negative and to increase positive biases in non-clinical groups (Harmer et al, 2003; Murphy et al, 2009). The medications seem to have a


very similar effect in clinical populations (Harmer et al, 2009; Tranter et al, 2009), suggesting that healthy volunteer studies may be usefully used as a model of the cognitive effects of


pharmacological treatments in patients and thus be useful in testing and developing new therapeutic interventions (Harmer, 2008; Harmer et al, 2011). Psychological treatments such as


cognitive behavioral therapy (CBT) have also been reported to influence these kinds of emotional processing measures (Mathews et al, 1995). In addition, more targeted and often implicit


cognitive training interventions (MacLeod et al, 2009) have recently been developed with the specific goal of reducing negative and increasing positive biases (see Figure 1c for a


description of a cognitive bias training task). These simple, computer-based training tasks have been found to alter processing biases (eg, in attention) in both non-clinical (Browning et


al, 2010b; MacLeod et al, 2002) and clinical groups (Amir et al, 2009) and, importantly, have also been found to reduce self-reported symptoms of anxiety and depression (Hakamata et al,


2010; Wells and Beevers, 2009). It is also more straightforward to devise neutral control tasks for training regimes than for complex psychotherapies, and thus training interventions lend


themselves much better to the controlled investigations of treatment mechanisms. The results reviewed above suggest that alteration of processing biases, from negative to positive, is a


common factor in the therapeutic effects of both pharmacological and cognitive treatments for emotional disorders (Browning et al, 2010a). In the current study, we extended this work by


examining how two specific forms of treatments interact; thus, we assessed whether combining a pharmacological and a cognitive treatment leads to an enhanced or diminished effect on


processing bias when compared with individually administered treatments. The mechanisms underlying treatment interactions are of obvious clinical interest as regimes combining


pharmacological and psychological interventions are a recognized treatment option in both depression and anxiety (NICE, 2007, 2009). Interestingly, although some evidence from clinical


trials in adults does suggest an acute advantage of combination over individually administered treatments (Keller et al, 2000), the advantage conferred seems to be somewhat inconsistent


(Cuijpers et al, 2009a; Foa et al, 2002; Furukawa et al, 2007; Pampallona et al, 2004), particularly when the psychological intervention is CBT (Cuijpers et al, 2009b). Indeed, there is


evidence to suggest that addition of antidepressants to CBT may reduce the durability of remission in panic disorder (Barlow et al, 2000). From a mechanistic perspective, the limited


clinical impact of combination regimes indicates that the two forms of treatment are unlikely to interact synergistically, rather it suggests that either they act independently or actively


interfere with each other. If, as hypothesized (Browning et al, 2010a), alterations of affective processing bias mediate the treatments’ clinical effects, then one of these patterns of


interaction (independence or interference) should be observed when the impact of combined treatment on affective processing is studied. This prediction was tested using a factorial


experimental design (see Figure 1b) in which non-clinical participants were administered 7 days of the selective serotonin reuptake inhibitor (SSRI) citalopram or a placebo while completing


either an active (positive) or a control cognitive bias training task, which was designed to alter attentional bias. In addition to measures of affective processing bias, the impact of


interventions on emotional resilience was assessed using subjective ratings of depression and anxiety in response to a negative mood induction. The specific predictions tested were that each


active intervention (ie, citalopram and positive cognitive bias training), when administered individually, would induce relatively positive processing biases and increase subsequent


emotional resilience. As discussed above, the results from clinical trials suggest that a synergistic interaction between treatments is unlikely; therefore, we hypothesized either no


interaction or active interference between the two interventions, although we had no strong rationale for selecting between these options. MATERIALS AND METHODS PARTICIPANTS A total of 64,


fluent English-speaking participants who were judged to be healthy on the basis of a medical screen and brief physical examination were recruited. Participants were also screened to exclude


current or previous axis I psychiatric disorder or alcohol/substance misuse using the Structured Clinical Interview for the DSM-IV (Spitzer et al, 2002). Other exclusion criteria included


taking any psychoactive medication, any significant neurological condition, familiarity with the tasks or stimuli used in the study, or any contraindication to taking SSRI medication. After


complete description of the study to participants, written informed consent to the study, which had been approved by a Local NHS Research Ethics Committee, was obtained. Participants were


randomized into one of the four treatment groups (see Figure 1b). Treatments were administered for 7 days. Participants were assessed immediately before and after treatment (see Figure 1a).


