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Original Investigation |

Abnormal Amygdala Resting-State Functional Connectivity in Adolescent Depression FREE

Kathryn R. Cullen, MD1; Melinda K. Westlund, BA2; Bonnie Klimes-Dougan, PhD2; Bryon A. Mueller, PhD1; Alaa Houri, BS1; Lynn E. Eberly, PhD3; Kelvin O. Lim, MD1
[+] Author Affiliations
1Department of Psychiatry, School of Medicine, University of Minnesota, Minneapolis
2Department of Psychology, College of Liberal Arts, University of Minnesota, Minneapolis
3Department of Biostatistics, School of Public Health, University of Minnesota, Minneapolis
JAMA Psychiatry. 2014;71(10):1138-1147. doi:10.1001/jamapsychiatry.2014.1087.
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Published online

Importance  Major depressive disorder (MDD) frequently emerges during adolescence and can lead to persistent illness, disability, and suicide. The maturational changes that take place in the brain during adolescence underscore the importance of examining neurobiological mechanisms during this time of early illness. However, neural mechanisms of depression in adolescents have been understudied. Research has implicated the amygdala in emotion processing in mood disorders, and adult depression studies have suggested amygdala-frontal connectivity deficits. Resting-state functional magnetic resonance imaging is an advanced tool that can be used to probe neural networks and identify brain-behavior relationships.

Objective  To examine amygdala resting-state functional connectivity (RSFC) in adolescents with and without MDD using resting-state functional magnetic resonance imaging as well as how amygdala RSFC relates to a broad range of symptom dimensions.

Design, Setting, and Participants  A cross-sectional resting-state functional magnetic resonance imaging study was conducted within a depression research program at an academic medical center. Participants included 41 adolescents and young adults aged 12 to 19 years with MDD and 29 healthy adolescents (frequency matched on age and sex) with no psychiatric diagnoses.

Main Outcomes and Measures  Using a whole-brain functional connectivity approach, we examined the correlation of spontaneous fluctuation of the blood oxygen level–dependent signal of each voxel in the whole brain with that of the amygdala.

Results  Adolescents with MDD showed lower positive RSFC between the amygdala and hippocampus, parahippocampus, and brainstem (z >2.3, corrected P < .05); this connectivity was inversely correlated with general depression (R = −.523, P = .01), dysphoria (R = −.455, P = .05), and lassitude (R = −.449, P = .05) and was positively correlated with well-being (R = .470, P = .03). Patients also demonstrated greater (positive) amygdala-precuneus RSFC (z >2.3, corrected P < .05) in contrast to negative amygdala-precuneus RSFC in the adolescents serving as controls.

Conclusions and Relevance  Impaired amygdala-hippocampal/brainstem and amygdala-precuneus RSFC have not previously been highlighted in depression and may be unique to adolescent MDD. These circuits are important for different aspects of memory and self-processing and for modulation of physiologic responses to emotion. The findings suggest potential mechanisms underlying both mood and vegetative symptoms, potentially via impaired processing of memories and visceral signals that spontaneously arise during rest, contributing to the persistent symptoms experienced by adolescents with depression.

Figures in this Article

Major depressive disorder (MDD) is a leading cause of disability and global disease burden1 and frequently emerges during adolescence.2 Many adolescents do not respond to evidence-based treatments,3,4 highlighting the need to better understand the underlying brain mechanisms. Current theory5,6 holds that frontolimbic neural networks underlying emotion processing are abnormal in MDD. However, neurobiological research in adolescents has lagged behind that in adults. Because of the significant brain maturational changes that occur during adolescence,7 the brain abnormalities in adolescent MDD could be different from those in adults. Developmental changes may contribute to the increased risk of disease onset during adolescence, while also providing a potential window for intervention to restore developmental trajectories. These considerations underscore the importance of advancing the understanding of the neurobiology of adolescent MDD.

The amygdala, an important area for processing threat and orchestrating a complex set of emotional and physiologic responses,8 has been centrally implicated in depression.9 Amygdala networks are involved in critical functions relevant to depression including emotion regulation (through connections to frontal and insular areas), modulation of sensory information (through connections with visual, auditory, taste, and olfactory cortices), and processing of visceral information in relation to emotional stimuli (through connections with the brainstem).10 Based on the importance of the amygdala in emotion systems and its implication in MDD, the present study focused on examining amygdala networks in adolescents with MDD.

Resting-state functional magnetic resonance imaging (rsfMRI) is an excellent tool for probing neural networks. This approach measures resting-state functional connectivity (RSFC) indexed by the correlation between brain regions in the pattern of spontaneous fluctuation of the blood oxygen level–dependent signal during rest.11 Positive and negative correlations are understood to reflect synchrony in regions subserving similar and opposite goals, respectively.12 Prior studies have shown that rsfMRI can reliably map RSFC in adults13 and children.14 Research15 in adults has suggested that MDD involves a deficit in amygdala-frontal connectivity. The first published rsfMRI study16 on adolescent depression failed to find amygdala RSFC abnormalities in 12 adolescents with MDD (most receiving medication) compared with 14 healthy adolescents serving as controls (HCs) but documented abnormally low RSFC in a subgenual anterior cingulate cortex–based network. Since then, several studies1721 have reported abnormal RSFC in children or adolescents with MDD. However, the only study20 focusing on the amygdala reported that children at risk for depression (because of personal and/or maternal history) had lower negative amygdala RSFC compared with HCs with a dorsal cognitive control network and lower positive RSFC with an inferior limbic network.

The primary goal of the present study was to examine amygdala RSFC in adolescents with MDD and in HCs. To extend beyond prior work, we examined a larger sample of unmedicated adolescents with fully syndromal MDD and no substance-abuse disorders. Taking into account recent concerns regarding rsfMRI research,2224 we incorporated robust methods to address physiologic noise and participant motion during scanning, without global signal removal. We predicted that, similar to adults with MDD,15 adolescents with MDD would show diminished amygdala-frontal RSFC. Given the continuing development of amygdala-frontal projections into adulthood25 and sexual dimorphism in adolescent brain development as previously reported,26 we explored group-by-sex and group-by-age interactions. Finally, we explored how amygdala RSFC related to overall depression severity as well as a broad set of depression and anxiety symptom dimensions.

