Modeling brain sex in the limbic system as phenotype for female-prevalent mental disorders.

BACKGROUND: Sex differences exist in the prevalence and clinical manifestation of several mental disorders, suggesting that sex-specific brain phenotypes may play key roles. Previous research used machine learning models to classify sex from imaging data of the whole brain and studied the association of class probabilities with mental health, potentially overlooking regional specific characteristics. METHODS: We here investigated if a regionally constrained model of brain volumetric imaging data may provide estimates that are more sensitive to mental health than whole brain-based estimates. Given its known role in emotional processing and mood disorders, we focused on the limbic system. Using two different cohorts of healthy subjects, the Human Connectome Project and the Queensland Twin IMaging, we investigated sex differences and heritability of brain volumes of limbic structures compared to non-limbic structures, and subsequently applied regionally constrained machine learning models trained solely on limbic or non-limbic features. To investigate the biological underpinnings of such models, we assessed the heritability of the obtained sex class probability estimates, and we investigated the association with major depression diagnosis in an independent clinical sample. All analyses were performed both with and without controlling for estimated total intracranial volume (eTIV). RESULTS: Limbic structures show greater sex differences and are more heritable compared to non-limbic structures in both analyses, with and without eTIV control. Consequently, machine learning models performed well at classifying sex based solely on limbic structures and achieved performance as high as those on non-limbic or whole brain data, despite the much smaller number of features in the limbic system. The resulting class probabilities were heritable, suggesting potentially meaningful underlying biological information. Applied to an independent population with major depressive disorder, we found that depression is associated with male-female class probabilities, with largest effects obtained using the limbic model. This association was significant for models not controlling for eTIV whereas in those controlling for eTIV the associations did not pass significance correction. CONCLUSIONS: Overall, our results highlight the potential utility of regionally constrained models of brain sex to better understand the link between sex differences in the brain and mental disorders.

Psychiatric disorders have different prevalence between sexes, with women being twice as likely to develop depression and anxiety across the lifespan. Previous studies have investigated sex differences in brain structure that might contribute to this prevalence but have mostly focused on a single-structure level, potentially overlooking the interplay between brain regions. Sex differences in structures responsible for emotional regulation (limbic system), affected in many psychiatric disorders, have been previously reported. Here, we apply a machine learning model to obtain an estimate of brain sex for each participant based on the volumes of multiple brain regions. Particularly, we compared the estimates obtained with a model based solely on limbic structures with those obtained with a non-limbic model (entire brain except limbic structures) and a whole brain model. To investigate the genetic determinants of the models, we assessed the heritability of the estimates between identical twins and fraternal twins. The estimates of all our models were heritable, suggesting a genetic component contributing to brain sex. Finally, to investigate the association with mental health, we compared brain sex estimates in healthy subjects and in a depressed population. We found an association between depression and brain sex in females for the limbic model, but not for the non-limbic model. No effect was found in males. Overall, our results highlight the potential utility of machine learning models of brain sex based on relevant structures to better understand the link between sex differences in the brain and mental disorders.

Fractional amplitude of low-frequency fluctuations in sensory-motor networks and limbic system as a potential predictor of treatment response in patients with schizophrenia.

BACKGROUND: Previous investigations have revealed substantial differences in neuroimaging characteristics between healthy controls (HCs) and individuals diagnosed with schizophrenia (SCZ). However, we are not entirely sure how brain activity links to symptoms in schizophrenia, and there is a need for reliable brain imaging markers for treatment prediction. METHODS: In this longitudinal study, we examined 56 individuals diagnosed with 56 SCZ and 51 HCs. The SCZ patients underwent a three-month course of antipsychotic treatment. We employed resting-state functional magnetic resonance imaging (fMRI) along with fractional Amplitude of Low Frequency Fluctuations (fALFF) and support vector regression (SVR) methods for data acquisition and subsequent analysis. RESULTS: In this study, we initially noted lower fALFF values in the right postcentral/precentral gyrus and left postcentral gyrus, coupled with higher fALFF values in the left hippocampus and right putamen in SCZ patients compared to the HCs at baseline. However, when comparing fALFF values in brain regions with abnormal baseline fALFF values for SCZ patients who completed the follow-up, no significant differences in fALFF values were observed after 3 months of treatment compared to baseline data. The fALFF values in the right postcentral/precentral gyrus and left postcentral gyrus, and the left postcentral gyrus were useful in predicting treatment effects. CONCLUSION: Our findings suggest that reduced fALFF values in the sensory-motor networks and increased fALFF values in the limbic system may constitute distinctive neurobiological features in SCZ patients. These findings may serve as potential neuroimaging markers for the prognosis of SCZ patients.

