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Original Investigation |

Toward a Neuroimaging Treatment Selection Biomarker for Major Depressive Disorder FREE

Callie L. McGrath, BA1,2; Mary E. Kelley, PhD3; Paul E. Holtzheimer III, MD5; Boadie W. Dunlop, MD1; W. Edward Craighead, PhD1; Alexandre R. Franco, PhD6; R. Cameron Craddock, PhD7,8; Helen S. Mayberg, MD1,4
[+] Author Affiliations
1Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, Georgia
2Graduate Division of Biological and Biomedical Sciences, Emory University, Atlanta, Georgia
3Department of Biostatistics and Bioinformatics, Emory University, Atlanta, Georgia
4Department of Neurology, Emory University, Atlanta, Georgia
5Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire
6Department of Electrical Engineering and Brain Institute, Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil
7Center for the Developing Brain, Child Mind Institute, New York, New York
8Nathan Kline Institute for Psychiatric Research, Orangeburg, New York
JAMA Psychiatry. 2013;70(8):821-829. doi:10.1001/jamapsychiatry.2013.143.
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Published online

Importance  Currently, fewer than 40% of patients treated for major depressive disorder achieve remission with initial treatment. Identification of a biological marker that might improve these odds could have significant health and economic impact.

Objective  To identify a candidate neuroimaging “treatment-specific biomarker” that predicts differential outcome to either medication or psychotherapy.

Design  Brain glucose metabolism was measured with positron emission tomography prior to treatment randomization to either escitalopram oxalate or cognitive behavior therapy for 12 weeks. Patients who did not remit on completion of their phase 1 treatment were offered enrollment in phase 2 comprising an additional 12 weeks of treatment with combination escitalopram and cognitive behavior therapy.

Setting  Mood and anxiety disorders research program at an academic medical center.

Participants  Men and women aged 18 to 60 years with currently untreated major depressive disorder.

Intervention  Randomized assignment to 12 weeks of treatment with either escitalopram oxalate (10-20 mg/d) or 16 sessions of manual-based cognitive behavior therapy.

Main Outcome and Measure  Remission, defined as a 17-item Hamilton Depression Rating Scale score of 7 or less at both weeks 10 and 12, as assessed by raters blinded to treatment.

Results  Positive and negative predictors of remission were identified with a 2-way analysis of variance treatment (escitalopram or cognitive behavior therapy) × outcome (remission or nonresponse) interaction. Of 65 protocol completers, 38 patients with clear outcomes and usable positron emission tomography scans were included in the primary analysis: 12 remitters to cognitive behavior therapy, 11 remitters to escitalopram, 9 nonresponders to cognitive behavior therapy, and 6 nonresponders to escitalopram. Six limbic and cortical regions were identified, with the right anterior insula showing the most robust discriminant properties across groups (effect size = 1.43). Insula hypometabolism (relative to whole-brain mean) was associated with remission to cognitive behavior therapy and poor response to escitalopram, while insula hypermetabolism was associated with remission to escitalopram and poor response to cognitive behavior therapy.

Conclusions and Relevance  If verified with prospective testing, the insula metabolism-based treatment-specific biomarker defined in this study provides the first objective marker, to our knowledge, to guide initial treatment selection for depression.

Trial Registration  Registered at clinicaltrials.gov (NCT00367341)

Figures in this Article

Major depressive disorder (MDD) is a highly prevalent, disabling, and costly illness.13 For a patient presenting with MDD, an antidepressant medication or evidence-based psychotherapy is currently recommended as first-line treatment.47 However, fewer than 40% of patients achieve remission with initial treatment,8,9 and choosing the “wrong” initial treatment has significant individual and societal costs due to continued distress, risk of suicide, loss of productivity, and wasted resources associated with 2 to 3 months of an ineffective treatment.10,11 Given the public health consequences of inadequately treated depression, a clinical or biological marker to guide initial treatment selection for MDD could have major health and economic impact.12

In other areas of medicine, identification of markers to guide treatment has significantly improved clinical outcome. For example, in cancer13 and heart disease,14 biomarkers are currently used to optimize initial treatment selection as well as guide treatment modifications with disease progression. Over the past several decades, a number of potential markers to guide antidepressant treatment have been investigated including clinical,15 immune,16 inflammatory,17 endocrine,18 genetic,1921 and imaging/electroencephalography2227 measures. Despite this extensive research, to our knowledge, no clinically useful marker to guide treatment selection has emerged.

In the process of developing a marker to guide antidepressant treatment selection, it is important to consider what qualities such a marker should have. Toward this goal, a nonspecific biomarker that predicts improvement regardless of treatment is not useful. Rather, a clinically meaningful and treatment-specific biomarker (TSB) should (1) predict an individual’s improvement to a specific treatment and (2) predict nonresponse to an alternative treatment. Such a biomarker can only be identified in a study that assesses outcome to 2 or more different treatments.

Previous neuroimaging studies have suggested that pretreatment brain activity patterns can predict efficacy, but those studies have generally focused on a particular treatment.26,27 For example, higher rostral cingulate and/or subgenual cingulate activity has been associated with greater improvement with antidepressant medications,28,29 sleep deprivation,30 and cingulotomy.31 Comparisons of different treatments have thus far identified markers of response and nonresponse but not patterns that differentiate among the treatments tested.22,32,33 Further, imaging studies demonstrate that medications and psychotherapy have differential effects on distinct brain regions,23,34 suggesting that baseline activity may indicate response to one treatment vs the other. Although, to our knowledge, no prior imaging study has directly assessed the association of pretreatment brain activity patterns with differential response to different treatments (eg, medication vs psychotherapy), these past studies strongly suggest that a neuroimaging-based TSB can be defined.

In this study, we measured pretreatment brain glucose metabolism in patients with MDD randomized to receive a selective serotonin reuptake inhibitor (escitalopram oxalate) or cognitive behavior therapy (CBT).35,36 Positron emission tomography (PET) scan measurement of glucose metabolism was selected based on its high reliability and availability combined with its established use for studies of baseline scan patterns in depression and effects of various antidepressant treatments.22,23,28,34,3743 Our aim was to define an imaging TSB for these 2 potential first-line treatments, ie, a brain activity pattern that distinguishes escitalopram remitters from both escitalopram nonresponders and CBT remitters while concurrently distinguishing CBT remitters from both CBT nonresponders and escitalopram remitters.