Participants

The University of Minnesota Institutional Review Board approved this study. Participants (or a parent for participants aged <18 years) provided written informed consent. Participants aged 17 years or younger provided written assent. Participants received financial compensation. Adolescents with MDD and HCs aged 12 to 19 years were recruited to participate through community postings and referrals from local mental health services. Adolescents with MDD were eligible if they had a primary diagnosis of MDD and had not received any psychotropic medication treatment for the past 2 months. Healthy adolescents were eligible if they had no current or past psychiatric diagnoses and were frequency matched to the MDD group on age and sex. Exclusion criteria for both groups included the presence of a neurologic or other chronic medical condition, mental retardation, pervasive developmental disorder, substance use disorder, bipolar disorder, or schizophrenia.

Assessment

After the informed consent process, all participants completed a comprehensive diagnostic assessment. Interviews were conducted separately with adolescents and parents and included the Schedule for Affective Disorders and Schizophrenia for School-Age Children–Present and Lifetime Version27 and the Children’s Depression Rating Scale–Revised (CDRS-R).28 Self-report measures assessing symptoms in the past 2 weeks included the Beck Depression Inventory-II (BDI-II)29,30 and the Inventory of Depression and Anxiety Symptoms (IDAS).3133 The IDAS provides a score for the following symptom dimensions: general depression, dysphoria, lassitude, insomnia, suicidality, appetite loss, appetite gain, ill temper, well-being, social anxiety, panic, and traumatic intrusion. Clinical and demographic measures were compared between groups using independent-samples, unpaired 2-tailed t tests (dimensional measures) and χ2 analyses (categorical measures).

Neuroimaging Data Acquisition

Data were acquired at the Center for Magnetic Resonance Research at the University of Minnesota (3T Tim Trio scanner; Siemens Corp). A 5-minute structural scan was acquired using a T1-weighted, high-resolution, magnetization-prepared gradient-echo sequence: repetition time, 2530 milliseconds; echo time, 3.65 milliseconds; inversion time, 1100 milliseconds; flip angle, 7°; field of view, 256 × 176 mm; voxel size, 1-mm isotropic; 224 slices; and generalized, autocalibrating, partially parallel acquisition acceleration factor, 2. The 6-minute rsfMRI scan (30 minutes into the overall protocol) comprised 180 contiguous echo planar imaging whole-brain volumes with repetition time, 2000 milliseconds; field of view, 220 × 220 mm; voxel size, 3.43 × 3.43 × 4 mm; and 34 interleaved slices (no skip), during which participants were instructed to stay awake with their eyes closed. Respiration and pulse rates were simultaneously recorded during the rsfMRI scan.

Anatomic Imaging Preprocessing

The T1 data, including brain extraction and parcellation of data, were processed into a standard set of anatomically based regions of white and gray matter (FreeSurfer, version 5.3; http://surfer.nmr.mgh.harvard.edu). FreeSurfer output was visually inspected; when any errors were identified (n = 2), they were manually corrected on a section-by-section basis. After the corrections were satisfactory, the pipeline’s remaining steps were repeated. No corrections were required in the vicinity of the amygdala. The processed T1 data were registered to the rsfMRI data using bbregister (https://surfer.nmr.mgh.harvard.edu/fswiki/bbregister).

rsfMRI Preprocessing

Image processing was conducted using tools from the FMRIB software library (http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/) as well as custom tools developed in MatLab (MathWorks; http://www.mathworks.com/products/matlab/). Initial processing included brain extraction and motion correction. A denoising procedure was applied incorporating RETROICOR34 to remove physiologic noise caused by cardiac and respiratory cycles as well as any linear trends. Correction for magnetic field inhomogeneity-induced geometric distortion was conducted using the field map. FreeSurfer-generated regions of interest (ROIs) for lateral ventricles (cerebrospinal fluid) and white matter were aligned with rsfMRI data using FLIRT (http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FLIRT). Mean blood oxygen level–dependent time series within these ROIs were extracted using fslmeants (http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Fslutils). We performed a regression of all other voxels’ time series on 8 nuisance variables: white matter time series, cerebrospinal fluid time series, and the 6 motion parameters. Data scrubbing was performed following the method of Power and colleagues,22 excluding any volume with a value for the temporal derivative of time courses’ root mean squared head motion variance value exceeding 8 and/or a framewise-dependent value exceeding 0.5, along with the previous volume and the 2 following volumes. If at least 33% of the volumes were removed, participants were excluded from analyses (2 MDD patients and 3 HCs). We conducted a Mann-Whitney test to examine whether the number of excluded volumes between groups was significantly different.

RSFC Analysis
First Level

A seed-based whole-brain approach was used to examine RSFC stemming from the left and right amygdala. To avoid misregistration errors, we used anatomically based ROIs. FreeSurfer-based right and left amygdala ROIs were registered to the preprocessed rsfMRI data, and the mean time series of voxels in these regions were extracted. These time series were used as primary regressors in separate (left and right) general linear model analyses of all other voxel time series, resulting in whole-brain amygdala RSFC maps. We used gaussian random field theory to correct for multiple testing with a cluster threshold of P < .05 and z > 2.3. Additional processing steps included spatial smoothing (5-mm kernel), prewhitening, and registration to anatomic data and standard space (Montreal Neurological Institute 152)35 for later group analysis.

Second Level

As noted in previous work,20 amygdala RSFC maps for the left and right amygdala were highly similar to each other (eFigure 1 and eFigure 2 in the Supplement). Therefore, following the work of others,20 to limit the number of tests and for ease of presentation, we conducted a second-level analysis to obtain the mean of each person’s right with their left amygdala RSFC maps.

Third Level

To address the primary study question, we conducted a voxel-wise analysis of mean amygdala RSFC comparing groups, including the covariates of age and sex, using the gaussian random field theory to correct for multiple comparisons, with a cluster z threshold > 2.3 and P < .05. We also conducted exploratory analyses to examine group-by-sex and group-by-age interaction effects on amygdala RSFC throughout the brain.

Fourth Level

A series of follow-up analyses used the significant clusters resulting from group analyses as a mask to extract mean z scores from each participant’s amygdala RSFC z score map. Within the MDD group, Pearson correlations were conducted on these z scores with symptom severity (CDRS-R and BDI-II total scores) and IDAS symptom domains. To account for multiple analyses conducted, we used Holm’s36 stepdown Bonferroni approach. Holm’s procedure is less conservative than the Bonferroni approach and, similar to the Bonferroni approach, does not require that the tests be independent. To explore whether additional clinical factors, such as prior medication exposure or the presence of a comorbid anxiety disorder, might have influenced the results, we compared the mean amygdala RSFC within these clusters between adolescents with MDD who were and were not medication naive, as well as between adolescents with MDD with and without a current anxiety disorder, using an independent-samples, 2-tailed unpaired t test.

