Neuropsychological deficits predate overt psychosis and overlap with the impairments in the established disease. However, to date, no single neurocognitive measure has shown sufficient power for a ...prognostic test. Thus, it remains to be determined whether multivariate neurocognitive pattern classification could facilitate the diagnostic identification of different at-risk mental states (ARMS) for psychosis and the individualized prediction of illness transition.
First, classification of 30 healthy controls (HC) vs 48 ARMS individuals subgrouped into 20 "early," 28 "late" ARMS subjects was performed based on a comprehensive neuropsychological test battery. Second, disease prediction was evaluated by categorizing the neurocognitive baseline data of those ARMS individuals with transition (n = 15) vs non transition (n = 20) vs HC after 4 years of follow-up. Generalizability of classification was estimated by repeated double cross-validation.
The 3-group cross-validated classification accuracies in the first analysis were 94.2% (HC vs rest), 85.0% (early at-risk subjects vs rest), and, 91.4% (late at-risk subjects vs rest) and 90.8% (HC vs rest), 90.8% (converters vs rest), and 89.0% (nonconverters vs rest) in the second analysis. Patterns distinguishing the early or late ARMS from HC primarily involved the verbal learning/memory domains, while executive functioning and verbal IQ deficits were particularly characteristic of the late ARMS. Disease transition was mainly predicted by executive and verbal learning impairments.
Different ARMS and their clinical outcomes may be reliably identified on an individual basis by evaluating neurocognitive test batteries using multivariate pattern recognition. These patterns may have the potential to substantially improve the early recognition of psychosis.
Abstract Objectives The aim of the study is to map a neural network of emotion processing and to identify differences in major depression compared to healthy controls. It is hypothesized that ...intentional perception of emotional faces activates connections between amygdala (Demir et al.), orbitofrontal cortex (OFC), anterior cingulate cortex (ACC) and prefrontal cortex (PFC) and that frontal-amygdala connections are altered in major depressive disorder (MDD). Methods Fifteen medication-free patients with MDD and fifteen healthy controls were enrolled. All subjects were assessed using the same face-matching functional Magnetic Resonance Imaging (fMRI) task, known to involve those areas. Brain activations were obtained using Statistical Parametric Mapping version 5 (SPM5) for data analysis and MARSBAR for extracting of fMRI time series. Then data was analyzed using structural equation modeling (SEM). Results A valid model was established for the left and the right hemispheres showing a circuit involving ACC, OFC, PFC and AMY. The left hemisphere shows significant lower connectivity strengths in patients than controls, for the pathway that goes from AMY to the OF11, and a trend of higher connectivity in patients for the path that goes from the PF9 to the OF11. In the right hemisphere, patients show lower connectivity coefficients in the paths from the AMY to OF11, from the AMY to ACC, and from the ACC to PF9. By the contrary, controls show lower connectivity strengths for the path that goes from ACC to AMY. Conclusions Functional disconnection between limbic and frontal brain regions could be demonstrated using structural equation modeling. The interpretation of these findings could be that there is an emotional processing bias with disconnection bilaterally between amygdala to orbitofrontal cortices and in addition a right disconnection between amygdala and ACC as well as between ACC and prefrontal cortex possibly in line with a more prominent role for the right hemisphere in emotion processing.
Structural neuroimaging has substantially advanced the neurobiological research of schizophrenia by describing a range of focal brain alterations as possible neuroanatomical underpinnings of the ...disease. Despite this progress, a considerable heterogeneity of structural findings persists that may reflect the phenomenological diversity of schizophrenia. It is unclear whether the range of possible clinical disease manifestations relates to a core structural brain deficit or to distinct structural correlates. Therefore, gray matter density (GMD) differences between 175 schizophrenic patients (SZ) and 177 matched healthy control subjects (HC) were examined in a three-step approach using cross-sectional and conjunctional voxel-based morphometry (VBM): (1) analysis of structural alterations irrespective of symptomatology; (2) subdivision of the patient sample according to a three-dimensional factor model of the PANSS and investigation of structural differences between these subsamples and healthy controls; (3) analysis of a common pattern of structural alterations present in all patient subsamples compared to healthy controls. Significant GMD reductions in patients compared to controls were identified within the prefrontal, limbic, paralimbic, temporal and thalamic regions. The disorganized symptom dimension was associated with bilateral alterations in temporal, insular and medial prefrontal cortices. Positive symptoms were associated with left-pronounced alterations in perisylvian regions and extended thalamic GMD losses. Negative symptoms were linked to the most extended alterations within orbitofrontal, medial prefrontal, lateral prefrontal and temporal cortices as well as limbic and subcortical structures. Thus, structural heterogeneity in schizophrenia may relate to specific patterns of GMD reductions that possibly share a common prefrontal-perisylvian pattern of structural brain alterations.
