Structural and functional neuroimaging studies in major depressive disorder with psychotic features: a critical review

Functional network characteristics in adolescent psychotic mood disorder: associations with symptom severity and treatment effects

Adolescent psychotic mood disorder (MDP) is a specific phenotype that characterized by more severe symptoms and prognosis compared to nonpsychotic mood disorder (MDNP). But the underlying neural mechanisms remain unknown, and graph theory analysis can help to understand possible mechanisms of psychotic symptoms from the perspective of functional networks. A total of 177 adolescent patients with mood disorders were recruited, including 61 MDP and 116 MDNP. Functional networks were constructed, and topological properties were compared between the two groups at baseline and after treatment, and the association between properties changes and symptom improvement was explored. Compared to the MDNP group, the MDP group exhibited higher small-world properties (FDR q = 0.003) and normalized clustering coefficients (FDR q = 0.008) but demonstrated decreased nodal properties in the superior temporal gyrus (STG), Heschl's gyrus, and medial cingulate gyrus (all FDR q < 0.05). These properties were found to be correlated with the severity of psychotic symptoms. Topological properties also changed with improvement of psychotic symptoms after treatment, and changes in degree centrality of STG in the MDP was significantly positive correlated with improvement of psychotic symptoms (r = 0.377, P = 0.031). This study indicated that functional networks are more severely impaired in patients with psychotic symptoms. Topological properties, particularly those associated with the STG, hold promise as emerging metrics for assessing symptoms and treatment efficacy in patients with psychotic symptoms.

Exosomal miR-1202 mediates Brodmann Area 44 functional connectivity changes in medication-free patients with major depressive disorder: An fMRI study

Previous large-sample postmortem study revealed that the expression of miR-1202 in brain tissues from Brodmann area 44 (BA44) was dysregulated in patients with major depressive disorder (MDDs). However, the specific in vivo neuropathological mechanism of miR-1202 as well as its interplay with BA44 circuits in the depressed brain are still unclear. Here, we performed a case-control study with imaging-genetic approach based on resting-state functional magnetic resonance imaging (MRI) data and miR-1202 quantification from 110 medication-free MDDs and 102 healthy controls. Serum-derived circulating exosomes that readily cross the blood-brain barrier were isolated to quantify miR-1202. For validation, repeated MR scans were performed after a six-week follow-up of antidepressant treatment on a cohort of MDDs. Voxelwise factorial analysis revealed two brain areas (including the striatal-thalamic region) in which the effect of depression on the functional connectivity with BA44 was significantly dependent on the expression level of exosomal miR-1202. Moreover, longitudinal change of the BA44 connectivity with the striatal-thalamic region in MDDs after antidepressant treatment was found to be significantly related to the level of miR-1202 expression. These findings revealed that the in vivo neuropathological effect of miR-1202 dysregulation in depression is possibly exerted by mediating neural functional abnormalities in BA44-striatal-thalamic circuits.

Unraveling the Role of the Blood-Brain Barrier in the Pathophysiology of Depression: Recent Advances and Future Perspectives

Depression is a highly prevalent psychological disorder characterized by persistent dysphoria, psychomotor retardation, insomnia, anhedonia, suicidal ideation, and a remarkable decrease in overall well-being. Despite the prevalence of accessible antidepressant therapies, many individuals do not achieve substantial improvement. Understanding the multifactorial pathophysiology and the heterogeneous nature of the disorder could lead the way toward better outcomes. Recent findings have elucidated the substantial impact of compromised blood-brain barrier (BBB) integrity on the manifestation of depression. BBB functions as an indispensable defense mechanism, tightly overseeing the transport of molecules from the periphery to preserve the integrity of the brain parenchyma. The dysfunction of the BBB has been implicated in a multitude of neurological disorders, and its disruption and consequent brain alterations could potentially serve as important factors in the pathogenesis and progression of depression. In this review, we extensively examine the pathophysiological relevance of the BBB and delve into the specific modifications of its components that underlie the complexities of depression. A particular focus has been placed on examining the effects of peripheral inflammation on the BBB in depression and elucidating the intricate interactions between the gut, BBB, and brain. Furthermore, this review encompasses significant updates on the assessment of BBB integrity and permeability, providing a comprehensive overview of the topic. Finally, we outline the therapeutic relevance and strategies based on BBB in depression, including COVID-19-associated BBB disruption and neuropsychiatric implications. Understanding the comprehensive pathogenic cascade of depression is crucial for shaping the trajectory of future research endeavors.

Brain metabolite levels in remitted psychotic depression with consideration of effects of antipsychotic medication

BACKGROUND

The neurobiology of psychotic depression is not well understood and can be confounded by antipsychotics. Magnetic resonance spectroscopy (MRS) is an ideal tool to measure brain metabolites non-invasively. We cross-sectionally assessed brain metabolites in patients with remitted psychotic depression and controls. We also longitudinally assessed the effects of olanzapine versus placebo on brain metabolites.

METHODS

Following remission, patients with psychotic depression were randomized to continue sertraline + olanzapine (n = 15) or switched to sertraline + placebo (n = 18), at which point they completed an MRS scan. Patients completed a second scan either 36 weeks later, relapse, or discontinuation. Where water-scaled metabolite levels were obtained and a Point-RESolved Spectroscopy sequence was utilized, choline, myo-inositol, glutamate + glutamine (Glx), N-acetylaspartate, and creatine were measured in the left dorsolateral prefrontal cortex (L-DLPFC) and dorsal anterior cingulate cortex (dACC). An ANCOVA was used to compare metabolites between patients (n = 40) and controls (n = 46). A linear mixed-model was used to compare olanzapine versus placebo groups.

RESULTS

Cross-sectionally, patients (compared to controls) had higher myo-inositol (standardized mean difference [SMD] = 0.84; 95%CI = 0.25-1.44; p = 0.005) in the dACC but not different Glx, choline, N-acetylaspartate, and creatine. Longitudinally, patients randomized to placebo (compared to olanzapine) showed a significantly greater change with a reduction of creatine (SMD = 1.51; 95%CI = 0.71-2.31; p = 0.0002) in the dACC but not glutamate + glutamine, choline, myo-inositol, and N-acetylaspartate.

CONCLUSIONS

Patients with remitted psychotic depression have higher myo-inositol than controls. Olanzapine may maintain creatine levels. Future studies are needed to further disentangle the mechanisms of action of olanzapine.

P50 sensory gating, cognitive deficits and depressive symptoms in first-episode antipsychotics-naïve schizophrenia

OBJECTIVE

Sensory gating P50 (SG-P50) may be involved in the pathophysiological mechanisms of impaired cognition in schizophrenia (SCZ). Comorbid depressive symptoms are common in SCZ patients and are also found to be associated with their cognitive impairment. However, it is unclear whether SG-P50 is abnormal in first episode antipsychotics naïve (FEAN) SCZ patients with depressive symptoms. Our aimed to investigate the relationships between SG-P50, depressive symptoms and neurocognition in FEAN-SCZ patients.

METHODS

We recruited 103 FEAN-SCZ patients (depression: n = 63; non-depression: n = 40) and 55 healthy controls. SG-P50 was measured using the standard auditory dual-click (S1&S2) paradigm. Clinical symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS) and the Hamilton Depression Rating Scale-17 (HDRS-17). Cognitive performance was evaluated using the MATRICS Consensus Cognitive Battery (MCCB).