Patient Selection

Written informed consent was obtained from all participants, with the protocol conducted as approved by the Emory institutional review board and registered at clinicaltrials.gov (NCT00367341). Eligible participants were adult outpatients with a primary diagnosis of MDD as assessed by the Structured Clinical Interview for DSM-IV-TR Axis I Disorders, Research Version, Patient Edition With Psychotic Screen44 and confirmed through a psychiatric evaluation conducted by a study psychiatrist. Patients aged 18 to 60 years were recruited through the Mood and Anxiety Disorders Program at Emory University via advertisements and clinician referrals.45 Patients were required to have moderate to severe symptoms of depression, defined as a 17-item Hamilton Depression Rating Scale (HDRS)46 score of 18 or more at screening and 15 or more at the baseline randomization visit. Exclusion criteria included a current diagnosis of a primary psychiatric disorder other than MDD; a medical or neurological condition that could contribute to depression or that might interfere with response to treatment such as chronic pain syndromes and irritable bowel syndrome; current suicidal ideation requiring urgent clinical intervention; comorbid substance abuse within the past 3 months; substance dependence within 12 months prior to the screening visit; current or intended pregnancy or breastfeeding; use of antidepressants within 7 days of the screening visit (5 weeks for fluoxetine); current psychotherapy at the time of screening; or receipt of electroconvulsive therapy within 6 months of the screening visit. Patients were also excluded if they had a lifetime history of failure to respond to 6 or more weeks of treatment with escitalopram oxalate (≥10 mg/d) or 4 or more sessions of CBT for depression.

Treatment Protocol

Treatment consisted of 2 phases: a short-term treatment phase (phase 1) and a combination treatment phase (phase 2). Phase 1 provided the data for this report. In phase 1, patients were randomly assigned (1:1 ratio) to receive a 12-week treatment course of either escitalopram oxalate (flexibly dosed from 10-20 mg/d) or manual-based, depression-focused CBT (16 one-hour sessions over 12 weeks) (Figure 1). Prior to study start, the study statistician prepared a permuted-block randomization schedule, with the assignments placed in order and sealed in opaque envelopes. Following acquisition of the pretreatment PET and magnetic resonance imaging scans, patients who continued to meet eligibility criteria were randomized to escitalopram or CBT. Escitalopram oxalate was started at 10 mg/d and could be increased to 20 mg/d at or after week 3 if the patient had an HDRS score more than 7 and was tolerating the medication. Down-titration to 10 mg/d was permitted if adverse effects were intolerable at the 20–mg/d dose. The CBT sessions were scheduled twice weekly for the first 4 weeks, followed by weekly sessions for the subsequent 8 weeks. Changes in symptom severity were assessed using the HDRS conducted by raters blinded to treatment group. Ratings were performed weekly for the first 6 weeks and then biweekly until week 12. Patients who did not remit on completion of their phase 1 treatment were offered enrollment in phase 2 comprising an additional 12 weeks of treatment with combination escitalopram and CBT.

Place holder to copy figure label and caption
Figure 1.
Study Design and Outcomes

Outcome groups defined by Hamilton Depression Rating Scale (HDRS) scores. Remission was defined as an HDRS score of 7 or less; partial response, as an HDRS score decrease of more than 30% but not achieving remission; and nonresponse, as an HDRS score decrease of 30% or less. Escitalopram was given as escitalopram oxalate. CBT indicates cognitive behavior therapy and PET, positron emission tomography.

Graphic Jump Location
Outcome Metrics

Clinical outcomes were defined using the HDRS, with the target end point being remission, defined as an HDRS score of 7 or less at both weeks 10 and 12 of phase 1 treatment,47 to ensure stability of remission beyond a single “good week.” Nonresponse was defined as a 30% or less HDRS score change from baseline to the phase 1 end point.48 Partial responders (change in HDRS score >30% but not achieving remission) and dropouts were not included in the analyses for this report to avoid potential dilution of either the remission or the nonresponse groups.

Imaging Acquisition

Prior to treatment randomization, brain glucose metabolism was measured using PET (High-Resolution Research Tomograph scanner; Siemens), using standard methods without arterial blood sampling.49 For each scan, a 370-MBq dose of fludeoxyglucose F18 (FDG) was administered intravenously, with a 20-minute 3-dimensional image acquisition beginning 40 minutes after tracer injection. During uptake, patients remained supine, awake, and resting with eyes closed and ears uncovered. Patients were given no explicit cognitive instructions but were asked to avoid ruminating on any 1 topic during the 40-minute FDG uptake period.21 Raw emission images were corrected for injected dose and attenuation (using cesium 137, 6-minute transmission scan), reconstructed, and smoothed to an in-plane resolution of 4.0 mm Full-Width Half-Maximum.34 A high-resolution T1-weighted structural magnetic resonance imaging scan was separately acquired for spatial normalization procedures and anatomical reference (TIM Trio 3-T whole-body scanner; Siemens) (3-dimensional magnetization-prepared rapid acquisition with gradient echo optimized at echo time = 5 milliseconds, repetition time = 35 milliseconds, matrix = 256 × 208 × 196, and 1-mm isotropic resolution).

Image Preprocessing

Attenuation-corrected PET images were coregistered to corresponding T1-weighted magnetic resonance imaging anatomical images using a 6-df linear transform and subsequently written into standard space using a nonlinear transform calculated from the T1-weighted image (DARTEL50 and SPM8; Wellcome Trust Centre for Neuroimaging, http://www.fil.ion.ucl.ac.uk/spm/). Four patients had no anatomical scan and were normalized using a study-specific FDG template. Spatially normalized images were smoothed with an 8-mm Full-Width Half-Maximum Gaussian kernel and corrected for differences in whole-brain global mean activity.23 Relative glucose metabolic rates were used for all analyses.

Image Analysis

A 2-way analysis of variance (ANOVA) with treatment (escitalopram or CBT) and outcome (remission or nonresponse) was performed to identify a putative escitalopram/CBT remission TSB using the baseline pretreatment FDG-PET scans (analyses performed with AFNI [National Institute of Mental Health, National Institutes of Health] and SPSS [IBM SPSS], statistical threshold P < .001 uncorrected, and a minimum cluster volume of 100 voxels, 0.34 mL). With this approach, a main effect of remission would identify brain regions associated with remission to treatment independent of randomization group, ie, a nonspecific biomarker. The treatment × outcome interaction would identify brain regions where the CBT treatment effect (remission or nonresponse) was distinguished from the escitalopram treatment effect (remission or nonresponse). Average normalized glucose metabolism values were extracted from clusters identified by the ANOVA (mean cluster activity) for further analysis.

