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Background In bipolar disorder (BD) the risk of suicide in adult life can be influenced by the interaction of adverse childhood experiences with the serotonin transporter polymorphism (5-HTTLPR). The cortico-limbic connectivity is a candidate endophenotype for the disorder, also related to suicidality and affected by the 5-HT system. Methods In 64 (*s carriers = 41; l/l = 23) depressed BD patients, we explored the effect of 5-HTTLPR on corticolimbic functional connectivity (FC) during emotional processing, and the role of FC in moderating/mediating the effect of early stressful events on suicidality among 5-HTTLPR groups, by implementing Generalized Structural Equation Model. Results 5-HTTLPR affects FC between amygdala (Amy) and anterior cingulate cortex (ACC), temporal pole, putamen/thalamus, and precuneus. The short allele was associated to a more inefficient corticolimbic connectivity. In 5-HTTLPR*s carriers, but not in l/l, the Amy-ACC functional coupling mediated the relationship between stress load and current suicidality. Limitations Patients were not drug-naive, and the recruitment took place in a single center, thus raising the possibility of population stratifications. The sample size is relatively small, but our findings can provide the background for replication study in independent and larger datasets. Conclusions Our results confirm the link between the 5-HTT promoter polymorphism and susceptibility to stress in BD, and suggest that cortico-limbic functional connectivity mediates these effects. This pattern could identify a vulnerability factor for the exacerbation of mood episodes after stressful life events particularly relevant in *s carriers.

Major depressive disorder (MDD) is a psychiatric disorder characterized by abnormal resting state functional connectivity (rsFC) in various neural networks and especially in default-mode network (DMN). However, inconsistent findings, i.e., increased and decreased DMN rsFC, have been reported, which raise the question for the source of DMN changes in MDD. Testing whether the DMN abnormalities in MDD can be traced to either a local, i.e., intra-network, or a global, i.e., inter-network, source, we conducted a novel sequence of rsFC analyses, i.e., global FC, intra-network FC, and inter-network FC. Moreover, all analyses were conducted without global signal regression (non-GSR) and with GSR in order to identify the impact of specifically the global component of functional connectivity on within-network functional connectivity within specifically the DMN. In MDD our findings demonstrate (i) increased representation of global signal correlation (GSCORR) in DMN regions, as confirmed independently by degree of centrality (DC) and by an independent DMN template, (ii) increased within-network DMN rsFC, (iii) highly increased inter-network rsFC of both lower- and higher order non-DMN networks with DMN, (iv) high accuracy in classifying MDD vs. healthy subjects by using GSCORR as predictor. Further supporting the global, i.e., non-DMN source of within-network rsFC of the DMN, all results were obtained only when including the global signal, i.e., non-GSR, but not when conducting GSR. Together, we show for the first time increased global signal representation within rsFC of DMN as stemming from inter-network sources as distinguished from local sources, i.e., within- or intra-DMN.