RESULTS

Compared with non-depressive patients, depressive patients had a significantly larger S2 amplitude (p = 0.005) and a higher S2/S1 ratio at trend level (p = 0.075) after corrected. There were significant differences in the scores of CPT-IP and Mazes (NAB) between depressive and non-depressive FEAN-SCZ patients (both p values < 0.05). For all patients, the SG-P50 S2/S1 ratio was significantly correlated with HDRS-17 score (r = 0.23, p = 0.020) and MCCB-Symbol coding (r = -0.16, p = 0.043). For depressive FEAN-SCZ patients, S2 amplitude was an independent predictor of the MCCB-Mazes (NAB) (β = -0.31, t = -2.52, p = 0.015).

CONCLUSIONS

SG-P50 deficit may be an informational biomarker for depressive symptoms and neurocognitive impairments in FEAN-SCZ patients.

Altered language network lateralization in euthymic bipolar patients: a pilot study

Bipolar patients (BD) in the euthymic phase show almost no symptoms, nevertheless possibility of relapse is still present. We expected to find a psychobiological trace of their vulnerability by analyzing a specific network-the Language Network (LN)-connecting many high-level processes and brain regions measured at rest. According to Crow's hypothesis on the key role of language in the origin of psychoses, we expected an altered asymmetry of the LN in euthymic BDs. Eighteen euthymic BD patients (10 females; age = 54.50 ± 11.38 years) and 16 healthy controls (HC) (8 females; age = 51.16 ± 11.44 years) underwent a functional magnetic resonance imaging scan at rest. The LN was extracted through independent component analysis. Then, LN time series was used to compute the fractional amplitude of the low-frequency fluctuation (fALFF) index, which was then correlated with clinical scales. Compared with HC, euthymic patients showed an altered LN with greater activation of Broca's area right homologous and anterior insula together with reduced activation of left middle temporal gyrus. The normalized fALFF analysis on BD patients' LN time series revealed that the Slow-5 fALFF band was positively correlated with residual mania symptoms but negatively associated with depression scores. In line with Crow's hypothesis postulating an altered language hemispheric asymmetry in psychoses, we revealed, in euthymic BD patients, a right shift involving both the temporal and frontal linguistic hubs. The fALFF applied to LN allowed us to highlight a number of significant correlations of this measure with residual mania and depression psychiatric symptoms.

Neurometabolic patterns of an "at risk for mental disorders" syndrome involve abnormalities in the thalamus and anterior midcingulate cortex

BACKGROUND

The ultra-high risk (UHR) paradigm allows the investigation of individuals at increased risk of developing psychotic or other mental disorders with the aim of making prevention and early intervention as specific as possible in terms of the individual outcome.

METHODS

Single-session ¹H-/³¹P-Chemical Shift Imaging of thalamus, prefrontal (DLPFC) and anterior midcingulate (aMCC) cortices was applied to 69 UHR patients for psychosis and 61 matched healthy controls. N-acetylaspartate (NAA), glutamate/glutamine complex (Glx), energy (PCr, ATP) and phospholipid metabolites were assessed, analysed by ANOVA (or ANCOVA [with covariates]) and correlated with symptomatology (SCL-90R).

RESULTS

The thalamus showed decreased NAA, inversely correlated with self-rated aggressiveness, as well as increased PCr, and altered phospholipid breakdown. While the aMCC showed a pattern of NAA decrease and PCr increase, the DLPFC showed PCr increase only in the close-to-psychosis patient subgroup. There were no specific findings in transition patients.

CONCLUSION

The results do not support the notion of a specific pre-psychotic neurometabolic pattern, but likely reflect correlates of an "at risk for mental disorders syndrome". This includes disturbed neuronal (mitochondrial) metabolism in the thalamus and aMCC, with emphasis on left-sided structures, and altered PL remodeling across structures.

The severity of inflammation in major neuropsychiatric disorders: comparison of neutrophil-lymphocyte and platelet-lymphocyte ratios between schizophrenia, bipolar mania, bipolar depression, major depressive disorder, and obsessive compulsive disorder

BACKGROUND

As non-specific markers of immune dysregulation, neutrophil-lymphocyte and platelet-lymphocyte ratios (NLR and PLR) have been consistently shown to be increased in major neuropsychiatric disorders. Although this increase seems to be trans-diagnostic, the extent to which its magnitude differs between disorders remains largely unclear.

AIM

The aim of this study was to directly compare the severity of inflammation (as reflected by NLR and PLR) between schizophrenia (Sch), bipolar mania (BD-M), bipolar depression (BD-D), major depressive disorder (MDD) and obsessive compulsive disorder (OCD).

METHODS

NLR and PLR were obtained for a total of 417 subjects (91 Sch, 70 BD-D, 37 BD-M, 93 MDD, 37 OCD, and 95 controls) and analyzed for group differences.

RESULTS

Sch, BD-M, BD-D and MDD presented with significantly higher NLR compared with both OCD and HC. NLR in BD-M was significantly higher than all the remaining groups, whereas Sch, BD-D and MDD presented with comparably elevated NLR. Moreover, BD-M, Sch and MDD had significantly higher PLR compared with HC.

CONCLUSION

These results suggest that the underlying inflammation may be most severe in BD-M, followed by Sch, BD-D and MDD. On the other hand, inflammation may be of negligible intensity in OCD, or at least undetectable by means of NLR or PLR.

Individualized diagnosis of major depressive disorder via multivariate pattern analysis of thalamic sMRI features

BACKGROUND

Magnetic resonance imaging (MRI) studies have found thalamic abnormalities in major depressive disorder (MDD). Although there are significant differences in the structure and function of the thalamus between MDD patients and healthy controls (HCs) at the group level, it is not clear whether the structural and functional features of the thalamus are suitable for use as diagnostic prediction aids at the individual level. Here, we were to test the predictive value of gray matter density (GMD), gray matter volume (GMV), amplitude of low-frequency fluctuations (ALFF), and fractional amplitude of low-frequency fluctuations (fALFF) in the thalamus using multivariate pattern analysis (MVPA).

METHODS

Seventy-four MDD patients and 44 HC subjects were recruited. The Gaussian process classifier (GPC) was trained to separate MDD patients from HCs, Gaussian process regression (GPR) was trained to predict depression scores, and Multiple Kernel Learning (MKL) was applied to explore the contribution of each subregion of the thalamus.

RESULTS

The primary findings were as follows: [1] The balanced accuracy of the GPC trained with thalamic GMD was 96.59% (P < 0.001). The accuracy of the GPC trained with thalamic GMV was 93.18% (P < 0.001). The correlation between Hamilton Depression Scale (HAMD) score targets and predictions in the GPR trained with GMD was 0.90 (P < 0.001, r2 = 0.82), and in the GPR trained with GMV, the correlation between HAMD score targets and predictions was 0.89 (P < 0.001, r2 = 0.79). [2] The models trained with ALFF and fALFF in the thalamus failed to discriminate MDD patients from HC participants. [3] The MKL model showed that the left lateral prefrontal thalamus, the right caudal temporal thalamus, and the right sensory thalamus contribute more to the diagnostic classification.