Post hoc analyses of the extracted regions from the ANOVA interaction were used to refine selection of a potential TSB pattern by examining the effect sizes of the group differences for each region. We defined a region as a true TSB if it differentiated both the remission and nonresponse differences (by treatment) and the escitalopram and CBT differences (by outcome); thus, there were 4 comparisons of interest to consider when evaluating each region of interest as a stratification tool for treatment recommendation. Given the limited sample size, we report these comparisons using effect size, rather than statistical significance, to quantify their actual potential use as an eventual TSB. The 2-group effect size can be interpreted as the difference in metabolic activity between specified groups in units of standard deviation.51 Because each region had a different magnitude of glucose metabolic activity and variation, each individual value was standardized using a z score, with regional z score means plotted to illustrate the nature of the regional interaction effects. Because these data are already standardized to the level of variation, there are no “error bars” in the related graphs.

To further assess the generalizability of findings identified in this restricted analysis to the full sample of study completers, metabolic activity was correlated with percentage of change in HDRS score within each treatment group to determine if the putative biomarkers identified in the ANOVA showed the predicted general pattern in the full cohort of phase 1 treatment completers.

Clinical Effects

Eighty-two patients were randomized to treatment; however, 2 patients received a change in their psychiatric diagnosis during the trial, and they were not used in the analyses. This resulted in 41 randomized to CBT and 39 to escitalopram. Sixty-five patients completed phase 1; 63 of the completers (79% of the total sample) had baseline FDG-PET scans available for analysis. Phase 1 remission rates were similar for both treatments: CBT = 12 of 33 (36.3%) and escitalopram = 12 of 30 (40.0%) (Figure 1 and Table 1). Nonresponse rates were also similar for both treatments: CBT = 9 of 33 (27.3%) and escitalopram = 6 of 30 (20.0%). Thirty-eight patients with clear outcomes and usable PET scans were included in the primary analysis: 12 patients with CBT remission, 11 patients with escitalopram remission, 9 patients with CBT nonresponse, and 6 patients with escitalopram nonresponse. There were no statistical differences in age, sex, or demographic or illness characteristics between randomization groups (escitalopram vs CBT). There were also no baseline demographic differences among the treatment-specific phase 1 outcome groups (Table 1). However, CBT nonresponders had higher baseline anxiety ratings (Hamilton Anxiety Rating Scale total score).

Table Graphic Jump LocationTable 1.  Group Comparisons of Clinical Characteristics
Neuroimaging Results
Treatment × Outcome ANOVA

There was no significant main effect of remission, ie, no treatment-nonspecific biomarker was identified. Significant treatment × outcome interaction effects were demonstrated for 6 regions: right anterior insula, right inferior temporal cortex (Brodmann area [BA] 20), left amygdala, left premotor cortex (BA 6), right motor cortex (BA 4), and precuneus (BA 7) (Table 2 and Figure 2).

Table Graphic Jump LocationTable 2.  Treatment by Outcome Interaction Results and Post hoc Analyses of Extracted Regions of Interest
Place holder to copy figure label and caption
Figure 2.
Potential Treatment-Specific Biomarker Candidates

Mean regional activity values for remitters and nonresponders segregated by treatment arm are plotted for the 6 regions showing a significant treatment × outcome analysis of variance interaction effect. Regional metabolic activity values are displayed as region/whole-brain metabolism converted to z scores. Regions match those shown in Table 2. Escitalopram was given as escitalopram oxalate. CBT indicates cognitive behavior therapy.

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Post hoc Analyses of Extracted Regions of Interest

The average effect sizes of each region for the various contrasts are shown in Table 2 in order of cluster size from the ANOVA. This was used to rank the regions of interest in the order of their potential utility as a discriminator. Only the insula and precuneus showed differences larger than 1 SD in all 4 contrasts, with the insula showing the largest average difference across all 4 comparisons. These findings indicate that metabolic activity of the right anterior insula is the most viable TSB candidate (Table 2 and Figure 3). Further, the anterior insula was the only region that showed relative hypometabolism in 1 group (region/whole-brain mean <1.0) and hypermetabolism in the other (region/whole-brain mean >1.0), adding support for potential use as a treatment stratification tool.

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Figure 3.
Right Anterior Insula as the Optimal Treatment-Specific Biomarker Candidate

Expanded view of findings. A, Scatterplot of insular activity from individual subjects in the remitter (REM) and nonresponder (NR) groups. Note: the anterior insula is the only region where the interaction subdivides patients into hypermetabolic (region/whole-brain mean >1.0) and hypometabolic (region/whole-brain mean <1.0) subgroups. B, Correlations of insula activity with percentage of change in Hamilton Depression Rating Scale (HDRS) score in the full cohort of subjects treated with cognitive behavior therapy (CBT) and escitalopram oxalate.

Graphic Jump Location
Assessment of the Insula TSB Across the Full Sample

There was a significant correlation between baseline insula activity and percentage of change in HDRS scores in both the CBT and escitalopram groups. A positive correlation was shown for the CBT group (r = 0.55; df = 31; P = .001) (Figure 3). In contrast, the escitalopram-treated patients showed an opposite but less significant correlation (r = −0.31; df = 28; P = .09). Both correlations are consistent with the more restricted findings in the binarized remitter-nonresponder analyses.

Although not a primary planned analysis, the presence of multiple regions identified in the ANOVA suggests that a combination rather than a single TSB might be more accurate in discriminating the groups. Although underpowered, a principal component analysis was performed using the 6 identified regions of interest. All regions loaded on 1 factor, which did not provide superior internal consistency to the insula alone (data not shown).

This 12-week randomized study of 2 first-line treatments for MDD identified 2 FDG-PET–defined brain pattern subtypes that differentially predicted remission to either CBT or escitalopram. Among the 6 identified cortical and limbic regions, the anterior insula metabolism best discriminated treatment outcome: insula hypometabolism was associated with remission to CBT and poor response to escitalopram, while insula hypermetabolism was associated with remission to escitalopram and poor response to CBT. These data suggest that insula metabolism alone (relative to each person’s whole-brain mean metabolism) may serve as a pretreatment biomarker to guide initial treatment selection (medication vs CBT) for a patient presenting with a major depressive episode. To validate the insula TSB, a prospective replication study in which patients are treated according to brain type will be required. That said, this forced-choice analytic strategy establishes a potential stratification algorithm for managing patients with MDD based on brain state rather than patient or professional preference, anticipating the real-world decision-making process faced by clinicians, namely, choosing a first treatment that will most likely lead to remission while also avoiding a treatment that is likely to fail.