Systemic lupus erythematosus-related brain abnormalities in the default mode network and the limbic system: A resting-state fMRI meta-analysis.

BACKGROUND: Systemic lupus erythematosus (SLE) is an immune-mediated and multi-systemic disease which may affect the nervous system, causing neuropsychiatric SLE (NPSLE). Recent neuroimaging studies have examined brain functional alterations in SLE. However, discrepant findings were reported. This meta-analysis aims to identify consistent resting-state functional abnormalities in SLE. METHODS: PubMed and Web of Science were searched to identify candidate resting-state functional MRI studies assessing SLE. A voxel-based meta-analysis was performed using the anisotropic effect-size version of the seed-based d mapping (AES-SDM). The abnormal intrinsic functional patterns extracted from SDM were mapped onto the brain functional network atlas to determine brain abnormalities at a network level. RESULTS: Twelve studies evaluating fifteen datasets were included in this meta-analysis, comprising 572 SLE patients and 436 healthy controls (HCs). Compared with HCs, SLE patients showed increased brain activity in the bilateral hippocampus and right superior temporal gyrus, and decreased brain activity in the left superior frontal gyrus, left middle temporal gyrus, bilateral thalamus, left inferior frontal gyrus and right cerebellum. Mapping the abnormal patterns to the network atlas revealed the default mode network and the limbic system as core neural systems commonly affected in SLE. LIMITATIONS: The number of included studies is relatively small, with heterogeneous analytic methods and a risk of publication bias. CONCLUSIONS: Brain functional alterations in SLE are predominantly found in the default mode network and the limbic system. These findings uncovered a consistent pattern of resting-state functional network abnormalities in SLE which may serve as a potential objective neuroimaging biomarker.

The difference in volumetric alternations of the orbitofrontal-limbic-striatal system between major depressive disorder and anxiety disorders: A systematic review and voxel-based meta-analysis.

BACKGROUND: Major depressive disorder (MDD) and anxiety disorders (ANX) are psychiatric disorders with high mutual comorbidity rates that might indicate some shared neurobiological pathways between them, but they retain diverse phenotypes that characterize themselves specifically. However, no consistent evidence exists for common and disorder-specific gray matter volume (GMV) alternations between them. METHODS: A systematic review and meta-analysis on voxel-based morphometry studies of patients with MDD and ANX were performed. The effect of comorbidity was explicitly controlled during disorder-specific analysis and particularly investigated in patient with comorbidity. RESULTS: A total of 45 studies with 54 datasets comprising 2196 patients and 2055 healthy participants met the inclusion criteria. Deficits in the orbitofrontal cortex, striatum, and limbic regions were found in MDD and ANX. The disorder-specific analyses showed decreased GMV in the bilateral anterior cingulate cortex, right striatum, hippocampus, and cerebellum in MDD, while decreased GMV in the left striatum, amygdala, insula, and increased cerebellar volume in ANX. A totally different GMV alternation pattern was shown involving bilateral temporal and parietal gyri and left fusiform gyrus in patients with comorbidity. LIMITATIONS: Owing to the design of included studies, only partial patients in the comorbid group had a secondary comorbidity diagnosis. CONCLUSION: Patients with MDD and ANX shared a structural disruption in the orbitofrontal-limbic-striatal system. The disorder-specific effects manifested their greatest severity in distinct lateralization and directionality of these changes that differentiate MDD from ANX. The comorbid group showed a totally different GMV alternation pattern, possibly suggesting another illness subtype that requires further investigation.

Morphological changes of the limbic system associated with acute and chronic low-back pain: A UK biobank imaging study.