CONCLUSIONS

The results suggested that GMD and GMV, but not functional indicators of the thalamus, have good potential for the individualized diagnosis of MDD. Furthermore, the thalamus shows the heterogeneity in the structural features of thalamic subregions for predicting MDD. To our knowledge, this is the first study to focus on the thalamus for the prediction of MDD using machine learning methods at the individual level.

Prenatal origins of neuropsychiatric diseases

AIM

The main objective is to review the available evidence in the literature for developmental origins of neuropsychiatric diseases and their underlying mechanisms. We also probe emerging cutting-edge prenatal MR imaging tools and their future role in advancing our understanding the prenatal footprints of neuropsychiatric disorders.

OBSERVATIONS

Both human and animal studies support early intrauterine origins of neuropsychiatric disease, particularly autism spectrum disorders (ASD), attention and hyperactivity disorders, schizophrenia, depression, anxiety and mood disorders. Specific mechanisms of intrauterine injury include infection, inflammation, hypoxia, hypoperfusion, ischaemia polysubstance use/abuse, maternal mental health and placental dysfunction.

CONCLUSIONS AND RELEVANCE

There is ample evidence to suggest developmental vulnerability of the foetal brain to intrauterine exposures that increases and individual's risk for neuropsychiatric disease, especially the risk of ASD, depression and anxiety. Elucidating the exact timing and mechanisms of injury can be difficult and require novel, non-invasive approaches to the study emerging structural and functional brain development of the foetus. Clinical care should both emphasise maternal health during pregnancy, as well as close, continued monitoring for at risk offspring throughout young adulthood for the early identification and treatment of neuropsychiatric diseases.

Heterogeneity and Classification of Recent Onset Psychosis and Depression: A Multimodal Machine Learning Approach

Diagnostic heterogeneity within and across psychotic and affective disorders challenges accurate treatment selection, particularly in the early stages. Delineation of shared and distinct illness features at the phenotypic and brain levels may inform the development of more precise differential diagnostic tools. We aimed to identify prototypes of depression and psychosis to investigate their heterogeneity, with common, comorbid transdiagnostic symptoms. Analyzing clinical/neurocognitive and grey matter volume (GMV) data from the PRONIA database, we generated prototypic models of recent-onset depression (ROD) vs. recent-onset psychosis (ROP) by training support-vector machines to separate patients with ROD from patients with ROP, who were selected for absent comorbid features (pure groups). Then, models were applied to patients with comorbidity, ie, ROP with depressive symptoms (ROP+D) and ROD participants with sub-threshold psychosis-like features (ROD+P), to measure their positions within the affective-psychotic continuum. All models were independently validated in a replication sample. Comorbid patients were positioned between pure groups, with ROP+D patients being more frequently classified as ROD compared to pure ROP patients (clinical/neurocognitive model: χ2 = 14.874; P < .001; GMV model: χ2 = 4.933; P = .026). ROD+P patient classification did not differ from ROD (clinical/neurocognitive model: χ2 = 1.956; P = 0.162; GMV model: χ2 = 0.005; P = .943). Clinical/neurocognitive and neuroanatomical models demonstrated separability of prototypic depression from psychosis. The shift of comorbid patients toward the depression prototype, observed at the clinical and biological levels, suggests that psychosis with affective comorbidity aligns more strongly to depressive rather than psychotic disease processes. Future studies should assess how these quantitative measures of comorbidity predict outcomes and individual responses to stratified therapeutic interventions.

Brain imaging features in schizophrenia with co-occurring auditory verbal hallucinations and depressive symptoms-Implication for novel therapeutic strategies to alleviate the reciprocal deterioration

BACKGROUND

Auditory verbal hallucinations (AVHs) and depressive symptoms are highly prevalent in schizophrenia, and recent progress has been made in understanding the reciprocal deterioration of both symptoms through structural and functional brain imaging studies. To date, there is limited literature on this topic. In this review, we synthesized the recent literature on the neuroimaging features of schizophrenia patients with concurrent AVHs and depressive symptoms.

METHODS

A literature search was conducted with the major databases using the keywords, mainly including schizophrenia, AVHs, depression, neuropsychiatric disorders, brain imaging, and magnetic resonance imaging.

RESULTS

The existing studies have shown that AVHs and depressive symptoms reciprocally deteriorate in patients with schizophrenia, which has challenged the conventional treatment of the disease. Interestingly, repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (tDCS) therapies have emerged as two efficacious brain stimulation treatments that can normalize the brain regions associated with the symptoms, as shown through functional and structural brain imaging studies. In light of these important findings, there is an urgent need to conduct in-depth neuronal mechanistic studies to identify targets for stimulation therapy.

CONCLUSIONS

These new findings may elucidate the pathological mechanisms underlying schizophrenia with concurrent AVHs and depressive symptoms. Furthermore, this review has important clinical implications for developing novel therapeutic strategies to alleviate the reciprocal deterioration AVHs and depressive symptoms of schizophrenia patients.

Psychiatric neuroimaging research in Brazil: historical overview, current challenges, and future opportunities

The last four decades have witnessed tremendous growth in research studies applying neuroimaging methods to evaluate pathophysiological and treatment aspects of psychiatric disorders around the world. This article provides a brief history of psychiatric neuroimaging research in Brazil, including quantitative information about the growth of this field in the country over the past 20 years. Also described are the various methodologies used, the wealth of scientific questions investigated, and the strength of international collaborations established. Finally, examples of the many methodological advances that have emerged in the field of in vivo neuroimaging are provided, with discussion of the challenges faced by psychiatric research groups in Brazil, a country of limited resources, to continue incorporating such innovations to generate novel scientific data of local and global relevance.

Structural brain networks in remitted psychotic depression

Major depressive disorder with psychotic features (psychotic depression) is a severe disorder. Compared with other psychotic disorders such as schizophrenia, relatively few studies on the neurobiology of psychotic depression have been pursued. Neuroimaging studies investigating psychotic depression have provided evidence for distributed structural brain abnormalities implicating the insular cortex and limbic system. We examined structural brain networks in participants (N = 245) using magnetic resonance imaging. This sample included healthy controls (n = 159) and the largest cross-sectional sample of patients with remitted psychotic depression (n = 86) collected to date. All patients participated in the Study of Pharmacotherapy of Psychotic Depression II randomized controlled trial. We used a novel, whole-brain, data-driven parcellation technique-non-negative matrix factorization-and applied it to cortical thickness data to derive structural covariance networks. We compared patients with remitted psychotic depression to healthy controls and found that patients had significantly thinner cortex in five structural covariance networks (insular-limbic, occipito-temporal, temporal, parahippocampal-limbic, and inferior fronto-temporal), confirming our hypothesis that affected brain networks would incorporate cortico-limbic regions. We also found that cross-sectional depression and severity scores at the time of scanning were associated with the insular-limbic network. Furthermore, the insular-limbic network predicted future severity scores that were collected at the time of recurrence of psychotic depression or sustained remission. Overall, decreased cortical thickness was found in five structural brain networks in patients with remitted psychotic depression and brain-behavior relationships were observed, particularly between the insular-limbic network and illness severity.