Participants

Forty-three unmedicated adolescents with MDD and 31 HC participants completed all procedures. After excluding participants with excessive motion, 41 adolescents with MDD (73% medication-naive) and 29 HCs were included in our final analyses (Table 1). There were no significant differences between the groups with respect to age, sex, or handedness. As expected, the groups differed significantly with respect to CDRS-R scores, BDI-II scores, and IDAS dimension scores. No significant group differences were detected between MDD medication-naive and medication-free participants with the exception of IDAS scores for insomnia, panic, and social anxiety (eTable in the Supplement). In the final sample, the number of excluded volumes was marginally different between groups (U69 = 440.5, P = .053), largely because the HC group had fewer people with no excluded volumes (eFigure 3 in the Supplement).

Table Graphic Jump LocationTable 1.  Demographic and Clinical Characteristics
Group Differences in Amygdala RSFC

Adolescents with MDD showed lower positive amygdala RSFC compared with HCs, with a cluster that included the left hippocampus and parahippocampus, as well as a small piece of orbitofrontal cortex and temporal pole, and extended into the brainstem (Figure 1 and Table 2; eFigure 4 in the Supplement presents a depiction of the orbitofrontal involvement). Additionally, the adolescents with MDD differed from the HCs in amygdala RSFC with the bilateral precuneus, with patients showing positive RSFC and HCs showing negative RSFC (Figure 2 and Table 2). Follow-up analyses revealed no significant group differences between medication-naive and medication-free participants with MDD in these circuits or between MDD participants with (25 [61%]) vs those without (16 [39%]) a comorbid anxiety disorder (defined by the presence of any current anxiety disorder). Our whole-brain analyses to examine group-by-age interaction and group-by-sex interaction in mean amygdala RSFC did not reveal any significant clusters. In addition, when the specific regions that showed group differences were further examined (precuneus and left hippocampus, parahippocampus, and brainstem), there were no significant group-by-age or group-by sex interactions.

Place holder to copy figure label and caption
Figure 1.
Lower Amygdala Functional Connectivity in Adolescents With Major Depressive Disorder (MDD)

A, The cluster resulting from group analysis of amygdala functional connectivity in the controls > MDD contrast, which includes the left hippocampus, parahippocampus, brainstem, orbitofrontal cortex, and temporal pole. The coordinates represent the position of the voxel with the highest intensity in Montreal Neurological Institute standard space (z = 5.00). B, The means (bars within the boxes) and ranges (limit lines) of functional connectivity z scores in this cluster for the 2 groups. The analyses were repeated with the MDD outlier removed and the results remained significant: t67 = 5.77; P < .001. z Values are represented by the color bars. HCs indicates healthy controls.

Graphic Jump Location
Table Graphic Jump LocationTable 2.  Size and Peak z Values of the Significant Clusters in the Group Analyses
Place holder to copy figure label and caption
Figure 2.
Greater Amygdala Functional Connectivity in Adolescents With Major Depressive Disorder (MDD)

A, The cluster resulting from group analysis of amygdala functional connectivity in the MDD > controls contrast, which includes the bilateral precuneus. The coordinates represent the position of the voxel with the highest intensity in Montreal Neurological Institute standard space (z = 4.3). B, The means (bars within the boxes) and ranges (limit lines) of functional connectivity z scores in this cluster for the 2 groups. z Values are represented by the color bars. HCs indicates healthy controls.

Graphic Jump Location
Correlations With Symptom Domains

Within the MDD group, we used Pearson correlation coefficients to examine how amygdala RSFC scores within the clusters identified above relate to clinical severity and IDAS dimensions (Table 3). Several significant correlations were noted for the amygdala-hippocampal and brainstem circuit, where participants with lower positive RSFC in this circuit had greater IDAS general depression, dysphoria, and lassitude scores as well as lower IDAS well-being scores. However, the summary scores on the CDRS-R and the BDI-II were not significantly correlated with RSFC in the identified amygdala networks.

Table Graphic Jump LocationTable 3.  Correlations Between Amygdala Connectivity z Scores and Symptom Domains for the MDD Group

In this study, we report abnormal amygdala RSFC in adolescents with MDD compared with that in HCs. The pattern of findings has not been previously reported in the depression literature, to our knowledge, and may represent important new information about the brain circuitry of MDD in adolescents. Strengths of the present study include the relatively large sample of adolescents with MDD who were not receiving medication (approximately twice the sample size evaluated in recent rsfMRI studies in similar populations17,18) and the rigorous methods used to remove noise associated with physiologic signals and motion. In addition, the results of the present study identify a fruitful avenue for future work by providing preliminary evidence that abnormal circuits map onto specific symptom dimensions.

Amygdala-Hippocampus and Parahippocampus RSFC

In the present study, adolescents with MDD showed lower positive RSFC compared with the HCs between the amygdala and a cluster involving the left hippocampus and parahippocampus, and this abnormality was associated with a lower sense of well-being and higher levels of general depression, dysphoria, and lassitude. The amygdala is richly connected with the hippocampus and parahippocampus,37,38 and positive RSFC between these regions has been shown39 in healthy adults. Studies in animal models4042 suggest that amygdala-hippocampal connections facilitate the modulation of emotional memories, and prior work4345 using task fMRI in healthy adults has shown that amygdala-hippocampal connectivity increases during encoding and retrieval of emotional memories. A study46 in adults with MDD using a memory task found that patients showed greater amygdala-hippocampal connectivity compared with healthy controls during successful encoding of negative emotional memories, but no significant group differences were found for neutral or positive memories. However, with findings similar to ours, a recent study47 of adults with MDD that used a whole-brain, multivariate pattern classification approach identified the amygdala-hippocampus as one of many connections showing lower RSFC compared with the RSFC in HCs, and 2 reports20,48 in populations at risk for MDD showed similar findings. Therefore, it could be that, in patients with or at risk for MDD, the circuit is underconnected during rest, potentially as a compensatory process to offset the hyperconnectivity that may occur during the processing of negative emotional memories and/or the general hyperactivity of the amygdala in depression.49,50 These speculations require further investigation examining (1) the dynamic change of amygdala-hippocampal connections across states of rest, memory encoding, and memory retrieval; (2) whether this abnormality represents a direct manifestation of illness or an adaptation owing to another abnormality (eg, excessive amygdala activation in depression); and (3) how RSFC and the related functions of this circuit might be restored as a consequence of treatment for MDD.