Background: Mental disorders may represent a risk factor for severe COVID-19. This study evaluated the risk of COVID-19 mortality, hospitalization, and intensive care unit (ICU) admission in patients with pre-existing mental disorders or exposure to psychopharmacological treatments. Methods: In this PRISMA-compliant systematic review and meta-analysis (PROSPERO-CRD42021233984), we searched Web of Science, PsycINFO, Cochrane, PubMed, and Ovid/PsycINFO databases through March 5, 2021 for studies reporting data on COVID-19 outcomes in psychiatric patients compared to controls. Risk of COVID-19 mortality was defined as the primary outcome, with hospitalization and ICU admission as secondary outcomes. We modeled random-effects meta-analyses to estimate crude (OR) and adjusted (aOR) odds ratios for these three outcomes. Heterogeneity was assessed using the I2 statistic, publication bias was tested with Egger regression and visual inspection of funnel plots. Newcastle Ottawa Scale was used to explore study quality. We estimated effect sizes associated with any pre-existing mental disorder as well as specific categories of mental disorders (psychotic disorders, mood disorders, substance use disorders, anxiety disorders, intellectual disabilities and developmental disorders), and exposure to psychopharmacological drug classes (antidepressants, antipsychotics, and anxiolytics). Severe mental illness was compared with other mental disorders. We also conducted subgroup analyses and meta-regressions to assess the effects of baseline COVID-19 treatment setting, patient age, country, pandemic phase, quality assessment score and adjustment for confounders. Findings: A total of 32 studies were included in the systematic review and 23 in the meta-analysis, representing 658,702 patients with COVID-19 (41,944 with mental disorders). The presence of any mental disorder was associated with increased risk of COVID-19 mortality (Crude OR 1·99, 95% CI 1·56-2·54; aOR 1·34, 95% CI 1·15-1·56). This association was confirmed in psychotic disorders (Crude OR 2·11, 95% CI 1·47-3·03; aOR 1·77, 95% CI 1·34-2·33), and mood disorders (Crude OR 1·98, 95% CI 1·48-2·64; aOR 1·44, 95% CI 1·14-1·82). An increased mortality risk with substance use disorders (Crude OR 1·76, 95% CI 1·30- 2·38; aOR 1·12, 95% CI 0·89-1·39) and intellectual disabilities and developmental disorders (Crude OR 1·47, 95% CI 1·08-2·01) was only established in unadjusted estimates. We detected no effect for anxiety disorders (Crude OR 1·06, 95% CI 0·75-1·51; aOR 1·01, 95% CI 0·76-1·34). COVID-19 mortality was also associated with exposure to antipsychotics (Crude OR 3·71, 95% CI 1·74-7·91; aOR 2·43, 95% CI 1·81-3·25) and anxiolytics (Crude OR 2·58, 95% CI 1·22-5·44; aOR 1·47, 95% CI 1·15-1·88), but with antidepressant exposure only in unadjusted models (Crude OR 2·23, 95% CI 1·06-4·71; aOR 1·18, 95% CI 0·93-1·50). Overall, mental disorders were consistently associated with increased risk of hospitalization (Crude OR: 2·24, 95% CI 1·70-2·94; aOR: 1·77, 95% CI 1·29-2·42), but not ICU admission (Crude OR 1·71, 95% CI 1-2·93; aOR 1·26, 95% CI 0·78-2·05). Increased rates of hospital and ICU admission were found in substance use disorders (Hospitalization - Crude OR: 2·66, 95% CI 1·79-3·95; aOR: 1·87, 95% CI 1·16-3·03; ICU - Crude OR 2·59, 95% CI 1·54-4·38) and for unadjusted estimates in mood disorders (Hospitalization Crude OR 2·26, 95% CI 1·33-3·86; aOR 1·26, 95% CI 0·64-2·50; ICU - Crude OR 2·39, 95% CI 1·15-5·00; aOR 1·13, 95% CI 0·70-1·84). Psychotic disorders were not associated with an increased risk of hospitalization (Crude OR 1·68, 95% CI 0·86-3·29; aOR: 1·34, 95% CI 0·61-2·94), and even showed a decreased risk of ICU admission in adjusted estimates (Crude OR 0·77, 95% CI 0·42- 1·42; aOR 0·75, 95% CI 0·62-0·91). Adjusted effect sizes were significantly higher for mortality (p=0·005) and lower for ICU admission (p

This paper systematically reviewed national COVID-19 vaccine deployment plans across 20 European countries. Multiple high-quality studies have shown odds ratios for comorbid severe mental illness, and schizophrenia in particular, to equal or even surpass those of other risk comorbidities included for prioritization. Evidence-based policy would then require severe mental illness to be included in the list of risk comorbidities. Yet several sources of bias may have caused the risks associated with severe mental illness to be overlooked by most countries. Mental disorders are often not included as predictors in COVID-19 outcome studies. Studies specifically investigating the risks of psychiatric comorbidity have not yet been summarized in systematic reviews or meta-analyses and were therefore ignored by some national strategies and mathematical models. In summary, European countries' vaccination strategies try to balance ethical and scientific evidence, but for individuals with severe mental illness an evidence policy disconnect remains. Most of these patients are treated in the community, and are currently overlooked by the majority of European COVID-19 vaccination strategies. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