Interaction of the Psychiatric Risk Gene Cacna1c With Post-weaning Social Isolation or Environmental Enrichment Does Not Affect Brain Mitochondrial Bioenergetics in Rats

The pathophysiology of neuropsychiatric disorders involves complex interactions between genetic and environmental risk factors. Confirmed by several genome-wide association studies, Cacna1c represents one of the most robustly replicated psychiatric risk genes. Besides genetic predispositions, environmental stress such as childhood maltreatment also contributes to enhanced disease vulnerability. Both, Cacna1c gene variants and stressful life events are associated with morphological alterations in the prefrontal cortex and the hippocampus. Emerging evidence suggests impaired mitochondrial bioenergetics as a possible underlying mechanism of these regional brain abnormalities. In the present study, we simulated the interaction of psychiatric disease-relevant genetic and environmental factors in rodents to investigate their potential effect on brain mitochondrial function using a constitutive heterozygous Cacna1c rat model in combination with a four-week exposure to either post-weaning social isolation, standard housing, or social and physical environmental enrichment. Mitochondria were isolated from the prefrontal cortex and the hippocampus to evaluate their bioenergetics, membrane potential, reactive oxygen species production, and respiratory chain complex protein levels. None of these parameters were considerably affected in this particular gene-environment setting. These negative results were very robust in all tested conditions demonstrating that Cacna1c depletion did not significantly translate into altered bioenergetic characteristics. Thus, further investigations are required to determine the disease-related effects on brain mitochondria.

Distinct structural brain circuits indicate mood and apathy profiles in bipolar disorder

Bipolar disorder (BD) is a severe manic-depressive illness. Patients with BD have been shown to have gray matter (GM) deficits in prefrontal, frontal, parietal, and temporal regions; however, the relationship between structural effects and clinical profiles has proved elusive when considered on a region by region or voxel by voxel basis. In this study, we applied parallel independent component analysis (pICA) to structural neuroimaging measures and the positive and negative syndrome scale (PANSS) in 110 patients (mean age 34.9 ± 11.65) with bipolar disorder, to examine networks of brain regions that relate to symptom profiles. The pICA revealed two distinct symptom profiles and associated GM concentration alteration circuits. The first PANSS pICA profile mainly involved anxiety, depression and guilty feelings, reflecting mood symptoms. Reduced GM concentration in right temporal regions predicted worse mood symptoms in this profile. The second PANSS pICA profile generally covered blunted affect, emotional withdrawal, passive/apathetic social withdrawal, depression and active social avoidance, exhibiting a withdrawal or apathy dominating component. Lower GM concentration in bilateral parietal and frontal regions showed worse symptom severity in this profile. In summary, a pICA decomposition suggested BD patients showed distinct mood and apathy profiles differing from the original PANSS subscales, relating to distinct brain structural networks.

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Structural relationships with symptoms in bipolar disorder are complex.

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A parallel ICA analysis of PANSS questions and structural images finds two correlated profiles.

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The first pair links mood symptoms with right temporal regions.

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The second pair highlights social withdrawal and apathy symptoms linked to bilateral frontal and parietal regions.

Characterizing Rapid Fluctuations of Resting State Functional Connectivity in Demyelinating, Neurodegenerative, and Psychiatric Conditions: From Static to Time-Varying Analysis

Functional magnetic resonance imaging (fMRI) at resting state (RS) has been widely used to characterize the main brain networks. Functional connectivity (FC) has been mostly assessed assuming that FC is static across the whole fMRI examination. However, FC is highly variable at a very fast time-scale, as demonstrated by neurophysiological techniques. Time-varying functional connectivity (TVC) is a novel approach that allows capturing reoccurring patterns of interaction among functional brain networks. Aim of this review is to provide a description of the methods currently used to assess TVC on RS fMRI data, and to summarize the main results of studies applying TVC in healthy controls and patients with multiple sclerosis (MS). An overview of the main results obtained in neurodegenerative and psychiatric conditions is also provided. The most popular TVC approach is based on the so-called “sliding windows,” in which the RS fMRI acquisition is divided in small temporal segments (windows). A window of fixed length is shifted over RS fMRI time courses, and data within each window are used to calculate FC and its variability over time. Sliding windows can be combined with clustering techniques to identify recurring FC states or used to assess global TVC properties of large-scale functional networks or specific brain regions. TVC studies have used heterogeneous methodologies so far. Despite this, similar results have been obtained across investigations. In healthy subjects, the default-mode network (DMN) exhibited the highest degree of connectivity dynamism. In MS patients, abnormal global TVC properties and TVC strengths were found mainly in sensorimotor, DMN and salience networks, and were associated with more severe structural MRI damage and with more severe physical and cognitive disability. Conversely, abnormal TVC measures of the temporal network were correlated with better cognitive performances and less severe fatigue. In patients with neurodegenerative and psychiatric conditions, TVC abnormalities of the DMN, attention and executive networks were associated to more severe clinical manifestations. TVC helps to provide novel insights into fundamental properties of functional networks, and improves the understanding of brain reorganization mechanisms. Future technical advances might help to clarify TVC association with disease prognosis and response to treatment.

Does Depressive-Type Schizophrenia Exist? How Do We Prove It?: An Updated Review and Overview

Depressive symptoms can occur at any point in the duration of schizophrenia. However, we are unable to predict if or when depression will occur in schizophrenic patients. Simultaneously, the standard treatment of depression in schizophrenic patients is the combination of antidepressants and antipsychotics, which has been minimally effective for most patients. Based on several studies, we hypothesized the existence of depressive-type schizophrenia and reviewed the substantial evidence supporting the hypothesis of depressive-type schizophrenia. Simultaneously, we propose technical methods to explore the neuropathology of depressive-type schizophrenia in order to identify the disease during its early stages and to predict how patients will respond to the standard treatment strategies. We believe that the new classification of depressive-type schizophrenia will differentiate it from other forms of depression. In return, this will aid in the discovery of new therapeutic strategies for combatting this disease.

Disrupted Brain Entropy And Functional Connectivity Patterns Of Thalamic Subregions In Major Depressive Disorder

PURPOSE

Entropy analysis of resting-state functional magnetic resonance imaging (R-fMRI) has recently been adopted to characterize brain temporal dynamics in some neuropsychological or psychiatric diseases. Thalamus-related dysfunction might be a potential trait marker of major depressive disorder (MDD), but the abnormal changes in the thalamus based on R-fMRI are still unclear from the perspective of brain temporal dynamics. The aim of this study was to identify local entropy changes and subregional connectivity patterns of the thalamus in MDD patients.

PATIENTS AND METHODS

We measured the sample entropy of the R-fMRI data from 46 MDD patients and 32 matched healthy controls. We employed the Louvain method for the module detection algorithm to automatically identify a functional parcellation of the thalamus and then examined the whole-brain subregional connectivity patterns.

RESULTS

The results indicated that the MDD patients had decreased entropy in the bilateral thalami compared with healthy controls. Increased functional connectivity between the thalamic subregions and the medial part of the superior frontal gyrus (mSFG) was found in MDD patients.

CONCLUSION

This study showed new evidence about sample entropy changes in MDD patients. The functional connectivity alterations that were widely distributed across almost all the thalamic subregions with the mSFG in MDD suggest a general involvement independent of the location and function of the subregions.

