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Clinical studies of major depression (MD) generally focus on group effects, yet interindividual differences in brain function are increasingly recognized as important and may even impact effect sizes related to group effects. Here, we examine the magnitude of individual differences in relation to group differences that are commonly investigated (e.g., related to MD diagnosis and treatment response). Functional MRI data from 107 participants (63 female, 44 male) were collected at baseline, 2, and 8 weeks during which patients received pharmacotherapy (escitalopram, N  = 68) and controls ( N  = 39) received no intervention. The unique contributions of different sources of variation were examined by calculating how much variance in functional connectivity was shared across all participants and sessions, within/across groups (patients vs controls, responders vs nonresponders, female vs male participants), recording sessions, and individuals. Individual differences and common connectivity across groups, sessions, and participants contributed most to the explained variance (>95% across analyses). Group differences related to MD diagnosis, treatment response, and biological sex made significant but small contributions (0.3-1.2%). High individual variation was present in cognitive control and attention areas, while low individual variation characterized primary sensorimotor regions. Group differences were much smaller than individual differences in the context of MD and its treatment. These results could be linked to the variable findings and difficulty translating research on MD to clinical practice. Future research should examine brain features with low and high individual variation in relation to psychiatric symptoms and treatment trajectories to explore the clinical relevance of the individual differences identified here., Competing Interests: B.N.F. has received grant/research support from Alternative Funding Plan Innovations Award, Brain and Behavior Research Foundation, Canadian Institutes of Health Research, Hamilton Health Sciences Foundation, J. P. Bickell Foundation, Ontario Brain Institute, Ontario Mental Health Foundation, Society for Women's Health Research, Teresa Cascioli Charitable Foundation, Eli Lilly, and Pfizer and has received consultant and/or speaker fees from AstraZeneca, Bristol-Myers Squibb, Canadian Psychiatric Association, CANMAT, Daiichi Sankyo, Lundbeck, Pfizer, Servier, and Sunovion. R.M. has received consulting and speaking honoraria from AbbVie, Allergan, Janssen, KYE, Lundbeck, Otsuka, and Sunovion and research grants from CAN-BIND, CIHR, Janssen, Lallemand, Lundbeck, Nubiyota, OBI, and OMHF. S.P. has been a consultant to Takeda, Bristol Myers Squibb, Lundbeck; has had a research contract with Assurex; and has equity in Mensante. R.W.L. has received speaker and consultant honoraria or research funds from AstraZeneca, Brain Canada, Bristol-Myers Squibb, the Canadian Institutes of Health Research (CIHR), the Canadian Network for Mood and Anxiety Treatments, the Canadian Psychiatric Association, Eli Lilly, Janssen, Lundbeck, Lundbeck Institute, Medscape, Otsuka, Pfizer, Servier, St. Jude Medical, Takeda, the University Health Network Foundation, Vancouver Coastal Health Research Institute, Allergan, Asia-Pacific Economic Cooperation, BC Leading Edge Foundation, Healthy Minds Canada, Michael Smith Foundation for Health Research, MITACS, Myriad Neuroscience, Ontario Brain Institute, Otsuka, Unity Health, Viatris, and VGH-UBCH Foundation. S.H.K. has received honoraria or research funds from Abbott, Alkermes, Allergan, Boehringer Ingelheim, Brain Canada, CIHR, Janssen, Lundbeck, Lundbeck Institute, Ontario Brain Institute, Ontario Research Fund, Otsuka, Pfizer, Servier, Sunovion, and Sun Pharmaceutical and holds stock in Field Trip Health. D.J.M. has received consulting and speaking honoraria from Lundbeck and Genomind. C.S. has received consulting and speaking honoraria from Pfizer, Otsuka, Bayer, Eisai, and research grants from CAN-BIND, CIHR, OBI, and SEAMO. S.C.S. is a senior Scientific Advisor and shareholder in ADMdx, which receives NIH funding, and during the period of this research, he had research grants from Brain Canada, Canada Foundation for Innovation (CFI), Canadian Institutes of Health Research (CIHR), and the Ontario Brain Institute in Canada. Other authors declare no competing financial interests., (Copyright © 2024 van der Wijk et al.)

Many previous intervention studies have used functional magnetic resonance imaging (fMRI) data to predict the antidepressant response of patients with major depressive disorder (MDD); however, practical constraints have limited many of those attempts to small, single centre studies which may not adequately reflect how these models will generalize when used in clinical practice. Not only does the act of collecting data at multiple sites generally increase sample sizes (a critical point in machine learning development) it also generates a more heterogeneous dataset due to systematic differences in scanners at different sites, and geographical differences in patient populations. As part of the Canadian Biomarker Integration Network in Depression (CAN-BIND-1) study, 144 MDD patients from six sites underwent resting state fMRI prior to starting escitalopram treatment, and again two weeks after the start. Here, we consider ways to use machine learning techniques to produce models that can predict response (measured at eight weeks after initiation), based on various parcellations, functional connectivity (FC) metrics, dimensionality reduction algorithms, and base learners, and also whether to use scans from one or both time points. Models that use only baseline (pre-treatment) or only week 2 (early-response) whole-brain FC features consistently failed to perform significantly better than default models. Utilizing the change in FC between these two time points, however, yielded significant results, with the best performing analytical pipeline achieving 69.6% (SD 10.8) accuracy. These results appear contrary to findings from many smaller single-site studies, which report substantially higher predictive accuracies from models trained on only baseline resting state FC features, suggesting these models may not generalize well beyond data used for development. Further, these results indicate the potential value of collecting data both before and shortly after treatment initiation., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