Background Cognitive impairment is a core feature of bipolar disorder, with a prevalence of about 64.4% during episodes and 57.1% in euthymia. Recent evidences suggest that cognitive deficits in BD may follow immune dysfunction and elevated levels of inflammatory cytokines have been reported during periods of depression, mania and euthymia, suggesting the presence of a chronic, low-grade inflammatory state. The aim of the study is to investigate if immune/inflammatory markers and especially chemokines associate to cognitive performances. Methods Seventy-six consecutively admitted inpatients with a depressive episode in course of bipolar disorder performed a neuropsychological evaluation with the Brief Assessment of Cognition in Schizophrenia and plasma blood levels of cytokines, chemokines and growth factors were analyzed with Luminex technology. Results Higher levels of IL-1β, IL-6, CCL2, CCL4, CCL5, CXCL10, and bFGF are associated with the likelihood of having a poor cognitive performance. Limitations Limitation include the lack of a group of healthy controls and the lack of information regarding previous psychopharmacological treatments, alcohol and tobacco use. Conclusions Our results confirm the importance of chemokines in bipolar disorder and suggest that inflammatory markers suggestive of a low-grade inflammatory state could contribute to the neurocognitive deficits observed in depressed patients.

Background Neuropsychological abnormalities have been proposed to contribute to the development and maintenance of Borderline Personality Disorder (BPD). Previous meta-analyses and reviews confirmed deficits in a broad range of cognitive domains, including attention, cognitive flexibility, memory, executive functions, planning, information processing, and visuospatial abilities, often suggested to underlie brain abnormalities. However, no study directly explored the structural neural correlates of these deficits in BPD, also accounting for the possible confounding effect of pharmacological treatments, often used as adjunctive symptom-targeted therapy in clinical setting. Methods In this study we compared the performance of 24 BPD patients to 24 healthy controls obtained at the neuropsychological battery “Brief Assessment and Cognition in Schizophrenia”, exploring the relationship between the cognitive impairments and current symptomatology, brain grey matter volumes and cortical thickness, controlling for medications load. Results Data revealed deficits in verbal memory and fluency, working memory, attention and speed of information processing and psychomotor speed and coordination when medication load was not in the model. Correcting for this variable, only the impairment in psychomotor abilities remained significant. A multiple regression confirmed the effect of this neuropsychological domain on the severity of BPD symptomatology (Borderline Evaluation of Severity Over Time). In BPD, the performance at psychomotor speed and coordination was also directly associated to cortical thickness in postcentral gyrus. Limitations Relatively small sample size, especially for neuroimaging. Conclusions Our study highlighted an influence of BPD neuropsychological impairments on symptomatology, and cortical thickness, prompting the potential clinical utility of a cognitive remediation program in BPD.

The Research Domani Criteria framework (RdoC) encourages research on specific impairments present across traditional nosological categories and suggests a list of biological and behavioral measures for assessing them. After a description of RdoC, in this article we focus on impairments of the ability of understanding others, specifically in Theory of Mind and empathy. We illustrate recent evidence on brain anomalies correlating with these deficits in Schizophrenia, Addiction Disorders and Mood Disorders populations. In the last section, we zoom out and consider this kind of research vis-à-vis the objection of being reductionistic that is, in favoring mechanistic accounts of mental disorders. We argue that metaphysical reductionism and explanatory reductionism are not conceptually entailed by the RdoC framework.