Antipsychotic and benzodiazepine use and brain morphology in schizophrenia and affective psychoses - Systematic reviews and birth cohort study

The aim of this paper was to investigate differences in brain structure volumes between schizophrenia and affective psychoses, and whether cumulative lifetime antipsychotic or benzodiazepine doses relate to brain morphology in these groups. We conducted two systematic reviews on the topic and investigated 44 schizophrenia cases and 19 with affective psychoses from the Northern Finland Birth Cohort 1966. The association between lifetime antipsychotic and benzodiazepine dose and brain MRI scans at the age of 43 was investigated using linear regression. Intracranial volume, sex, illness severity, and antipsychotic/benzodiazepine doses were used as covariates. There were no differences between the groups in brain structure volumes. In schizophrenia, after adjusting for benzodiazepine dose and symptoms, a negative association between lifetime antipsychotic dose and the nucleus accumbens volume remained. In affective psychoses, higher lifetime benzodiazepine dose associated with larger volumes of total gray matter and hippocampal volume after controlling for antipsychotic use and symptoms. It seems that in addition to antipsychotics, the severity of symptoms and benzodiazepine dose are also associated with brain structure volumes. These results suggest, that benzodiazepine effects should also be investigated also independently and not only as a confounder.

Aberrant Prefrontal-Thalamic-Cerebellar Circuit in Schizophrenia and Depression: Evidence From a Possible Causal Connectivity

Neuroimaging studies have suggested the presence of abnormalities in the prefrontal-thalamic-cerebellar circuit in schizophrenia (SCH) and depression (DEP). However, the common and distinct structural and causal connectivity abnormalities in this circuit between the two disorders are still unclear. In the current study, structural and resting-state functional magnetic resonance imaging (fMRI) data were acquired from 20 patients with SCH, 20 depressive patients and 20 healthy controls (HC). Voxel-based morphometry analysis was first used to assess gray matter volume (GMV). Granger causality analysis, seeded at regions with altered GMVs, was subsequently conducted. To discover the differences between the groups, ANCOVA and post hoc tests were performed. Then, the relationships between the structural changes, causal connectivity and clinical variables were investigated. Finally, a leave-one-out resampling method was implemented to test the consistency. Statistical analyses showed the GMV and causal connectivity changes in the prefrontal-thalamic-cerebellar circuit. Compared with HC, both SCH and DEP exhibited decreased GMV in middle frontal gyrus (MFG), and a lower GMV in MFG and medial prefrontal cortex (MPFC) in SCH than DEP. Compared with HC, both patient groups showed increased causal flow from the right cerebellum to the MPFC (common causal connectivity abnormalities). And distinct causal connectivity abnormalities (increased causal connectivity from the left thalamus to the MPFC in SCH than HC and DEP, and increased causal connectivity from the right cerebellum to the left thalamus in DEP than HC and SCH). In addition, the structural deficits in the MPFC and its causal connectivity from the cerebellum were associated with the negative symptom severity in SCH. This study found common/distinct structural deficits and aberrant causal connectivity patterns in the prefrontal-thalamic-cerebellar circuit in SCH and DEP, which may provide a potential direction for understanding the convergent and divergent psychiatric pathological mechanisms between SCH and DEP. Furthermore, concomitant structural and causal connectivity deficits in the MPFC may jointly contribute to the negative symptoms of SCH.

Epidemiology of psychotic depression - systematic review and meta-analysis

Large amount of data have been published on non-psychotic depression (NPD), schizophrenia (SZ), and bipolar disorder, while psychotic depression (PD) as an own entity has received much smaller attention. We performed a systematic review and meta-analyses on epidemiology, especially incidence and prevalence, risk factors, and outcomes of PD. A systematic search to identify potentially relevant studies was conducted using four electronic databases and a manual search. The search identified 1764 unique potentially relevant articles, the final study included 99 articles. We found that the lifetime prevalence of PD varies between 0.35% and 1%, with higher rates in older age. Onset age of PD was earlier than that of NPD in younger samples, but later in older samples. There were no differences in gender distribution in PD v. NPD, but higher proportion of females was found in PD than in SZ or in psychotic bipolar disorder (PBD). Risk factors have rarely been studied, the main finding being that family history of psychosis and bipolar disorder increases the risk of PD. Outcomes of PD were mostly worse when compared with NPD, but better compared with SZ and schizoaffective disorder. The outcome compared with PBD was relatively similar, and somewhat varied depending on the measure of the outcome. Based on this review, the amount of research on PD is far from that of NPD, SZ, and bipolar disorder. Based on our findings, PD seems distinguishable from related disorders and needs more scientific attention.

MicroRNA132 associated multimodal neuroimaging patterns in unmedicated major depressive disorder

There is compelling evidence that epigenetic factors contribute to the manifestation of depression, in which microRNA132 (miR-132) is suggested to play a pivotal role in the pathogenesis and neuronal mechanisms underlying the symptoms of depression. Additionally, several depression-associated genes [MECP2, ARHGAP32 (p250GAP), CREB, and period genes] were experimentally validated as miR-132 targets. However, most studies regarding miR-132 in major depressive disorder are based on post-mortem, animal models or genetic comparisons. This work will be the first attempt to investigate how miR-132 dysregulation may impact covariation of multimodal brain imaging data in 81 unmedicated major depressive patients and 123 demographically-matched healthy controls, as well as in a medication-naïve subset of major depressive patients. MiR-132 values in blood (patients > controls) was used as a prior reference to guide fusion of three MRI features: fractional amplitude of low frequency fluctuations, grey matter volume, and fractional anisotropy. The multimodal components correlated with miR-132 also show significant group difference in loadings. Results indicate that (i) higher miR-132 levels in major depressive disorder are associated with both lower fractional amplitude of low frequency fluctuations and lower grey matter volume in fronto-limbic network; and (ii) the identified brain regions linked with increased miR-132 levels were also associated with poorer cognitive performance in attention and executive function. Using a data-driven, supervised-learning method, we determined that miR-132 dysregulation in major depressive disorder is associated with multi-facets of brain function and structure in fronto-limbic network (the key network for emotional regulation and memory), which deepens our understanding of how miR-132 dysregulation in major depressive disorders contribute to the loss of specific brain areas and is linked to relevant cognitive impairments.

Convergence and divergence of neurocognitive patterns in schizophrenia and depression

BACKGROUND

Neurocognitive impairments are frequently observed in schizophrenia and major depressive disorder (MDD). However, it remains unclear whether reported neurocognitive abnormalities could objectively identify an individual as having schizophrenia or MDD.

METHODS

The current study included 220 first-episode patients with schizophrenia, 110 patients with MDD and 240 demographically matched healthy controls (HC). All participants performed the short version of the Wechsler Adult Intelligence Scale-Revised in China; the immediate and delayed logical memory of the Wechsler Memory Scale-Revised in China; and seven tests from the computerized Cambridge Neurocognitive Test Automated Battery to evaluate neurocognitive performance. The three-class AdaBoost tree-based ensemble algorithm was employed to identify neurocognitive endophenotypes that may distinguish between subjects in the categories of schizophrenia, depression and HC. Hierarchical cluster analysis was applied to further explore the neurocognitive patterns in each group.