There is a growing interest in examining the wealth of data generated by fusing functional and structural imaging information sources. These approaches may have clinical utility in identifying disruptions in the brain networks that underlie major depressive disorder (MDD). We combined an existing software toolbox with a mathematically dense statistical method to produce a novel processing pipeline for the fast and easy implementation of data fusion analysis (FATCAT-awFC). The novel FATCAT-awFC pipeline was then utilized to identify connectivity (conventional functional, conventional structural and anatomically weighted functional connectivy) changes in MDD patients compared to healthy comparison participants (HC). Data were acquired from the Canadian Biomarker Integration Network for Depression (CAN-BIND-1) study. Large-scale resting-state networks were assessed. We found statistically significant anatomically-weighted functional connectivity (awFC) group differences in the default mode network and the ventral attention network, with a modest effect size (d < 0.4). Functional and structural connectivity seemed to overlap in significance between one region-pair within the default mode network. By combining structural and functional data, awFC served to heighten or reduce the magnitude of connectivity differences in various regions distinguishing MDD from HC. This method can help us more fully understand the interconnected nature of structural and functional connectivity as it relates to depression., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Quality assurance (QA) is crucial in longitudinal and/or multi-site studies, which involve the collection of data from a group of subjects over time and/or at different locations. It is important to regularly monitor the performance of the scanners over time and at different locations to detect and control for intrinsic differences (e.g., due to manufacturers) and changes in scanner performance (e.g., due to gradual component aging, software and/or hardware upgrades, etc.). As part of the Ontario Neurodegenerative Disease Research Initiative (ONDRI) and the Canadian Biomarker Integration Network in Depression (CAN-BIND), QA phantom scans were conducted approximately monthly for three to four years at 13 sites across Canada with 3T research MRI scanners. QA parameters were calculated for each scan using the functional Biomarker Imaging Research Network's (fBIRN) QA phantom and pipeline to capture between- and within-scanner variability. We also describe a QA protocol to measure the full-width-at-half-maximum (FWHM) of slice-wise point spread functions (PSF), used in conjunction with the fBIRN QA parameters. Variations in image resolution measured by the FWHM are a primary source of variance over time for many sites, as well as between sites and between manufacturers. We also identify an unexpected range of instabilities affecting individual slices in a number of scanners, which may amount to a substantial contribution of unexplained signal variance to their data. Finally, we identify a preliminary preprocessing approach to reduce this variance and/or alleviate the slice anomalies, and in a small human data set show that this change in preprocessing can have a significant impact on seed-based connectivity measurements for some individual subjects. We expect that other fMRI centres will find this approach to identifying and controlling scanner instabilities useful in similar studies., Competing Interests: Declaration of Conflicting Interests The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: S. Strother is the Chief Scientific Officer of ADMdx, Inc., which receives NIH funding, and he currently has research grants from Brain Canada, Canada Foundation for Innovation (CFI), Canadian Institutes of Health Research (CIHR), and the Ontario Brain Institute in Canada., (Copyright © 2021. Published by Elsevier Inc.)

Task-based functional neuroimaging methods are increasingly being used to identify biomarkers of treatment response in psychiatric disorders. To facilitate meaningful interpretation of neural correlates of tasks and their potential changes with treatment over time, understanding the reliability of the blood-oxygen-level dependent (BOLD) signal of such tasks is essential. We assessed test-retest reliability of an emotional conflict task in healthy participants collected as part of the Canadian Biomarker Integration Network in Depression. Data for 36 participants, scanned at three time points (weeks 0, 2, and 8) were analyzed, and intra-class correlation coefficients (ICC) were used to quantify reliability. We observed moderate reliability (median ICC values between 0.5 and 0.6), within occipital, parietal, and temporal regions, specifically for conditions of lower cognitive complexity, that is, face, congruent or incongruent trials. For these conditions, activation was also observed within frontal and sub-cortical regions, however, their reliability was poor (median ICC < 0.2). Clinically relevant prognostic markers based on task-based fMRI require high predictive accuracy at an individual level. For this to be achieved, reliability of BOLD responses needs to be high. We have shown that reliability of the BOLD response to an emotional conflict task in healthy individuals is moderate. Implications of these findings to further inform studies of treatment effects and biomarker discovery are discussed., (© 2019 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.)

Finding a clinically useful neuroimaging biomarker that can predict treatment response in patients with major depressive disorder (MDD) is challenging, in part because of poor reproducibility and generalizability of findings across studies. Previous work has suggested that posterior hippocampal volumes in depressed patients may be associated with antidepressant treatment outcomes. The primary purpose of this investigation was to examine further whether posterior hippocampal volumes predict remission following antidepressant treatment. Magnetic resonance imaging (MRI) scans from 196 patients with MDD and 110 healthy participants were obtained as part of the first study in the Canadian Biomarker Integration Network in Depression program (CAN-BIND 1) in which patients were treated for 16 weeks with open-label medication. Hippocampal volumes were measured using both a manual segmentation protocol and FreeSurfer 6.0. Baseline hippocampal tail (Ht) volumes were significantly smaller in patients with depression compared to healthy participants. Larger baseline Ht volumes were positively associated with remission status at weeks 8 and 16. Participants who achieved early sustained remission had significantly greater Ht volumes compared to those who did not achieve remission by week 16. Ht volume is a prognostic biomarker for antidepressant treatment outcomes in patients with MDD.

Methods: We studied 48 MDD and 30 HC who performed an emotional conflict task in a functional magnetic resonance imaging (fMRI) scanner., Results: On the emotional conflict task, MDD and HC demonstrated a robust emotional Stroop effect in reaction time and accuracy. Overall, accuracy was lower in MDD compared to HC with no significant reaction time differences. The fMRI data indicated lower BOLD activation in MDD compared to HC on comparisons of all trials, congruent, incongruent, and incongruent > congruent trials in regions including right inferior temporal gyrus, lateral occipital cortex, and occipital fusiform gyrus. Behavioural and neuroimaging data indicated no group differences in fearful versus happy face processing., Limitations: Inclusion of a neutral condition may have provided a valuable contrast to how MDD and HC process stimuli without emotional valence compared to stimuli with a strong emotional valence., Conclusions: MDD and HC demonstrated a robust emotional Stroop effect. Compared to HC, MDD demonstrated an overall reduced accuracy on the emotional conflict task and reduced BOLD activity in regions important for face perception and emotion information processing, with no differences in responding to fearful versus happy faces. These findings provide support for the theory of emotion context insensitivity in individuals with depression., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Introduction: Behavioral symptoms are commonly reported by patients with primary biliary cholangitis (PBC). In other patient populations, symptoms are commonly associated with hippocampal volume reduction linked to neuroinflammation (inferred from regional iron deposition), as demonstrated by magnetic resonance imaging (MRI). We hypothesized that PBC patients would exhibit reduced volume and increased iron deposition of the hippocampus., Methods: Seventeen female non-cirrhotic PBC patients and 17 age/gender-matched controls underwent 3-Tesla T 1 -weighted MRI and quantitative susceptibility mapping (QSM; an indicator of iron deposition). The hippocampus and its subfields were segmented from T 1 images using Freesurfer, and susceptibility of the whole hippocampus was calculated from QSM images. Volume and susceptibility were compared between groups, and associations with PBC-40 score and disease indicators (years since diagnosis, Fibroscan value, alkaline phosphatase level, clinical response to ursodeoxycholic acid (UDCA)) were investigated., Results: PBC patients exhibited significantly reduced hippocampal volume (p = 0.023) and increased susceptibility (p = 0.048). Subfield volumes were reduced for the subiculum, molecular layer, granule cell layer of the dentate gyrus and CA4 (p < 0.05). Fibroscan value was significantly correlated with PBC-40 (Spearman's rho = 0.499; p = 0.041) and disease duration (Spearman's rho = 0.568; p = 0.017)., Discussion: Our findings suggest hippocampal changes occur early in the disease course of PBC, similar in magnitude to those observed in major depressive disorder and neurodegenerative diseases., Translational Impact: Clinical management of PBC could include early interventional strategies that promote hippocampal neurogenesis that may beneficially impact behavioral symptoms and improve quality of life.