One of the greatest challenges in providing early effective treatment in mood disorders is the early differential diagnosis between major depression (MDD) and bipolar disorder (BD). A remarkable need exists to identify reliable biomarkers for these disorders. We integrate structural neuroimaging techniques (i.e. Tract-based Spatial Statistics, TBSS, and Voxel-based morphometry) in a multiple kernel learning procedure in order to define a predictive function of BD against MDD diagnosis in a sample of 148 patients. We achieved a balanced accuracy of 73.65% with a sensitivity for BD of 74.32% and specificity for MDD of 72.97%. Mass-univariates analyses showed reduced grey matter volume in right hippocampus, amygdala, parahippocampal, fusiform gyrus, insula, rolandic and frontal operculum and cerebellum, in BD compared to MDD. Volumes in these regions and in anterior cingulate cortex were also reduced in BD compared to healthy controls (n = 74). TBSS analyses revealed widespread significant effects of diagnosis on fractional anisotropy, axial, radial, and mean diffusivity in several white matter tracts, suggesting disruption of white matter microstructure in depressed patients compared to healthy controls, with worse pattern for MDD. To best of our knowledge, this is the first study combining grey matter and diffusion tensor imaging in predicting BD and MDD diagnosis. Our results prompt brain quantitative biomarkers and multiple kernel learning as promising tool for personalized treatment in mood disorders.

Background Dialectical Behavior Therapy Skills Training (DBT-ST) as stand-alone treatment has demonstrated promising outcomes for the treatment of alcohol use disorder (AUD) and concurrent substance use disorders (SUDs). However, no studies have so far empirically investigated factors that might predict efficacy of this therapeutic model. Methods 275 treatment-seeking individuals with AUD and other SUDs were consecutively admitted to a 3-month DBT-ST program (in- + outpatient; outpatient settings). The machine learning routine applied (i.e. penalized regression combined with a nested cross-validation procedure) was conducted in order to estimate predictive values of a wide panel of clinical variables in a single statistical framework on drop-out and substance-use behaviors, dealing with related multicollinearity, and eliminating redundant variables. Results The cross-validated elastic net model significantly predicted the drop-out. The bootstrap analysis revealed that subjects who showed substance-use behaviors during the intervention and who were treated with the mixed setting (i.e., in- and outpatient) program, together with higher ASI alcohol scores were associated with an higher probability of drop-out. On the contrary, older subjects, higher levels of education, together with higher scores of DERS awareness subscale were negatively associated to drop-out. Similarly, lifetime co-diagnoses of anxiety, bipolar, and gambling disorders, together with bulimia nervosa negatively predicted the drop-out. The machine learning model did not identify predictive variables of substance-use behaviors during the treatment. Conclusions The DBT-ST program could be considered a valid therapeutic approach especially when AUD and other SUDs co-occur with other psychiatric conditions and, it is carried out as a full outpatient intervention.

The identification of antidepressant response predictors in bipolar disorder (BD) may provide new potential enhancements in treatment selection. Repeated total sleep deprivation combined with light therapy (TSD+LT) can acutely reverse depressive symptoms and has been proposed as a model antidepressant treatment. This study aims at investigating the effect of TSD+LT on effective connectivity and neural response in cortico-limbic circuitries during implicit processing of fearful and angry faces in patients with BD. fMRI and Dynamic Causal Modeling (DCM) were combined to study the effect of chronotherapeutics on neural responses in healthy controls (HC, n = 35) and BD patients either responder (RBD, n = 26) or non responder (nRBD, n = 11) to 3 consecutive TSD+LT sessions. Twenty-four DCMs exploring connectivity between anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC), Amygdala (Amy), fusiform gyrus and visual cortex were constructed. After treatment, patients significantly increased their neural responses in DLPFC, ACC and insula. nRBD showed lower baseline and endpoint neural responses than RBD. The increased activity in ACC and in medial prefrontal cortex, associated with antidepressant treatment, was positively associated with the improvement of depressive symptomatology. Only RBD patients increased intrinsic connectivity from DLPFC to ACC and reduced the modulatory effect of the task on Amy-DLPFC connection. A successful antidepressant treatment was associated with an increased functional activity and connectivity within cortico-limbic networks, suggesting the possible role of these measures in providing possible biomarkers for treatment efficacy.