RESULTS

The AdaBoost algorithm identified individual's diagnostic class with an average accuracy of 77.73% (80.81% for schizophrenia, 53.49% for depression and 86.21% for HC). The average area under ROC curve was 0.92 (0.96 in schizophrenia, 0.86 in depression and 0.92 in HC). Hierarchical cluster analysis revealed for MDD and schizophrenia, convergent altered neurocognition patterns related to shifting, sustained attention, planning, working memory and visual memory. Divergent neurocognition patterns for MDD and schizophrenia related to motor speed, general intelligence, perceptual sensitivity and reversal learning were identified.

CONCLUSIONS

Neurocognitive abnormalities could predict whether the individual has schizophrenia, depression or neither with relatively high accuracy. Additionally, the neurocognitive features showed promise as endophenotypes for discriminating between schizophrenia and depression.

Grey and white matter volumes either in treatment-naïve or hormone-treated transgender women: a voxel-based morphometry study

Many previous magnetic resonance imaging (MRI) studies have documented sex differences in brain morphology, but the patterns of sexual brain differences in transgender women - male sex assigned at birth - with a diagnosis of gender dysphoria (TW) have been rarely investigated to date. We acquired T1-weighted MRI data for the following four (n = 80) groups: treatment-naïve TW (TNTW), TW treated with cross-sex hormones for at least one year (TTW), cisgender men, and cisgender women (cisgender individuals as controls). Differences in whole-brain and regional white matter volume and grey matter volume (GMV) were assessed using voxel-based morphometry. We found lower global brain volumes and regional GMVs in a large portion of the posterior-superior frontal cortex in the cisgender women group than in the TTW and cisgender men groups. Additionally, both transgender groups exhibited lower bilateral insular GMVs than the cisgender women group. Our results highlight differences in the insula in both transgender groups; such differences may be characteristic of TW. Furthermore, these alterations in the insula could be related to the neural network of body perception and reflect the distress that accompanies gender dysphoria.

Disrupted topology of hippocampal connectivity is associated with short-term antidepressant response in major depressive disorder

BACKGROUND

Graph theoretical analyses have identified disrupted functional topological organization across the brain in patients with major depressive disorder (MDD). However, the relationship between brain topology and short-term treatment responses in patients with MDD remains unknown.

METHODS

Sixty-eight patients with MDD and 63 cognitively normal (CN) subjects were recruited at baseline and underwent resting-state functional magnetic resonance imaging scans. Graph theory analysis was used to examine group differences in the whole-brain functional topological properties. The association between altered brain topology and the early antidepressant response was examined.

RESULTS

Patients with MDD showed lower normalized clustering coefficients, lower small-worldness scalars and increased nodal efficiencies in the default mode network and decreased nodal efficiencies in basal ganglia and hippocampal networks. In addition, the decreased nodal efficiency in left hippocampus was negatively correlated with depressive severity at baseline and positively correlated with changes in the depressive scores after two weeks of antidepressant treatment.

LIMITATIONS

The patients in the present study received different medications.

CONCLUSION

These findings indicated that the altered brain functional topological organization in patients with MDD is associated with the treatment response in the early phase of medication. Therefore, brain topology assessments might be considered a useful and convenient predictor of short-term antidepressant responses.

Neurocognitive Graphs of First-Episode Schizophrenia and Major Depression Based on Cognitive Features

Neurocognitive deficits are frequently observed in patients with schizophrenia and major depressive disorder (MDD). The relations between cognitive features may be represented by neurocognitive graphs based on cognitive features, modeled as Gaussian Markov random fields. However, it is unclear whether it is possible to differentiate between phenotypic patterns associated with the differential diagnosis of schizophrenia and depression using this neurocognitive graph approach. In this study, we enrolled 215 first-episode patients with schizophrenia (FES), 125 with MDD, and 237 demographically-matched healthy controls (HCs). The cognitive performance of all participants was evaluated using a battery of neurocognitive tests. The graphical LASSO model was trained with a one-vs-one scenario to learn the conditional independent structure of neurocognitive features of each group. Participants in the holdout dataset were classified into different groups with the highest likelihood. A partial correlation matrix was transformed from the graphical model to further explore the neurocognitive graph for each group. The classification approach identified the diagnostic class for individuals with an average accuracy of 73.41% for FES vs HC, 67.07% for MDD vs HC, and 59.48% for FES vs MDD. Both of the neurocognitive graphs for FES and MDD had more connections and higher node centrality than those for HC. The neurocognitive graph for FES was less sparse and had more connections than that for MDD. Thus, neurocognitive graphs based on cognitive features are promising for describing endophenotypes that may discriminate schizophrenia from depression.

Differential failure to deactivate the default mode network in unipolar and bipolar 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.

Depression and Schizophrenia: Cause, Consequence, or Trans-diagnostic Issue?

The presence of depression in schizophrenia has been a challenge to the Kraepelinian dichotomy, with various attempts to save the fundamental distinction including evoking and refining diagnoses such as schizoaffective disorder. But the tectonic plates are shifting. Here we put forward a summary of recent evidence regarding the prevalence, importance, possible aetiological pathways and treatment challenges that recognizing depression in schizophrenia bring. Taken together we propose that depression is more than comorbidity and that increased effective therapeutic attention to mood symptoms will be needed to improve outcomes and to support prevention.

Self-reported psychosis-like experiences in patients with mood disorders

BACKGROUND

Self-reported psychosis-like experiences (PEs) may be common in patients with mood disorders, but their clinical correlates are not well known. We investigated their prevalence and relationships with self-reported symptoms of depression, mania, anxiety, borderline (BPD) and schizotypal (SPD) personality disorders among psychiatric patients with mood disorders.

METHODS

The Community Assessment of Psychic Experiences (CAPE-42), Mood Disorder Questionnaire (MDQ), McLean Screening Instrument (MSI), The Beck Depressive Inventory (BDI), Overall Anxiety Severity and Impairment Scale (OASIS) and Schizotypal Personality Questionnaire-Brief form (SPQ-B) were filled in by patients with mood disorders (n=282) from specialized care. Correlation coefficients between total scores and individual items of CAPE-42 and BDI, SPQ-B, MSI and MDQ were estimated. Hierarchical multivariate regression analysis was conducted to examine factors influencing the frequency of self-reported PE.

RESULTS

PEs are common in patients with mood disorders. The "frequency of positive symptoms" score of CAPE-42 correlated strongly with total score of SPQ-B (rho=0.63; P<0.001) and moderately with total scores of BDI, MDQ, OASIS and MSI (rho varied from 0.37 to 0.56; P<0.001). Individual items of CAPE-42 correlated moderately with specific items of BDI, MDQ, SPQ-B and MSI (r_φ varied from 0.2 to 0.5; P<0.001). Symptoms of anxiety, mania or hypomania and BPD were significant predictors of the "frequency of positive symptoms" score of CAPE-42.

CONCLUSIONS

Several, state- and trait-related factors may underlie self-reported PEs among mood disorder patients. These include cognitive-perceptual distortions of SPD; distrustfulness, identity disturbance, dissociative and affective symptoms of BPD; and cognitive biases related to depressive or manic symptoms.