Objectives: This review synthesized literature on brain activity, indexed by functional magnetic resonance imaging (fMRI), during visual affective information processing in major depressive disorder (MDD). Activation was examined in regions consistently implicated in emotive processing, including the anterior cingulate cortex (ACC), prefrontal cortex (PFC), amygdala, thalamus/basal ganglia and hippocampus. We also reviewed the effects of antidepressant interventions on brain activity during emotive processing., Methods: Sixty-four fMRI studies investigating neural activity during visual emotive information processing in MDD were included., Results: Evidence indicates increased ventro-rostral ACC activity to emotive stimuli and perhaps decreased dorsal ACC activity in MDD. Findings are inconsistent for the PFC, though medial PFC hyperactivity tends to emerge to emotive information processing in the disorder. Depressed patients display increased amygdala activation to negative and arousing stimuli. MDD may also be associated with increased activity to negative, and decreased activity to positive, stimuli in basal ganglia/thalamic structures. Finally, there may be increased hippocampus activation during negative information processing. Typically, antidepressant interventions normalize these activation patterns., Conclusion: In general, depressed patients have increased activation to emotive, especially negative, visual stimuli in regions involved in affective processing, with the exception of certain PFC regions; this pattern tends to normalize with treatment.

Ruminative brooding is associated with increased vulnerability to major depression. Individuals who regularly ruminate will often try to reduce the frequency of their negative thoughts by actively suppressing them. We aim to identify the neural correlates underlying thought suppression in at-risk and depressed individuals. Three groups of women were studied; a major depressive disorder group, an at-risk group (having a first degree relative with depression) and controls. Participants performed a mixed block-event fMRI paradigm involving thought suppression, free thought and motor control periods. Participants identified the re-emergence of "to-be-suppressed" thoughts ("popping" back into conscious awareness) with a button press. During thought suppression the control group showed the greatest activation of the dorsolateral prefrontal cortex, followed by the at-risk, then depressed group. During the re-emergence of intrusive thoughts compared to successful re-suppression of those thoughts, the control group showed the greatest activation of the anterior cingulate cortices, followed by the at-risk, then depressed group. At-risk participants displayed anomalies in the neural regulation of thought suppression resembling the dysregulation found in depressed individuals. The predictive value of these changes in the onset of depression remains to be determined.

The intraparietal sulcus (IPS) is recruited during tasks requiring attention, maintenance and manipulation of information in working memory (WM). While WM tasks often show broad bilateral engagement along the IPS, topographic maps of contralateral (CL) visual space have been identified along the IPS, similar to retinotopic maps in visual cortex. In the present study, we asked how these visuotopic IPS regions are differentially involved in the maintenance and manipulation of spatial information in WM. Visuotopic mapping was performed in 26 participants to define regions of interest along the IPS, corresponding to previously described IPS0-4. In a separate task, we showed that while maintaining the location of a briefly flashed target in WM preferentially engaged CL IPS, manipulation of spatial information by mentally rotating the target around a circle engaged bilateral IPS, peaking in IPS1 in most participants. Functional connectivity analyses showed increased interaction between the IPS and prefrontal regions during manipulation, as well as interhemispheric interactions. Two control tasks demonstrated that covert attention shifts, and nonspatial manipulation (arithmetic), engaged patterns of IPS activation and connectivity that were distinct from WM manipulation. These findings add to our understanding of the role of IPS in spatial WM maintenance and manipulation., (© The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Whether magnetic resonance imaging studies can provide useful information to clinicians who treat people with major depressive disorder remains to be established. There are, however, several recent findings that suggest that likelihood of response may be predicted by imaging findings. For example, morphometric studies have examined whether hippocampus volume is associated with clinically meaningful outcomes such as response to treatment. In general, patients who remit have larger pretreatment hippocampus volumes bilaterally compared with those who do not remit. There are similar preliminary findings for the anterior cingulate cortex. There are also a number of functional imaging studies that have identified different activity patterns in those who are likely to respond to treatment compared with those who are not. Using positron emission tomography, investigators have reported different patterns of response to treatment in those treated with medication compared with those treated with psychotherapy. Some of the potential barriers to the routine use of imaging in psychiatric practice are reviewed briefly.

Bilateral reductions in the volume of the anterior cingulate cortex have been reported in patients with major depressive disorder (MDD) when compared with findings in healthy controls. We compared regional brain volumes in the subgenual prefrontal cortex (SGPFC; Brodmann area (BA) 24(sg)), subcallosal gyrus (BA25) and paracingulate gyrus (BA32) in healthy control subjects and a large and well-characterized sample of patients with recurrent MDD, all of whom had received extensive antidepressant therapy. Patients with a remitted episode of MDD had SGPFC volumes larger than those of healthy controls, while those in an active illness episode did not differ from controls. There were no differences in subcallosal gyrus and paracingulate gyrus volumes between patients with MDD and healthy controls, with the exception that women with MDD had smaller paracingulate volumes than their sex-matched controls. This effect was not related to duration of illness, number of previous episodes, age at illness onset, or age at the time of scanning. Our findings demonstrate SGPFC volume increases in association with long-term antidepressant therapy and suggest that this result may be linked to positive clinical response.

