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Objective This study determined the clinical utility of an fMRI classification algorithm predicting medication‐class of response in patients with challenging mood diagnoses. Methods Ninety‐nine 16–27‐year‐olds underwent resting state fMRI scans in three groups—BD, MDD and healthy controls. A predictive algorithm was trained and cross‐validated on the known‐diagnosis patients using maximally spatially independent components (ICs), constructing a similarity matrix among subjects, partitioning the matrix in kernel space and optimizing support vector machine classifiers and IC combinations. This classifier was also applied to each of 12 new individual patients with unclear mood disorder diagnoses. Results Classification within the known‐diagnosis group was approximately 92.4% accurate. The five maximally contributory ICs were identified. Applied to the complicated patients, the algorithm diagnosis was consistent with optimal medication‐class of response to sustained recovery in 11 of 12 cases (i.e., almost 92% accuracy). Conclusion This classification algorithm performed well for the know‐diagnosis but also predicted medication‐class of response in difficult‐to‐diagnose patients. Further research can enhance this approach and extend these findings to be more clinically accessible.

OBJECTIVE: Marijuana (MJ) use is common. Research shows risks for psychiatric illnesses, including major depressive disorder (MDD) and cognitive deficits with MJ use, particularly early-onset use. We investigated cognitive function, functional connectivity, and genetic risk with MDD alone and combined with MJ use, and differences between early-vs. late-onset/non-MJ use in youth. METHOD: A total of 74 youth in four groups were studied: healthy control, MDD, frequent MJ use and current/past MDD plus frequent MJ use. Psychiatric symptoms, cognitive performance and demographics were measured. Default mode network (DMN) brain connectivity was determined. Risk alleles in six genes of interest were evaluated. RESULTS: DMN differences among groups in reward-processing and motor control regions were found; the effects of MJ use and MDD were distinct. Early-onset MJ use was associated with lower IQ and hyperconnectivity within areas of the DMN. Early-onset MJ use was associated with the BDNF risk allele. CONCLUSIONS: Cognitive deficits linked with early-onset MJ use were present within several years after MJ use began and may result from, predispose to, or share a common cause with early-onset MJ use. The DMN was affected by MDD, MJ and their combination, as well as by early-onset MJ use. BDNF carrier state may predispose to early-onset MJ use.© 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd. Language: en

Objective: To determine whether patients with major depressive disorder (MDD) display morphologic, functional, and metabolic brain abnormalities in limbic-cortical regions at a baseline magnetic resonance (MR) scan and whether these changes are normalized in MDD patients in remission at a follow-up scan. Method: A longitudinal 3.0-Tesla (T) magnetic resonance imaging (MRI) study was carried out with cortical thickness measurements with a surface-based approach, perfusion measurements with three-dimensional (3D) pseudo-continuous arterial spin labeling (pCASL), and spectroscopy (1H-MRS) measurements in the anterior cingulate cortex (ACC) with water as an internal reference adjusted for cerebrospinal fluid content. We examined 23 MDD patients and 26 healthy controls. MDD patients underwent a baseline MRI at inclusion and were invited to a follow-up scan when they were in remission or after a 6-month follow-up period. Results: Major findings were a significantly thinner posterior cingulate cortex in non-remitters than in remitters, a significant decrease in perfusion in the frontal lobes and the ACC in non-remitters compared with healthy controls at baseline and significantly reduced N-acetylaspartate, myo-inositol, and glutamate levels in MDD patients compared with healthy controls at baseline. Conclusion: Using novel MRI techniques, we have found abnormalities in cerebral regions related to cortical-limbic pathways in MDD patients.

Objective: The goal of this study was to investigate the relationship between default mode network connectivity and the severity of post-traumatic stress disorder (PTSD) symptoms in a sample of eleven acutely traumatized subjects. Method: Participants underwent a 5.5 min resting functional magnetic resonance imaging scan. Brain areas whose activity positively correlated with that of the posterior cingulate/precuneus (PCC) were assessed. To assess the relationship between severity of PTSD symptoms and PCC connectivity, the contrast image representing areas positively correlated with the PCC was correlated with the subjects’ Clinician Administered PTSD Scale scores. Results: Results suggest that resting state connectivity of the PCC with the perigenual anterior cingulate and the right amygdala is associated with current PTSD symptoms and that correlation with the right amygdala predicts future PTSD symptoms. Conclusion: These results may contribute to the development of prognostic tools to distinguish between those who will and those who will not develop PTSD.