Amygdala-Brainstem RSFC

Our findings showed decreased RSFC between the amygdala and brainstem in adolescents with MDD; to our knowledge, these data have not previously been reported in the depression literature. Animal research10 has identified amygdala-brainstem connectivity as an important network for modulating visceral function in relation to emotional stimuli. Excitatory pathways extend from the amygdala to brainstem centers such as periaqueductal gray, locus ceruleus, raphe nucleus, and autonomic-related brainstem nuclei; modulatory pathways from these centers project back to the amygdala.51 These pathways are important for basic functioning, such as arousal and appetitive drives. In the present study, RSFC in this circuit correlated with lassitude and, at a trend level of P ≤ .05, appetite loss and insomnia. These preliminary findings suggest that impaired connectivity in this circuit underlies some of the vegetative aspects of MDD. Further research probing this hypothesis with experimental paradigms to assess arousal systems are needed.

Amygdala-Precuneus RSFC

In the present study, adolescents with MDD had positive RSFC between the amygdala and precuneus in contrast to healthy adolescents who showed negative RSFC in this circuit. The precuneus is involved in the processing of self-relevant information5258 and in episodic memory encoding and retrieval.56,59 It is an important node within the default mode network, a group of brain regions that are more active at rest than during a task.60 Negative amygdala-precuneus RSFC has been documented in studies of healthy adults.39,61 Again, although this circuit has not previously been highlighted in the depression literature, recent reports have noted a similar pattern in related populations including adults with high levels of neuroticism,62 children with personal or maternal history of MDD,20 and adults with a history of childhood maltreatment.48 Together, these findings suggest that impaired negative RSFC (or in our study, the presence of positive connectivity) between 2 regions with opposing functions (rest vs threat) may be an important mechanism in depression. Positive synchrony between these regions during rest could underlie a failure to suppress negative self-thoughts that spontaneously emerge during rest. Alternatively, this synchrony could contribute to “disproportionate emotional coloring of self-referential or autobiographical information processing.”62(p842) Both of these possibilities could feasibly perpetuate clinical features seen in depression, such as rumination and the persistently negative mood state.

Amygdala-Frontal RSFC

We predicted that adolescents with MDD would show an amygdala-frontal RSFC deficit. However, the results revealed the deficit to be primarily in subcortical regions (eg, the hippocampus and brainstem). Only a small piece of the cluster representing lower amygdala RSFC in patients compared with HCs extended into the orbitofrontal cortex (eFigure 4 in the Supplement). Several prior studies15,6365 in adults have documented impaired amygdala-frontal RSFC, with mixed results regarding the location and whether the impairment is in positive or negative RSFC. Variance in findings across depression studies could arise from differences in the methods, the heterogeneity of illness, and/or developmental effects.66 Perhaps because the frontal lobe and its limbic connections are still developing during adolescence,7,25 adolescents with depression show a different pattern than adults, with more prominent findings in subcortical areas that mature earlier. It may be that amygdala-frontal RSFC deficits emerge during early adulthood as the MDD vs HC gap in frontal development trajectories widen. Although the results of our age-by-group interaction analysis do not support this hypothesis, longitudinal research examining the trajectory of amygdala RSFC across development into adulthood in youth with and without MDD will be necessary to further examine this question.

Limitations

We have interpreted our amygdala RSFC group difference findings based on the clinical features of MDD and what is known about the function of the implicated brain regions. However, these interpretations of our observational data should be considered preliminary and speculative. Confirmation of the hypotheses suggested here will require further research using a multimodal approach that includes behavioral methods capable of investigating the function of the circuits in question (eg, self-processing and emotional memory). Furthermore, our findings regarding clinical correlations between RSFC and symptom dimensions should be interpreted with caution because the large number of tests that were conducted relative to the sample size. Future research is needed with larger samples to further examine the relationships between RSFC and symptom dimensions.

The cross-sectional design of this study prohibits causal interpretations of the results. It is unclear whether the abnormalities reported represent risk markers for MDD or whether they emerge during the course of illness as a result of disease processes. Longitudinal research using these measures, ideally beginning with high-risk adolescents before the onset of the illness and tracking the course of the illness after onset, is needed to address these questions.

Similar to the population in other adolescent depression studies,1618,67 the participants in our sample had relatively high rates of current comorbid anxiety disorders. This outcome is a limitation because the findings may not be specific to MDD. However, post hoc analyses comparing patients with vs those without anxiety disorders on the amygdala-hippocampus and amygdala-precuneus circuits did not reveal any significant differences. Furthermore, because there were no significant associations between the main amygdala connectivity findings with any of the anxiety dimensions from the IDAS, the abnormalities appear to be more related to depression than anxiety symptoms in these patients.

As has been recently highlighted in the literature,22,23 motion of the participant during the scan can significantly affect rsfMRI findings. Several methods have been proposed outlining approaches to reduce the effect of motion artifacts, one of which we incorporated into our study.22 We removed volumes exceeding our threshold, resulting in variance across the participants in the number of volumes for final analysis. Because RSFC can change over time,68 this variable introduces the possibility that removed volumes could potentially have altered the overall RSFC measure. We and others22 believe that the potential for introducing artificial correlations from motion artifacts was a far greater risk than that of losing these short, randomly spaced epochs of resting data.

Certain limitations arise from our seed-based approach. We used a hypothesis-driven approach for our rsfMRI data analysis, correlating the time series of a seed ROI with every voxel as an index of whole-brain functional RSFC.11 This approach limits the results based on which seed region is chosen. Data-driven approaches avoid this limitation, but the results can be more difficult to interpret. Furthermore, we used an ROI of the entire amygdala, but prior work39 has shown that amygdala subregions have dissociable functional networks. Future research should investigate how RSFC patterns in adolescents with MDD vary across amygdala subregions; such research would benefit from recent advances in acquisition methods that allow for higher spatial resolution.69 Many studies define seeds by creating a sphere in standard space around a location from the literature16,70 or with use of an atlas-defined region.15 Such approaches have limitations inherent to between-person differences in anatomy. To address this issue, we defined our seed regions based on each participant’s anatomy using FreeSurfer. This method introduces the potential limitations of the automated approach to accurately parcellate the anatomy. However, FreeSurfer-based parcellation of the amygdala is superior to other automated methods in some respects.71,72 Several recent studies7376 have used FreeSurfer to investigate the amygdala volume in different populations with a range of clinical problems. Furthermore, we visually inspected each person’s FreeSurfer results to identify and correct errors, which did not occur in our ROIs.