Background: Striatal volume changes reported in bipolar disorders could represent artifacts of medication or comorbid conditions, or illness related changes, either biological predispositions or consequences of illness burden. We conducted volumetric high-risk study to investigate whether striatal volume changes represent primary biological risk factor for bipolar disorders., Methods: High-risk (HR) participants (age range 15-30 years) were recruited from families multiply affected with bipolar disorders. They included 20 affected and 26 unaffected offspring of parents with primary mood disorders, matched by age and sex with 31 controls without a personal or family history of psychiatric disorders. Striatal volumes were measured on 1.5T 3D anatomical MRI images using standard methods., Results: There was a significant difference between groups (affected, unaffected HR and control subjects) in caudate volumes (F=3.50, DF=2; 74 and p=0.04) in absence of putamen volume changes. The caudate volumes were largest in unaffected HR subjects without differences between affected and control or affected and unaffected HR subjects. The maximum changes were found in the head of the caudate. Controlling for non-independence of observations in multiple subjects per family yielded non-significant differences., Conclusions: Despite the biological plausibility, partial agreement with previous studies and nominal statistical significance, controlling for non-independence of observations within families changed the increased caudate volumes among unaffected subjects to non-significant. We thus present these findings as negative, pending further replication. Striatal volume abnormalities did not meet criteria for endophenotype in this study.

Objective: A number of studies have used magnetic resonance imaging to examine volumetric differences in temporal structures in subjects suffering from major depressive disorder. Studies have reported lower hippocampal and amygdala volume, but results have been inconsistent. The authors were interested, therefore, in examining these studies in the aggregate in order to determine whether hippocampal volume is lower in major depressive disorder. They also examined factors that may contribute to the disparate results in the literature., Method: A meta-analysis was conducted of studies that used magnetic resonance imaging to assess the volume of the hippocampus and related structures in patients with major depressive disorder., Results: Patients were seen to have lower hippocampal volume relative to comparison subjects, detectable if the hippocampus was measured as a discrete structure., Conclusions: Although the effect of major depressive disorder on amygdala volume remains to be conclusively established, inclusion of the amygdala with the hippocampus appears to have decreased the likelihood of detecting volumetric differences in either structure. Slice thickness or other scan parameters did not account for a substantive amount of the variance in results, whereas clinical variables of the populations studied, such as duration of illness or presence of abuse, may account for much of the discrepancy between findings.

Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen's d = 0.14, 95% CI: 0.08-0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.

Studies of clinical populations that combine MRI data generated at multiple sites are increasingly common. The Canadian Biomarker Integration Network in Depression (CAN-BIND; www.canbind.ca) is a national depression research program that includes multimodal neuroimaging collected at several sites across Canada. The purpose of the current paper is to provide detailed information on the imaging protocols used in a number of CAN-BIND studies. The CAN-BIND program implemented a series of platform-specific MRI protocols, including a suite of prescribed structural and functional MRI sequences supported by real-time monitoring for adherence and quality control. The imaging data are retained in an established informatics and databasing platform. Approximately 1300 participants are being recruited, including almost 1000 with depression. These include participants treated with antidepressant medications, transcranial magnetic stimulation, cognitive behavioural therapy and cognitive remediation therapy. Our ability to analyze the large number of imaging variables available may be limited by the sample size of the substudies. The CAN-BIND program includes a multimodal imaging database supported by extensive clinical, demographic, neuropsychological and biological data from people with major depression. It is a resource for Canadian investigators who are interested in understanding whether aspects of neuroimaging--alone or in combination with other variables--can predict the outcomes of various treatment modalities., Introduction Treatment of major depressive disorder (MDD) is evidence-based, but treatment selection is not personalized to the features of an individual's illness. (1) The discovery of biomarkers --or predictors--of treatment [...]

Background: Adults with significant childhood trauma and/or serious mental illness may exhibit persistent structural brain changes within limbic structures, including the amygdala. Little is known about the structure of the amygdala prior to the onset of SMI, despite the relatively high prevalence of trauma in at-risk youth. Methods: Data were gathered from the Canadian Psychiatric Risk and Outcome study. A total of 182 youth with a mean age of 18.3 years completed T1-weighted MRI scans along with clinical assessments that included questionnaires on symptoms of depression and anxiety. Participants also completed the Childhood Trauma and Abuse Scale. We used a novel subfield-specific amygdala segmentation workflow as a part of FreeSurfer 6.0 to examine amygdala structure. Results: Participants with higher trauma scores were more likely to have smaller amygdala volumes, particularly within the basal regions. Among various types of childhood trauma, sexual and physical abuse had the largest effects on amygdala subregions. Abuse-related differences in the right basal region mediated the severity of depression and anxiety symptoms, even though no participants met criteria for clinical diagnosis at the time of assessment. Conclusion: The experience of physical or sexual abuse may leave detectable structural alterations in key regions of the amygdala, potentially mediating the risk of psychopathology in trauma-exposed youth. [ABSTRACT FROM AUTHOR]

Despite the wide application of the magnetic resonance imaging (MRI) technique, there are no widely used standards on naming and describing MRI sequences. The absence of consistent naming conventions presents a major challenge in automating image processing since most MRI software require a priori knowledge of the type of the MRI sequences to be processed. This issue becomes increasingly critical with the current efforts toward open-sharing of MRI data in the neuroscience community. This manuscript reports an MRI sequence detection method using imaging metadata and a supervised machine learning technique. Three datasets from the Brain Center for Ontario Data Exploration (Brain-CODE) data platform, each involving MRI data from multiple research institutes, are used to build and test our model. The preliminary results show that a random forest model can be trained to accurately identify MRI sequence types, and to recognize MRI scans that do not belong to any of the known sequence types. Therefore the proposed approach can be used to automate processing of MRI data that involves a large number of variations in sequence names, and to help standardize sequence naming in ongoing data collections. This study highlights the potential of the machine learning approaches in helping manage health data. [ABSTRACT FROM AUTHOR]

