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Background: One hypothesis proposed to underlie formal thought disorder (FTD), the incoherent speech is seen in some patients with schizophrenia, is that it reflects impairment in frontal/executive function. While this proposal has received support in neuropsychological studies, it has been relatively little tested using functional imaging. This study aimed to examine brain activations associated with FTD, and its two main factor-analytically derived subsyndromes, during the performance of a working memory task. Methods: Seventy patients with schizophrenia showing a full range of FTD scores and 70 matched healthy controls underwent fMRI during the performance of the 2-back version of the n-back task. Whole-brain corrected, voxel-based correlations with FTD scores were examined in the patient group. Results: During 2-back performance the patients showed clusters of significant inverse correlation with FTD scores in the inferior frontal cortex and dorsolateral prefrontal cortex bilaterally, the left temporal cortex and subcortically in the basal ganglia and thalamus. Further analysis revealed that these correlations reflected an association only with 'alogia' (poverty of speech, poverty of content of speech and perseveration) and not with the 'fluent disorganization' component of FTD. Conclusions: This study provides functional imaging support for the view that FTD in schizophrenia may involve impaired executive/frontal function. However, the relationship appears to be exclusively with alogia and not with the variables contributing to fluent disorganization. [ABSTRACT FROM AUTHOR]

Background: A leading theory of the negative symptoms of schizophrenia is that they reflect reduced responsiveness to rewarding stimuli. This proposal has been linked to abnormal (reduced) dopamine function in the disorder, because phasic release of dopamine is known to code for reward prediction error (RPE). Nevertheless, few functional imaging studies have examined if patients with negative symptoms show reduced RPE-associated activations., Methods: Matched groups of DSM-5 schizophrenia patients with high negative symptom scores (HNS, N = 27) or absent negative symptoms (ANS, N = 27) and healthy controls (HC, N = 30) underwent fMRI scanning while they performed a probabilistic monetary reward task designed to generate a measure of RPE., Results: In the HC, whole-brain analysis revealed that RPE was positively associated with activation in the ventral striatum, the putamen, and areas of the lateral prefrontal cortex and orbitofrontal cortex, among other regions. Group comparison revealed no activation differences between the healthy controls and the ANS patients. However, compared to the ANS patients, the HNS patients showed regions of significantly reduced activation in the left ventrolateral and dorsolateral prefrontal cortex, and in the right lingual and fusiform gyrus. HNS and ANS patients showed no activation differences in ventral striatal or midbrain regions-of-interest (ROIs), but the HNS patients showed reduced activation in a left orbitofrontal cortex ROI., Conclusions: The findings do not suggest that a generalized reduction of RPE signalling underlies negative symptoms. Instead, they point to a more circumscribed dysfunction in the lateral frontal and possibly the orbitofrontal cortex.

The role of both cannabis use and genetic background has been shown in the risk for psychosis. However, the effect of the interplay between cannabis and variability at the endocannabinoid receptor genes on the neurobiological underpinnings of psychosis remains inconclusive. Through a case-only design, including patients with a first-episode of psychosis (n = 40) classified as cannabis users (50%) and non-users (50%), we aimed to evaluate the interaction between cannabis use and common genetic variants at the endocannabinoid receptor genes on brain activity. Genetic variability was assessed by genotyping two Single Nucleotide Polymorphisms (SNP) at the cannabinoid receptor type 1 gene ( CNR1 ; rs1049353) and cannabinoid receptor type 2 gene (CNR2 ; rs2501431). Functional Magnetic Resonance Imaging (fMRI) data were obtained while performing the n-back task. Gene × cannabis interaction models evidenced a combined effect of CNR1 and CNR2 genotypes and cannabis use on brain activity in different brain areas, such as the caudate nucleus, the cingulate cortex and the orbitofrontal cortex. These findings suggest a joint role of cannabis use and cannabinoid receptor genetic background on brain function in first-episode psychosis, possibly through the impact on brain areas relevant to the reward circuit.

