Abnormal baseline brain activity in suicidal and non-suicidal patients with major depressive disorder

Functional magnetic resonance imaging alternations in suicide attempts individuals and their association with gene expression

BACKGROUND

Functional Magnetic Resonance Imaging (fMRI) has shown brain activity alterations in individuals with a history of attempted suicide (SA) who are diagnosed with depression disorder (DD) or bipolar disorder (BD). However, patterns of spontaneous brain activity and their genetic correlations need further investigation.

METHODS

A voxel-based meta-analysis of 19 studies including 26 datasets, involving 742 patients with a history of SA and 978 controls (both nonsuicidal patients and healthy controls) was conducted. We examined fMRI changes in SA patients and analyzed the association between these changes and gene expression profiles using data from the Allen Human Brain Atlas by partial least squares regression analysis.

RESULTS

SA patients demonstrated increased spontaneous brain activity in several brain regions including the bilateral inferior temporal gyrus, hippocampus, fusiform gyrus, and right insula, and decreased activity in areas like the bilateral paracentral lobule and inferior frontal gyrus. Additionally, 5,077 genes were identified, exhibiting expression patterns associated with SA-related fMRI alterations. Functional enrichment analyses demonstrated that these SA-related genes were enriched for biological functions including glutamatergic synapse and mitochondrial structure. Concurrently, specific expression analyses showed that these genes were specifically expressed in the brain tissue, in neurons cells, and during early developmental periods.

CONCLUSION

Our findings suggest a neurobiological basis for fMRI abnormalities in SA patients with DD or BD, potentially guiding future genetic and therapeutic research.

Alterations in electroencephalographic functional connectivity in individuals with major depressive disorder: a resting-state electroencephalogram study

Background

Major depressive disorder (MDD) is the leading cause of disability among all mental illnesses with increasing prevalence. The diagnosis of MDD is susceptible to interference by several factors, which has led to a trend of exploring objective biomarkers. Electroencephalography (EEG) is a non-invasive procedure that is being gradually applied to detect and diagnose MDD through some features such as functional connectivity (FC).

Methods

In this research, we analyzed the resting-state EEG of patients with MDD and healthy controls (HCs) in both eyes-open (EO) and eyes-closed (EC) conditions. The phase locking value (PLV) method was utilized to explore the connection and synchronization of neuronal activities spatiotemporally between different brain regions. We compared the PLV between participants with MDD and HCs in five frequency bands (theta, 4-8 Hz; alpha, 8-12 Hz; beta1, 12-16 Hz; beta2, 16-24 Hz; and beta3, 24-40 Hz) and further analyzed the correlation between the PLV of connections with significant differences and the severity of depression (via the scores of 17-item Hamilton Depression Rating Scale, HDRS-17).

Results

During the EO period, lower PLVs were found in the right temporal-left midline occipital cortex (RT-LMOC; theta, alpha, beta1, and beta2) and posterior parietal-right temporal cortex (PP-RT; beta1 and beta2) in the MDD group compared with the HC group, while PLVs were higher in the MDD group in LT-LMOC (beta2). During the EC period, for the MDD group, lower theta and beta (beta1, beta2, and beta3) PLVs were found in PP-RT, as well as lower theta, alpha, and beta (beta1, beta2, and beta3) PLVs in RT-LMOC. Additionally, in the left midline frontal cortex-right temporal cortex (LMFC-RT) and posterior parietal cortex-right temporal cortex (PP-RMOC), higher PLVs were observed in beta2. There were no significant correlations between PLVs and HDRS-17 scores when connections with significantly different PLVs (all p > 0.05) were checked.

Conclusion

Our study confirmed the presence of differences in FC between patients with MDD and healthy individuals. Lower PLVs in the connection of the right temporal-left occipital cortex were mostly observed, whereas an increase in PLVs was observed in patients with MDD in the connections of the left temporal with occipital lobe (EO), the circuits of the frontal-temporal lobe, and the parietal-occipital lobe. The trends in FC involved in this study were not correlated with the level of depression.

Limitations

The study was limited due to the lack of further analysis of confounding factors and follow-up data. Future studies with large-sampled and long-term designs are needed to further explore the distinguishable features of EEG FC in individuals with MDD.

Changed brain entropy and functional connectivity patterns induced by electroconvulsive therapy in majoy depression disorder

OBJECTIVE

Our objective is to innovatively integrate both linear and nonlinear characteristics of brain signals in Electroconvulsive Therapy (ECT) research, with the goal of uncovering deeper insights into the pathogenesis of Major Depressive Disorder (MDD) and identifying novel targets for other physical intervention therapies.