BackgroundImpaired emotional processing is a core feature of schizophrenia (SZ). Consistent findings suggested that abnormal emotional processing in SZ could be paralleled by a disrupted functional and structural integrity within the fronto-limbic circuitry. The effective connectivity of emotional circuitry in SZ has never been explored in terms of causal relationship between brain regions. We used functional magnetic resonance imaging and Dynamic Causal Modeling (DCM) to characterize effective connectivity during implicit processing of affective stimuli in SZ.MethodsWe performed DCM to model connectivity between amygdala (Amy), dorsolateral prefrontal cortex (DLPFC), ventral prefrontal cortex (VPFC), fusiform gyrus (FG) and visual cortex (VC) in 25 patients with SZ and 29 HC. Bayesian Model Selection and average were performed to determine the optimal structural model and its parameters.ResultsAnalyses revealed that patients with SZ are characterized by a significant reduced top-down endogenous connectivity from DLPFC to Amy, an increased connectivity from Amy to VPFC and a decreased driving input to Amy of affective stimuli compared to HC. Furthermore, DLPFC to Amy connection in patients significantly influenced the severity of psychopathology as rated on Positive and Negative Syndrome Scale.ConclusionsResults suggest a functional disconnection in brain network that contributes to the symptomatic outcome of the disorder. Our findings support the study of effective connectivity within cortico-limbic structures as a marker of severity and treatment efficacy in SZ.

Background: Neuropsychological deficits constitute enduring trait-like features in bipolar disorder (BD), and persist in euthymia. White matter (WM) abnormalities are one of the most consistently reported findings in neuroimaging studies of BD. We hypothesized that neuropsychological performances could correlate with WM integrity in a sample of bipolar patients in core WM tracts. Methods: Seventy-eight patients affected by BD were evaluated for verbal memory, working memory, psychomotor coordination, executive functions, attention and information processing, and verbal fluency through the Brief Assessment of Cognition in Schizophrenia. White matter integrity was evaluated using DTI and tract-based spatial statistics with threshold free cluster enhancement (p>0.949). Results: We observed that cognitive performances in attention and information processing, working memory, executive functions and psychomotor coordination were associated with DTI measures of WM integrity in several association fibres: inferior and superior longitudinal fasciculus, inferior fronto-occipital fasciculus, cingulum bundle, corpus callosum, and corona radiata. Limitation: The drug treatments administered during the course of the illness could have influenced DTI measures and neurocognitive function. Other limitations include issues such as generalizability due to the lack of a control group, possible undetected past comorbidities, population stratification, and the presence of a 28% of patients which previously experienced delusions. Conclusions: This is the first study to use a validated cognitive battery to investigate the principal cognitive domains in BD. Our data confirm the importance of WM integrity as a neurobiological underpinning of cognitive deficits.

Catechol-O-methyltransferase (COMT) inactivates catecholamines, Val/Val genotype was associated to an increased amygdala (Amy) response to negative stimuli and can influence the symptoms severity and the outcome of bipolar disorder, probably mediated by the COMT polymorphism (rs4680) interaction between cortical and subcortical dopaminergic neurotransmission. The aim of this study is to explore how rs4680 and implicit emotional processing of negative emotional stimuli could interact in affecting the Amy connectivity in bipolar depression. Forty-five BD patients (34 Met carriers vs. 11 Val/Val) underwent fMRI scanning during implicit processing of fearful and angry faces. We explore the effect of rs4680 on the strength of functional connectivity from the amygdalae to whole brain. Val/Val and Met carriers significantly differed for the connectivity between Amy and dorsolateral prefrontal cortex (DLPFC) and supramarginal gyrus. Val/Val patients showed a significant positive connectivity for all of these areas, where Met carriers presented a significant negative one for the connection between DLPFC and Amy. Our findings reveal a COMT genotype-dependent difference in corticolimbic connectivity during affective regulation, possibly identifying a neurobiological underpinning of clinical and prognostic outcome of BD. Specifically, a worse antidepressant recovery and clinical outcome previously detected in Val/Val patients could be associated to a specific increased sensitivity to negative emotional stimuli.