The psychosocial functioning of individuals suffering from bipolar disorder (BD) has a significant impact on prognosis and quality of life. The aim of this study was to assess brain functional correlates of psychosocial functioning in BD individuals during the performance of a working memory task. Sixty-two subjects (31 euthymic BD individuals and 31 matched healthy controls) underwent structural and functional magnetic resonance imaging scanning while performing the 1- and 2-back versions of the n-back task (1-back and 2-back). The Functional Assessment Short Test (FAST) and its subdomains were used to assess functioning. Whole brain analysis revealed only overall activation differences between BD patients and healthy controls, but the patients showed failure of de-activation in the medial frontal cortex. Six clusters of significant inverse correlation with the FAST scores were found in the dorsolateral prefrontal cortex, the superior parietal cortex, and temporo-occipital regions bilaterally, and in the left inferior frontal cortex. Cognitive and occupational functioning were the subdomains most significantly associated with brain activation in these clusters. The results suggest that poor psychosocial functioning in BD individuals is associated with hypoactivation in a range of cortical regions, including the fronto-parietal working memory network and inferior temporo-occipital regions., Competing Interests: Declaration of competing interest Dr. Vieta has received grants and served as consultant, advisor or CME speaker for the following entities (unrelated to the present work): AB-Biotics, Abbott, Allergan, Angelini, Dainippon Sumitomo Pharma, Ferrer, Gedeon Richter, Janssen, Lundbeck, Otsuka, Sage, Sanofi-Aventis, and Takeda. Dr. Verdolini has received financial support for CME activities and travel funds from the following entities (unrelated to the present work): Angelini, Janssen, Lundbeck, Otsuka. The other authors declare that they have no conflicts of interest., (Copyright © 2022 Elsevier B.V. All rights reserved.)

The KCNH2 gene, encoding for a subunit of a voltage-gated potassium channel, has been identified as a key element of neuronal excitability and a promising novel therapeutic target for schizophrenia (SZ). Nonetheless, evidence highlighting the role of KCNH2 on cognitive and brain activity phenotypes comes mainly from studies based on healthy controls (HC). Therefore, we aimed to study the role of KCNH2 on the brain functional differences between patients with SZ and HC. The fMRI sample comprised 78 HC and 79 patients with SZ (matched for age, sex and premorbid IQ). We studied the effect of the polymorphism KCNH2-rs3800779 on attention and working memory-related brain activity, evaluated through the N-back task, in regions with detected diagnostic differences (regression model, controlled for age, sex and premorbid IQ, FEAT-FSL). We report a significant diagnosis x KCNH2 interaction on brain activity (1-back vs baseline contrast) at the medial superior prefrontal cortex (Zmax=3.55, p = 0.00861). In this region, patients with SZ carrying the risk genotype (AA) show a deactivation failure, while HC depict the opposite pattern towards deactivation. The brain region with significant diagnosis x KCNH2 interaction has been previously associated with SZ. The results of this study, in which the role of KCNH2 on fMRI response is analysed for the first time in patients, suggest that KCNH2 variability contributes to inefficient brain activity modulation during the N-back task in affected subjects. These data may pave the way to further understand how KCNH2 genetic variability is related to the pathophysiological mechanisms underlying schizophrenia., Competing Interests: Declaration of Competing Interest All the authors declare that they have no conflicts of interest., (Copyright © 2022 Elsevier B.V. and ECNP. All rights reserved.)

The Computerised Multiple Elements Test (CMET) is a novel executive task to assess goal management and maintenance suitable for use within the fMRI environment. Unlike classical executive paradigms, it resembles neuropsychological multi-elements tests that capture goal management in a more ecological way, by requiring the participant to switch between four simple games within a specified time period. The present study aims to evaluate an fMRI version of the CMET and examine its brain correlates. Thirty-one healthy participants performed the task during fMRI scanning. During each block, they were required to play four simple games, with the transition between games being made either voluntarily (executive condition) or automatically (control condition). The executive condition was associated with increased activity in fronto-parietal and cingulo-opercular regions, with anterior insula activity linked to better task performance. In an additional analysis, the activated regions showed to form functional networks during resting-state and to overlap the executive fronto-parietal and cingulo-opercular networks identified in resting-state with independently defined seeds. These results show the ability of the CMET to elicit activity in well-known executive networks, becoming a potential tool for the study of executive impairment in neurological and neuropsychiatric populations in a more ecological way than classical paradigms., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature.)