Two participants in the citalopram group experienced side effects (one nausea and one insomnia), which prevented completion of the study and resulted in data being available for 62


participants. For female participants, the study was completed outside the premenstrual week. QUESTIONNAIRE MEASURES Participants completed questionnaire assessments of depressive (Beck


Depression Inventory (Beck et al, 1961)) and anxious symptomatology (Trait subscale of the State-Trait Anxiety Inventory (Spielberger et al, 1983)) as well as state measures of anxiety


(state-STAI) and mood (Positive and Negative Affect Scale (PANAS); Watson et al, 1988) both before and after treatment. EXPERIMENTAL INTERVENTIONS _Pharmacological intervention._ All


participants were provided with 7 days supply of either citalopram 20 mg or lactose placebo capsules. The capsules were identical in appearance, and participants were instructed to take them


every morning, starting on the following morning and including the day of post-treatment assessment. _Cognitive bias training_. The cognitive bias training task used (Figure 1c) was a


computerized, face-based, visual-probe training (MacLeod et al, 2002), which has been developed to alter attentional bias to emotional information. Similar tasks have been found to improve


symptoms of anxiety and depression (Hakamata et al, 2010; Wells and Beevers, 2009). On the basis of the widely used dot-probe task (MacLeod et al, 1986), a pair of facial expressions


(Lundqvist et al, 1998; Matsumoto and Ekman, 1988; Tottenham et al, 2009), was briefly presented and followed by a probe (one or two dots), which appeared behind one of the faces. The faces


displayed positive (happy), neutral, or negative (fearful and angry) expressions with each trial of the task displaying faces from two different valences (vertical visual angle of stimuli


≈11°, vertical separation of stimuli ≈3.5°). This resulted in three possible face pair types: positive-neutral, positive-negative, and negative-neutral. The positive training condition


included a majority (87.5%) of trials in which the probe replaced the relatively positive face (ie, during negative-neutral trials, the neutral face is relatively more positive, whereas


during happy-neutral or happy-negative trials, the happy face is more positive). When completing the positive training, participants learn to deploy their attention toward the relatively


positive face as this predicts the probe location; that is, they develop a positive attentional bias. Control training was identical in every respect other than the location of the probe,


which was equally often found behind the positive and negative faces. A single session of the task involved two blocks of 48 trials each (each block included 16 trials of the three different


face pair combinations). The blocks differed in the duration of time the stimuli were presented (500 or 1000 ms). Previous studies of attentional bias training have tended to use a more


restricted range of stimuli valence and presentation durations. However, a concern with using only one type of training trial is that it will limit the degree to which the effects of


training generalize from the laboratory to real-world experiences, which is believed to be essential if training is to have a meaningful clinical effect (MacLeod et al, 2009). This concern


has prompted recent studies of attentional bias training to deploy various trial types (Hayes et al, 2010) and motivated the range of stimuli valence and presentation times used in the


current study. All participants completed the training sessions twice daily at home (Blackwell and Holmes, 2010) using a laptop computer, which was supplied to them for the duration of the


study. _Compliance with interventions._ Compliance with both pharmacological and bias training interventions was encouraged by providing participants with a log book in which they recorded


the date and time that medication had been taken and training completed. In addition, participants were contacted by researchers on three occasions during the treatment week to check whether


they were complying with the study protocol. ASSESSMENT TASKS _Emotional word categorization task; assessing emotional bias for self referential information._ In all, 60 personality


characteristics selected to be extremely disagreeable (eg, hostile) or agreeable (honest; taken from the study by Anderson (1968)) were presented on the computer screen for 500 ms. These


words were matched in terms of word length, ratings of frequency, and meaningfulness (Harmer et al, 2004). Participants were asked to categorize whether they would be pleased or upset if


they overheard someone else referring to them as possessing the characteristic described by the words, so that the judgment was in part self-referring. Categorization bias is estimated by


comparing the mean reaction times to categorize positive _vs_ negative words. _Emotional memory task; assessing memory bias._ Recognition and recall of the personality trait words presented


in the emotional word categorization task was also assessed (Harmer et al, 2004). During the recognition task, volunteers were asked to indicate whether they recognized the word for each


item on a list containing the 60 targets along with 60 matched distractors (30 likeable and 30 dislikeable). Recall was assessed simply by asking participants to list as many words as they


could remember from the categorization task. Memory bias is reflected in the relative number of positive _vs_ negative words correctly recognized or recalled. _Visual-probe task; assessing


attentional bias._ A face-based visual-probe task (MacLeod et al, 1986), was completed before and after treatment to ensure that the bias training intervention had altered attentional


function. The task was similar to the bias training task in that attention to a novel set of positive, negative, and neutral faces were assessed (the set of face stimuli used in training