L-type Ca2+ channels in mood, cognition and addiction: integrating human and rodent studies with a focus on behavioural endophenotypes

Brain Cav 1.2 and Cav 1.3 L-type Ca2+ channels play key physiological roles in various neuronal processes that contribute to brain function. Genetic studies have recently identified CACNA1C as a candidate risk gene for bipolar disorder (BD), schizophrenia (SCZ), major depressive disorder (MDD) and autism spectrum disorder (ASD), and CACNA1D for BD and ASD, suggesting a contribution of Cav 1.2 and Cav 1.3 Ca2+ signalling to the pathophysiology of neuropsychiatric disorders. Once considered sole clinical entities, it is now clear that BD, SCZ, MDD and ASD share common phenotypic features, most likely due to overlapping neurocircuitry and common molecular mechanisms. A major future challenge lies in translating the human genetic findings to pathological mechanisms that are translatable back to the patient. One approach for tackling such a daunting scientific endeavour for complex behaviour-based neuropsychiatric disorders is to examine intermediate biological phenotypes in the context of endophenotypes within distinct behavioural domains. This will better allow us to integrate findings from genes to behaviour across species, and improve the chances of translating preclinical findings to clinical practice.

Towards diagnostic markers for the psychoses

Psychotic disorders are currently grouped under broad phenomenological diagnostic rubrics. Researchers hope that progress in identifying aetiological mechanisms will ultimately enable more precise division of heterogeneous diagnoses into specific and valid subgroups. This goal has been an aim of psychiatry since the 19th century, when patients with general paresis were thought to have "insanity" similar to dementia praecox and manic depressive illness. Nowadays, the constructs of organic-induced and substance-induced psychotic disorder show that our diagnostic classification system already reflects, in part, aetiological factors. Most recently, gene copy number variation and autoimmunity have been associated with schizophrenia. We suggest how, on the basis of recent scientific advances, we can progress the identification of further putative subgroups and make the most of currently available interventions. Prompt diagnosis and treatment, and a more routine search for causes, could preserve function and improve outcome, and therefore be more acceptable to patients and carers.

Bilaterally reduced claustral volumes in schizophrenia and major depressive disorder: a morphometric postmortem study

Multiple brain structural abnormalities have been reported in schizophrenia and major depressive disorder. A majority of disease-affected brain regions act as relay nodes within neural networks, which are known to be impaired in neuropsychiatric diseases. One of these regions is the claustrum, which has the highest connectivity in the human brain by regional volume. Its possible involvement in disturbed connectivity is yet incompletely explored, however. The present study aimed at searching for possible structural deviations of the claustrum in neuropsychiatric disorders. We found bilaterally reduced claustral volumes both in schizophrenia and in major depressive disorder. These structural impairments may have different, disease-related consequences: In patients with schizophrenia, they may contribute to sensory processing impairments, and in patients with major depressive disorder to disturbances in salience.

Neural correlates of hallucinations in bipolar disorder

Objective:

Approximately one-half of all patients affected by bipolar disorder present with psychotic features on at least one occasion. Several studies have found that alterations in the activity of mesolimbic and prefrontal regions are related to aberrant salience in psychotic patients. The aim of the present study was to investigate the structural correlates of a history of hallucinations in a sample of euthymic patients with bipolar I disorder (BD-I).

Methods:

The sample consisted of 21 euthymic patients with BD-I and no comorbid axis I DSM-IV-TR disorders. Voxel based morphometry (VBM) was used to compare patients with and without a lifetime history of hallucinations. Preprocessing was performed using the Diffeomorphic Anatomical Registration through Exponentiated Lie Algebra (DARTEL) algorithm for VBM in SPM8. Images were processed using optimized VBM.

Results:

The main finding of the present study was a reduction in gray matter volume in the right posterior insular cortex of patients with BD-I and a lifetime history of hallucinations, as compared to subjects with the same diagnosis but no history of hallucinations.

Conclusions:

This finding supports the presence of abnormalities in the salience network in BD patients with a lifetime history of hallucinations. These alterations may be associated with an aberrant assignment of salience to the elements of one’s own experience, which could result in psychotic symptoms.

Unexplained Painful Physical Symptoms in Patients with Major Depressive Disorder: Prevalence, Pathophysiology and Management

Patients with major depression often report pain. In this article, we review the current literature regarding the prevalence and consequences, as well as the pathophysiology, of unexplained painful physical symptoms (UPPS) in patients with major depressive disorder (MDD). UPPS are experienced by approximately two-thirds of depressed patients. The presence of UPPS makes a correct diagnosis of depression more difficult. Moreover, UPPS are a predictor of a poor response to treatment and a more chronic course of depression. Pain, in the course of depression, also has a negative impact on functioning and quality of life. Frequent comorbidity of depression and UPPS has inspired the formulation of an hypothesis regarding a shared neurobiological mechanism of both conditions. Evidence from neuroimaging studies has shown that frontal-limbic dysfunction in depression may explain abnormal pain processing, leading to the presence of UPPS. Increased levels of proinflamatory cytokines and substance P in patients with MDD may also clarify the pathophysiology of UPPS. Finally, dysfunction of the descending serotonergic and noradrenergic pathways that normally suppress ascending sensations has been proposed as a core mechanism of UPPS. Psychological factors such as catastrophizing also play a role in both depression and chronic pain. Therefore, pharmacological treatment and/or cognitive therapy are recommended in the treatment of depression with UPPS. Some data suggest that serotonin and noradrenaline reuptake inhibitors (SNRIs) are more effective than selective serotonin reuptake inhibitors (SSRIs) in the alleviation of depression and UPPS. However, the pooled analysis of eight randomised clinical trials showed similar efficacy of duloxetine (an SNRI) and paroxetine (an SSRI) in reducing UPPS in depression. Further integrative studies examining genetic factors (e.g. polymorphisms of genes for interleukins, serotonin transporter and receptors), molecular factors (e.g. cytokines, substance P) and neuroimaging findings (e.g. functional studies during painful stimulation) might provide further explanation of the pathophysiology of UPPS in MDD and therefore facilitate the development of more effective methods of treatment.

Alterations in effective connectivity anchored on the insula in major depressive disorder

Recent work has identified disruption of several brain networks involving limbic and cortical regions that contribute to the generation of diverse symptoms of major depressive disorder (MDD). Of particular interest are the networks anchored on the right anterior insula, which binds the cortical and limbic regions to enable key functions that integrate bottom-up and top-down information in emotional and cognitive processing. Emotional appraisal has been linked to a presumed hierarchy of processing, from sensory percepts to affective states. But it is unclear whether the network level dysfunction seen in depression relates to a breakdown of this presumed hierarchical processing system from sensory to higher cognitive regions, mediated by core limbic regions (e.g. insula). In 16 patients with current MDD, and 16 healthy controls, we investigated differences in directional influences between anterior insula and the rest of the brain using resting-state functional magnetic resonance imaging (fMRI) and Granger-causal analysis (GCA), using anterior insula as a seed region. Results showed a failure of reciprocal influence between insula and higher frontal regions (dorsomedial prefrontal cortex) in addition to a weakening of influences from sensory regions (pulvinar and visual cortex) to the insula. This suggests dysfunction of both sensory and putative self-processing regulatory loops centered around the insula in MDD. For the first time, we demonstrate a network-level processing defect extending from sensory to frontal regions through insula in depression. Within limitations of inferences drawn from GCA of resting fMRI, we offer a novel framework to advance targeted network modulation approaches to treat depression.