ObjectiveOne factor potentially contributing to the heterogeneity of previous results on structural grey matter alterations in adult participants suffering from post-traumatic stress disorder (PTSD) is the varying levels of dissociative symptomatology. The aim of this study was therefore to test whether the recently defined dissociative subtype of PTSD characterized by symptoms of depersonalization and derealization is characterized by specific differences in volumetric brain morphology. MethodWhole-brain MRI data were acquired for 59 patients with PTSD. Voxel-based morphometry was carried out to test for group differences between patients classified as belonging (n=15) vs. not belonging (n=44) to the dissociative subtype of PTSD. The correlation between dissociation (depersonalization/derealization) severity and grey matter volume was computed. ResultsPatients with PTSD classified as belonging to the dissociative subtype exhibited greater grey matter volume in the right precentral and fusiform gyri as well as less volume in the right inferior temporal gyrus. Greater dissociation severity was associated with greater volume in the right middle frontal gyrus. ConclusionThe results of this first whole-brain investigation of specific grey matter volume in dissociative subtype PTSD indentified structural aberrations in regions subserving the processing and regulation of emotional arousal. These might constitute characteristic biomarkers for the dissociative subtype PTSD.

Objective Electroencephalographic (EEG) neurofeedback training has been shown to produce plastic modulations in salience network and default mode network functional connectivity in healthy individuals. In this study, we investigated whether a single session of neurofeedback training aimed at the voluntary reduction of alpha rhythm (8–12 Hz) amplitude would be related to differences in EEG network oscillations, functional MRI (fMRI) connectivity, and subjective measures of state anxiety and arousal in a group of individuals with post-traumatic stress disorder (PTSD). Method Twenty-one individuals with PTSD related to childhood abuse underwent 30 min of EEG neurofeedback training preceded and followed by a resting-state fMRI scan. Results Alpha desynchronizing neurofeedback was associated with decreased alpha amplitude during training, followed by a significant increase (‘rebound’) in resting-state alpha synchronization. This rebound was linked to increased calmness, greater salience network connectivity with the right insula, and enhanced default mode network connectivity with bilateral posterior cingulate, right middle frontal gyrus, and left medial prefrontal cortex. Conclusion Our study represents a first step in elucidating the potential neurobehavioural mechanisms mediating the effects of neurofeedback treatment on regulatory systems in PTSD. Moreover, it documents for the first time a spontaneous EEG ‘rebound’ after neurofeedback, pointing to homeostatic/compensatory mechanisms operating in the brain.

To determine whether patients with major depressive disorder (MDD) display morphologic, functional, and metabolic brain abnormalities in limbic-cortical regions at a baseline magnetic resonance (MR) scan and whether these changes are normalized in MDD patients in remission at a follow-up scan.A longitudinal 3.0-Tesla (T) magnetic resonance imaging (MRI) study was carried out with cortical thickness measurements with a surface-based approach, perfusion measurements with three-dimensional (3D) pseudo-continuous arterial spin labeling (pCASL), and spectroscopy (1H-MRS) measurements in the anterior cingulate cortex (ACC) with water as an internal reference adjusted for cerebrospinal fluid content. We examined 23 MDD patients and 26 healthy controls. MDD patients underwent a baseline MRI at inclusion and were invited to a follow-up scan when they were in remission or after a 6-month follow-up period.Major findings were a significantly thinner posterior cingulate cortex in non-remitters than in remitters, a significant decrease in perfusion in the frontal lobes and the ACC in non-remitters compared with healthy controls at baseline and significantly reduced N-acetylaspartate, myo-inositol, and glutamate levels in MDD patients compared with healthy controls at baseline.Using novel MRI techniques, we have found abnormalities in cerebral regions related to cortical-limbic pathways in MDD patients.