RATIONALE:Lithium is the mainstay for the treatment of bipolar disorder (BD) and inhibits glycogen synthase kinase-3β (GSK-3β). The less active GSK-3β promoter gene variants have been associated with less detrimental clinical features of BD. GSK-3β gene variants and lithium can influence brain gray and white matter structure in psychiatric conditions, so we studied their combined effect in BD.OBJECTIVES:The aim of this study is to investigate the effects of ongoing long-term lithium treatment and GSK-3β promoter rs334558 polymorphism on regional gray matter (GM) volumes of patients with BD.MATERIALS AND METHODS:GM volumes were estimated with 3.0 Tesla MRI in 150 patients affected by a major depressive episode in course of BD. Duration of lifetime lithium treatment was retrospectively assessed. Analyses were performed by searching for significant effects of lithium and rs334558 in the whole brain.RESULTS:The less active GSK-3β rs334558*G gene promoter variant and the long-term administration of lithium were synergistically associated with increased GM volumes in the right frontal lobe, in a large cluster encompassing the boundaries of subgenual and orbitofrontal cortex (including Brodmann areas 25, 11, and 47). Effects of lithium on GM revealed in rs334558*G carriers only, consistent with previously reported clinical effects in these genotype groups, and were proportional to the duration of treatment.CONCLUSIONS:Lithium and rs334558 influenced GM volumes in areas critical for the generation and control of affect, which have been widely implicated in the process of BD pathophysiology. In the light of the protective effects of lithium on white matter integrity, our results suggest that the clinical effects of lithium associate with a neurotrophic effect on the whole brain, probably mediated by GSK-3β inhibition.

Background Adverse childhood experiences (ACE) can lead to several negative consequences in adult life, are highly prevalent in psychiatric disorders where they associate with clinical and brain morphological features. Grey matter volume loss is a central characteristic of bipolar disorder (BD) and schizophrenia (SCZ). The aim of this study is to measure the effect of diagnosis and ACE on GM volume in a sample of patients with BD or SCZ compared with healthy controls (HC). Methods We studied 206 depressed BD patients, 96 SCZ patients and 136 healthy subjects. GM volumes were estimated with 3.0 Tesla MRI and analyzed with VBM technique. The effect of diagnosis was investigated in the whole sample and separately exposed to high and low ACE subjects. Results An effect of diagnosis was observed in orbitofrontal cortex encompassing BA 47 and insula, and in the thalamus. HC had the highest volume and SCZ patients the lowest with BD patients showing an intermediate volume. This pattern persisted only in subjects with high ACE. No differences were observed for low ACE subjects. Limitations The three diagnostic groups differ for age and education, previous and current medications, and treatment periods. Conclusions Our results underline the importance of ACE on the neural underpinnings of psychiatric psychopathology and suggest a major role of exposure to ACE for the GM deficits to reveal in clinical populations. Exposure to early stress is a crucial factor that must be taken in to account when searching for biomarkers of BD and SCZ.