We report abnormal amygdala RSFC in the largest sample to date of adolescents with MDD. The findings could reflect impairments in the networks that process spontaneous memories that arise during rest and underlie persistent negative mood and vegetative symptoms in these adolescents. Future research using multimodal approaches that incorporate experimental paradigms to probe relevant systems implicated in memory, self-processing, and arousal would be ideal for further illuminating brain-behavior relationships in adolescents with MDD. Given the differences from previous findings in adults, it may be that RSFC abnormalities evolve over the course of development. Longitudinal research is needed to understand how RSFC changes throughout development, course of illness, and treatment response in adolescents with MDD.

Submitted for Publication: November 25, 2013; final revision received April 22, 2014; accepted April 27, 2014.

Corresponding Author: Kathryn R. Cullen, MD, Department of Psychiatry, School of Medicine, University of Minnesota, F268 West Bldg, 2450 Riverside Ave, Minneapolis MN 55454 (rega0026@umn.edu).

Published Online: August 13, 2014. doi:10.1001/jamapsychiatry.2014.1087.

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

Study concept and design: Cullen, Klimes-Dougan, Mueller, Lim.

Acquisition, analysis, or interpretation of data: Cullen, Klimes-Dougan, Westlund, Mueller, Houri, Eberly.

Drafting of the manuscript: Cullen, Klimes-Dougan, Westlund, Lim.

Critical revision of the manuscript for important intellectual content: Cullen, Klimes-Dougan, Westlund, Mueller, Houri, Eberly.

Statistical analysis: Cullen, Westlund, Houri, Eberly.

Obtained funding: Cullen.

Administrative, technical, or material support: Cullen, Klimes-Dougan, Mueller.

Study supervision: Cullen, Klimes-Dougan.

Conflict of Interest Disclosures: None reported.

Funding/Support: The study was funded by National Institute of Mental Health grant K23MH090421 (Dr Cullen) and Biotechnology Research Center grant P41 RR008079 (Center for Magnetic Resonance Research), the National Alliance for Research on Schizophrenia and Depression, the University of Minnesota Graduate School, and the Minnesota Medical Foundation. This work was carried out in part using computing resources at the University of Minnesota Supercomputing Institute.

Role of the Sponsor: The funding sources supported the roles of design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation of the manuscript. The funding sources were not involved in the decision to submit the manuscript for publication.

Additional Contributions: We first and foremost thank the patients and families who contributed to this study.