With improvements to both scan quality and facial recognition software, there is an increased risk of participants being identified by a 3D render of their structural neuroimaging scans, even when all other personal information has been removed. To prevent this, facial features should be removed before data are shared or openly released, but while there are several publicly available software algorithms to do this, there has been no comprehensive review of their accuracy within the general population. To address this, we tested multiple algorithms on 300 scans from three neuroscience research projects, funded in part by the Ontario Brain Institute, to cover a wide range of ages (3–85 years) and multiple patient cohorts. While skull stripping is more thorough at removing identifiable features, we focused mainly on defacing software, as skull stripping also removes potentially useful information, which may be required for future analyses. We tested six publicly available algorithms (afni_refacer, deepdefacer, mri_deface, mridefacer, pydeface, quickshear), with one skull stripper (FreeSurfer) included for comparison. Accuracy was measured through a pass/fail system with two criteria; one, that all facial features had been removed and two, that no brain tissue was removed in the process. A subset of defaced scans were also run through several preprocessing pipelines to ensure that none of the algorithms would alter the resulting outputs. We found that the success rates varied strongly between defacers, with afni_refacer (89%) and pydeface (83%) having the highest rates, overall. In both cases, the primary source of failure came from a single dataset that the defacer appeared to struggle with - the youngest cohort (3–20 years) for afni_refacer and the oldest (44–85 years) for pydeface, demonstrating that defacer performance not only depends on the data provided, but that this effect varies between algorithms. While there were some very minor differences between the preprocessing results for defaced and original scans, none of these were significant and were within the range of variation between using different NIfTI converters, or using raw DICOM files. [ABSTRACT FROM AUTHOR]

Background: Many patients with primary biliary cholangitis (PBC) experience non-hepatic symptoms that are possibly linked to altered interoception, the sense of the body’s internal state. We used magnetic resonance imaging (MRI) to determine if PBC patients exhibit structural and functional changes of the thalamus and insula, brain regions that process signals related to interoception. Methods: Fifteen PBC patients with mild disease and 17 controls underwent 3 Tesla T1-weighted MRI, resting-state functional MRI, and quantitative susceptibility mapping (QSM), to measure thalamic and insular volume, neuronal activity and iron deposition, respectively. Group differences were assessed using analysis of covariance, and stepwise linear regression was used to determine the predictive power of clinical indicators of disease. Results: PBC patients exhibited reduced thalamic volume (p < 0.01), and ursodeoxycholic acid (UDCA) non-responders exhibited lower left thalamus activity (p = 0.05). PBC patients also exhibited reduced anterior insula activity (p = 0.012), and liver stiffness positively correlated with MRI indicators of anterior insula iron deposition (p < 0.02). Conclusions: PBC affects structure and function of brain regions critically important to interoception. Moreover, these brain changes occur in patients with early, milder disease and thus may potentially be reversible. [ABSTRACT FROM AUTHOR]

Background: Current practice for selecting pharmacological and non-pharmacological antidepressant treatments has yielded low response and remission rates in Major Depressive Disorder (MDD). Neuroimaging biomarkers of brain structure and function may be useful in guiding treatment selection by predicting response vs. non-response outcomes.Methods: In this review, we summarize data from studies examining predictors of treatment response using structural and functional neuroimaging modalities, as they pertain to pharmacotherapy, psychotherapy, and stimulation treatment strategies. A literature search was conducted in OVID Medline, EMBASE, and PsycINFO databases with coverage from January 1990 to January 2017.Results: Several imaging biomarkers of therapeutic response in MDD emerged: frontolimbic regions, including the prefrontal cortex, anterior cingulate cortex, hippocampus, amygdala, and insula were regions of interest. Since these sub-regions are implicated in the etiology of MDD, their association with response outcomes may be the result of treatments having a normalizing effect on structural or activation abnormalities.Limitations: The direction of findings is inconsistent in studies examining these biomarkers, and variation across 'biotypes' within MDD may account for this. Limitations in sample size and differences in methodology likely also contribute.Conclusions: The identification of accurate, reliable neuroimaging biomarkers of treatment response holds promise toward improving treatment outcomes and reducing burden of illness for patients with MDD. However, before these biomarkers can be translated into clinical practice, they will need to be replicated and validated in large, independent samples, and integrated with data from other biological systems. [ABSTRACT FROM AUTHOR]

Background: Impairment of recollection memory is consistently reported in patients with major depressive disorder (MDD) and may reflect underlying functional hippocampal changes, particularly in those with extensive histories of illness. We hypothesized that relative to controls, patients with a protracted course of illness would show diminished hippocampal activation on functional magnetic resonance imaging (fMRI) during a recollection memory task. Methods: Patients who experienced 3 or more previously treated depressive episodes were compared with age- and sex-matched controls. We acquired fMRI data while participants performed a recollection memory process dissociation task. Results: Using bilateral regions of interest (ROIs) prescribed for the right and left hippocampal/ parahippocampal complex, we observed increased activation of the right hippocampal and left parahippocampal gyrus in controls compared with patients with MDD during recollection memory trials. Within-group comparisons revealed heightened engagement of the hippocampal head (R/L) for controls during recollection trials, and greater activation of the hippocampal body/tail (R/L) during the learn-list encoding period in both the MDD and control groups. Recollection memory performance was significantly correlated with changes in blood oxygen level-dependent signal during recollection trials in the ROIs of the right hippocampus and right hippocampal head. Limitations: This study was limited by the inclusion of patients taking antidepressant medication, raising the possibility that the reported findings were treatment effects. Conclusion: The findings of decreased recruitment of the right hippocampal and left parahippocampal gyrus in patients with MDD suggest that these regions may be sensitive to the impact of disease burden and repeated episodes of MDD. This attenuated activation may represent stable changes in hippocampal function that occur over the course of illness in patients with MDD. The findings from within-group comparisons show that the group differences in the activation of the right hippocampal head were driven by greater engagement of this region among controls during recollection memory performance. These results also associate recollection performance impairments in patients with MDD with diminished hippocampal engagement. [ABSTRACT FROM AUTHOR]

Variability in treatment response is a major challenge in the treatment of patients with major depression, and there are few reliable predictors of clinical outcomes. Recent advances in brain-imaging technologies offer promise that neural markers might be useful in the prediction of treatment outcomes. Emerging evidence suggests that hippocampal and anterior cingulate volumes and brain activity in the subgenual cingulate and amygdala may predict treatment response in depression. There are some obvious limitations to the routine use of imaging as a tool for predicting who will respond to a course of treatment. Nonetheless, it is reasonable to consider whether non-invasive brain-imaging methods such as magnetic resonance imaging and electroencephalography combined with sensitive clinical measures of early treatment changes will someday be routinely applied to guide treatment selection for people with depression. [ABSTRACT FROM AUTHOR]