BACKGROUND: Low back pain (LBP) is a major public health issue that influences physical and emotional factors integral to the limbic system. This study aims to investigate the association between LBP and brain morphometry alterations as the duration of LBP increases (acute vs. chronic). METHODS: We used the UK Biobank data to investigate the morphological features of the limbic system in acute LBP (N = 115), chronic LBP (N = 243) and controls (N = 358), and tried to replicate our findings with an independent dataset composed of 45 acute LBP participants evaluated at different timepoints throughout 1 year from the OpenPain database. RESULTS: We found that in comparison with chronic LBP and pain-free controls, acute LBP was associated with increased volumes of the nucleus accumbens, amygdala, hippocampus, and thalamus, and increased grey matter volumes in the hippocampus and posterior cingulate gyrus. In the replication cohort, we found non-significantly larger hippocampus and thalamus volumes in the 3-month visit (acute LBP) compared to the 1-year visit (chronic LBP), with similar effect sizes as the UK Biobank dataset. CONCLUSIONS: Our results suggest that acute LBP is associated with dramatic morphometric increases in the limbic system and mesolimbic pathway, which may reflect an active brain response and self-regulation in the early stage of LBP. SIGNIFICANCE: Our study suggests that LBP in the acute phase is associated with the brain morphometric changes (increase) in some limbic areas, indicating that the acute phase of LBP may represent a crucial stage of self-regulation and active response to the disease's onset.

Association between limbic system lesions and anxiety in persons with multiple sclerosis.

BACKGROUND: Persons with Multiple Sclerosis (PwMS) have a higher rate of anxiety and depression than the general population. Depression has been associated with clinical relapses; temporal lesions were shown to predict depression severity. Anxiety is considerably understudied. The role of MS lesions in the limbic system is also understudied, partly due to difficulties identifying limbic lesions on standard 1.5 and 3 Tesla MRI. METHODS: This is a retrospective study of 23 PwMS who underwent 7T MRI on the same day as completing the Hospital Anxiety and Depression Scale (HADS). MRI was performed on a Siemens 7T MRI Plus and an 8-channel transmit coil with 32 receiver channels operating in pTx mode. MP2RAGE and DIR-SPACE sequences were analyzed to determine the number of lesions within the limbic system. RESULTS: The median number of lesions in the limbic system was 2.0 (range 0-7). When comparing the presence or absence of lesions in the limbic system, there was a significant relationship with anxiety (X2 (1, N = 23)=4.44, p = 0.035), but not for depression. CONCLUSION: Although only a small sample size, this study provides preliminary evidence that lesions in the limbic system are associated with the presence of anxiety in PwMS. This relationship warrants further investigation.

The Cortico-Limbo-Thalamo-Cortical Circuits: An Update to the Original Papez Circuit of the Human Limbic System.

The Papez circuit, first proposed by James Papez in 1937, is a circuit believed to control memory and emotions, composed of the cingulate cortex, entorhinal cortex, parahippocampal gyrus, hippocampus, hypothalamus, and thalamus. Pursuant to James Papez, Paul Yakovlev and Paul MacLean incorporated the prefrontal/orbitofrontal cortex, septum, amygdalae, and anterior temporal lobes into the limbic system. Over the past few years, diffusion-weighted tractography techniques revealed additional limbic fiber connectivity, which incorporates multiple circuits to the already known complex limbic network. In the current review, we aimed to comprehensively summarize the anatomy of the limbic system and elaborate on the anatomical connectivity of the limbic circuits based on the published literature as an update to the original Papez circuit.

EEG coherences of the fronto-limbic circuit between patients with major depressive disorder and healthy controls.

BACKGROUND: Imaging studies found that patients with major depressive disorder (MDD) showed abnormal functional connectivity in the fronto-limbic circuit, including the prefrontal cortex (PFC), anterior cingulate cortex (ACC), and limbic system (amygdala). This study used electroencephalography (EEG) coherence as an indicator of functional connectivity in the fronto-limbic circuit and examined the group differences between the MDD group and healthy controls (HC group), and the associations between EEG coherence and depressive symptoms. METHODS: 125 and 132 participants in the MDD and HC groups have measured the symptoms of depression and anxiety, and delta, theta, alpha, and beta1-beta4 EEG coherences in the fronto-limbic circuit and examined the differences between the two groups, and the associations between the EEG coherence and depressive symptoms were examined. RESULTS: Lower theta, alpha, beta1, beta3, and beta4 coherence in the fronto-limbic circuit and higher beta2 coherence between the PFC and limbic system in the MDD group than in the HC group. Negative correlations between delta, theta, beta1, beta3, and beta4 coherence and total depression, cognitive depression, and somatic depression; positive correlations between beta2 coherences in the PFC and limbic system, and total depression and cognitive depression scores in the MDD group. LIMITATIONS: Whether low EEG coherence in the fronto-limbic circuit is applicable to other subtypes of MDD requires further study. CONCLUSIONS: Low EEG coherences in the fronto-limbic circuit were related to depressive symptoms, and increased functional connectivity in the fronto-limbic circuit can be applied by neurofeedback in future studies.