_vs_ testing was counterbalanced between participants). During the task, probe location was balanced between the relatively more negative and positive stimuli, and deployment of attention


was assessed using blocks of trials in which the stimuli were presented for either 100 ms or for the durations used in training (500 and 1000 ms, order of blocks counterbalanced). This


resulted in a total of 144 trials. Importantly, this task is able to assess whether the attentional bias training produced, as expected, a generalized tendency to divert attention away from


negative and toward positive information as opposed to a more limited effect on a specific stimuli valence. The estimate of attentional bias is obtained by comparing the mean reaction time


when the probe replaces the relatively negative _vs_ positive face (Wilson and MacLeod, 2003). _Mood induction task; assessing emotional reactivity to external events._ To assess emotional


reactivity to external events, participants were required to complete a mood induction task (Clark, 1983; Velten, 1968). During the task (Holmes et al, 2009), participants listened to sad


music (Russia under the Mongolian Yoke by Prokofiev played at 50% normal speed) while reading negative self-referent statements on the computer screen (‘It seems such an effort to do


anything’). Such procedures have been reliably shown to produce increased negative mood in non-clinical groups (Clark, 1983). State measures of negative mood (negative-PANAS) and anxiety


(state-STAI) were taken before and after the task with the critical outcome being the change in these scores induced by the task. STATISTICAL ANALYSIS Mixed model analyses of variance


(ANOVAs) were constructed with the between-subject factors of medication (citalopram, placebo) and training (positive, control). This resulted in estimates of the effect of each active


intervention (ie, main effects of training and medication) and, critically, an interaction term (medication × training), which assesses for the presence of positive or negative interactions.


The emotional word categorization and memory tasks included a single within-subject factor, word valence (positive, negative). Addition of the within-subject factor of test time to the


analyses of the questionnaire measures, visual probe, and mood induction tasks allowed changes in these outcomes across time to be assessed. The visual probe task included additional


within-subject factors coding for the face pairs presented (positive-neutral, positive-negative, negative neutral). and the durations the face stimuli were presented for (100, 500, 1000 ms),


which allowed assessment of whether the training effect was influenced by any of these factors. Baseline questionnaire and demographic measures were analyzed using univariate ANOVAs. After


inspection of the data, extreme reaction times (outside 200–800 ms for the visual probe task and 200–1600 ms for the categorization task) were removed before calculating the mean. RESULTS


DEMOGRAPHIC AND BASELINE DATA The groups were well matched in terms of age, gender, and baseline scores on mood and anxiety measures (see Table 1), indicating that randomization had been


successful. There was no effect of either intervention or their interaction on change in any of the baseline measures listed in Table 1 (all _p_>0.14). EFFECTS OF INTERVENTIONS ON


EMOTIONAL BIASES _Emotional memory._ As shown in Figure 2a, the individual interventions of positive training plus placebo or control training plus citalopram produced a relative increase in


the number of positive _vs_ negative words recognized, compared with control training plus placebo. In contrast, co-administration of the interventions (positive training plus citalopram)


produced no change in memory bias at all. Thus, there was interference between the two interventions for the emotional memory task (Figure 2a; training × medication × emotion; F=5.1,


df=1,58, _p_=0.03). This effect on overall emotional bias was driven by a pronounced training × medication interaction for recognition of negative words (Figure 2b; F=12.6, df=1,58,


_p_=0.001), with a similar pattern being found, to a significantly reduced extent, for the recognition of positive words (not illustrated; F=4.4, df=1,58 _p_=0.04). _Post hoc_ analysis


(Figure 2b) revealed that each intervention on its own produced a significant reduction in the number of negative words recognized, whereas the combination of interventions produced no


change from baseline. Indeed, the combined intervention group displayed increased recognition memory for negative words when compared with the individual intervention groups. Analysis of the


number of words recalled, as opposed to recognized, revealed no significant effects of either intervention or their interaction (all _p_>0.38). _Emotional word categorization_. The speed


of word categorization also displayed an interference effect with a similar pattern to that displayed in word recognition (Figure 2c; training × medication × emotion; F=4.5, df=1,58,