Schizophrenia is a complex psychiatric disorder that displays an outstanding interindividual variability in clinical manifestation and neurobiological substrates. A better characterization and quantification of this heterogeneity could guide the search for both common abnormalities (linked to lower intersubject variability) and the presence of biological subtypes (leading to a greater heterogeneity across subjects). In the current study, we address interindividual variability in functional connectome by means of resting-state fMRI in a large sample of patients with schizophrenia and healthy controls. Among the different metrics of distance/dissimilarity used to assess variability, geodesic distance showed robust results to head motion. The main findings of the current study point to (i) a higher between subject heterogeneity in the functional connectome of patients, (ii) variable levels of heterogeneity throughout the cortex, with greater variability in frontoparietal and default mode networks, and lower variability in the salience network, and (iii) an association of whole-brain variability with levels of clinical symptom severity and with topological properties of brain networks, suggesting that the average functional connectome overrepresents those patients with lower functional integration and with more severe clinical symptoms. Moreover, after performing a graph theoretical analysis of brain networks, we found that patients with more severe clinical symptoms had decreased connectivity at both whole-brain level and within the salience network, and that patients with higher negative symptoms had large-scale functional integration deficits., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Deficits in emotion processing are a core feature of schizophrenia, but their neurobiological bases are poorly understood. Previous research, mainly focused on emotional face processing and emotion recognition deficits, has shown controverted results. Furthermore, the use of faces has been questioned for not entailing an appropriate stimulus to study emotional processing. This highlights the importance of investigating emotional processing abnormalities using evocative stimuli. For the first time, we have studied the brain responses to scenic stimuli in patients with schizophrenia. We selected scenes from the IAPS that elicit fear, disgust, happiness, and sadness. Twenty-six patients with schizophrenia and thirty age-, sex- and premorbid IQ-matched healthy controls were included. Behavioral task results show that patients tended to misclassify disgust and sadness as fear. Brain responses in patients were different from controls in images eliciting disgust and fear. In response to disgust images, patients hyperactivated the right temporal cortex, which was not activated by the controls. With fear images, hyperactivation was observed in brain regions involved in fear processing, including midline regions from the medial frontal cortex to the anterior cingulate cortex, the superior frontal gyrus, inferior and superior temporal cortex, and visual areas. These results suggest that schizophrenia is characterized by hyper-responsivity to stimuli evoking high-arousal, negative emotions, and a bias towards fear in emotion recognition., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Although executive and other cognitive deficits have been found in patients with borderline personality disorder (BPD), whether these have brain functional correlates has been little studied. This study aimed to examine patterns of task-related activation and de-activation during the performance of a working memory task in patients with the disorder., Methods: Sixty-seven DSM-IV BPD patients and 67 healthy controls underwent fMRI during the performance of the n-back task. Linear models were used to obtain maps of within-group activations and areas of differential activation between the groups., Results: On corrected whole-brain analysis, there were no activation differences between the BPD patients and the healthy controls during the main 2-back v. baseline contrast, but reduced activation was seen in the precentral cortex bilaterally and the left inferior parietal cortex in the 2-back v. 1-back contrast. The patients showed failure of de-activation affecting the medial frontal cortex and the precuneus, plus in other areas. The changes did not appear to be attributable to previous history of depression, which was present in nearly half the sample., Conclusions: In this study, there was some, though limited, evidence for lateral frontal hypoactivation in BPD during the performance of an executive task. BPD also appears to be associated with failure of de-activation in key regions of the default mode network.