METHODS

We measured brain entropy (BEN) in 42 MDD patients and 42 matched healthy controls (HC) using rs-fMRI data. Brain regions that differed significantly in patients with MDD before and after ECT were extracted. Then, we use these brain regions as seed points to investigate the differences in whole-brain resting-state functional connectivity (RSFC) patterns before and after ECT.

RESULTS

Compared to HCs, patients had higher BEN levels in the right precuneus (PCUN.R) and right angular gyrus (ANG.R). After ECT, patients had lower BEN levels in the PCUN.R and ANG.R. Compared with before ECT, patients showed significantly increased RSFC after ECT between the PCUN.R and right middle temporal gyrus and ANG.R. Significantly increased RSFC was observed between the ANG.R and right middle frontal gyrus and right supramarginal gyrus after ECT.

CONCLUSION

Combining the linear and nonlinear characteristics of brain signals can effectively explore the pathogenesis of depression and provide new targets for ECT.

Whole-brain structural and functional neuroimaging of individuals who attempted suicide and people who did not: A systematic review and exploratory coordinate-based meta-analysis

Suicide is the cause of death of approximately 800,000 people a year. Despite the relevance of this behaviour, risk assessment tools rely on clinician experience and subjective ratings. Given that previous suicide attempts are the single strongest predictors of future attempts, we designed a systematic review and coordinate-based meta-analysis to demonstrate whether neuroimaging features can help distinguish individuals who attempted suicide from subjects who did not. Out of 5,659 publications from PubMed, Scopus, and Web of Science, we summarised 102 experiments and meta-analysed 23 of them. A cluster in the right superior temporal gyrus, a region implicated in emotional processing, might be functionally hyperactive in individuals who attempted suicide. No statistically significant differences in brain morphometry were evidenced. Furthermore, we used JuSpace to show that this cluster is enriched in 5-HT1A heteroreceptors in the general population. This exploratory meta-analysis provides a putative neural substrate linked to previous suicide attempts. Heterogeneity in the analytical techniques and weak or absent power analysis of the studies included in this review currently limit the applicability of the findings, the replication of which should be prioritised.

Functional connectivity and network analysis in adolescents with major depressive disorder showing suicidal behavior

BACKGROUND

This study aimed to gather a homogeneous sample of adolescent patients to analyze the differences in functional connectivity and brain network parameters between suicidal and non-suicidal major depressive disorder (MDD) patients using a data-driven whole-brain approach.

METHODS

Patients recruited at the psychiatry department of Korea University Guro Hospital from November 2014 to March 2020 were diagnosed with MDD, were 13-18 years old, had IQ scores >80, had no family history of psychotic or personality disorders, had no smoking or alcohol consumption history, and were drug-naïve to psychotropic medication. Depressive symptoms were assessed using the Hamilton Depression Rating Scale and the Children's Depression Inventory. Structural and functional MRI scans were conducted and analyzed using the CONN toolbox.

RESULTS

Of 74 enrolled patients, 62 were analyzed. Regions of interest (ROIs) showing higher betweenness centrality in non-suicidal patients were the left superior temporal gyrus and left supramarginal gyrus. ROIs showing higher betweenness centrality in suicidal patients were the right hippocampus, left intracalcarine cortex, right inferior temporal gyrus, and the lateral visual network. Suicidal patients also showed different resting state functional connectivity profiles from non-suicidal patients.

LIMITATIONS

Small sample size.

CONCLUSION

Suicidal patients may overthink and overvalue future risks while having a more negatively biased autobiographical memory. Social cognition and the ability to overcome egocentricity bias seem to weaken. Such features can disrupt cognitive recovery and resilience, leading to more suicidal behaviors. Therefore, increased suicidality is not acquired, but is an innate trait.

Altered fractional amplitude of low-frequency fluctuations in the superior temporal gyrus: a resting-state fMRI study in anxious depression

BACKGROUND

Anxious depression, which is a common subtype of major depressive disorder, has distinct clinical features from nonanxious depression. However, little is known about the neurobiological characteristics of anxious depression. In this study, we explored resting-state regional brain activity changes between anxious depression and nonanxious depression.