_p_=0.04). Thus, participants who received a single active intervention displayed a decrease in the reaction time to categorize negative _vs_ positive words, whereas the combination group


displayed less effect. _Post hoc_ analysis comparing the differences between the groups did not reach statistical significance. DID BIAS TRAINING ALTER ATTENTIONAL FUNCTION? As expected,


positive attentional bias training, when compared with control training, led to a general increase in attentional bias toward positive faces (training × time × probe location; F=7.0,


df=1,58, _p_=0.01). This effect was not modified by the duration at which the stimuli were presented, the face pair types which were presented, or the medication group (all _p_>0.3). For


further analysis of the visual probe data, see Supplementary Methods. DID THE INTERVENTIONS ALTER RESILIENCE TO THE MOOD INDUCTION? Citalopram protected participants against the negative


effects of the mood induction task (Figure 3). Relative to participants who received placebo, those who took citalopram (NB both the citalopram control and citalopram-positive groups)


displayed a smaller average increase in negative-PANAS score (time × drug; F=6.9, df=1,58, _p_=0.01). The cognitive bias training group (positive _vs_ control) did not influence emotional


resilience (time × training; F=0.9, df=1,58, _p_=0.35) and there was no interaction between the interventions (time × drug × training; F=0.7, df=1,58, _p_=0.39). The results from the


emotional bias tasks suggest that the protective effect of citalopram should be eroded in the group which also completed positive bias training and, although an overall interaction effect


was not found in the omnibus ANOVA, inspection of Figure 3 suggests such a pattern. Statistical comparison of the citalopram control and citalopram-positive groups indicated that this


predicted effect was present at a trend level (F=3.6, df=1, 29, _p_=0.07). Participants’ anxious symptoms, as measured by the state-STAI, were not influenced by either intervention or their


interaction (all _p_>0.5). WERE THE COGNITIVE EFFECTS OF THE INTERVENTIONS RELATED TO THEIR EFFECTS ON EMOTIONAL REACTIVITY? If, as predicted (Harmer, 2008), the cognitive effects of the


interventions mediate their impact on emotional vulnerability, the emotional bias and vulnerability measures should correlate within a treatment group. Consistent with this, a significant


positive correlation within citalopram-treated participants was found between the number of negative words recognized during the memory task and the subsequent increase in the negative-PANAS


score induced by mood induction (_r_=0.44, _p_=0.01). No correlation was found between these measures for the positive bias training group (_r_=−0.29, _p_=0.39). DISCUSSION The current


study is the first to explore the interaction between an SSRI and positive cognitive bias training on biomarker measures relevant to depression and anxiety. In line with predictions,


concurrent administration of the pharmacological and psychological active interventions was found to produce an interference effect on measures of emotional memory and categorization bias.


Citalopram, but not positive bias training, was found to protect against the effects of the negative mood induction with the degree of protection being predicted by the extent to which the


drug reduced memory for negative words. These results provide a conceptual framework for starting to compare and understand the mechanisms of treatment associated with drugs on the one hand


and aspects of psychological therapy on the other, for emotional disorders. The current study used an experimental medicine model to test specific predictions about the mechanisms of


treatment interaction within a tightly controlled laboratory setting (Browning et al, 2010a). In line with previous work, both citalopram (Harmer et al, 2004; Murphy et al, 2009) and


positive cognitive bias training (Browning et al, 2010b; MacLeod et al, 2002) on their own produced relatively positive changes in emotional bias, consistent with the idea that this may be a


common process in treatments of emotional disorders (Harmer, 2008). However, the critical result from the current study is that combining the SSRI with training of positive emotional bias


reduced the effect of either alone. As suggested in the ‘Introduction’ section, this cognitive interference effect may provide a plausible mechanism for the modest clinical impact of such


combination treatments. More generally, it suggests that laboratory-based assessment of affective processing biases, which is sensitive to the effects of both pharmacological and


psychological interventions, presents a valuable opportunity to investigate the mechanisms underlying the interaction between disparate treatments for anxiety and depression. Using a