Objectives: The profiles of cortical abnormalities in schizophrenia and bipolar disorder, and how far they resemble each other, have only been studied to a limited extent. The aim of this study was to identify and compare the changes in cortical morphology associated with these pathologies., Methods: A total of 384 subjects, including 128 patients with schizophrenia, 128 patients with bipolar disorder and 127 sex-age-matched healthy subjects, were examined using cortical surface-based morphology. Four cortical structural measures were studied: cortical volume (CV), cortical thickness (CT), surface area (SA) and gyrification index (GI). Group comparisons for each separate cortical measure were conducted., Results: At a threshold of P = 0.05 corrected, both patient groups showed significant widespread CV and CT reductions in similar areas compared to healthy subjects. However, the changes in schizophrenia were more pronounced. While CV decrease in bipolar disorder was exclusively explained by cortical thinning, in schizophrenia it was driven by changes in CT and partially by SA. Reduced GI was only found in schizophrenia. The direct comparison between both disorders showed significant reductions in all measures in patients with schizophrenia., Conclusions: Cortical volume and cortical thickness deficits are shared between patients with schizophrenia and bipolar disorder, suggesting that both pathologies may be affected by similar environmental and neurodegenerative factors. However, the exclusive alteration in schizophrenia of metrics related to the geometry and curvature of the brain cortical surface (SA, GI) suggests that this group is influenced by additional neurodevelopmental and genetic factors., Competing Interests: Declaration of Competing of Interest All authors declare that they have no conflicts of interest., (Copyright © 2019 The Author(s). Published by Elsevier Inc. All rights reserved.)

Magnetic resonance imaging (MRI) has been proposed as a source of information for automatic prediction of individual diagnosis in schizophrenia. Optimal integration of data from different MRI modalities is an active area of research aimed at increasing diagnostic accuracy. Based on a sample of 96 patients with schizophrenia and a matched sample of 115 healthy controls that had undergone a single multimodal MRI session, we generated individual brain maps of gray matter vbm, 1back, and 2back levels of activation ( n back fMRI), maps of amplitude of low-frequency fluctuations (resting-state fMRI), and maps of weighted global brain connectivity (resting-state fMRI). Four unimodal classifiers (Ridge, Lasso, Random Forests, and Gradient boosting) were applied to these maps to evaluate their classification accuracies. Based on the assignments made by the algorithms on test individuals, we quantified the amount of predictive information shared between maps (what we call redundancy analysis). Finally, we explored the added accuracy provided by a set of multimodal strategies that included post-classification integration based on probabilities, two-step sequential integration, and voxel-level multimodal integration through one-dimensional-convolutional neural networks (1D-CNNs). All four unimodal classifiers showed the highest test accuracies with the 2back maps (80% on average) achieving a maximum of 84% with the Lasso. Redundancy levels between brain maps were generally low (overall mean redundancy score of 0.14 in a 0-1 range), indicating that each brain map contained differential predictive information. The highest multimodal accuracy was delivered by the two-step Ridge classifier (87%) followed by the Ridge maximum and mean probability classifiers (both with 85% accuracy) and by the 1D-CNN, which achieved the same accuracy as the best unimodal classifier (84%). From these results, we conclude that from all MRI modalities evaluated task-based fMRI may be the best unimodal diagnostic option in schizophrenia. Low redundancy values point to ample potential for accuracy improvements through multimodal integration, with the two-step Ridge emerging as a suitable strategy., (Copyright © 2019 Salvador, Canales-Rodríguez, Guerrero-Pedraza, Sarró, Tordesillas-Gutiérrez, Maristany, Crespo-Facorro, McKenna and Pomarol-Clotet.)