A role for the anterior insula in major depression is well established. The insula is crucial in mediating the translation of visceral experiences to subjective feeling states.52 Additionally, anterior insula activity is linked to behaviors relevant to depression including interoception, emotional self-awareness, decision making, and cognitive control.5355 The anterior insula is extensively connected to various frontal, limbic, and brainstem regions, including the anterior cingulate cortex, amygdala, and hypothalamus.56 Volume reductions of the anterior but not posterior insula have been described in currently ill patients with MDD as well as patients with remitted MDD compared with healthy controls.57 Changes in insula activity occur with a variety of treatments for MDD, including medication,58 vagus nerve stimulation,59 deep brain stimulation,60 and mindfulness training,61 suggesting a role for this region in mediating antidepressant response and remission more generally.62 Notably, past studies have reported both increases33 and decreases39 in baseline resting-state activity relative to never-depressed control subjects. This is consistent with the presence of at least 2 baseline patterns within the broader population of depressed patients. Most recently, baseline insula activity has been correlated with response to vagus nerve stimulation.26 These previous studies taken together with the current findings support the anterior insula as a potential candidate for an imaging TSB.

Contrary to past published studies,63 the rostral anterior cingulate did not discriminate the outcome subgroups in either the main effect or interaction analyses. A post hoc examination of responder and nonresponder differences within each treatment arm did reveal a nonsignificant rostral cingulate activity difference, with metabolism in responders greater than nonresponders, but solely in the escitalopram group. While consistent with past reports, this finding did not meet the TSB criteria defined for the current study, ie, a region whose activity can differentiate both good and poor outcomes for both treatments.

Critical to the stated aims, remission (rather than response) was the targeted end point in this study because the presence of residual symptoms is a known predictor of clinical relapse, even in patients with significant improvement.64,65 Because the primary aim of this study was to identify distinct brain patterns that optimally predict remission to each of 2 specific treatments, patients with unclear treatment outcomes were excluded from the primary analysis (ie, responders without remission and partial responders). This enriched sample allowed for detection of clear remission and nonresponse signals; as such, these analyses did not attempt to characterize the neurobiological variability of patients with more ambiguous clinical outcomes. This is a commonly used approach when the goal is to develop or test a biological signal for stratifying subjects.66,67 Nevertheless, baseline insula activity did correlate significantly with change in depression severity across all subjects, supporting the interpretation that insula activity is a plausible TSB suitable for further testing. Based on the correlational analysis across all subjects, the data further suggest that the anterior insula TSB may most optimally identify those patients who require CBT.

If confirmed with prospective testing, this putative TSB has both clinical and pathophysiological implications. At present, treatment failure with antidepressant medication often leads to the addition of a second drug and not a categorical switch to an evidence-based psychotherapy.68 Results herein suggest that patients who require CBT have a distinct neurophysiology that differs categorically from patients who require escitalopram and knowledge of such may help to improve current clinical practice patterns. Further, using this or any other imaging-based TSB to define patient subgroups provides a brain-based platform to investigate genetic, immune, neuroendocrine, and behavioral variations from a new perspective.

While these first results are encouraging, there are several limitations. Clearly, there are patients who are not successfully treated with either of these 2 options, either alone or in combination.69 Therefore, our strategy can be best seen as a first-line stratification approach to treatment selection. Future studies, in addition to testing this insula biomarker prospectively, should include a design that works to identify patients resistant to both of these first-line treatments.60,70

The lack of a placebo arm could be considered a limitation, but given the randomized design of the study, there is no reason to believe that placebo responders would be unevenly distributed between the 2 groups. Thus, even if present, placebo effects on remission rates would be expected to be similar in both treatment groups. Although inclusion of a placebo arm might have provided further insights into mediators of improvement during treatment, the absence of a placebo arm does not diminish the potential clinical utility of the identified TSB.

It is also possible that these results are specific to the cohort recruited for this trial. As such, a stratification strategy based on insula metabolism will require prospective testing in a new group of comparably depressed patients. Similarly, additional studies will be required to determine if remitters to other medications have a similar or different TSB from that seen with escitalopram or if remitters to other evidence-based psychotherapies have a similar TSB to that seen with CBT.71,72 Such studies are critical next steps toward the development of biology-based algorithms to guide treatment selection for MDD at all stages of illness. Still, if replicated, the insula TSB defined in this study would provide the first objective marker to guide initial treatment selection for major depression, an important advance in potentially reducing the costs and disability associated with this highly prevalent disorder.

Corresponding Author: Helen S. Mayberg, MD, Emory University, Department of Psychiatry, 101 Woodruff Cir, WMB 4313, Atlanta, GA 30322 (hmayber@emory.edu).

Submitted for Publication: August 29, 2012; final revision received January 11, 2013; accepted January 14, 2013.

Published Online: June 12, 2013. doi:10.1001/jamapsychiatry.2013.143.

Author Contributions: Dr Mayberg had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Conflict of Interest Disclosures: Dr Dunlop has received honoraria for consulting work performed for Bristol-Myers Squibb, MedAvante, Pfizer, and Roche. He has received research support from AstraZeneca, Bristol-Myers Squibb, Evotec, Forest, GlaxoSmithKline, Novartis, Ono Pharmaceuticals, Pfizer, Shire, Takeda, and Transcept. Dr Holtzheimer has received consulting fees from St Jude Medical Neuromodulation and Cervel Neurotech and an honorarium from Johnson & Johnson. Dr Craighead is a board member of Hugarheill, an Icelandic company dedicated to the prevention of depression, and he receives book royalties from John Wiley & Sons. He is a consultant to the George West Mental Health Foundation that oversees Skyland Trail, a residential treatment facility in Atlanta, Georgia. Dr Mayberg has received consulting and intellectual property licensing fees from St Jude Medical Inc.

Funding/Support: This work was supported by National Institutes of Health grants R01 MH073719 (Dr Mayberg), T32 GM08695 (Ms McGrath), K23 MH086690 (Dr Dunlop), and K23 MH077869 (Dr Holtzheimer).

Additional Contributions: Treating psychotherapists: Sheethal Reddy, PhD, Patrick Sylvers, PhD, Lorie Ritschel, PhD, Meredith Jones, PhD, Mary Heekin, LCSW, Maryrose Gerardi, PhD, and Jill Rosenberg, LCSW. Treating physicians: Ebrahim Haroon, MD, Jeffrey Rakofsky, MD, Dylan Wint, MD, and Corey Beck, MD. Clinical coordinators: Ronald Chismar, RN, Melanie Galanti, BA, Rachelle Gibson, RN, Lauren Marx, BS, Melissa McKenzie, BA, and Tanja Mletzko, MA. Imaging team: Rebecca DeMayo, MA, Eundria Hill, MSW, Kiseung Choi, MS, and Justin Rajendra, BA. Raters: Margo Aaron, BA, Yara Betancourt, BA, Cristina Velasquez Delgado, BA, Novall Khan, BS, Ximena Marincic, BS, and Christopher Vaughan, BA.