There is a need to identify clinically useful biomarkers in major depressive disorder (MDD). In this context the functional connectivity of the orbitofrontal cortex (OFC) to other areas of the affect ...regulation circuit is of interest. The aim of this study was to identify neural changes during antidepressant treatment and correlates associated with the treatment outcome. In an exploratory analysis it was investigated whether functional connectivity measures moderated a response to mirtazapine and venlafaxine. Twenty-three drug-free patients with MDD were recruited from the Department of Psychiatry and Psychotherapy of the Ludwig-Maximilians University in Munich. The patients were subjected to a 4-wk randomized clinical trial with two common antidepressants, venlafaxine or mirtazapine. Functional connectivity of the OFC, derived from functional magnetic resonance imaging with an emotional face-matching task, was measured before and after the trial. Higher OFC connectivity with the left motor areas and the OFC regions prior to the trial characterized responders (p<0.05, false discovery rate). The treatment non-responders were characterized by higher OFC-cerebellum connectivity. The strength of response was positively correlated with functional coupling between left OFC and the caudate nuclei and thalami. Differences in longitudinal changes were detected between venlafaxine and mirtazapine treatment in the motor areas, cerebellum, cingulate gyrus and angular gyrus. These results indicate that OFC functional connectivity might be useful as a marker for therapy response to mirtazapine and venlafaxine and to reconstruct the differences in their mechanism of action.
Background Major depressive disorder is associated with both structural and functional alterations in the emotion regulation network of the central nervous system. The relation between structural and ...functional changes is largely unknown. Therefore, we sought to determine the relation between structural differences and functional alterations during the recognition of emotional facial expressions. Methods We examined 13 medication-free patients with major depression and 15 healthy controls by use of structural T1 -weighted high-resolution magnetic resonance imaging (MRI) and functional MRI during 1 session. We set the statistical threshold for the analysis of imaging data to p < 0.001 (uncorrected). Results As shown by voxel-based morphometry, depressed patients had reductions in orbitofrontal cortex volume and increases in cerebellar volume. Additionally, depressed patients showed increased activity during emotion recognition in the middle frontal cortex, caudate nucleus, precuneus and lingual gyrus. Within this cerebral network, the orbitofrontal volumes were negatively correlated in depressed patients but not in healthy controls with changes in blood oxygen level–dependent signal in the middle frontal gyrus, caudate nucleus, precuneus and supplementary motor area. Limitations Our results are limited by the relatively small sample size. Conclusions This combined functional and structural MRI study provides evidence that the orbitofrontal cortex is a key area in major depression and that structural changes result in functional alterations within the emotional circuit. Whether these alterations in the orbitofrontal cortex are also related to persistent emotional dysfunction in remitted mental states and, therefore, are related to the risk of depression needs further exploration.
Abstract Deficits in executive functioning have been described as a core feature of schizophrenia and have been linked to patterns of fronto-temporo-limbic brain alterations. To date, such ...structure–cognition relationships have not been explored in a clinically defined at-risk mental state (ARMS) for psychosis using whole-brain neuroimaging techniques. Therefore, we used voxel-based morphometry in 40 ARMS and 30 matched healthy control (HC) individuals to investigate whether gray and white matter volumes (1) correlated with the performance in the Trail-Making Test B (TMT-B), an established measure of executive functioning, and (2) were volumetrically linked to the ventromedial prefrontal cortex (VMPFC), found to be associated with TMT-B in the ARMS during the first analysis step. We found the ARMS subjects to be specifically impaired in their TMT-B performance versus HC. Brain-cognition associations involving the insular cortices were observed in the HC, but not in the ARMS individuals. Conversely, TMT-B correlations in the VMPFC, the cerebellum, the fronto-callosal white matter were detected in the ARMS, but not the HC group. The VMPFC was linked to the temporo-limbic cortices in HC, whereas the connectivity pattern in the ARMS involved the left temporal and dorsolateral prefrontal cortex, the cerebellum, the right SMA and extended portions of the fronto-callosal white matter. These findings suggest that executive deficits are already present in the ARMS for psychosis and may be subserved by structurally altered networks of interconnected cortical and subcortical brain regions in line with the disconnectivity hypothesis of schizophrenia.