Prefrontal, parietal, and limbic condition-dependent differences in bipolar disorder: a large-scale meta-analysis of functional neuroimaging studies.

BACKGROUND: Over the past few decades, neuroimaging research in Bipolar Disorder (BD) has identified neural differences underlying cognitive and emotional processing. However, substantial clinical and methodological heterogeneity present across neuroimaging experiments potentially hinders the identification of consistent neural biomarkers of BD. This meta-analysis aims to comprehensively reassess brain activation and connectivity in BD in order to identify replicable differences that converge across and within resting-state, cognitive, and emotional neuroimaging experiments. METHODS: Neuroimaging experiments (using fMRI, PET, or arterial spin labeling) reporting whole-brain results in adults with BD and controls published from December 1999-June 18, 2019 were identified via PubMed search. Coordinates showing significant activation and/or connectivity differences between BD participants and controls during resting-state, emotional, or cognitive tasks were extracted. Four parallel, independent meta-analyses were calculated using the revised activation likelihood estimation algorithm: all experiment types, all resting-state experiments, all cognitive experiments, and all emotional experiments. To confirm reliability of identified clusters, two different meta-analytic significance tests were employed. RESULTS: 205 published studies yielding 506 individual neuroimaging experiments (150 resting-state, 134 cognitive, 222 emotional) comprising 5745 BD and 8023 control participants were included. Five regions survived both significance tests. Individuals with BD showed functional differences in the right posterior cingulate cortex during resting-state experiments, the left amygdala during emotional experiments, including those using a mixed (positive/negative) valence manipulation, and the left superior and right inferior parietal lobules during cognitive experiments, while hyperactivating the left medial orbitofrontal cortex during cognitive experiments. Across all experiments, there was convergence in the right caudate extending to the ventral striatum, surviving only one significance test. CONCLUSIONS: Our findings indicate reproducible localization of prefrontal, parietal, and limbic differences distinguishing BD from control participants that are condition-dependent, despite heterogeneity, and point towards a framework for identifying reproducible differences in BD that may guide diagnosis and treatment.

Social threat, fronto-cingulate-limbic morphometry, and symptom course in depressed adolescents: a longitudinal investigation.

BACKGROUND: Psychosocial stressors characterized by social threat, such as interpersonal loss and social rejection, are associated with depression in adolescents. Few studies, however, have examined whether social threat affects fronto-cingulate-limbic systems implicated in adolescent depression. METHODS: We assessed lifetime stressor severity across several domains using the Stress and Adversity Inventory (STRAIN) in 57 depressed adolescents (16.15 ± 1.32 years, 34 females), and examined whether the severity of social threat and non-social threat stressors was associated with gray matter volumes (GMVs) in the anterior cingulate cortex (ACC), amygdala, hippocampus, and nucleus accumbens (NAcc). We also examined how lifetime social threat severity and GMVs in these regions related to depressive symptoms at baseline and over 9 months. RESULTS: General stressor severity was related to greater depression severity at baseline and over 9 months. Moreover, greater severity of social threat (but not non-social threat) stressors was associated with smaller bilateral amygdala and NAcc GMVs, and smaller bilateral surface areas of caudal and rostral ACC (all pFDR ⩽ 0.048). However, neither social threat nor non-social threat stressor severity was related to hippocampal GMVs (all pFDR ⩾ 0.318). All fronto-cingulate-limbic structures that were associated with the severity of social threat were negatively associated with greater depression severity over 9 months (all pFDR ⩽ 0.014). Post-hoc analyses suggested that gray matter morphometry of bilateral amygdala, NAcc, and rostral and caudal ACC mediated the association between social threat and depression severity in adolescents over 9 months (all pFDR < 0.048). CONCLUSIONS: Social threat specifically affects fronto-cingulate-limbic pathways that contribute to the maintenance of depression in adolescents.