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D’Empaire  I, Guico-Pabia  CJ, Preskorn  SH.  Antidepressant treatment and altered CYP2D6 activity: are pharmacokinetic variations clinically relevant? J Psychiatr Pract. 2011;17(5):330-339.
PubMed   |  Link to Article
Konarski  JZ, Kennedy  SH, Segal  ZV,  et al.  Predictors of nonresponse to cognitive behavioural therapy or venlafaxine using glucose metabolism in major depressive disorder. J Psychiatry Neurosci. 2009;34(3):175-180.
PubMed
Kennedy  SH, Konarski  JZ, Segal  ZV,  et al.  Differences in brain glucose metabolism between responders to CBT and venlafaxine in a 16-week randomized controlled trial. Am J Psychiatry. 2007;164(5):778-788.
PubMed   |  Link to Article
DeBattista  C, Kinrys  G, Hoffman  D,  et al.  The use of referenced-EEG (rEEG) in assisting medication selection for the treatment of depression. J Psychiatr Res. 2011;45(1):64-75.
PubMed   |  Link to Article
Leuchter  AF, Cook  IA, Marangell  LB,  et al.  Comparative effectiveness of biomarkers and clinical indicators for predicting outcomes of SSRI treatment in Major Depressive Disorder: results of the BRITE-MD study. Psychiatry Res. 2009;169(2):124-131.
PubMed   |  Link to Article
Conway  CR, Chibnall  JT, Gangwani  S,  et al.  Pretreatment cerebral metabolic activity correlates with antidepressant efficacy of vagus nerve stimulation in treatment-resistant major depression: a potential marker for response? J Affect Disord. 2012;139(3):283-290.
PubMed   |  Link to Article
Siegle  GJ, Thompson  WK, Collier  A,  et al.  Toward clinically useful neuroimaging in depression treatment: prognostic utility of subgenual cingulate activity for determining depression outcome in cognitive therapy across studies, scanners, and patient characteristics. Arch Gen Psychiatry. 2012;69(9):913-924.
PubMed   |  Link to Article
Mayberg  HS, Brannan  SK, Mahurin  RK,  et al.  Cingulate function in depression: a potential predictor of treatment response. Neuroreport. 1997;8(4):1057-1061.
PubMed   |  Link to Article
Pizzagalli  D, Pascual-Marqui  RD, Nitschke  JB,  et al.  Anterior cingulate activity as a predictor of degree of treatment response in major depression: evidence from brain electrical tomography analysis. Am J Psychiatry. 2001;158(3):405-415.
PubMed   |  Link to Article
Wu  J, Buchsbaum  MS, Gillin  JC,  et al.  Prediction of antidepressant effects of sleep deprivation by metabolic rates in the ventral anterior cingulate and medial prefrontal cortex. Am J Psychiatry. 1999;156(8):1149-1158.
PubMed
Dougherty  DD, Weiss  AP, Cosgrove  GR,  et al.  Cerebral metabolic correlates as potential predictors of response to anterior cingulotomy for treatment of major depression. J Neurosurg. 2003;99(6):1010-1017.
PubMed   |  Link to Article
Brody  AL, Saxena  S, Stoessel  P,  et al.  Regional brain metabolic changes in patients with major depression treated with either paroxetine or interpersonal therapy: preliminary findings. Arch Gen Psychiatry. 2001;58(7):631-640.
PubMed   |  Link to Article
Ketter  TA, Kimbrell  TA, George  MS,  et al.  Baseline cerebral hypermetabolism associated with carbamazepine response, and hypometabolism with nimodipine response in mood disorders. Biol Psychiatry. 1999;46(10):1364-1374.
PubMed   |  Link to Article
Goldapple  K, Segal  Z, Garson  C,  et al.  Modulation of cortical-limbic pathways in major depression: treatment-specific effects of cognitive behavior therapy. Arch Gen Psychiatry. 2004;61(1):34-41.
PubMed   |  Link to Article
Beck  A, Rush  A, Shaw  B, Emery  G. Cognitive Therapy of Depression. New York, NY: Guilford; 1979.
Beck  AT.  The current state of cognitive therapy: a 40-year retrospective. Arch Gen Psychiatry. 2005;62(9):953-959.
PubMed   |  Link to Article
Bartlett  EJ, Barouche  F, Brodie  JD,  et al.  Stability of resting deoxyglucose metabolic values in PET studies of schizophrenia. Psychiatry Res. 1991;40(1):11-20.
PubMed   |  Link to Article
Brody  AL, Saxena  S, Silverman  DH,  et al.  Brain metabolic changes in major depressive disorder from pre- to post-treatment with paroxetine. Psychiatry Res. 1999;91(3):127-139.
PubMed   |  Link to Article
Kimbrell  TA, Ketter  TA, George  MS,  et al.  Regional cerebral glucose utilization in patients with a range of severities of unipolar depression. Biol Psychiatry. 2002;51(3):237-252.
PubMed   |  Link to Article
Drevets  WC, Price  JL, Bardgett  ME, Reich  T, Todd  RD, Raichle  ME.  Glucose metabolism in the amygdala in depression: relationship to diagnostic subtype and plasma cortisol levels. Pharmacol Biochem Behav. 2002;71(3):431-447.
PubMed   |  Link to Article
Saxena  S, Brody  AL, Ho  ML, Zohrabi  N, Maidment  KM, Baxter  LR  Jr.  Differential brain metabolic predictors of response to paroxetine in obsessive-compulsive disorder versus major depression. Am J Psychiatry. 2003;160(3):522-532.
PubMed   |  Link to Article
Little  JT, Ketter  TA, Kimbrell  TA,  et al.  Bupropion and venlafaxine responders differ in pretreatment regional cerebral metabolism in unipolar depression. Biol Psychiatry. 2005;57(3):220-228.
PubMed   |  Link to Article
Milak  MS, Parsey  RV, Lee  L,  et al.  Pretreatment regional brain glucose uptake in the midbrain on PET may predict remission from a major depressive episode after three months of treatment. Psychiatry Res. 2009;173(1):63-70.
PubMed   |  Link to Article
First  MB, Spitzer  RL, Gibbon  M, Williams  JBW. Structured Clinical Interview for DSM-IV-TR Axis I Disorders, Research Version, Patient Edition With Psychotic Screen (SCID-I/P W/PSY SCREEN). New York: Biometrics Research, New York State Psychiatric Institute; 2002.