biomarker model, the results from the current study suggest that combining cognitive bias training of attention with an SSRI may not be a useful intervention strategy for depression and


anxiety. Such an effect is consistent with the hypothesis that intact amygdala function is necessary for cognitive bias training to occur and that SSRIs interfere with training by impairing


amygdala function (Browning et al, 2010a). However, this mechanism does not explain why cognitive bias training was also found to interfere with the effects of citalopram. If replicated,


such a pattern of results may indicate that generalization of the effect of SSRIs to measures of mood and emotional memory only occur when the medication is able to influence participants’


interpretation of emotionally ambiguous events. In other words, if individuals are presented only with positive information (as is the case with positive training), there may be no


opportunity for the medication to alter a maladaptive appraisal of the information and thus to improve mood. It is difficult to generalize these results to the combination of SSRIs with full


therapist-delivered CBT. However, adopting an experimental psychopathology approach to CBT suggests that it can be decomposed into theory-driven constituent parts, which may be individually


tested. Given this, alteration of attentional processing bias, modeled in the current study using the bias training task, is likely to be only one of the many mechanisms by which complex


psychotherapies such as CBT improve mood and anxiety and thus, other facets of CBT may be independent of, or even interact synergistically with, SSRIs. For example, although the current


cognitive training regime has targeted attentional bias, it would be interesting to consider whether alteration of the other key biases associated with anxiety and depression, such as


interpretation bias (Mathews and MacLeod, 2005), may complement the effects of SSRIs. More broadly, other forms of pharmacotherapy may interact positively with cognitive bias training


regimes. Indeed, an interesting recent study provides some evidence that D-cycloserine may enhance the basic attentional bias training effect (Behar et al, 2010). Perhaps the most promising


application of the experimental approach used in the current study will involve identifying the specific combinations of pharmacological and psychological interventions which complement each


other, and then testing whether treatment regimes that show potential in the laboratory go on to deliver benefit in the clinic. Citalopram, but not positive cognitive bias training, was


found to protect participants from the effects of a negative mood induction. This is the first demonstration, to our knowledge, that an SSRI can protect healthy volunteers from the effects


of negative mood induction in the laboratory and critically, this effect was predicted by the degree to which the medication reduced memory for negative words. Therefore, these results are


consistent with the proposal that alterations in affective processing mediate the therapeutic effect of the medication (Harmer, 2008). However, contrary to expectations, the change in bias


produced by cognitive training was not sufficient to alter mood resilience and did not mimic the protective effects of the SSRI. A possible explanation for this lack of effect is that the


negative mood induction procedure used in the current study may be more suited to investigating depressive rather than anxious vulnerability. Consistent with this, the protective effect of


citalopram was evident on a scale of negative affect (the negative-PANAS) rather than a specific measure of anxiety (state-STAI). Although there is evidence that attentional cognitive bias


training does ameliorate symptoms of depression, this literature is less consistent (Baert et al, 2010; Wells _et al_, 2009) than that demonstrating an anxiolytic effect (Hakamata et al,


2010). Thus, the specific emotional challenge used may not be optimal in detecting the impact of training on subjective emotional experience. Finally, some of the caveats in interpreting the


results of this study should be acknowledged. We have suggested that our results may have clinical implications; however, extrapolating these laboratory results to the clinic requires two


assumptions. First, it assumes that the degree of affective bias change induced by a treatment is a reasonable proxy for the clinical efficacy of that treatment, and second, it assumes that


the cognitive effects of the interventions demonstrated in this study of healthy volunteers are an accurate reflection of their effects in clinical populations. Support for these assumptions


is provided by previous work, which has demonstrated that the initial effects of antidepressants on affective bias predict later clinical response (Tranter et al, 2009) and by the


similarity between the effects of the treatments on affective biases in non-clinical and clinical populations (Harmer et al, 2004, 2009). Furthermore, the finding that the cognitive effects


of citalopram predicted its protective effect during the mood induction task supports a link between affective bias and subjective mood. However, a more direct test of these assumptions


would obviously be provided by replicating the current findings in a clinical sample. A second caveat is that the stability and persistence of any cognitive bias training is likely to be


influenced both by the reliability of the measures of cognitive bias (see Supplementary Materials and Schmukle, 2005) and by the variability in the induced bias itself (MacLeod et al, 2009;