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Tang  Y, Kong  L, Wu  F,  et al.  Decreased functional connectivity between the amygdala and the left ventral prefrontal cortex in treatment-naive patients with major depressive disorder: a resting-state functional magnetic resonance imaging study. Psychol Med. 2013;43(9):1921-1927.
PubMed   |  Link to Article
Cullen  KR, Gee  DG, Klimes-Dougan  B,  et al.  A preliminary study of functional connectivity in comorbid adolescent depression. Neurosci Lett. 2009;460(3):227-231.
PubMed   |  Link to Article
Gabbay  V, Ely  BA, Li  Q,  et al.  Striatum-based circuitry of adolescent depression and anhedonia. J Am Acad Child Adolesc Psychiatry. 2013;52(6):628-641.e613.
PubMed   |  Link to Article
Connolly  CG, Wu  J, Ho  TC,  et al.  Resting-state functional connectivity of subgenual anterior cingulate cortex in depressed adolescents. Biol Psychiatry. 2013;74(12):898-907.
PubMed   |  Link to Article
Jin  C, Gao  C, Chen  C,  et al.  A preliminary study of the dysregulation of the resting networks in first-episode medication-naive adolescent depression. Neurosci Lett. 2011;503(2):105-109.
PubMed   |  Link to Article
Luking  KR, Repovs  G, Belden  AC,  et al.  Functional connectivity of the amygdala in early-childhood-onset depression. J Am Acad Child Adolesc Psychiatry. 2011;50(10):1027-1041.e1023.
PubMed   |  Link to Article
Gaffrey  MS, Luby  JL, Repovš  G,  et al.  Subgenual cingulate connectivity in children with a history of preschool-depression. Neuroreport. 2010;21(18):1182-1188.
PubMed   |  Link to Article
Power  JD, Barnes  KA, Snyder  AZ, Schlaggar  BL, Petersen  SE.  Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. Neuroimage. 2012;59(3):2142-2154.
PubMed   |  Link to Article
Satterthwaite  TD, Wolf  DH, Loughead  J,  et al.  Impact of in-scanner head motion on multiple measures of functional connectivity: relevance for studies of neurodevelopment in youth. Neuroimage. 2012;60(1):623-632.
PubMed   |  Link to Article
Murphy  K, Birn  RM, Handwerker  DA, Jones  TB, Bandettini  PA.  The impact of global signal regression on resting state correlations: are anti-correlated networks introduced? Neuroimage. 2009;44(3):893-905.
PubMed   |  Link to Article
Cunningham  MG, Bhattacharyya  S, Benes  FM.  Amygdalo-cortical sprouting continues into early adulthood: implications for the development of normal and abnormal function during adolescence. J Comp Neurol. 2002;453(2):116-130.
PubMed   |  Link to Article
Lenroot  RK, Gogtay  N, Greenstein  DK,  et al.  Sexual dimorphism of brain developmental trajectories during childhood and adolescence. Neuroimage. 2007;36(4):1065-1073.
PubMed   |  Link to Article
Kaufman  J, Birmaher  B, Brent  D,  et al.  Schedule for Affective Disorders and Schizophrenia for School-Age Children–Present and Lifetime Version (K-SADS-PL): initial reliability and validity data. J Am Acad Child Adolesc Psychiatry. 1997;36(7):980-988.
PubMed   |  Link to Article
Poznanski  EO, Freman  LN, Mokros  HB.  Children’s Depression Rating Scale–Revised. Psychopharmacol Bull. 1985;21:979-989.
Beck  AT, Steer  RA, Brown  KB. Beck Depression Inventory–Revised. San Antonio, TX: Harcourt Brace; 1996.
Osman  A, Kopper  BA, Barrios  F, Gutierrez  PM, Bagge  CL.  Reliability and validity of the Beck Depression Inventory–II with adolescent psychiatric inpatients. Psychol Assess. 2004;16(2):120-132.
PubMed   |  Link to Article
Watson  D, O’Hara  MW, Simms  LJ,  et al.  Development and validation of the Inventory of Depression and Anxiety Symptoms (IDAS). Psychol Assess. 2007;19(3):253-268.
PubMed   |  Link to Article
Watson  D, O’Hara  MW, Chmielewski  M,  et al.  Further validation of the IDAS: evidence of convergent, discriminant, criterion, and incremental validity. Psychol Assess. 2008;20(3):248-259.
PubMed   |  Link to Article
Watson  D, O’Hara  MW, Naragon-Gainey  K,  et al.  Development and validation of new anxiety and bipolar symptom scales for an expanded version of the IDAS (the IDAS-II). Assessment. 2012;19(4):399-420.
PubMed   |  Link to Article
Glover  GH, Li  TQ, Ress  D.  Image-based method for retrospective correction of physiological motion effects in fMRI: RETROICOR. Magn Reson Med. 2000;44(1):162-167.
PubMed   |  Link to Article
Mazziotta  JC, Toga  AW, Evans  A, Fox  P, Lancaster  J; International Consortium for Brain Mapping (ICBM).  A probabilistic atlas of the human brain: theory and rationale for its development. Neuroimage. 1995;2(2):89-101.
PubMed   |  Link to Article
Holm  S.  A simple sequentially rejective Bonferroni test procedure. Scand J Stat. 1979;6(2):65-70.
Amaral  DG, Insausti  R.  Retrograde transport of D-[3H]-aspartate injected into the monkey amygdaloid complex. Exp Brain Res. 1992;88(2):375-388.
PubMed   |  Link to Article
Stefanacci  L, Suzuki  WA, Amaral  DG.  Organization of connections between the amygdaloid complex and the perirhinal and parahippocampal cortices in macaque monkeys. J Comp Neurol. 1996;375(4):552-582.
PubMed   |  Link to Article
Roy  AK, Shehzad  Z, Margulies  DS,  et al.  Functional connectivity of the human amygdala using resting state fMRI. Neuroimage. 2009;45(2):614-626.
PubMed   |  Link to Article
Hamann  SB, Ely  TD, Grafton  ST, Kilts  CD.  Amygdala activity related to enhanced memory for pleasant and aversive stimuli. Nat Neurosci. 1999;2(3):289-293.
PubMed   |  Link to Article
Izquierdo  I, Medina  JH.  Memory formation: the sequence of biochemical events in the hippocampus and its connection to activity in other brain structures. Neurobiol Learn Mem. 1997;68(3):285-316.
PubMed   |  Link to Article
Kemppainen  S, Jolkkonen  E, Pitkänen  A.  Projections from the posterior cortical nucleus of the amygdala to the hippocampal formation and parahippocampal region in rat. Hippocampus. 2002;12(6):735-755.
PubMed   |  Link to Article
Smith  AP, Stephan  KE, Rugg  MD, Dolan  RJ.  Task and content modulate amygdala-hippocampal connectivity in emotional retrieval. Neuron. 2006;49(4):631-638.
PubMed   |  Link to Article
Greenberg  DL, Rice  HJ, Cooper  JJ, Cabeza  R, Rubin  DC, Labar  KS.  Co-activation of the amygdala, hippocampus and inferior frontal gyrus during autobiographical memory retrieval. Neuropsychologia. 2005;43(5):659-674.
PubMed   |  Link to Article
Dolcos  F, LaBar  KS, Cabeza  R.  Remembering one year later: role of the amygdala and the medial temporal lobe memory system in retrieving emotional memories. Proc Natl Acad Sci U S A. 2005;102(7):2626-2631.
PubMed   |  Link to Article
Hamilton  JP, Gotlib  IH.  Neural substrates of increased memory sensitivity for negative stimuli in major depression. Biol Psychiatry. 2008;63(12):1155-1162.
PubMed   |  Link to Article
Zeng  LL, Shen  H, Liu  L,  et al.  Identifying major depression using whole-brain functional connectivity: a multivariate pattern analysis. Brain. 2012;135(pt 5):1498-1507.
PubMed   |  Link to Article
van der Werff  SJ, Pannekoek  JN, Veer  IM,  et al.  Resting-state functional connectivity in adults with childhood emotional maltreatment. Psychol Med. 2013;43(9):1825-1836.
PubMed   |  Link to Article
Sheline  YI, Barch  DM, Donnelly  JM, Ollinger  JM, Snyder  AZ, Mintun  MA.  Increased amygdala response to masked emotional faces in depressed subjects resolves with antidepressant treatment: an fMRI study. Biol Psychiatry. 2001;50(9):651-658.
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
Price  JL, Drevets  WC.  Neurocircuitry of mood disorders. Neuropsychopharmacology. 2010;35(1):192-216.
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Kircher  TT, Senior  C, Phillips  ML,  et al.  Towards a functional neuroanatomy of self processing: effects of faces and words. Brain Res Cogn Brain Res. 2000;10(1-2):133-144.
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Kjaer  TW, Nowak  M, Lou  HC.  Reflective self-awareness and conscious states: PET evidence for a common midline parietofrontal core. Neuroimage. 2002;17(2):1080-1086.
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Amft  M, Bzdok  D, Laird  AR, Fox  PT, Schilbach  L, Eickhoff  SB.  Definition and characterization of an extended social-affective default network. Brain Struct Funct. 2014;219(1):8. doi:10.1007/s00429-013-0698-0.
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Buckner  RL, Carroll  DC.  Self-projection and the brain. Trends Cogn Sci. 2007;11(2):49-57.
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Cavanna  AE, Trimble  MR.  The precuneus: a review of its functional anatomy and behavioural correlates. Brain. 2006;129(pt 3):564-583.
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Kircher  TT, Brammer  M, Bullmore  E, Simmons  A, Bartels  M, David  AS.  The neural correlates of intentional and incidental self processing. Neuropsychologia. 2002;40(6):683-692.
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Lou  HC, Luber  B, Crupain  M,  et al.  Parietal cortex and representation of the mental self. Proc Natl Acad Sci U S A. 2004;101(17):6827-6832.
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Fletcher  PC, Frith  CD, Baker  SC, Shallice  T, Frackowiak  RS, Dolan  RJ.  The mind’s eye—precuneus activation in memory-related imagery. Neuroimage. 1995;2(3):195-200.
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Raichle  ME, MacLeod  AM, Snyder  AZ, Powers  WJ, Gusnard  DA, Shulman  GL.  A default mode of brain function. Proc Natl Acad Sci U S A. 2001;98(2):676-682.
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Zhang  S, Li  CS.  Functional connectivity mapping of the human precuneus by resting state fMRI. Neuroimage. 2012;59(4):3548-3562.
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Aghajani  M, Veer  IM, van Tol  MJ,  et al.  Neuroticism and extraversion are associated with amygdala resting-state functional connectivity. Cogn Affect Behav Neurosci. 2014;14(2):836-848.
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Tahmasian  M, Knight  DC, Manoliu  A,  et al.  Aberrant intrinsic connectivity of hippocampus and amygdala overlap in the fronto-insular and dorsomedial-prefrontal cortex in major depressive disorder. Front Hum Neurosci. 2013;7:639.
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Yue  Y, Yuan  Y, Hou  Z, Jiang  W, Bai  F, Zhang  Z.  Abnormal functional connectivity of amygdala in late-onset depression was associated with cognitive deficits. PLoS One. 2013;8(9):e75058. doi:10.1371/journal.pone.0075058.
PubMed   |  Link to Article
Veer  IM, Beckmann  CF, van Tol  MJ,  et al.  Whole brain resting-state analysis reveals decreased functional connectivity in major depression. Front Syst Neurosci. 2010;4:4. doi:10.3389/fnsys.2010.00041.
PubMed   |  Link to Article
Sharpley  CF, Bitsika  V.  Differences in neurobiological pathways of four “clinical content” subtypes of depression. Behav Brain Res. 2013;256:368-376.
PubMed   |  Link to Article
Treatment for Adolescents with Depression Study (TADS) Team.  The Treatment for Adolescents With Depression Study (TADS): demographic and clinical characteristics. J Am Acad Child Adolesc Psychiatry. 2005;44(1):28-40.
PubMed   |  Link to Article
Chang  C, Glover  GH.  Time-frequency dynamics of resting-state brain connectivity measured with fMRI. Neuroimage. 2010;50(1):81-98.
PubMed   |  Link to Article
Uğurbil  K, Xu  J, Auerbach  EJ,  et al; WU-Minn HCP Consortium.  Pushing spatial and temporal resolution for functional and diffusion MRI in the Human Connectome Project. Neuroimage. 2013;80(5):80-104.
PubMed   |  Link to Article
Margulies  DS, Kelly  AM, Uddin  LQ, Biswal  BB, Castellanos  FX, Milham  MP.  Mapping the functional connectivity of anterior cingulate cortex. Neuroimage. 2007;37(2):579-588.
PubMed   |  Link to Article
Dewey  J, Hana  G, Russell  T,  et al; HIV Neuroimaging Consortium.  Reliability and validity of MRI-based automated volumetry software relative to auto-assisted manual measurement of subcortical structures in HIV-infected patients from a multisite study. Neuroimage. 2010;51(4):1334-1344.
PubMed   |  Link to Article
Morey  RA, Petty  CM, Xu  Y,  et al.  A comparison of automated segmentation and manual tracing for quantifying hippocampal and amygdala volumes. Neuroimage. 2009;45(3):855-866.
PubMed   |  Link to Article
Butterworth  P, Cherbuin  N, Sachdev  P, Anstey  KJ.  The association between financial hardship and amygdala and hippocampal volumes: results from the PATH Through Life project. Soc Cogn Affect Neurosci. 2012;7(5):548-556.
PubMed   |  Link to Article
Rahman  AS, Xu  J, Potenza  MN.  Hippocampal and amygdalar volumetric differences in pathological gambling: a preliminary study of the associations with the behavioral inhibition system. Neuropsychopharmacology. 2014;39(3):738-745.
PubMed   |  Link to Article
Haukvik  UK, McNeil  T, Lange  EH,  et al.  Pre- and perinatal hypoxia associated with hippocampus/amygdala volume in bipolar disorder. Psychol Med. 2014;44(5):975-985..
PubMed
Chao  L, Weiner  M, Neylan  T.  Regional cerebral volumes in veterans with current versus remitted posttraumatic stress disorder. Psychiatry Res. 2013;213(3):193-201.
PubMed   |  Link to Article