Dunlop  BW, Kelley  ME, Mletzko  TC, Velasquez  CM, Craighead  WE, Mayberg  HS.  Depression beliefs, treatment preference, and outcomes in a randomized trial for major depressive disorder. J Psychiatr Res. 2012;46(3):375-381.
PubMed   |  Link to Article
Hamilton  M.  A rating scale for depression. J Neurol Neurosurg Psychiatry. 1960;23:56-62.
PubMed   |  Link to Article
Rush  AJ, Trivedi  MH, Stewart  JW,  et al.  Combining Medications to Enhance Depression Outcomes (CO-MED): acute and long-term outcomes of a single-blind randomized study. Am J Psychiatry. 2011;168(7):689-701.
PubMed   |  Link to Article
Nierenberg  AA, Farabaugh  AH, Alpert  JE,  et al.  Timing of onset of antidepressant response with fluoxetine treatment. Am J Psychiatry. 2000;157(9):1423-1428.
PubMed   |  Link to Article
Phelps  ME, Huang  SC, Hoffman  EJ, Selin  C, Sokoloff  L, Kuhl  DE.  Tomographic measurement of local cerebral glucose metabolic rate in humans with (F-18)2-fluoro-2-deoxy-D-glucose: validation of method. Ann Neurol. 1979;6(5):371-388.
PubMed   |  Link to Article
Ashburner  J.  A fast diffeomorphic image registration algorithm. Neuroimage. 2007;38(1):95-113.
PubMed   |  Link to Article
Cohen  J. Statistical Power Analysis for the Behavioral Sciences. 2nd ed. Hillsdale, NJ: Lawrence Erlbaum Associated; 1988.
Critchley  HD, Wiens  S, Rotshtein  P, Ohman  A, Dolan  RJ.  Neural systems supporting interoceptive awareness. Nat Neurosci. 2004;7(2):189-195.
PubMed   |  Link to Article
Farb  NA, Segal  ZV, Anderson  AK.  Attentional modulation of primary interoceptive and exteroceptive cortices. Cereb Cortex. 2013;23(1):114-126.
PubMed   |  Link to Article
Craig  AD.  How do you feel—now? The anterior insula and human awareness. Nat Rev Neurosci. 2009;10(1):59-70.
PubMed   |  Link to Article
Critchley  HD.  Neural mechanisms of autonomic, affective, and cognitive integration. J Comp Neurol. 2005;493(1):154-166.
PubMed   |  Link to Article
Augustine  JR.  Circuitry and functional aspects of the insular lobe in primates including humans. Brain Res Brain Res Rev. 1996;22(3):229-244.
PubMed   |  Link to Article
Takahashi  T, Yücel  M, Lorenzetti  V,  et al.  Volumetric MRI study of the insular cortex in individuals with current and past major depression. J Affect Disord. 2010;121(3):231-238.
PubMed   |  Link to Article
Kennedy  SH, Evans  KR, Krüger  S,  et al.  Changes in regional brain glucose metabolism measured with positron emission tomography after paroxetine treatment of major depression. Am J Psychiatry. 2001;158(6):899-905.
PubMed   |  Link to Article
Conway  CR, Sheline  YI, Chibnall  JT, George  MS, Fletcher  JW, Mintun  MA.  Cerebral blood flow changes during vagus nerve stimulation for depression. Psychiatry Res. 2006;146(2):179-184.
PubMed   |  Link to Article
Mayberg  HS, Lozano  AM, Voon  V,  et al.  Deep brain stimulation for treatment-resistant depression. Neuron. 2005;45(5):651-660.
PubMed   |  Link to Article
Farb  NAS, Segal  ZV, Mayberg  H,  et al.  Attending to the present: mindfulness meditation reveals distinct neural modes of self-reference. Soc Cogn Affect Neurosci. 2007;2(4):313-322.
PubMed   |  Link to Article
Fu  CH, Steiner  H, Costafreda  SG.  Predictive neural biomarkers of clinical response in depression: a meta-analysis of functional and structural neuroimaging studies of pharmacological and psychological therapies. Neurobiol Dis. 2013;52:75-83.
PubMed   |  Link to Article
Pizzagalli  DA.  Frontocingulate dysfunction in depression: toward biomarkers of treatment response. Neuropsychopharmacology. 2011;36(1):183-206.
PubMed   |  Link to Article
Paykel  ES, Ramana  R, Cooper  Z, Hayhurst  H, Kerr  J, Barocka  A.  Residual symptoms after partial remission: an important outcome in depression. Psychol Med. 1995;25(6):1171-1180.
PubMed   |  Link to Article
Judd  LL, Paulus  MJ, Schettler  PJ,  et al.  Does incomplete recovery from first lifetime major depressive episode herald a chronic course of illness? Am J Psychiatry. 2000;157(9):1501-1504.
PubMed   |  Link to Article
Ridker  PM, Hennekens  CH, Buring  JE, Rifai  N.  C-reactive protein and other markers of inflammation in the prediction of cardiovascular disease in women. N Engl J Med. 2000;342(12):836-843.
PubMed   |  Link to Article
Ridker  PM.  Cardiology Patient Page. C-reactive protein: a simple test to help predict risk of heart attack and stroke. Circulation. 2003;108(12):e81-e85.
PubMed   |  Link to Article
Gaynes  BN, Dusetzina  SB, Ellis  AR,  et al.  Treating depression after initial treatment failure: directly comparing switch and augmenting strategies in STAR*D. J Clin Psychopharmacol. 2012;32(1):114-119.
PubMed   |  Link to Article
Thase  ME, Friedman  ES, Biggs  MM,  et al.  Cognitive therapy versus medication in augmentation and switch strategies as second-step treatments: a STAR*D report. Am J Psychiatry. 2007;164(5):739-752.
PubMed   |  Link to Article
Rush  AJ, Warden  D, Wisniewski  SR,  et al.  STAR*D: revising conventional wisdom. CNS Drugs. 2009;23(8):627-647.
PubMed
Dunlop  BW, Binder  EB, Cubells  JF,  et al.  Predictors of remission in depression to individual and combined treatments (PReDICT): study protocol for a randomized controlled trial. Trials. 2012;13(1):106.
PubMed   |  Link to Article
Kennedy  SH, Downar  J, Evans  KR,  et al.  The Canadian Biomarker Integration Network in Depression (CAN-BIND): advances in response prediction. Curr Pharm Des. 2012;18(36):5976-5989.
PubMed   |  Link to Article