Functional connectivity of limbic system and prefrontal cortex years after pre-eclampsia: 7-Tesla functional magnetic resonance imaging study.

OBJECTIVE: Pre-eclampsia is a vascular complication of pregnancy, associated with a long-term risk of cerebrovascular and mental disorders. We explored whether formerly pre-eclamptic women exhibit differences in functional brain organization, especially in regions that may explain the commonly reported emotional symptoms and cognitive complaints even years after the pregnancy. METHODS: Formerly pre-eclamptic women and control women with a history of normotensive pregnancy underwent structural and functional 7-Tesla magnetic resonance imaging scans. Using graph theoretical analysis, the efficiency and clustering coefficient of the functional brain network were investigated. The study included local analysis focusing on particular brain structures, such as the limbic system and the prefrontal cortex, and global analysis of the whole cerebrum. Univariable and multivariable linear regression was used to investigate the relationship between brain network-related graph measures and the group (formerly pre-eclamptic or control). RESULTS: A total of 17 control parous women and 55 women with a history of pre-eclampsia were recruited. The time intervals between the index pregnancy and recruitment were 8.0 and 5.6 years for the two groups, respectively. Compared with control women, formerly pre-eclamptic women had higher local efficiency in the prefrontal cortex (P = 0.048) and anterior cingulate cortex (P = 0.03) but lower local efficiency and local clustering coefficient in the amygdala (P = 0.004 and P = 0.02, respectively) and parahippocampal cortex (P = 0.007 and P = 0.008, respectively). No differences were found in the global functional brain organization. CONCLUSIONS: Compared to controls with a history of normotensive pregnancy, formerly pre-eclamptic women displayed a different local functional brain organization. These differences in functional connectivity, especially in the limbic regions and the prefrontal cortex, are in line with the psychological and cognitive complaints reported commonly by women with a history of pre-eclampsia. © 2022 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

ENIGMA-anxiety working group: Rationale for and organization of large-scale neuroimaging studies of anxiety disorders.

Anxiety disorders are highly prevalent and disabling but seem particularly tractable to investigation with translational neuroscience methodologies. Neuroimaging has informed our understanding of the neurobiology of anxiety disorders, but research has been limited by small sample sizes and low statistical power, as well as heterogenous imaging methodology. The ENIGMA-Anxiety Working Group has brought together researchers from around the world, in a harmonized and coordinated effort to address these challenges and generate more robust and reproducible findings. This paper elaborates on the concepts and methods informing the work of the working group to date, and describes the initial approach of the four subgroups studying generalized anxiety disorder, panic disorder, social anxiety disorder, and specific phobia. At present, the ENIGMA-Anxiety database contains information about more than 100 unique samples, from 16 countries and 59 institutes. Future directions include examining additional imaging modalities, integrating imaging and genetic data, and collaborating with other ENIGMA working groups. The ENIGMA consortium creates synergy at the intersection of global mental health and clinical neuroscience, and the ENIGMA-Anxiety Working Group extends the promise of this approach to neuroimaging research on anxiety disorders.

Correlation of anatomical involvement patterns of insular gliomas with subnetworks of the limbic system.