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Copyright of Journal of Psychiatry & Neuroscience is the property of CMA Impact Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Increased, decreased, as well as unchanged pituitary volumes have been reported in bipolar disorders (BD). It is unclear, whether abnormal pituitary volumes increase vulnerability for BD (primary vulnerability marker), or are secondary to burden of illness. To address this question, we performed the first high-risk study of pituitary volumes in affected and unaffected relatives of bipolar subjects. High-risk participants (age range 15–30 years) were recruited from families multiply affected with BD and included 24 unaffected, 19 affected subjects with first or second degree bipolar I or II relative, matched by age and sex with 31 controls without a personal or family history of psychiatric disorders. Pituitary volumes were measured on 1.5 T 3D anatomical MRI images using standard methods. We found comparable pituitary volumes among unaffected, affected relatives of bipolar patients and controls. There were no differences in pituitary volumes between male and female subjects nor was there any sex by group interaction. Analyzing 26 participants with bipolar I parent or excluding 5 medicated subjects did not change the results. There were no differences between subjects from families containing bipolar I versus families containing only bipolar II subjects. The lack of abnormalities in unaffected and also affected subjects early in the course of illness in our study, as well as previous investigations of bipolar and familial unipolar children and adolescents, suggest that pituitary volume abnormalities are unlikely to be a primary risk factor for mood disorders. [ABSTRACT FROM AUTHOR]

Most previous magnetic resonance imaging (MRI) studies of patients with bipolar disorder (BD) report similar hippocampus (HC) volumes across patients and controls, but because patients studied were heterogeneous with respect to course of illness variables and medication status, the conclusions of these studies remain equivocal. Lithium (Li) is the reference-standard drug for BD and its role as an important agent in neuroprotection and neurogenesis has been documented in human and in animal studies. We compared the volume of the HC, hippocampal head (Hh), and body/tail (Hbt) in three groups with no history of medication use before entry into this study: (a) a group of patients treated with Li for 1–8 weeks and then scanned; (b) a group comprised of patients who were unmedicated at the time of scan; and (c) a group of patients treated with either valproic acid or lamotrigine. Healthy age- and sex-matched comparison subjects were also scanned. HC volumes did not differ between the unmedicated and healthy comparison groups. There was a bilateral increase in volumes of HC and Hh in the Li-treated group compared to the unmedicated group, an effect that was apparent even over a brief treatment period. Our study provides further confirmation that Li can exert structural effects on the HC, which are detectable in vivo. The study emphasizes the need to control for even brief exposure to medication in volumetric studies of the HC.Neuropsychopharmacology (2008) 33, 361–367; doi:10.1038/sj.npp.1301405; published online 4 April 2007 [ABSTRACT FROM AUTHOR]

The author reflects on the use of neuroimaging techniques in diagnosing psychiatric conditions. She mentions data from researchers which revealed the potential of combining functional magnetic resonance imaging (MRI) methods and a support vector machine (SVM) pattern classification method to correctly sort depressed patients. She indicates that neuroimaging could reduce sample sizes in treatment studies by eliminating patients who are likely to respond to a specific treatment modality.

Background: Identifying objective biomarkers can assist in predicting remission/non-remission to treatment, improving remission rates, and reducing illness burden in major depressive disorder (MDD).Methods: Sixteen MDD 8-week remitters (MDD-8), twelve 16-week remitters (MDD-16), 14 non-remitters (MDD-NR) and 30 healthy comparison participants (HC) completed a functional magnetic resonance imaging emotional conflict task at baseline, prior to treatment with escitalopram, and 8 weeks after treatment initiation. Patients were followed 16 weeks to assess remitter status.Results: All groups demonstrated emotional Stroop in reaction time (RT) at baseline and Week 8. There were no baseline differences between HC and MDD-8, MDD-16, or MDD-NR in RT or accuracy. By Week 8, MDD-8 demonstrated poorer accuracy compared to HC. Compared to HC, the baseline blood-oxygen level dependent (BOLD) signal was decreased in MDD-8 in brain-stem and thalamus; in MDD-16 in lateral occipital cortex, middle temporal gyrus, and cuneal cortex; in MDD-NR in lingual and occipital fusiform gyri, thalamus, putamen, caudate, cingulate gyrus, insula, cuneal cortex, and middle temporal gyrus. By Week 8, there were no BOLD activity differences between MDD groups and HC.Limitations: The Emotional Conflict Task lacks a neutral (non-emotional) condition, restricting interpretation of how mood may influence perception of non-emotionally valenced stimuli.Conclusions: The Emotional Conflict Task is not an objective biomarker for remission trajectory in patients with MDD receiving escitalopram treatment. Escitalopram may have influenced emotion recognition in MDD groups in terms of augmented accuracy and BOLD signal in response to an Emotional Conflict Task, following 8 weeks of escitalopram treatment. [ABSTRACT FROM AUTHOR]

Preclinical research implicates stress-induced upregulation of the enzyme, serum- and glucocorticoid-regulated kinase 1 (SGK1), in reduced hippocampal volume. In the current study, we tested the hypothesis that greater SGK1 mRNA expression in humans would be associated with lower hippocampal volume, but only among those with a history of prolonged stress exposure, operationalized as childhood maltreatment (physical, sexual, and/or emotional abuse). Further, we examined whether baseline levels of SGK1 and hippocampal volume, or changes in these markers over the course of antidepressant treatment, would predict treatment outcomes in adults with major depression [MDD]. We assessed SGK1 mRNA expression from peripheral blood, and left and right hippocampal volume at baseline, as well as change in these markers over the first 8 weeks of a 16-week open-label trial of escitalopram as part of the Canadian Biomarker Integration Network in Depression program (MDD [ n = 161] and healthy comparison participants [ n = 91]). Childhood maltreatment was assessed via contextual interview with standardized ratings. In the full sample at baseline, greater SGK1 expression was associated with lower hippocampal volume, but only among those with more severe childhood maltreatment. In individuals with MDD, decreases in SGK1 expression predicted lower remission rates at week 16, again only among those with more severe maltreatment. Decreases in hippocampal volume predicted lower week 16 remission for those with low childhood maltreatment. These results suggest that both glucocorticoid-related neurobiological mechanisms of the stress response and history of childhood stress exposure may be critical to understanding differential treatment outcomes in MDD. ClinicalTrials.gov: NCT01655706 Canadian Biomarker Integration Network for Depression Study [ABSTRACT FROM AUTHOR]