Figures

Place holder to copy figure label and caption
Figure 1.
Study Design and Outcomes

Outcome groups defined by Hamilton Depression Rating Scale (HDRS) scores. Remission was defined as an HDRS score of 7 or less; partial response, as an HDRS score decrease of more than 30% but not achieving remission; and nonresponse, as an HDRS score decrease of 30% or less. Escitalopram was given as escitalopram oxalate. CBT indicates cognitive behavior therapy and PET, positron emission tomography.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.
Potential Treatment-Specific Biomarker Candidates

Mean regional activity values for remitters and nonresponders segregated by treatment arm are plotted for the 6 regions showing a significant treatment × outcome analysis of variance interaction effect. Regional metabolic activity values are displayed as region/whole-brain metabolism converted to z scores. Regions match those shown in Table 2. Escitalopram was given as escitalopram oxalate. CBT indicates cognitive behavior therapy.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 3.
Right Anterior Insula as the Optimal Treatment-Specific Biomarker Candidate

Expanded view of findings. A, Scatterplot of insular activity from individual subjects in the remitter (REM) and nonresponder (NR) groups. Note: the anterior insula is the only region where the interaction subdivides patients into hypermetabolic (region/whole-brain mean >1.0) and hypometabolic (region/whole-brain mean <1.0) subgroups. B, Correlations of insula activity with percentage of change in Hamilton Depression Rating Scale (HDRS) score in the full cohort of subjects treated with cognitive behavior therapy (CBT) and escitalopram oxalate.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1.  Group Comparisons of Clinical Characteristics
Table Graphic Jump LocationTable 2.  Treatment by Outcome Interaction Results and Post hoc Analyses of Extracted Regions of Interest