Objectives: While widespread cortical and subcortical brain functional abnormalities have been found in bipolar disorder, the changes that take place between illness phases and recovery are less clearly documented. Only a small number of longitudinal studies of manic patients, in particular, have been carried out., Methods: Twenty-six bipolar patients underwent fMRI during performance of the n-back working memory task when manic and again after recovery. Twenty-six matched healthy controls were also scanned on two occasions. Task-related activations and de-activations were examined., Results: When manic, the patients showed clusters of significantly reduced activation in the left dorsolateral prefrontal cortex (DLPFC)/precentral cortex and the parietal cortex/superior precuneus bilaterally. They also showed failure of de-activation in the ventromedial frontal cortex (vmPFC). After recovery, activation in the left DLPFC/precentral cortex and in the bilateral parietal cortex/superior precuneus clusters increased significantly. However, failure of de-activation remained present in the vmPFC., Conclusions: Recovery from mania is associated with normalization of DLPFC and parietal hypoactivation, but not with vmPFC failure of de-activation, which accordingly appears to represent a trait abnormality in the disorder., (© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Background: Structural imaging studies of borderline personality disorder (BPD) have found regions of reduced cortical volume, but these have varied considerably across studies. Reduced hippocampus and amygdala volume have also been a regular finding in studies using conventional volumetric measurement. How far comorbid major depression, which is common in BPD and can also affect in brain structure, influences the findings is not clear., Methods: Seventy-six women with BPD and 76 matched controls were examined using whole-brain voxel-based morphometry (VBM). The hippocampus and amygdala were also measured, using both conventional volume measurement and VBM within a mask restricted to these two subcortical structures. Lifetime history of major depression was assessed using structured psychiatric interview., Results: At a threshold of p = 0.05 corrected, the BPD patients showed clusters of volume reduction in the dorsolateral prefrontal cortex bilaterally and in the pregenual/subgenual medial frontal cortex. There was no evidence of volume reductions in the hippocampus or amygdala, either on conventional volumetry or using VBM masked to these regions. Instead there was evidence of right-sided enlargement of these structures. No significant structural differences were found between patients with and without lifetime major depression., Conclusions: According to this study, BPD is characterized by a restricted pattern of cortical volume reduction involving the dorsolateral frontal cortex and the medial frontal cortex, both areas of potential relevance for the clinical features of the disorder. Previous findings concerning reduced hippocampus and amygdala volume in the disorder are not supported. Brain structural findings in BPD do not appear to be explainable on the basis of history of associated lifetime major depression.

Objectives: Neuroimaging studies have revealed evidence of brain functional abnormalities in bipolar depressive disorder (BDD) and major depressive disorder (MDD). However, few studies to date have compared these two mood disorders directly., Methods: Matched groups of 26 BDD type I patients, 26 MDD patients and 26 healthy controls underwent functional magnetic resonance imaging (fMRI) while performing the n-back working memory task. A whole-brain ANOVA was used to compare the three groups and clusters of significant difference were examined further using region-of-interest (ROI) analysis., Results: The whole-brain ANOVA revealed a single cluster of significant difference in the medial frontal cortex. The BDD and MDD patients both showed failure to deactivate in this area compared to the controls. The BDD patients showed significantly greater failure of deactivation than the MDD patients, which was not accounted for by differences in severity or chronicity of illness between them., Conclusions: Failure of deactivation, considered to reflect default mode network dysfunction, is present to a greater extent in bipolar than unipolar depression. The study of this network may be useful in the search for brain markers that distinguish the two disorders., (© 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