Schlam, 2008). As our study was designed to test the immediate impact of interventions on cognitive functioning and mood reactivity, we did not assess the degree to which the induced biases


persisted and remained stable after completion of the treatment. Future studies may be able to address this limitation by retesting the effects of the treatments at later time points. Third,


we monitored compliance with the pharmacological aspect of treatment using participants’ self-report only. It would have been reassuring also to have access to serum citalopram levels to


objectively confirm compliance. Fourth, we did not collect detailed information on participants’ family history of depression. Given the previous finding that this factor is associated with


more pronounced negative mood effects of tryptophan depletion (Klaassen et al, 1999), it would be interesting to investigate whether it also mediated the protective effects of citalopram


found during the mood induction task. Finally, it should also be acknowledged that the sample sizes used in the study were relatively modest. Thus, although the study was able to identify


significant interactions between the two treatments, other treatment effects may not have been detected because of insufficient power. The current study has used an experimental medicine


approach to investigate how specific psychological and pharmacological interventions for the emotional disorders interact at the cognitive level. The results suggest that active interference


occurs between these two interventions such that administering them concurrently produces a smaller effect than when they are administered separately. This provides a plausible conceptual


framework for beginning to investigate the modest clinical results seen when the two forms of treatment are combined in clinical settings and suggests that pinpointing the cognitive actions


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Article  Google Scholar  Download references ACKNOWLEDGEMENTS This research was supported by a Wellcome Trust Fellowship to Dr Browning (081672). Dr Holmes was supported by a Wellcome Trust


Clinical Fellowship (088217). AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Department of Psychiatry, University of Oxford, Oxford, UK Michael Browning, Maud Grol, Verena Ly, Guy M Goodwin,


 Emily A Holmes & Catherine J Harmer Authors * Michael Browning View author publications You can also search for this author inPubMed Google Scholar * Maud Grol View author publications


You can also search for this author inPubMed Google Scholar * Verena Ly View author publications You can also search for this author inPubMed Google Scholar * Guy M Goodwin View author


publications You can also search for this author inPubMed Google Scholar * Emily A Holmes View author publications You can also search for this author inPubMed Google Scholar * Catherine J


Harmer View author publications You can also search for this author inPubMed Google Scholar CORRESPONDING AUTHOR Correspondence to Michael Browning. ETHICS DECLARATIONS COMPETING INTERESTS


GMG has held grants from Bailly Thomas, Sanofi-Aventis, and Servier, received honoraria for speaking or chairing educational meetings from AstraZeneca, Bristol-Meyers Squibb, Eisai,


Lundbeck, Sanofi-Aventis, and Servier, and advised AstraZeneca, Bristol-Meyers Squibb, Boehringer Ingelheim, Cephalon, Hoffman-Laroche, Janssen-Cilag, Lilly, Lundbeck, P1vital, Roche,


Sanofi-aventis, Shering Plough, Servier, and Wyeth. He holds shares in P1vital and acted as expert witness for Lilly and Servier. CJH is on the advisory board of P1vital Ltd and holds shares


in this company. She is a company director and holds shares in Oxford Psychologists Ltd. The other authors declare no conflict of interest. ADDITIONAL INFORMATION Supplementary Information


accompanies the paper on the Neuropsychopharmacology website SUPPLEMENTARY INFORMATION SUPPLEMENTARY INFORMATION (DOC 112 KB) POWERPOINT SLIDES POWERPOINT SLIDE FOR FIG. 1 POWERPOINT SLIDE


FOR FIG. 2 POWERPOINT SLIDE FOR FIG. 3 RIGHTS AND PERMISSIONS This work is licensed under the Creative Commons Attribution-NonCommercial-Share Alike 3.0 Unported License. To view a copy of


this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/ Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Browning, M., Grol, M., Ly, V. _et al._ Using an


Experimental Medicine Model to Explore Combination Effects of Pharmacological and Cognitive Interventions for Depression and Anxiety. _Neuropsychopharmacol_ 36, 2689–2697 (2011).


https://doi.org/10.1038/npp.2011.159 Download citation * Received: 11 April 2011 * Revised: 02 July 2011 * Accepted: 08 July 2011 * Published: 10 August 2011 * Issue Date: December 2011 *


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currently available for this article. Copy to clipboard Provided by the Springer Nature SharedIt content-sharing initiative KEYWORDS * SSRI * anxiety * depression * emotional processing *


cognitive bias * memory