METHOD

Resting-state functional magnetic resonance (rs-fMRI) imaging data were collected from 60 patients with anxious depression, 38 patients with nonanxious depression, and 60 matched healthy controls (HCs). One-way analysis of variance was performed to compare the whole-brain fractional amplitude of low-frequency fluctuation (fALFF) in the three groups. The correlation between the fALFF values and the clinical measures was examined.

RESULTS

Compared with those of HCs, the fALFF values in the left superior temporal gyrus (STG) in patients with anxious depression were significantly increased, while the fALFF values in the left middle temporal gyrus (MTG), left STG, and right STG in patients with nonanxious depression were significantly increased. Patients with anxious depression showed reduced fALFF values in the right STG compared with patients with nonanxious depression (p < 0.001, corrected). Within the anxious depression group, fALFF value in the right STG was positively correlated with the cognitive disturbance score (r = 0.36, p = 0.005 corrected).

CONCLUSION

The bilateral STG and left MTG, which are related to the default mode network, appear to be key brain regions in nonanxious depression, while the right STG plays an essential role in the neuropathological mechanism of anxious depression.

Reduced suicidality after electroconvulsive therapy is linked to increased frontal brain activity in depressed patients: a resting-state fMRI study

Objective

Suicidality is commonly observed in patients with depressive episodes, and electroconvulsive therapy (ECT) has been found to be effective in treating these patients. However, the role of ECT in suicidality remains unclear. This study used resting-state functional magnetic resonance imaging (rs-fMRI) to explore the changes in brain function before and after ECT in depressed patients with suicidality.

Methods

In total, 26 depressed patients with suicidality underwent rs-fMRI at baseline and after 8-12 sessions of ECT. In addition, 32 healthy controls (HCs) matched for age, gender, and educational level underwent rs-fMRI once. The amplitude of low-frequency fluctuations (ALFF), the fractional amplitude of low-frequency fluctuations (fALFF), and regional homogeneity (ReHo) were measured to evaluate whole brain function. Differences between the groups and time points (before and after ECT) were compared. Clinical symptoms were assessed using the 17-item Hamilton Depression Scale (HAMD-17) and Beck Scale for Suicide Ideation (BSSI).

Results

At baseline, patients exhibited decreased ALFF in the right postcentral and precentral gyrus and decreased fALFF in the right supramarginal and postcentral gyrus, left superior frontal gyrus (SFG), as well as the superior and middle temporal gyrus compared to HCs. Patients also had lower ReHo in the left amygdala, anterior cingulate, and postcentral gyrus, and in the right thalamus, insula, and postcentral gyrus. They also exhibited higher ALFF in the bilateral temporal gyrus and insula as well as higher fALFF in the cerebellum. Following ECT, fALFF in the left SFG and orbital frontal cortex (OFC) significantly increased and was inversely correlated with the reduction of BSSI scores (r = -0.416, p = 0.048), whereas no correlation was found with changes in HAMD-17scores.

Conclusion

Our findings suggest that the left SFG and OFC may play a key role in the mechanism of ECT for suicidality. The decrease of fALFF in the left SFG and OFC may represent a potential mechanism through which ECT effectively treats suicidality in depressed patients.

Increased subcortical brain activity in anxious but not depressed individuals

BACKGROUND

Anxiety and depressive symptoms usually co-occur. Neuroimaging abnormalities in patients with depression and anxiety disorders are therefore related to a combination of symptoms. Here, we used a large population study to select individuals with anxiety, depressive, or both anxiety and depressive symptoms to identify whether neuroimaging differences are unique or shared between anxiety and depressive symptoms.

METHODS

We selected four groups of 200 individuals (anxiety, depression, anxiety and depression, controls) from the UK Biobank, matched for age, sex, intelligence, and educational attainment (total N = 800). We extracted the amplitude of low frequency fluctuations (ALFF) from resting-state functional magnetic resonance imaging data, which indexes spontaneous neuronal activity. Group differences were assessed using permutation testing to correct for multiple comparisons, with age, sex, IQ, and head motion as covariates.

RESULTS

Compared to controls, anxious individuals had higher ALFF values in many subcortical brain regions including the striatum, thalamus, medial temporal lobe, midbrain, pons, as well as the cerebellum. Anxious individuals also showed higher ALFF in the hippocampus, parahippocampal gyrus, cerebellum, and pons compared to individuals with depressive symptoms. No significant differences were found for the depression and combined anxiety/depression groups. Post-hoc tests with largest possible samples showed comparable results in the anxiety group and in the combined group, but still no significant differences for the depression group.