OBJECTIVE: Gliomas frequently involve the insula both primarily and secondarily by invasion. Despite the high connectivity of the human insula, gliomas do not spread randomly to or from the insula but follow stereotypical anatomical involvement patterns. In the majority of cases, these patterns correspond to the intrinsic connectivity of the limbic system, except for tumors with aggressive biology. On the basis of these observations, the authors hypothesized that these different involvement patterns may be correlated with distinct outcomes and analyzed these correlations in an institutional cohort. METHODS: Fifty-nine patients who had undergone surgery for insular diffuse gliomas and had complete demographic, pre- and postoperative imaging, pathology, molecular genetics, and clinical follow-up data were included in the analysis (median age 37 years, range 21-71 years, M/F ratio 1.68). Patients with gliomatosis and those with only minor involvement of the insula were excluded. The presence of T2-hyperintense tumor infiltration was evaluated in 12 anatomical structures. Hierarchical biclustering was used to identify co-involved structures, and the findings were correlated with established functional anatomy knowledge. Overall survival was evaluated using Kaplan-Meier and Cox proportional hazards regression analysis (17 parameters). RESULTS: The tumors involved the anterior insula (98.3%), posterior insula (67.8%), temporal operculum (47.5%), amygdala (42.4%), frontal operculum (40.7%), temporal pole (39%), parolfactory area (35.6%), hypothalamus (23.7%), hippocampus (16.9%), thalamus (6.8%), striatum (5.1%), and cingulate gyrus (3.4%). A mean 4.2 ± 2.6 structures were involved. On the basis of hierarchical biclustering, 7 involvement patterns were identified and correlated with cortical functional anatomy (pure insular [11.9%], olfactocentric [15.3%], olfactoopercular [33.9%], operculoinsular [15.3%], striatoinsular [3.4%], translimbic [11.9%], and multifocal [8.5%] patterns). Cox regression identified hippocampal involvement (p = 0.006) and postoperative tumor volume (p = 0.027) as significant negative independent prognosticators of overall survival and extent of resection (p = 0.015) as a significant positive independent prognosticator. CONCLUSIONS: The study findings indicate that insular gliomas primarily involve the olfactocentric limbic girdle and that involvement in the hippocampocentric limbic girdle is associated with a worse prognosis.

Test-retest reliability of dynamic functional connectivity in naturalistic paradigm functional magnetic resonance imaging.

Dynamic functional connectivity (dFC) has been increasingly used to characterize the brain transient temporal functional patterns and their alterations in diseased brains. Meanwhile, naturalistic neuroimaging paradigms have been an emerging approach for cognitive neuroscience with high ecological validity. However, the test-retest reliability of dFC in naturalistic paradigm neuroimaging is largely unknown. To address this issue, we examined the test-retest reliability of dFC in functional magnetic resonance imaging (fMRI) under natural viewing condition. The intraclass correlation coefficients (ICC) of four dFC statistics including standard deviation (Std), coefficient of variation (COV), amplitude of low frequency fluctuation (ALFF), and excursion (Excursion) were used to measure the test-retest reliability. The test-retest reliability of dFC in naturalistic viewing condition was then compared with that under resting state. Our experimental results showed that: (a) Global test-retest reliability of dFC was much lower than that of static functional connectivity (sFC) in both resting-state and naturalistic viewing conditions; (b) Both global and local (including visual, limbic and default mode networks) test-retest reliability of dFC could be significantly improved in naturalistic viewing condition compared to that in resting state; (c) There existed strong negative correlation between sFC and dFC, weak negative correlation between dFC and dFC-ICC (i.e., ICC of dFC), as well as weak positive correlation between dFC-ICC and sFC-ICC (i.e., ICC of sFC). The present study provides novel evidence for the promotion of naturalistic paradigm fMRI in functional brain network studies.

Sweets for my sweet: modulation of the limbic system drives salience for sweet foods after deep brain stimulation in Parkinson's disease.

BACKGROUND: An increase in body weight is observed in the majority of patients with Parkinson's disease (PD) who undergo deep brain stimulation (DBS) of the subthalamic nucleus (STN) although the mechanisms are unclear. OBJECTIVES: To identify the stimulation-dependent effects on reward-associated and attention-associated neural networks and to determine whether these alterations in functional connectivity are associated with the local impact of DBS on different STN parcellations. METHODS: We acquired functional task-related MRI data from 21 patients with PD during active and inactive STN DBS and 19 controls while performing a food viewing paradigm. Electrode placement in the STN was localised using a state-of-the-art approach. Based on the 3D model, the local impact of STN DBS was estimated. RESULTS: STN DBS resulted in a mean improvement of motor function of 22.6%±15.5% (on medication) and an increase of body weight of ~4 kg within 2 years of stimulation. DBS of the limbic proportion of the STN was associated with body weight gain and an increased functional connectivity within the salience network and at the same time with a decreased activity within the reward-related network in the context of sweet food images. CONCLUSIONS: Our findings indicate increased selective attention for high-caloric foods and a sweet food seeking-like behaviour after DBS particularly when the limbic proportion of the STN was stimulated.