Abstract: The neuronal mechanisms underlying the pathophysiology of bipolar disorder (BD) have not been fully characterized. The aim of this study was to compare metabolite levels in the hippocampus and the orbitofrontal cortex in a homogenous population of 12 euthymic patients with well-established BD and 12 age- and sex-matched healthy comparison subjects. Using a GE Signa, 3-Tesla scanner, we performed proton magnetic resonance spectroscopy (H-MRS) to examine levels of N-acetyl aspartate, glutamate and choline-containing compounds. Choline-containing compounds were significantly increased in the hippocampus and the orbitofrontal cortex in BD patients relative to control subjects. Significant elevations of glycerophosphocholine+phosphocholine (GPC+PCh) were measured in the hippocampus and the orbitofrontal cortex of patients. As choline is a marker of membrane phospholipid metabolism, the elevated choline in patients may indicate increased membrane breakdown in the brain regions examined. Abnormal neuronal loss within the hippocampus and orbitofrontal cortex further supports previous work suggesting that these regions are involved in the pathophysiology of BD. [Copyright &y& Elsevier]

Youth at clinical high risk (CHR) for psychosis can present not only with characteristic attenuated psychotic symptoms but also may have other comorbid conditions, including anxiety and depression. These undifferentiated mood symptoms can overlap with the clinical presentation of youth with Distress syndromes. Increased resting-state functional connectivity within cerebello-thalamo-cortical (CTC) pathways has been proposed as a trait-specific biomarker for CHR. However, it is unclear whether this functional neural signature remains specific when compared to a different risk group: youth with Distress syndromes. The purpose of the present work was to describe CTC alterations that distinguish between CHR and Distressed individuals. Using machine learning algorithms, we analyzed CTC connectivity features of CHR (n = 51), Distressed (n = 41), and healthy control (n = 36) participants. We found four cerebellar (lobes VII and left Crus II anterior/posterior) and two basal ganglia (right putamen and right thalamus) nodes containing a set of specific connectivity features that distinguished between CHR, Distressed and healthy control groups. Hyperconnectivity between medial lobule VIIb, somatomotor network and middle temporal gyrus was associated with CHR status and more severe symptoms. Detailed atlas parcellation suggested that CHR individuals may have dysfunction mainly within the associative (cognitive) pathways, particularly, between those brain areas responsible for the multi-sensory signal integration. [ABSTRACT FROM AUTHOR]

Abstract Neuroimaging studies assessing neurobiological differences between patients with major depressive disorder (MDD) and healthy controls (HC) are often hindered by small sample sizes and heterogeneity of the patient sample. We performed a comprehensive literature search for studies assessing cortical thickness between patient and control groups, including studies investigating treatment effects on cortical thickness. We identified 34 studies meeting criteria for the systematic review and used Seed-based d Mapping to meta-analyze 24 of those that met additional criteria. Analysis of the full sample of subjects (MDD = 1073; HC = 936) revealed significant thinning in the MDD group in the bilateral orbitofrontal gyrus (BA 11), left pars opercularis (BA 45) and left calcarine fissure/lingual gyrus (BA 17), as well as an area of significant thickening in the left supramarginal gyrus (BA 40). These results support other imaging modalities that report disruptions in various frontal and temporal areas in MDD and identify additional areas in all major cerebral lobes likely to be significant when parsing for biomarkers of treatment or relapse. Highlights • We need informative neurobiological markers for major depressive disorder. • Recent neuroimaging studies found differences in cortical thickness between groups. • In MDD, we found cortical thinning in frontal and occipital regions (BA 11, 45, 17). • There was cortical thickening in one parietal area (BA 40). • Assessing multiple neurobiological parameters is recommended for future studies. [ABSTRACT FROM AUTHOR]

Background: Major Depressive Disorder (MDD) is highly prevalent and potentially devastating, with widespread aberrations in brain activity. Thalamocortical networks are a potential candidate marker for psychopathology in MDD, but have not yet been thoroughly investigated. Here we examined functional connectivity between major cortical areas and thalamus.Method: Resting-state fMRI from 54 MDD patients and 40 healthy controls were collected. The cortex was segmented into six regions of interest (ROIs) consisting of frontal, temporal, parietal, and occipital lobes and pre-central and post-central gyri. BOLD signal time courses were extracted from each ROI and correlated with voxels in thalamus, while removing signals from every other ROI.Results: Our main findings showed that MDD patients had predominantly increased connectivity between medial thalamus and temporal areas, and between medial thalamus and somatosensory areas. Furthermore, a positive correlation was found between thalamo-temporal connectivity and severity of symptoms.Limitations: Most of the patients in this study were not medication naïve and therefore we cannot rule out possible long-term effects of antidepressant use on the findings.Conclusion: The abnormal connectivity between thalamus and temporal, and thalamus and somatosensory regions may represent impaired cortico-thalamo-cortical modulation underlying emotional, and sensory disturbances in MDD. In the context of similar abnormalities in thalamocortical systems across major psychiatric disorders, thalamocortical dysconnectivity could be a reliable transdiagnostic marker. [ABSTRACT FROM AUTHOR]

Objectives: Many studies have reported that adults with recurrent major depressive disorder (MDD) have smaller hippocampal volumes than control participants. The data are more variable in youth with MDD, where findings have been inconsistent and the effects of factors such as age and co-morbidity have not been systematically examined. This study therefore assessed hippocampus and subgenual anterior cingulate (sgACC) morphometry in 168 youth, aged 12-25, with or without MDD and comorbid anxiety.Methods: Structural magnetic resonance imaging (MRI) scans and clinical assessments were obtained from 80 participants with MDD (36 with comorbid anxiety disorder) and 88 age-matched control participants.Results: Participants with MDD had smaller right hippocampi than controls (p=.013). Older depressed participants (20.1-25 years) had smaller hippocampal volumes than younger ones (<20.1 years; p=.05); this age effect was not apparent in controls (p=.46). Depression scores, indexed by the HAMD17, correlated with hippocampal volumes in older depressed youth. Depressed participants with comorbid anxiety had smaller sgACC, but not hippocampal, volumes than those without anxiety (p=.042).Limitations: Longitudinal, versus cross-sectional, studies can most optimally assess the influence of depression on neurodevelopmental profiles. Though our participants were largely treatment-naïve or in their first week of pharmacotherapy, a handful had extensive treatment histories; thus, treatment history may have influenced brain morphometry.Conclusions: Age effects were apparent when hippocampal volumes of older and younger participants with MDD were compared; such differences were not apparent in healthy participants. Comorbid anxiety was associated with decreased sgACC volumes suggesting delayed or altered neurodevelopment in a key emotion regulation region. [ABSTRACT FROM AUTHOR]