Figures

Place holder to copy figure label and caption
Figure 1.
Lower Amygdala Functional Connectivity in Adolescents With Major Depressive Disorder (MDD)

A, The cluster resulting from group analysis of amygdala functional connectivity in the controls > MDD contrast, which includes the left hippocampus, parahippocampus, brainstem, orbitofrontal cortex, and temporal pole. The coordinates represent the position of the voxel with the highest intensity in Montreal Neurological Institute standard space (z = 5.00). B, The means (bars within the boxes) and ranges (limit lines) of functional connectivity z scores in this cluster for the 2 groups. The analyses were repeated with the MDD outlier removed and the results remained significant: t67 = 5.77; P < .001. z Values are represented by the color bars. HCs indicates healthy controls.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.
Greater Amygdala Functional Connectivity in Adolescents With Major Depressive Disorder (MDD)

A, The cluster resulting from group analysis of amygdala functional connectivity in the MDD > controls contrast, which includes the bilateral precuneus. The coordinates represent the position of the voxel with the highest intensity in Montreal Neurological Institute standard space (z = 4.3). B, The means (bars within the boxes) and ranges (limit lines) of functional connectivity z scores in this cluster for the 2 groups. z Values are represented by the color bars. HCs indicates healthy controls.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1.  Demographic and Clinical Characteristics
Table Graphic Jump LocationTable 2.  Size and Peak z Values of the Significant Clusters in the Group Analyses
Table Graphic Jump LocationTable 3.  Correlations Between Amygdala Connectivity z Scores and Symptom Domains for the MDD Group