Connectome-based model predicts individual psychopathic traits in college students.

BACKGROUND: Psychopathic traits have been suggested to increase the risk of violations of socio-moral norms. Previous studies revealed that abnormal neural signatures are associated with elevated psychopathic traits; however, whether the intrinsic network architecture can predict psychopathic traits at the individual level remains unclear. METHODS: The present study utilized connectome-based predictive modeling (CPM) to investigate whether whole-brain resting-state functional connectivity (RSFC) can predict psychopathic traits in the general population. Resting-state fMRI data were collected from 84 college students with varying psychopathic traits measured by the Levenson Self-Report Psychopathy Scale (LSRP). RESULTS: Functional connections that were negatively correlated with psychopathic traits predicted individual differences in total LSRP and secondary psychopathy score but not primary score. Particularly, nodes with the most connections in the predictive connectome anchored in the prefrontal cortex (e.g., anterior prefrontal cortex and orbitofrontal cortex) and limbic system (e.g., anterior cingulate cortex and insula). In addition, the connections between the occipital network (OCCN) and cingulo-opercular network (CON) served as a significant predictive connectome for total LSRP and secondary psychopathy score. CONCLUSION: CPM constituted by whole-brain RSFC significantly predicted psychopathic traits individually in the general population. The brain areas including the prefrontal cortex and limbic system and large-scale networks including the CON and OCCN play special roles in the predictive model-possibly reflecting atypical cognitive control and affective processing for individuals with elevated psychopathic traits. These findings may facilitate detection and potential intervention of individuals with maladaptive psychopathic tendency.

A deep learning toolbox for automatic segmentation of subcortical limbic structures from MRI images.

A tool was developed to automatically segment several subcortical limbic structures (nucleus accumbens, basal forebrain, septal nuclei, hypothalamus without mammillary bodies, the mammillary bodies, and fornix) using only a T1-weighted MRI as input. This tool fills an unmet need as there are few, if any, publicly available tools to segment these clinically relevant structures. A U-Net with spatial, intensity, contrast, and noise augmentation was trained using 39 manually labeled MRI data sets. In general, the Dice scores, true positive rates, false discovery rates, and manual-automatic volume correlation were very good relative to comparable tools for other structures. A diverse data set of 698 subjects were segmented using the tool; evaluation of the resulting labelings showed that the tool failed in less than 1% of cases. Test-retest reliability of the tool was excellent. The automatically segmented volume of all structures except mammillary bodies showed effectiveness at detecting either clinical AD effects, age effects, or both. This tool will be publicly released with FreeSurfer (surfer.nmr.mgh.harvard.edu/fswiki/ScLimbic). Together with the other cortical and subcortical limbic segmentations, this tool will allow FreeSurfer to provide a comprehensive view of the limbic system in an automated way.

Prefrontal-limbic-striatum dysconnectivity associated with negative emotional endophenotypes in bipolar disorder during depressive episodes.

BACKGROUND: The prefrontal-limbic-subcortical network has been suggested as an important circuitry in the pathophysiology underlying bipolar disorder during depressive episodes (BDD). However, the relationships between disrupted prefrontal-limbic-subcortical connection and the emotional endophenotypes in BDD patients remain largely unclear. METHODS: Forty-three BDD patients and 63 matched healthy controls (HCs) underwent the resting-state functional magnetic resonance imaging scan. The altered clusters were first identified by using a spatial pairwise clustering method and then were extracted as regions of interest to calculate the functional connectivity (FC). Group comparisons were conducted to identify the abnormal FCs. Classification analysis was employed to examine whether the altered FCs could distinguish BDD from HCs. The relationships between FC alterations and the emotional endophenotypes as measured by the Affective Neuroscience Personality Scales (ANPS) were further detected in BDD. RESULTS: Compared with HCs, BDD patients showed abnormal FCs in the prefrontal-limbic-striatum circuit. Importantly, the altered FCs yielded 84.91% accuracy (p< 1/5000) with 93.65% sensitivity and 72.09% specificity in differentiating between BDD and HCs. Moreover, the decreased FCs in the prefrontal-striatum and prefrontal-limbic systems were positively correlated with negative emotional endophenotypes of Sadness and Fear scores. CONCLUSIONS: The findings demonstrated that prefrontal-limbic-striatum disconnection may be identified as a potential effective biomarker for BDD, which could help further explain the neurobiological mechanisms underlying BDD.