Several studies have demonstrated that structural brain change is detectable in the hippocampus in both patients, with schizophrenia and major depression. Only few studies, however, compared both ...clinical disease entities directly and no larger study has tried to take different disease stages into account. The objectives of this study are to investigate whether hippocampal volumes are reduced in patients with schizophrenia and those with major depression with the same duration of illness compared to healthy controls and to assess further changes at different disease stages. A total of 319 inpatients and healthy controls were enrolled and investigated with magnetic resonance imaging (MRI). Hippocampal volumes were measured using the segmentation software BRAINS. Bilateral hippocampal volume reductions were detected in both schizophrenic and depressed patients compared to healthy control (HC) subjects. Although younger, schizophrenic (SZ) patients showed in their MRI scans significant bilaterally reduced hippocampal volumes compared to patients with major depression. Although the hippocampal reductions were similar at the onset of symptomatic manifestation of both diseases, there was a further significant reduction of the left hippocampus in the recurrently ill SZ subgroup. The data suggest rather dynamic structural brain alterations in schizophrenia compared to major depression. Here, the presented application of the comparative neuroscience approach, by the use of large neuroimaging MRI databases, seems highly valuable. In the field of psychiatry, with its still controversial operationalized descriptive diagnostic entities, the cross-nosological approach provides a helpful tool to better elucidate the still unknown brain pathologies and their underlying molecular mechanisms beyond a single nosological entity.
Identification of individuals at high risk of developing psychosis has relied on prodromal symptomatology. Recently, machine learning algorithms have been successfully used for magnetic resonance ...imaging-based diagnostic classification of neuropsychiatric patient populations.
To determine whether multivariate neuroanatomical pattern classification facilitates identification of individuals in different at-risk mental states (ARMS) of psychosis and enables the prediction of disease transition at the individual level.
Multivariate neuroanatomical pattern classification was performed on the structural magnetic resonance imaging data of individuals in early or late ARMS vs healthy controls (HCs). The predictive power of the method was then evaluated by categorizing the baseline imaging data of individuals with transition to psychosis vs those without transition vs HCs after 4 years of clinical follow-up. Classification generalizability was estimated by cross-validation and by categorizing an independent cohort of 45 new HCs.
Departments of Psychiatry and Psychotherapy, Ludwig-Maximilians-University, Munich, Germany.
The first classification analysis included 20 early and 25 late at-risk individuals and 25 matched HCs. The second analysis consisted of 15 individuals with transition, 18 without transition, and 17 matched HCs.
Specificity, sensitivity, and accuracy of classification.
The 3-group, cross-validated classification accuracies of the first analysis were 86% (HCs vs the rest), 91% (early at-risk individuals vs the rest), and 86% (late at-risk individuals vs the rest). The accuracies in the second analysis were 90% (HCs vs the rest), 88% (individuals with transition vs the rest), and 86% (individuals without transition vs the rest). Independent HCs were correctly classified in 96% (first analysis) and 93% (second analysis) of cases.
Different ARMSs and their clinical outcomes may be reliably identified on an individual basis by assessing patterns of whole-brain neuroanatomical abnormalities. These patterns may serve as valuable biomarkers for the clinician to guide early detection in the prodromal phase of psychosis.
Background The orbitofrontal cortex (OFC) plays a crucial role in emotion-processing circuits and should therefore also be included in models of the pathophysiology of major depression. The aim of ...this study was to compare the functional connectivity of the OFC during emotion processing in patients with major depression and healthy control subjects. Methods Twenty-five untreated patients with major depression and 15 healthy control subjects were investigated using a functional magnetic resonance imaging face-matching task. Results Dorsal anterior cingulate cortex, precuneus, and cerebellum activity showed less connectivity with the OFC in patients than in control subjects. In contrast, functional connectivity between the OFC and the right dorsolateral prefrontal cortex (DLPFC), right inferior frontal operculum, and left motor areas was increased in patients compared with healthy control subjects. Conclusions The OFC plays a key role in the pathophysiology of major depression. The observed imbalance of OFC connectivity seems to represent a neural mechanism of the processing bias. From a neurobiological point of view, the uncoupling of precuneus and gyrus cinguli activity from the OFC might be associated with problems in the regulation of self-schemas, whereas the increased connectivity of the DLPFC to the OFC might represent a higher neural response to negative stimuli.
PDF