CONCLUSIONS

Anxiety but not depressive symptoms were associated with increased subcortical activity during rest. This suggest that anxiety symptoms may have the largest contribution to the neuroimaging differences in individuals with depression and anxiety disorders.

Frequency-dependent alterations in regional homogeneity associated with puberty hormones in girls with central precocious puberty: A resting-state fMRI study

OBJECTIVE

Central precocious puberty (CPP) patients are at significantly higher risk of emotional, mental, and behavioral disorders than those normal pubertal population. However, to date, the definite mechanism of how puberty hormones affect patients with CPP remains unclear. This regional homogeneity (ReHo) study aimed to explore the impact of premature hypothalamus-pituitary-gonadal (HPG) axis activation on brain function alteration in girls with CPP, meanwhile, to explore the relationship between gonadotropin and gonadal hormones levels, abnormal brain activity and cognitive function.

METHODS

In this prospective study, a total of 85 girls who were suspected of having CPP were enrolled from the Child Healthcare Department of the Second Affiliated Hospital of Wenzhou Medical University Hospital from June 2018 to May 2021, including 41 CPP girls and 44 non-CPP girls. All participants collected the 0, 30, 60 min blood luteinizing hormone (LH), follicle-stimulating hormone (FSH), 0, 30 min estradiol (E2) and baseline cortisol (COR) and prolactin (PRL) concentrations after gonadotrophin-releasing hormone (GnRH) stimulating test. Resting-state magnetic resonance imaging (rs-MRI) scans were performed for all participants at 2 weeks before the GnRH stimulating test, voxel-wise ReHo was calculated in the standard frequency band (0.01-0.10 Hz), and in slow-4 (0.027-0.073 Hz) and slow-5 (0.01-0.027 Hz). Wechsler Intelligence Scale for Children Fourth Edition (WISC-IV) was also collected. Independent-sample t-test or Mann-Whitney U test was used to compare the differences between two groups. The correlation analysis among abnormal brain regions, serum hormone levels and WISC-IV scores were performed by Spearman or partial correlation analysis.

RESULTS

Compared to the non-CPP group, the CPP group showed higher regional homogeneity (ReHo) values in the left inferior temporal gyrus (ITG.L), as well as lower ReHo values in left superior temporal gyrus (STG.L), left superior occipital gyrus (SOG.L) and the right middle gyrus (MTG.R) in slow4.in slow5 frequency band, CPP group demonstrated decreased ReHo values in bilateral orbital part of superior frontal gyrus and medial superior frontal gyrus.

LIMITATION

Due to the cross-section design of this study, further research is needed to explore the relationships between age, premature activation HPG axis and brain function changes.

CONCLUSION

Our findings demonstrate that premature HPG axis activation and alterations in puberty hormones, may lead to changes in brain activity and cognitive function. This rs-fMRI study may enhance our understanding of the neuroendocrine mechanisms of mood, behavior, and cognitive function alterations in patients with CPP.

Childhood sexual abuse related to brain activity abnormalities in right inferior temporal gyrus among major depressive disorder

Regional brain activity abnormalities have been reported in major depressive disorder (MDD) with childhood trauma (CT). However, these findings were variable and equivocal. The present study aims to explore further the correlation between CT and the amplitude of low-frequency fluctuations (ALFF) alteration in MDD. In this study, we recruited 60 healthy controls (HCs) and 66 MDD patients to complete resting-state fMRI scans. All MDD patients were evaluated clinical symptoms and childhood trauma experience using the Hamilton Depression Rating Scale-17 (HDRS-17), the Hamilton Anxiety Scale (HAMA), and the Childhood Trauma Questionnaire (CTQ). Compared to HCs, MDD patients demonstrated significantly altered ALFF in the right middle occipital gyrus (MOG), bilateral inferior temporal gyrus (ITG), bilateral cerebellum posterior lobe, bilateral anterior cingulate gyrus (ACC), and bilateral superior frontal gyrus (SFG). More importantly, we found negative correlation between childhood sexual abuse (CSA) scores and ALFF value appeared mainly in the right ITG among MDD patients. After adjusting for covariates (age, gender, mean framewise displacement (FD), HRDS-17, and HAMA scores), this correlation remained significant. Meanwhile, ALFF in the right ITG could distinguish MDD patients with or without CSA (area under the curve (AUC) = 0.713). Our findings revealed that the regional brain activity abnormalities in the right ITG might be a potential biomarker for MDD patients with CSA.