A relatively large number of studies have investigated the power of structural magnetic resonance imaging (sMRI) data to discriminate patients with schizophrenia from healthy controls. However, very few of them have also included patients with bipolar disorder, allowing the clinically relevant discrimination between both psychotic diagnostics. To assess the efficacy of sMRI data for diagnostic prediction in psychosis we objectively evaluated the discriminative power of a wide range of commonly used machine learning algorithms (ridge, lasso, elastic net and L0 norm regularized logistic regressions, a support vector classifier, regularized discriminant analysis, random forests and a Gaussian process classifier) on main sMRI features including grey and white matter voxel-based morphometry (VBM), vertex-based cortical thickness and volume, region of interest volumetric measures and wavelet-based morphometry (WBM) maps. All possible combinations of algorithms and data features were considered in pairwise classifications of matched samples of healthy controls (N = 127), patients with schizophrenia (N = 128) and patients with bipolar disorder (N = 128). Results show that the selection of feature type is important, with grey matter VBM (without data reduction) delivering the best diagnostic prediction rates (averaging over classifiers: schizophrenia vs. healthy 75%, bipolar disorder vs. healthy 63% and schizophrenia vs. bipolar disorder 62%) whereas algorithms usually yielded very similar results. Indeed, those grey matter VBM accuracy rates were not even improved by combining all feature types in a single prediction model. Further multi-class classifications considering the three groups simultaneously made evident a lack of predictive power for the bipolar group, probably due to its intermediate anatomical features, located between those observed in healthy controls and those found in patients with schizophrenia. Finally, we provide MRIPredict (https://www.nitrc.org/projects/mripredict/), a free tool for SPM, FSL and R, to easily carry out voxelwise predictions based on VBM images.

Schizophrenia is considered a disorder of abnormal brain connectivity. Although whole brain maps of averaged bivariate voxel correlations have been successfully applied to study connectivity abnormalities in schizophrenia these maps do not adequately explore the multivariate nature of brain connectivity. Here we adapt a novel method for high-dimensional regression (supervised principal component regression) to estimate brain maps of multivariate non redundant connectivity (NRC) from resting functional Magnetic Resonance Imaging (fMRI) data of 116 patients with schizophrenia and 122 matched controls. Disorder related differences in NRC involved caudate hyper-connectivity and hypo-connectivity of several cortical areas such as the dorsal cingulate, the cuneus and the right postcentral cortex. These abnormalities were coupled with abnormalities in the amplitude of signal fluctuations and, to a minor extent, with differences in the dimensionality of connectivity patterns as quantified by the number of supervised principal components. Second level seed correlation analyses linked the observed abnormalities to an additional set of brain regions relevant to schizophrenia such as the thalamus and the temporal cortex. The non redundant connectivity maps proposed here are a new tool that will complement the information provided by other already available voxel based whole brain connectivity measures.

Background: The profile of grey matter abnormalities and related white-matter pathology in schizoaffective disorder has only been studied to a limited extent. The aim of this study was to identify grey- and white-matter abnormalities in patients with schizoaffective disorder using complementary structural imaging techniques., Methods: Forty-five patients meeting Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition criteria and Research Diagnostic Criteria for schizoaffective disorder and 45 matched healthy controls underwent structural-T1 and diffusion magnetic resonance imaging to enable surface-based brain morphometry and diffusion tensor imaging analyses. Analyses were conducted to determine group differences in cortical volume, cortical thickness and surface area, as well as in fractional anisotropy and mean diffusivity., Results: At a threshold of p = 0.05 corrected, all measures revealed significant differences between patients and controls at the group level. Spatial overlap of abnormalities was observed across the various structural neuroimaging measures. In grey matter, patients with schizoaffective disorder showed abnormalities in the frontal and temporal lobes, striatum, fusiform, cuneus, precuneus, lingual and limbic regions. White-matter abnormalities were identified in tracts connecting these areas, including the corpus callosum, superior and inferior longitudinal fasciculi, anterior thalamic radiation, uncinate fasciculus and cingulum bundle., Conclusion: The spatial overlap of abnormalities across the different imaging techniques suggests widespread and consistent brain pathology in schizoaffective disorder. The abnormalities were mainly detected in areas that have commonly been reported to be abnormal in schizophrenia, and to some extent in bipolar disorder, which may explain the clinical and aetiological overlap in these disorders.