References

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PubMed   |  Link to Article
Thomason  ME, Dennis  EL, Joshi  AA,  et al.  Resting-state fMRI can reliably map neural networks in children. Neuroimage. 2011;55(1):165-175.
PubMed   |  Link to Article
Tang  Y, Kong  L, Wu  F,  et al.  Decreased functional connectivity between the amygdala and the left ventral prefrontal cortex in treatment-naive patients with major depressive disorder: a resting-state functional magnetic resonance imaging study. Psychol Med. 2013;43(9):1921-1927.
PubMed   |  Link to Article
Cullen  KR, Gee  DG, Klimes-Dougan  B,  et al.  A preliminary study of functional connectivity in comorbid adolescent depression. Neurosci Lett. 2009;460(3):227-231.
PubMed   |  Link to Article
Gabbay  V, Ely  BA, Li  Q,  et al.  Striatum-based circuitry of adolescent depression and anhedonia. J Am Acad Child Adolesc Psychiatry. 2013;52(6):628-641.e613.
PubMed   |  Link to Article
Connolly  CG, Wu  J, Ho  TC,  et al.  Resting-state functional connectivity of subgenual anterior cingulate cortex in depressed adolescents. Biol Psychiatry. 2013;74(12):898-907.
PubMed   |  Link to Article
Jin  C, Gao  C, Chen  C,  et al.  A preliminary study of the dysregulation of the resting networks in first-episode medication-naive adolescent depression. Neurosci Lett. 2011;503(2):105-109.
PubMed   |  Link to Article
Luking  KR, Repovs  G, Belden  AC,  et al.  Functional connectivity of the amygdala in early-childhood-onset depression. J Am Acad Child Adolesc Psychiatry. 2011;50(10):1027-1041.e1023.
PubMed   |  Link to Article
Gaffrey  MS, Luby  JL, Repovš  G,  et al.  Subgenual cingulate connectivity in children with a history of preschool-depression. Neuroreport. 2010;21(18):1182-1188.
PubMed   |  Link to Article
Power  JD, Barnes  KA, Snyder  AZ, Schlaggar  BL, Petersen  SE.  Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. Neuroimage. 2012;59(3):2142-2154.
PubMed   |  Link to Article
Satterthwaite  TD, Wolf  DH, Loughead  J,  et al.  Impact of in-scanner head motion on multiple measures of functional connectivity: relevance for studies of neurodevelopment in youth. Neuroimage. 2012;60(1):623-632.
PubMed   |  Link to Article
Murphy  K, Birn  RM, Handwerker  DA, Jones  TB, Bandettini  PA.  The impact of global signal regression on resting state correlations: are anti-correlated networks introduced? Neuroimage. 2009;44(3):893-905.
PubMed   |  Link to Article
Cunningham  MG, Bhattacharyya  S, Benes  FM.  Amygdalo-cortical sprouting continues into early adulthood: implications for the development of normal and abnormal function during adolescence. J Comp Neurol. 2002;453(2):116-130.
PubMed   |  Link to Article
Lenroot  RK, Gogtay  N, Greenstein  DK,  et al.  Sexual dimorphism of brain developmental trajectories during childhood and adolescence. Neuroimage. 2007;36(4):1065-1073.
PubMed   |  Link to Article
Kaufman  J, Birmaher  B, Brent  D,  et al.  Schedule for Affective Disorders and Schizophrenia for School-Age Children–Present and Lifetime Version (K-SADS-PL): initial reliability and validity data. J Am Acad Child Adolesc Psychiatry. 1997;36(7):980-988.
PubMed   |  Link to Article
Poznanski  EO, Freman  LN, Mokros  HB.  Children’s Depression Rating Scale–Revised. Psychopharmacol Bull. 1985;21:979-989.
Beck  AT, Steer  RA, Brown  KB. Beck Depression Inventory–Revised. San Antonio, TX: Harcourt Brace; 1996.
Osman  A, Kopper  BA, Barrios  F, Gutierrez  PM, Bagge  CL.  Reliability and validity of the Beck Depression Inventory–II with adolescent psychiatric inpatients. Psychol Assess. 2004;16(2):120-132.
PubMed   |  Link to Article
Watson  D, O’Hara  MW, Simms  LJ,  et al.  Development and validation of the Inventory of Depression and Anxiety Symptoms (IDAS). Psychol Assess. 2007;19(3):253-268.
PubMed   |  Link to Article
Watson  D, O’Hara  MW, Chmielewski  M,  et al.  Further validation of the IDAS: evidence of convergent, discriminant, criterion, and incremental validity. Psychol Assess. 2008;20(3):248-259.
PubMed   |  Link to Article
Watson  D, O’Hara  MW, Naragon-Gainey  K,  et al.  Development and validation of new anxiety and bipolar symptom scales for an expanded version of the IDAS (the IDAS-II). Assessment. 2012;19(4):399-420.
PubMed   |  Link to Article
Glover  GH, Li  TQ, Ress  D.  Image-based method for retrospective correction of physiological motion effects in fMRI: RETROICOR. Magn Reson Med. 2000;44(1):162-167.
PubMed   |  Link to Article
Mazziotta  JC, Toga  AW, Evans  A, Fox  P, Lancaster  J; International Consortium for Brain Mapping (ICBM).  A probabilistic atlas of the human brain: theory and rationale for its development. Neuroimage. 1995;2(2):89-101.
PubMed   |  Link to Article
Holm  S.  A simple sequentially rejective Bonferroni test procedure. Scand J Stat. 1979;6(2):65-70.
Amaral  DG, Insausti  R.  Retrograde transport of D-[3H]-aspartate injected into the monkey amygdaloid complex. Exp Brain Res. 1992;88(2):375-388.
PubMed   |  Link to Article
Stefanacci  L, Suzuki  WA, Amaral  DG.  Organization of connections between the amygdaloid complex and the perirhinal and parahippocampal cortices in macaque monkeys. J Comp Neurol. 1996;375(4):552-582.
PubMed   |  Link to Article
Roy  AK, Shehzad  Z, Margulies  DS,  et al.  Functional connectivity of the human amygdala using resting state fMRI. Neuroimage. 2009;45(2):614-626.
PubMed   |  Link to Article
Hamann  SB, Ely  TD, Grafton  ST, Kilts  CD.  Amygdala activity related to enhanced memory for pleasant and aversive stimuli. Nat Neurosci. 1999;2(3):289-293.
PubMed   |  Link to Article
Izquierdo  I, Medina  JH.  Memory formation: the sequence of biochemical events in the hippocampus and its connection to activity in other brain structures. Neurobiol Learn Mem. 1997;68(3):285-316.
PubMed   |  Link to Article
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Supplement.

eFigure 1. Group (MDD, control) amygdala connectivity maps are shown for left and right amygdala, showing the similarity of these maps

eFigure 2. Results of group analyses when left and right amygdala connectivity was examined separately

eFigure 3. Number of excluded volumes per group based on the data scrubbing methods used to address subject motion during scanning

eFigure 4. The spatial extent of the amygdala connectivity group difference in the Controls>MDD cluster, highlighting the area extending into the left orbitofrontal cortex

eTable. Demographic and clinical characteristics for MDD group, comparing adolescents with and without a history of prior psychotropic medication exposure

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