Analysis of functional connectivity in depression based on a weighted hyper-network method

Objective. Brain connectivity network is a vital tool to reveal the interaction between different brain regions. Currently, most functional connectivity methods can only capture pairs of information to construct brain networks which ignored the high-order correlations between brain regions.Approach. Therefore, this study proposed a weighted connectivity hyper-network based on resting-state EEG data, and then applied to depression identification and analysis. The hyper-network model was build based on least absolute shrinkage and selection operator sparse regression method to effectively represent the higher-order relationships of brain regions. On this basis, by integrating the correlation-based weighted hyper-edge information, the weighted hyper-network is constructed, and the topological features of the network are extracted for classification.Main results. The experimental results obtained an optimal accuracy compared to the traditional coupling methods. The statistical results on network metrics proved that there were significant differences between depressive patients and normal controls. In addition, some brain regions and electrodes were found and discussed to highly correlate with depression by analyzing of the critical nodes and hyper-edges.Significance. These may help discover disease-related biomarkers important for depression diagnosis.

Associations between abnormal spontaneous neural activity and clinical variables, eye movements, and event-related potential indicators in major depressive disorder

Background

This study aimed to investigate the correlations between abnormal spontaneous neural activity measured with fractional amplitude of low-frequency fluctuations (fALFF) and clinical variables, eye movements, and event-related potential indicators in patients with major depressive disorder (MDD).

Methods

We recruited 42 patients with MDD and 42 healthy controls (HCs) and collected their clinical variables, eye movement, event-related potential, and resting-state functional magnetic resonance imaging (rs-fMRI) data. The fALFF, support vector machine (SVM), and correlation analysis were used to analyze the data.

Results

The results of the study showed that the fALFF values of the sensorimotor network, including the right middle temporal gyrus, right cerebellar Crus2, left occipital gyrus, and left middle temporal gyrus, were significantly higher compared to HCs. Correlation analysis showed that the abnormal fALFF value of the right cerebellar Crus2 was inversely correlated with the active coping scores of the Simplified Coping Style Questionnaire in the patients (r = -0.307, p = 0.048). No correlation was observed between abnormal fALFF values and other clinical symptoms, neuropsychological tests, eye movements, and event-related potential-related indicators in patients with MDD. fALFF values in the left middle temporal gyrus could be used to distinguish patients with MDD from HCs with an accuracy of 78.57%.

Conclusions

Patients with MDD exhibited enhanced spontaneous neural activity in the sensorimotor network. No associations were found between abnormal spontaneous neural activity and clinical variables, eye movements, and event-related potential related indicators in MDD.

Abnormal amplitude of low-frequency fluctuation values as a neuroimaging biomarker for major depressive disorder with suicidal attempts in adolescents: A resting-state fMRI and support vector machine analysis

Objective

Major depressive disorder (MDD) is associated with suicidal attempts (SAs) among adolescents, with suicide being the most common cause of mortality in this age group. This study explored the predictive utility of support vector machine (SVM)-based analyses of amplitude of low-frequency fluctuation (ALFF) results as a neuroimaging biomarker for aiding the diagnosis of MDD with SA in adolescents.

Methods

Resting-state functional magnetic resonance imaging (rs-fMRI) analyses of 71 first-episode, drug-naive adolescent MDD patients with SA and 54 healthy control individuals were conducted. ALFF and SVM methods were used to analyze the imaging data.

Results

Relative to healthy control individuals, adolescent MDD patients with a history of SAs showed reduced ALFF values in the bilateral medial superior frontal gyrus (mSFG) and bilateral precuneus. These lower ALFF values were also negatively correlated with child depression inventory (CDI) scores while reduced bilateral precuneus ALFF values were negatively correlated with Suicidal Ideation Questionnaire Junior (SIQ-JR) scores. SVM analyses showed that reduced ALFF values in the bilateral mSFG and bilateral precuneus had diagnostic accuracy levels of 76.8% (96/125) and 82.4% (103/125), respectively.

Conclusion

Adolescent MDD patients with a history of SA exhibited abnormal ALFF. The identified abnormalities in specific brain regions may be involved in the pathogenesis of this condition and may help identify at-risk adolescents. Specifically, reductions in the ALFF in the bilateral mSFG and bilateral precuneus may be indicative of MDD and SA in adolescent patients.

Aberrant dynamic functional connectivity in corticostriatal circuitry in depressed bipolar II disorder with recent suicide attempt

BACKGROUND

The underlying neurobiological mechanisms on suicidal behavior in bipolar disorder remain unclear. We aim to explore the mechanisms of suicide by detecting dynamic functional connectivity (dFC) of corticostriatal circuitry and cognition in depressed bipolar II disorder (BD II) with recent suicide attempt (SA).