Introduction: Cognitive impairment in the euthymic phase is a well-established finding in bipolar disorder. However, its brain structural and/or functional correlates are uncertain., Methods: Thirty-three euthymic bipolar patients with preserved memory and executive function and 28 euthymic bipolar patients with significant memory and/or executive impairment, as defined using two test batteries, the Rivermead Behavioural Memory Test (RBMT) and the Behavioural Assessment of the Dysexecutive Syndrome (BADS), plus 28 healthy controls underwent structural MRI using voxel-based morphometry (VBM). Twenty-seven of the cognitively preserved patients, 23 of the cognitively impaired patients and 28 controls also underwent fMRI during performance of the n-back working memory task., Results: No clusters of grey or white matter volume difference were found between the two patient groups. During n-back performance, the cognitively impaired patients showed hypoactivation compared to the cognitively preserved patients in a circumscribed region in the right dorsolateral prefrontal cortex. Both patient groups showed failure of de-activation in the medial frontal cortex compared to the healthy controls., Conclusions: Cognitive impairment in euthymic bipolar patients appears from this study to be unrelated to structural brain abnormality, but there was some evidence for an association with altered prefrontal function.

Background: Delusional disorder has been the subject of very little investigation using brain imaging., Aims: To examine potential structural and/or functional brain abnormalities in this disorder., Method: We used structural imaging (voxel-based morphometry, VBM) and functional imaging (during performance of the n-back task and whole-brain resting connectivity analysis) to examine 22 patients meeting DSM-IV criteria for delusional disorder and 44 matched healthy controls., Results: The patients showed grey matter reductions in the medial frontal/anterior cingulate cortex and bilateral insula on unmodulated (but not on modulated) VBM analysis, failure of de-activation in the medial frontal/anterior cingulate cortex during performance of the n-back task, and decreased resting-state connectivity in the bilateral insula., Conclusions: The findings provide evidence of brain abnormality in the medial frontal/anterior cingulate cortex and insula in delusional disorder. A role for the former region in the pathogenesis of delusions is consistent with several other lines of evidence., (© The Royal College of Psychiatrists 2016.)

Background: The psychological profile of patients with borderline personality disorder (BPD), with impulsivity and emotional dysregulation as core symptoms, has guided the search for abnormalities in specific brain areas such as the hippocampal-amygdala complex and the frontomedial cortex. However, whole-brain imaging studies so far have delivered highly heterogeneous results involving different brain locations., Methods: Functional resting-state and diffusion magnetic resonance imaging data were acquired in patients with BPD and in an equal number of matched control subjects (n = 60 for resting and n = 43 for diffusion). While mean diffusivity and fractional anisotropy brain images were generated from diffusion data, amplitude of low-frequency fluctuations and global brain connectivity images were used for the first time to evaluate BPD-related brain abnormalities from resting functional acquisitions., Results: Whole-brain analyses using a p = .05 corrected threshold showed a convergence of alterations in BPD patients in genual and perigenual structures, with frontal white matter fractional anisotropy abnormalities partially encircling areas of increased mean diffusivity and global brain connectivity. Additionally, a cluster of enlarged amplitude of low-frequency fluctuations (high resting activity) was found involving part of the left hippocampus and amygdala. In turn, this cluster showed increased resting functional connectivity with the anterior cingulate., Conclusions: With a multimodal approach and without using a priori selected regions, we prove that structural and functional abnormality in BPD involves both temporolimbic and frontomedial structures as well as their connectivity. These structures have been previously related to behavioral and clinical symptoms in patients with BPD., (Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background: Evidence from decades of magnetic resonance imaging (MRI) research in bipolar disorder has been summarized in meta-analyses of various MRI modalities. Notably, although structural MRI studies suggest gray matter reductions are restricted to specific cortical regions, functional MRI has also shown involvement of subcortical dysfunction. Such disparity in results is open to discussion and requires further exploration with additional MRI modalities., Methods: We applied whole-brain high angular resolution molecular diffusion imaging to compare different properties of the water diffusion process in brain tissues, using different contrasts. Specifically, we looked at fractional anisotropy, mean diffusivity, probability of return to the origin, and generalized fractional anisotropy in a sample of 40 euthymic patients with bipolar disorder and 40 well-matched healthy control subjects., Results: Convergent abnormalities were detected by contrasts in various tissue types. Apart from alterations in white matter (in corpus callosum, cingulum bundle, corona radiata, and superior fronto-occipital fasciculus) and cortical gray matter (in medial frontal cortex, left insula, Heschl's gyrus, and cerebellum), three of the contrasts (fractional anisotropy, mean diffusivity, and generalized fractional anisotropy) revealed abnormalities in subcortical structures, including the hippocampus, the thalamus and the caudate nucleus., Conclusions: Our findings point to a wider pattern of axonal pathology in bipolar disorder than previously thought. Although findings related to cortical gray matter are consistent with structural meta-analyses, subcortical abnormalities suggest a cytoarchitectonic basis for previously reported subcortical dysfunction. Diffusion results could be interpreted in terms of loss of tissue volume and/or altered membrane permeability, agreeing with both hypotheses of mitochondrial malfunction and neuroinflammation., (© 2013 Society of Biological Psychiatry Published by Society of Biological Psychiatry All rights reserved.)