References

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PubMed   |  Link to Article
D’Empaire  I, Guico-Pabia  CJ, Preskorn  SH.  Antidepressant treatment and altered CYP2D6 activity: are pharmacokinetic variations clinically relevant? J Psychiatr Pract. 2011;17(5):330-339.
PubMed   |  Link to Article
Konarski  JZ, Kennedy  SH, Segal  ZV,  et al.  Predictors of nonresponse to cognitive behavioural therapy or venlafaxine using glucose metabolism in major depressive disorder. J Psychiatry Neurosci. 2009;34(3):175-180.
PubMed
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PubMed   |  Link to Article
DeBattista  C, Kinrys  G, Hoffman  D,  et al.  The use of referenced-EEG (rEEG) in assisting medication selection for the treatment of depression. J Psychiatr Res. 2011;45(1):64-75.
PubMed   |  Link to Article
Leuchter  AF, Cook  IA, Marangell  LB,  et al.  Comparative effectiveness of biomarkers and clinical indicators for predicting outcomes of SSRI treatment in Major Depressive Disorder: results of the BRITE-MD study. Psychiatry Res. 2009;169(2):124-131.
PubMed   |  Link to Article
Conway  CR, Chibnall  JT, Gangwani  S,  et al.  Pretreatment cerebral metabolic activity correlates with antidepressant efficacy of vagus nerve stimulation in treatment-resistant major depression: a potential marker for response? J Affect Disord. 2012;139(3):283-290.
PubMed   |  Link to Article
Siegle  GJ, Thompson  WK, Collier  A,  et al.  Toward clinically useful neuroimaging in depression treatment: prognostic utility of subgenual cingulate activity for determining depression outcome in cognitive therapy across studies, scanners, and patient characteristics. Arch Gen Psychiatry. 2012;69(9):913-924.
PubMed   |  Link to Article
Mayberg  HS, Brannan  SK, Mahurin  RK,  et al.  Cingulate function in depression: a potential predictor of treatment response. Neuroreport. 1997;8(4):1057-1061.
PubMed   |  Link to Article
Pizzagalli  D, Pascual-Marqui  RD, Nitschke  JB,  et al.  Anterior cingulate activity as a predictor of degree of treatment response in major depression: evidence from brain electrical tomography analysis. Am J Psychiatry. 2001;158(3):405-415.
PubMed   |  Link to Article
Wu  J, Buchsbaum  MS, Gillin  JC,  et al.  Prediction of antidepressant effects of sleep deprivation by metabolic rates in the ventral anterior cingulate and medial prefrontal cortex. Am J Psychiatry. 1999;156(8):1149-1158.
PubMed
Dougherty  DD, Weiss  AP, Cosgrove  GR,  et al.  Cerebral metabolic correlates as potential predictors of response to anterior cingulotomy for treatment of major depression. J Neurosurg. 2003;99(6):1010-1017.
PubMed   |  Link to Article
Brody  AL, Saxena  S, Stoessel  P,  et al.  Regional brain metabolic changes in patients with major depression treated with either paroxetine or interpersonal therapy: preliminary findings. Arch Gen Psychiatry. 2001;58(7):631-640.
PubMed   |  Link to Article
Ketter  TA, Kimbrell  TA, George  MS,  et al.  Baseline cerebral hypermetabolism associated with carbamazepine response, and hypometabolism with nimodipine response in mood disorders. Biol Psychiatry. 1999;46(10):1364-1374.
PubMed   |  Link to Article
Goldapple  K, Segal  Z, Garson  C,  et al.  Modulation of cortical-limbic pathways in major depression: treatment-specific effects of cognitive behavior therapy. Arch Gen Psychiatry. 2004;61(1):34-41.
PubMed   |  Link to Article
Beck  A, Rush  A, Shaw  B, Emery  G. Cognitive Therapy of Depression. New York, NY: Guilford; 1979.
Beck  AT.  The current state of cognitive therapy: a 40-year retrospective. Arch Gen Psychiatry. 2005;62(9):953-959.
PubMed   |  Link to Article
Bartlett  EJ, Barouche  F, Brodie  JD,  et al.  Stability of resting deoxyglucose metabolic values in PET studies of schizophrenia. Psychiatry Res. 1991;40(1):11-20.
PubMed   |  Link to Article
Brody  AL, Saxena  S, Silverman  DH,  et al.  Brain metabolic changes in major depressive disorder from pre- to post-treatment with paroxetine. Psychiatry Res. 1999;91(3):127-139.
PubMed   |  Link to Article
Kimbrell  TA, Ketter  TA, George  MS,  et al.  Regional cerebral glucose utilization in patients with a range of severities of unipolar depression. Biol Psychiatry. 2002;51(3):237-252.
PubMed   |  Link to Article
Drevets  WC, Price  JL, Bardgett  ME, Reich  T, Todd  RD, Raichle  ME.  Glucose metabolism in the amygdala in depression: relationship to diagnostic subtype and plasma cortisol levels. Pharmacol Biochem Behav. 2002;71(3):431-447.
PubMed   |  Link to Article
Saxena  S, Brody  AL, Ho  ML, Zohrabi  N, Maidment  KM, Baxter  LR  Jr.  Differential brain metabolic predictors of response to paroxetine in obsessive-compulsive disorder versus major depression. Am J Psychiatry. 2003;160(3):522-532.
PubMed   |  Link to Article
Little  JT, Ketter  TA, Kimbrell  TA,  et al.  Bupropion and venlafaxine responders differ in pretreatment regional cerebral metabolism in unipolar depression. Biol Psychiatry. 2005;57(3):220-228.
PubMed   |  Link to Article
Milak  MS, Parsey  RV, Lee  L,  et al.  Pretreatment regional brain glucose uptake in the midbrain on PET may predict remission from a major depressive episode after three months of treatment. Psychiatry Res. 2009;173(1):63-70.
PubMed   |  Link to Article
First  MB, Spitzer  RL, Gibbon  M, Williams  JBW. Structured Clinical Interview for DSM-IV-TR Axis I Disorders, Research Version, Patient Edition With Psychotic Screen (SCID-I/P W/PSY SCREEN). New York: Biometrics Research, New York State Psychiatric Institute; 2002.
Dunlop  BW, Kelley  ME, Mletzko  TC, Velasquez  CM, Craighead  WE, Mayberg  HS.  Depression beliefs, treatment preference, and outcomes in a randomized trial for major depressive disorder. J Psychiatr Res. 2012;46(3):375-381.
PubMed   |  Link to Article
Hamilton  M.  A rating scale for depression. J Neurol Neurosurg Psychiatry. 1960;23:56-62.
PubMed   |  Link to Article
Rush  AJ, Trivedi  MH, Stewart  JW,  et al.  Combining Medications to Enhance Depression Outcomes (CO-MED): acute and long-term outcomes of a single-blind randomized study. Am J Psychiatry. 2011;168(7):689-701.
PubMed   |  Link to Article
Nierenberg  AA, Farabaugh  AH, Alpert  JE,  et al.  Timing of onset of antidepressant response with fluoxetine treatment. Am J Psychiatry. 2000;157(9):1423-1428.
PubMed   |  Link to Article
Phelps  ME, Huang  SC, Hoffman  EJ, Selin  C, Sokoloff  L, Kuhl  DE.  Tomographic measurement of local cerebral glucose metabolic rate in humans with (F-18)2-fluoro-2-deoxy-D-glucose: validation of method. Ann Neurol. 1979;6(5):371-388.
PubMed   |  Link to Article
Ashburner  J.  A fast diffeomorphic image registration algorithm. Neuroimage. 2007;38(1):95-113.
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Significance of right anterior insula activation for mental health intervention
Posted on June 26, 2013
Tegeler CH (1), Gerdes L (2), Lee SW (2), Shaltout H (1).
(1) Wake Forest School of Medicine, Winston-Salem, North Carolina. (2) Brain State Technologies LLC, Scottsdale, Arizona.
Conflict of Interest: Dr. Tegeler reports non-salary research funding from Brain State Technologies LLC in 2011, for a pilot clinical trial. Lee Gerdes and Dr. Lee are employees and shareholders of Brain State Technologies LLC. Dr. Shaltout reports no conflicts of interest.
We applaud McGrath and colleagues (2013) for exploring the use of brain state as a way to predict differential outcomes from either psychotherapy or medication as treatment for depression. Hypometabolism in the right anterior insula correlated with symptom reduction through cognitive behavioral therapy, whereas hypermetabolism in the right anterior insula correlated with symptom reduction through escitalopram. In their discussion the authors pointed out roles of the anterior insula for interoception, self-awareness, and cognitive control. We wish to highlight additionally that the insulae are loci for lateralized management of autonomic functioning. In particular the right anterior insula regulates sympathetic activity, and the left insula appears to be responsible for parasympathetic activation (Craig 2005; Cechetto et al., 2009; Beissner et al, 2013). Thus it may be that depressed individuals with greater right anterior insular activity have higher sympathetic arousal and are relatively impaired in their capacity to successfully apply cognitive-behavioral strategies. These individuals may preferentially benefit from anti-depressant medications, which can have effects on autonomic tone (Chang et al., 2012). In our own work we have found that hemispheric lateralization of autonomic management may be discerned through surface electroencephalic recordings, with clinical implications. We recently reported on a relationship between heart rate variability and high frequency temporal lobe electroencephalic asymmetry calculated from two-channel, one-minute recordings. Rightward temporal asymmetry correlated with higher heart rate and lower standard deviation of the RR interval (Tegeler et al. 2013). Furthermore in a clinical trial for individuals with insomnia and depressive symptoms we found a trend for auto-calibration of right dominant high frequency temporal activity towards greater symmetry to correlate with insomnia symptom reduction (Gerdes et al., 2013). We are thus excited that data from PET and surface electroencephalic recordings may be converging on a unitary conclusion about the role of lateralized activity in temporal lobe-region structures, for mental health intervention.Beissner F, Meissner K, Bar KJ, and Napadow V. (2013). The autonomic brain: an activation likelihood estimation meta-analysis for central processing of autonomic function. J Neurosci. 33(25): 10503-11.Cechetto DF and Shoemaker JK. (2009). Functional neuroanatomy of autonomic regulation. Neuroimage. 47(3): 795-803.Chang JS, Ha K, Yoon IY, Yoo CS, Yi SH, Her JY, Ha TH, and Park T. (2012). Patterns of cardiorespiratory coordination in young women with recurrent major depressive disorder treated with escitalopram or venlafaxine. Prog Neuropsychopharmacol Biol Psychiatry. 39(1): 136-42.Craig AD. (2005). Forebrain emotional asymmetry: a neuroanatomical basis? Trends Cogn Sci. 9(12): 566-71.Gerdes L, Gerdes P, Lee SW, and Tegeler C. (2013). HIRREM: a non-invasive, allostatic methodology for relaxation and auto-calibration of neural oscillations. Brain Behav. 3(2): 193-205.McGrath CL, Kelley ME, Holtzheimer PE, Dunlop BW, Craighead WE, Franco AR, Craddock RC, and Mayberg HS. (2013). Towards a neuroimaging treatment selection biomarker for major depressive disorder. JAMA Psychiatry. Jun 12: 1-9.Tegeler CH, Lee S, Tegeler C, and Shaltout H. (2013). Correlation between temporal lobe EEG asymmetry and heart rate variability. Neurology. Feb 12, 2013; 80 (Meeting abstracts 1): P03:031.
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