Background Changes of white matter (WM) microstructure have been proposed as structural biomarkers of bipolar disorder (BD). The chronotherapeutic combination of repeated total sleep deprivation and morning light therapy (TSD+LT) can acutely reverse depressive symptoms in approximately 60% of patients, and it has been proposed as a model antidepressant treatment to investigate the neurobiological correlates of rapid antidepressant response. Methods We tested if baseline DTI measures can predict response to treatment in 70 in-patients affected by a major depressive episode in the course of BD, treated with chronotherapeutics for one week. We performed whole-brain tract-based spatial statistics with threshold-free cluster enhancement for the DTI measures of WM microstructure integrity: fractional anisotropy, axial, radial, and mean diffusivity. Results Increased mean and radial water diffusivity correlated with poor antidepressant response to TSD+LT in core WM tracts which are crucial for the functional integrity of the brain, including corpus callosum, corona radiata, cingulum bundle, superior longitudinal fasciculus, inferior fronto-occipital fasciculus, and thalamic radiation. Limitations Limitations include issues such as generalizability, possible population stratification, medications and their effects on DTI measures, and no placebo control for chronotherapeutics. We could not consider other factors such as gene–environment interactions. Conclusions The association of increased radial and mean diffusivity with poor response to chronotherapeutic treatment warrants interest for the study of DTI measures of WM microstructure as markers for treatment response in bipolar depression.

Bipolar disorder is a severe, disabling and life-threatening illness, which affects nearly 2% of the general population. The identification of reliable and objective biomarkers may aid early diagnosis and optimize treatment efficacy. Through a careful overview of the neuroimaging studies which investigated the structural, functional, and effective connectivity in bipolar disorder, we explored the role of a disconnected cortico-limbic circuitry in the development and maintenance of the disorder. This review offers perspectives and suggestions for future research, in order to propose the corticolimbic disconnection as a neurobiological underpinning and biomarker for bipolar psychopathology. ©2014 Informa UK, Ltd.

Panic disorder has been associated with dysfunctional neuropsychological dimensions, including anxiety sensitivity. Brain-imaging studies of the neural correlates of emotional processing have identified a network of structures that constitute the neural circuitry for emotions. The anterior cingulate cortex (ACC), medial prefrontal cortex (mPFC) and insula, which are part of this network, are also involved in the processing of threat-related stimuli. The aim of the study was to investigate if neural activity in response to emotional stimuli in the cortico-limbic network is associated to anxiety sensitivity in panic disorder. In a sample of 18 outpatients with panic disorder, we studied neural correlates of implicit emotional processing of facial affect expressions with a face-matching paradigm; correlational analyses were performed between brain activations and anxiety sensitivity. The correlational analyses performed showed a positive correlation between anxiety sensitivity and brain activity during emotional processing in regions encompassing the PFC, ACC and insula. Our data seem to confirm that anxiety sensitivity is an important component of panic disorder. Accordingly, the neural underpinnings of anxiety sensitivity could be an interesting focus for treatment and further research.

Background:Bipolar disorder (BD) is a severe, disabling and life-threatening illness. Disturbances in emotion and affective processing are core features of the disorder with affective instability being paralleled by mood-congruent biases in information processing that influence evaluative processes and social judgment. Several lines of evidence, coming from neuropsychological and imaging studies, suggest that disrupted neural connectivity could play a role in the mechanistic explanation of these cognitive and emotional symptoms. The aim of the present study is to investigate the effective connectivity in a sample of bipolar patients.Methods:Dynamic causal modeling (DCM) technique was used to study 52 inpatients affected by bipolar disorders consecutively admitted to San Raffaele hospital in Milano and forty healthy subjects. A face-matching task was used as activation paradigm.Results:Patients with BD showed a significantly reduced endogenous connectivity in the DLPFC to Amy connection. There was no significant group effect upon the endogenous connection from Amy to ACC, from ACC to Amy and from DLPFC to ACC.Conclusions:Both DLPFC and ACC are part of a network implicated in emotion regulation and share strong reciprocal connections with the amygdale. The pattern of abnormal or reduced connectivity between DLPFC and amygdala may reflect abnormal modulation of mood and emotion typical of bipolar patients.