Interrelations of Cerebral Hemodynamics with Parameters of Cardiac Function and Brain Tissue in Patients with Ischemic Stroke.

We analyzed interrelations between the cerebral blood flow, cardiac output, and condition of the brain substance in 530 patients with ischemic stroke. Dependencies between the linear blood flow velocities in all arteries supplying the brain, as well as between the total volume blood flow through the internal carotid arteries and left ventricular stroke volume were revealed. The severity of atrophy was maximum in the parietal lobes (median 1.5 (1.0; 2.0)) and minimum in the occipital lobes (median 0.5 (0; 1.0)). Temporal lobes cortical atrophy significantly correlated with changes in the limbic system and in the periventricular and deep white matter; a significant weak inverse correlation of this parameter with blood flow in the middle cerebral artery was also found. Changes in the periventricular white matter (but not in deep white matter) demonstrated a significant inverse correlation with blood flow in the middle and anterior cerebral arteries.

Functional Connectivity in Antipsychotic-Treated and Antipsychotic-Naive Patients With First-Episode Psychosis and Low Risk of Self-harm or Aggression: A Secondary Analysis of a Randomized Clinical Trial.

Importance: Altered functional connectivity (FC) is a common finding in resting-state functional magnetic resonance imaging (rs-fMRI) studies of people with psychosis, yet how FC disturbances evolve in the early stages of illness, and how antipsychotic treatment influences these disturbances, remains unknown. Objective: To investigate longitudinal FC changes in antipsychotic-naive and antipsychotic-treated patients with first-episode psychosis (FEP). Design, Setting, and Participants: This secondary analysis of a triple-blind, randomized clinical trial was conducted over a 5-year recruitment period between April 2008 and December 2016 with 59 antipsychotic-naive patients with FEP receiving either a second-generation antipsychotic or a placebo pill over a treatment period of 6 months. Participants were required to have low suicidality and aggression, to have a duration of untreated psychosis of less than 6 months, and to be living in stable accommodations with social support. Both FEP groups received intensive psychosocial therapy. A healthy control group was also recruited. Participants completed rs-fMRI scans at baseline, 3 months, and 12 months. Data were analyzed from May 2019 to August 2020. Interventions: Resting-state functional MRI was used to probe brain FC. Patients received either a second-generation antipsychotic or a matched placebo tablet. Both patient groups received a manualized psychosocial intervention. Main Outcomes and Measures: The primary outcomes of this analysis were to investigate (1) FC differences between patients and controls at baseline; (2) FC changes in medicated and unmedicated patients between baseline and 3 months; and (3) associations between longitudinal FC changes and clinical outcomes. An additional aim was to investigate long-term FC changes at 12 months after baseline. These outcomes were not preregistered. Results: Data were analyzed for 59 patients (antipsychotic medication plus psychosocial treatment: 28 [47.5%]; mean [SD] age, 19.5 [3.0] years; 15 men [53.6%]; placebo plus psychosocial treatment: 31 [52.5%]; mean [SD] age, 18.8 [2.7]; 16 men [51.6%]) and 27 control individuals (mean [SD] age, 21.9 [1.9] years). At baseline, patients showed widespread functional dysconnectivity compared with controls, with reductions predominantly affecting interactions between the default mode network, limbic systems, and the rest of the brain. From baseline to 3 months, patients receiving placebo showed increased FC principally within the same systems; some of these changes correlated with improved clinical outcomes (canonical correlation analysis R = 0.901; familywise error-corrected P = .005). Antipsychotic exposure was associated with increased FC primarily between the thalamus and the rest of the brain. Conclusions and Relevance: In this secondary analysis of a clinical trial, antipsychotic-naive patients with FEP showed widespread functional dysconnectivity at baseline, followed by an early normalization of default mode network and cortical limbic dysfunction in patients receiving placebo and psychosocial intervention. Antipsychotic exposure was associated with FC changes concentrated on thalamocortical networks. Trial Registration: ACTRN12607000608460.