Processing of emotions has been an enduring topic of interest in neuroimaging research, but studies have mostly used facial emotional stimuli. The aim of this study was to determine neural networks involved in emotion processing using scenic emotional visual stimuli. One hundred and twenty photographs from the International Affective Picture System (IAPS), including ecological scenes of disgust, fear, happiness, and sadness, were presented to 40 healthy participants while they underwent functional magnetic imaging resonance (fMRI). Afterwards they evaluated the emotional content of the pictures in an offline task. The occipito-temporal cortex and the amygdala-hippocampal complex showed a non-specific emotion-related activation, which was more marked in response to negative emotions than to happiness. The temporo-parietal cortex and the ventral anterior cingulate gyrus showed deactivation, with the former being marked for all emotions except fear and the latter being most marked for disgust. The fusiform gyrus showed activation in response to disgust and deactivation in response to happiness or sadness. Brain regions involved in processing of scenic emotion therefore resemble those reported for facial expressions of emotion in that they respond to a range of different emotions, although there appears to be specificity in the intensity and direction of the response.

Most scoliosis are idiopathic (80%) and occur more frequently in adolescent girls. Plain radiography is the imaging method of choice, both for the initial study and follow-up studies but has the disadvantage of using ionizing radiation. The breasts are exposed to x-ray along these repeated examinations. The authors present a range of recommendations in order to optimize radiographic exam technique for both conventional and digital x-ray settings to prevent unnecessary patients' radiation exposure and to reduce the risk of breast cancer in patients with scoliosis. With analogue systems, leaded breast protectors should always be used, and with any radiographic equipment, analog or digital radiography, the examination should be performed in postero-anterior projection and optimized low-dose techniques. The ALARA (as low as reasonable achievable) rule should always be followed to achieve diagnostic quality images with the lowest feasible dose., (Copyright © 2014. Published by Elsevier Espana.)

Background: Bipolar depression has been found to be associated with changes in prefrontal cortex activity during performance of cognitive tasks. However, the role of task-related de-activations has been little investigated., Method: Forty-one bipolar depressed patients and 41 matched normal controls underwent fMRI scanning while performing baseline, 1-back and 2-back versions of the n-back task. Linear models were used to obtain maps of within-group activations and areas of differential activation between the groups., Results: The bipolar depressed patients showed reduced activation in the dorsolateral prefrontal cortex (DLPFC) bilaterally and several other regions. After controlling for differences in task performance only differences in the DLPFC and cerebellum remained. Left DLPFC activation was inversely correlated with Hamilton and MADRS scores. The patients showed failure to de-activate in the medial prefrontal cortex, an area corresponding to the anterior medial node of the default mode network., Limitations: To confirm default mode network dysfunction demonstration of resting-state connectivity abnormalities would also be required. The study was carried out on treated patients, and did not assess for presence of depressive symptoms in the healthy controls., Conclusions: Both prefrontal cortical and default mode network dysfunction appear to characterise bipolar depression. The former, but not the latter, is associated with symptom severity., (Copyright © 2012 Elsevier B.V. All rights reserved.)