Basal ganglia and thalamic morphology in schizophrenia and bipolar disorder

In this study, we examined the morphology of the basal ganglia and thalamus in bipolar disorder (BP), schizophrenia-spectrum disorders (SCZ-S), and healthy controls (HC) with particular interest in differences related to the absence or presence of psychosis. Volumetric and shape analyses of the basal ganglia and thalamus were performed in 33 BP individuals [12 without history of psychotic features (NPBP) and 21 with history of psychotic features (PBP)], 32 SCZ-S individuals [28 with SCZ and 4 with schizoaffective disorder], and 27 HC using FreeSurfer-initiated large deformation diffeomorphic metric mapping. Significant volume differences were found in the caudate and globus pallidus, with volumes smallest in the NPBP group. Shape abnormalities showing inward deformation of superior regions of the caudate were observed in BP (and especially in NPBP) compared with HC. Shape differences were also found in the globus pallidus and putamen when comparing BP and SCZ-S groups. No significant differences were seen in the nucleus accumbens and thalamus. In summary, structural abnormalities in the caudate and globus pallidus are present in BP and SCZ-S. Differences were more apparent in the NPBP subgroup. The findings herein highlight the potential importance of separately examining BP subgroups in neuroimaging studies.

Understanding tDCS effects in schizophrenia: a systematic review of clinical data and an integrated computation modeling analysis

Although recent clinical studies using transcranial direct current stimulation (tDCS) for schizophrenia showed encouraging results, several tDCS montages were employed and their current flow pattern has not been investigated. We performed a systematic review to identify clinical tDCS studies in schizophrenia. We then applied computer head modeling analysis for prediction of current flow. Out of 41 references, we identified 12 relevant studies. The most employed montage was anode and cathode over the left dorsolateral prefrontal and temporoparietal cortex, respectively. Computational model analysis predicted activation and under-activation under the anode and the cathode, respectively, occurring in areas respectively associated with negative and positive symptoms. We also identified tDCS-induced electrical currents in cortical areas between the electrodes (frontoparietal network) and, to a lesser extent, in deeper structures involved in schizophrenia pathophysiology. Mechanisms of tDCS effects in schizophrenia and the usefulness of computer modeling techniques for planning tDCS trials in schizophrenia are discussed.

Operationalizing Cognitive Science and Technologies' Research and Development; the "Brain and Cognition Study Group (BCSG)" Initiative from Shiraz, Iran

Recent advances in brain and cognitive science studies have revolutionized concepts in neural dynamics, regulating mechanisms, coding systems and information processing networks which govern our function and behavior. Hidden aspects of neurological and psychiatric diseases are being understood and hopes for their treatment are emerging. Although the two comprehensive mega-projects on brain mapping are in place in the United States and Europe; the proportion of science contributed by the developing countries should not be downsized. With the granted supports from the Cognitive Sciences and Technologies Council (CSTC), Iran can take its role in research on brain and cognition further. The idea of research and development in Cognitive Sciences and Technologies (CST) is being disseminated across the country by CSTC. Towards this goal, the first Shiraz interdisciplinary meeting on CST was held on 9 January 2014 in Namazi hospital, Shiraz. CST research priorities, infrastructure development, education and promotion were among the main topics discussed during this interactive meeting. The steering committee of the first CST meeting in Shiraz decided to frame future research works within the "Brain and Cognition Study Group-Shiraz" (BCSG-Shiraz). The study group comprises scientific leaders from various allied disciplines including neuroscience, neurosurgery, neurology, psychiatry, psychology, radiology, physiology, bioengineering, biophysics, applied physics and telecommunication. As the headquarter for CST in the southern Iran, BCSG-Shiraz is determined to advocate "brain and cognition" awareness, education and research in close collaboration with CSTC. Together with CSTC, Shiraz Neuroscience Research center (SNRC) will take the initiative to cross boundaries in interdisciplinary works and multi-centric research projects within the study group.

A multi-site resting state fMRI study on the amplitude of low frequency fluctuations in schizophrenia

Background: This multi-site study compares resting state fMRI amplitude of low frequency fluctuations (ALFF) and fractional ALFF (fALFF) between patients with schizophrenia (SZ) and healthy controls (HC).

Methods: Eyes-closed resting fMRI scans (5:38 min; n = 306, 146 SZ) were collected from 6 Siemens 3T scanners and one GE 3T scanner. Imaging data were pre-processed using an SPM pipeline. Power in the low frequency band (0.01–0.08 Hz) was calculated both for the original pre-processed data as well as for the pre-processed data after regressing out the six rigid-body motion parameters, mean white matter (WM) and cerebral spinal fluid (CSF) signals. Both original and regressed ALFF and fALFF measures were modeled with site, diagnosis, age, and diagnosis × age interactions.

Results: Regressing out motion and non-gray matter signals significantly decreased fALFF throughout the brain as well as ALFF in the cortical edge, but significantly increased ALFF in subcortical regions. Regression had little effect on site, age, and diagnosis effects on ALFF, other than to reduce diagnosis effects in subcortical regions. There were significant effects of site across the brain in all the analyses, largely due to vendor differences. HC showed greater ALFF in the occipital, posterior parietal, and superior temporal lobe, while SZ showed smaller clusters of greater ALFF in the frontal and temporal/insular regions as well as in the caudate, putamen, and hippocampus. HC showed greater fALFF compared with SZ in all regions, though subcortical differences were only significant for original fALFF.

Conclusions: SZ show greater eyes-closed resting state low frequency power in frontal cortex, and less power in posterior lobes than do HC; fALFF, however, is lower in SZ than HC throughout the cortex. These effects are robust to multi-site variability. Regressing out physiological noise signals significantly affects both total and fALFF measures, but does not affect the pattern of case/control differences.

Epidemiological and clinical characterization following a first psychotic episode in major depressive disorder: comparisons with schizophrenia and bipolar I disorder in the Cavan-Monaghan First Episode Psychosis Study (CAMFEPS)

While recent research on psychotic illness has focussed on the nosological, clinical, and biological relationships between schizophrenia and bipolar disorder, little attention has been directed to the most common other psychotic diagnosis, major depressive disorder with psychotic features (MDDP). As this diagnostic category captures the confluence between dimensions of psychotic and affective psychopathology, it is of unappreciated heuristic potential to inform on the nature of psychotic illness. Therefore, the epidemiology and clinical characteristics of MDDP were compared with those of schizophrenia and bipolar disorder within the Cavan-Monaghan First Episode Psychosis Study (n = 370). Epidemiologically, the first psychotic episode of MDDP (n = 77) was uniformly distributed across the adult life span, while schizophrenia (n = 73) and bipolar disorder (n = 73) were primarily disorders of young adulthood; the incidence of MDDP, like bipolar disorder, did not differ between the sexes, while the incidence of schizophrenia was more common in males than in females. Clinically, MDDP was characterized by negative symptoms, executive dysfunction, neurological soft signs (NSS), premorbid intellectual function, premorbid adjustment, and quality of life similar to those for schizophrenia, while bipolar disorder was characterized by less prominent negative symptoms, executive dysfunction and NSS, and better quality of life. These findings suggest that what we currently categorize as MDDP may be more closely aligned with other psychotic diagnoses than has been considered previously. They indicate that differences in how psychosis is manifested vis-à-vis depression and mania may be quantitative rather than qualitative and occur within a dimensional space, rather than validating categorical distinctions.