Abstract: Neurobiological mechanisms underlying the development of major depressive disorder (MDD) may differ depending on age-of-onset. Our aim was to compare patients who differ in age-of-onset, while controlling for illness duration, and number of depressive episodes. By directly comparing early-(EOD) and late-onset (LOD) patients, we examined whether age-of-onset is associated with changes in the extent or spatial pattern of cortical thickness. Cross-sectional comparison of cortical thickness in EOD vs. LOD. Age-of-onset was determined based on self-report, with EOD defined as onset prior to age 25. Reduced cortical thickness in the dorsal–lateral prefrontal cortex (DLPFC), pre- and postcentral gyrus, and the lingual gyrus were found in EOD compared to healthy controls (p<0.001). In linear regression models controlling for number of episodes, illness duration, severity, and sex, differences (at p<0.001) were found between EOD and LOD in the bilateral posterior cingulate, parahippocampal gyri, right precuneus, lingual, and fusiform gyri, but not the DLPFC. EOD is associated with greater disturbances in cortical thickness than LOD, even when duration of illness and other factors are controlled. These results provide novel insights on how development of depression is differentiated by age. [Copyright &y& Elsevier]

Background: There is substantial inconsistency in results of brain structural magnetic resonance imaging studies in adult bipolar disorder. This is likely consequent upon limited statistical power of studies together with their clinical and methodological heterogeneity. The current study was undertaken to perform an international collaborative mega-analysis of regional volumetric measurements of individual patient and healthy subject data, to optimize statistical power, detect case-control differences, assess the association of psychotropic medication usage with brain structural variation, and detect other possible sources of heterogeneity. Methods: Eleven international research groups contributed published and unpublished data on 321 individuals with bipolar disorder I and 442 healthy subjects. We used linear mixed effects regression models to evaluate differences in brain structure between patient groups. Results: Individuals with bipolar disorder had increased right lateral ventricular, left temporal lobe, and right putamen volumes. Bipolar patients taking lithium displayed significantly increased hippocampal and amygdala volume compared with patients not treated with lithium and healthy comparison subjects. Cerebral volume reduction was significantly associated with illness duration in bipolar individuals. Conclusions: The application of mega-analysis to bipolar disorder imaging identified lithium use and illness duration as substantial and consistent sources of heterogeneity, with lithium use associated with regionally specific increased brain volume. [ABSTRACT FROM AUTHOR]

Investigation of the insula may inform understanding of the etiopathogenesis of major depressive disorder (MDD). In the present study, we introduced a novel gray matter volume (GMV) based structural covariance technique, and applied it to a multi-centre study of insular subregions of 157 patients with MDD and 93 healthy controls from the Canadian Biomarker Integration Network in Depression (CAN-BIND, https://www.canbind.ca/). Specifically, we divided the unilateral insula into three subregions, and investigated their coupling with whole-brain GMV-based structural brain networks (SBNs). We compared between-group difference of the structural coupling patterns between the insular subregions and SBNs. The insula was divided into three subregions, including an anterior one, a superior-posterior one and an inferior-posterior one. In the comparison between MDD patients and controls we found that patients' right anterior insula showed increased inter-network coupling with the default mode network, and it showed decreased inter-network coupling with the central executive network; whereas patients' right ventral-posterior insula showed decreased inter-network coupling with the default mode network, and it showed increased inter-network coupling with the central executive network. We also demonstrated that patients' loading parameters of the right ventral-posterior insular structural covariance negatively correlated with their suicidal ideation scores; and controls' loading parameters of the right ventral-posterior insular structural covariance positively correlated with their motor and psychomotor speed scores, whereas these phenomena were not found in patients. Additionally, we did not find significant inter-network coupling between the whole-brain SBNs, including salience network, default mode network, and central executive network. Our work proposed a novel technique to investigate the structural covariance coupling between large-scale structural covariance networks, and provided further evidence that MDD is a system-level disorder that shows disrupted structural coupling between brain networks. • Structural covariance analyses may offer network-level insights into the etiopathogenesis of depression • Depression is associated to SBN differences, and these SBN are anatomically co-localized to functional networks. • Our data shows a lateralized SBN difference to the posterior right insula associated to suicidal ideation and psychomotor slowing. [ABSTRACT FROM AUTHOR]

Diversos estudios han utilizado las imágenes por resonancia magnética para examinar las diferencias volumétricas de las estructuras temporales en los individuos con trastorno depresión mayor. Los estudios constataron un menor volumen hipocampal y amigdalar, aunque los resultados han sido contradictorios. Por este motivo, los autores decidieron analizar los estudios conjuntamente para determinar si el volumen hipocampal era menor en el trastorno depresión mayor. También examinaron algunos factores que podrían explicar la disparidad de resultados observadas en la bibliografía. Método: Se efectuó un metaanálisis de los estudios que utilizaron imágenes por resonancia magnética para determinar el volumen del hipocampo y de las estructuras afines en pacientes con trastorno depresivo mayor. Resultados: Al medir el hipocampo como una estructura independiente, se constato un menor volumen hipocampal en los pacientes que en los individuos de control. Conclusiones: Si bien aún no se ha determinado de forma definitiva la influencia del trastorno depresivo mayor sobre el volumen amigdalar, el análisis del complejo hipocampo-amígdala disminuye la probabilidad de detectar diferencias volumétricas en cualquiera de las dos estructuras. El grosor del corte u otros parámetros tomográficos no explican la variabilidad de los resultados, mientras que las variables clínicas de las poblaciones estudiadas, como la duración de la enfermedad o la existencia de malos tratos, explican gran parte de las discrepancias entre los resultados. [ABSTRACT FROM PUBLISHER]