METHODS

We analyzed resting-state functional magnetic resonance imaging (fMRI) data from 68 depressed patients with BD-II (30 with SA and 38 without SA) and 35 healthy controls (HCs). The whole-brain dFC variability of corticostriatal circuitry was calculated using a sliding-window analysis. Their correlations with cognitive dysfunction were further detected. Support vector machine (SVM) classification tested the potential of dFC to differentiate BD-II with SA from HCs.

RESULTS

Increased dFC variability between the right vCa and the right insula was found in SA compared to non-SA and HCs, and negatively correlated with speed of processing. Decreased dFC variability between the left dlPu and the right postcentral gyrus was found in non-SA compared to SA and HCs, and positively correlated with reasoning problem-solving. Both SA and non-SA exhibited decreased dFC variability between the right dCa and the left MTG, and between the right dlPu and the right calcarine when compared to HCs. SVM classification achieved an accuracy of 75.24 % and AUC of 0.835 to differentiate SA from non-SA, while combining the abnormal dFC features between SA and non-SA.

CONCLUSIONS

Aberrant dFC variability of corticostriatal circuitry may serve as potential neuromarker for SA in BD-II, which might help to discriminate suicidal BD-II patients from non-suicidal patients and HCs.

The impacts of anhedonia on brain functional alterations in patients with major depressive disorder: A resting-state functional magnetic resonance imaging study of regional homogeneity

BACKGROUND

Anhedonia, as one of the core manifestations of major depressive disorder (MDD), has an effect on prognosis of the disease. However, the neuropathology of MDD is complex and the neural basis of anhedonia remains unclear. The aim of the present study was to investigate the impacts of anhedonia on brain functional alterations in patients with MDD.

METHODS

A total of 62 individuals including MDD patients with anhedonia (n = 22), MDD patients without anhedonia (n = 20), and healthy controls (HCs, n = 20) were recruited. All participants underwent resting-state functional magnetic resonance imaging scanning and intrinsic brain function was explored by using regional homogeneity (ReHo) method. A two-sample t-test was performed to explore ReHo differences between MDD patients and HCs, then analysis of variance (ANOVA) was introduced to obtain brain regions with significant differences among three groups, and finally post hoc tests were calculated for inter-group comparisons. Correlations between ReHo values of each survived area and clinical characteristics in MDD patients were further analyzed.

RESULTS

Compared with HCs, MDD showed increased ReHo in the left superior temporal gyrus (STG) and bilateral inferior frontal gyrus (IFG), as well as decreased ReHo in the left superior frontal gyrus (SFG). Interestingly, this relationship was attenuated and no longer significant after consideration for the effect of anhedonia in MDD patients. MDD patients with anhedonia were more likely to exhibit decreased ReHo in the left SFG and left middle cingulate gyrus (MCG) when comparing to HCs. No significant difference was found between MDD patients without anhedonia and HCs, either the two groups of MDD patients. There was no significant association between ReHo values of each survived area and clinical characteristics in MDD patients.

CONCLUSIONS

The present results suggest that the impacts of anhedonia on brain functional alterations in MDD should be emphasized and disturbed intrinsic brain function in the frontal-limbic regions may be associated with anhedonia in MDD patients.

Changes in gray matter volume following electroconvulsive therapy in adolescent depression with suicidal ideation: A longitudinal structural magnetic resonance imaging study

Objective

We aimed to investigate changes in whole-brain gray matter volumes (GMVs) before and after electroconvulsive therapy (ECT) in adolescents with major depressive disorder (MDD) and suicidal ideation (SI).

Methods

Thirty adolescents with MDD and SI were observed, and structural magnetic resonance imaging (sMRI) was performed at baseline and after ECT for each patient. But Twenty-five healthy controls (HCs) were scanned only at baseline. The voxel-based morphometry (VBM) techniques were used to examine GMVs.

Results

Compared with HCs, MDDs at baseline showed decreased GMVs in the left middle temporal gyrus, right superior temporal gyrus, right middle temporal gyrus, left precuneus, right precuneus, and left superior frontal gyrus. After ECT, MDDs showed increased GMVs in the right superior frontal gyrus and right superior temporal gyrus. Pearson's correlation found that Beck Scale for Suicide Ideation (BSSI) scores at baseline were negatively correlated with GMVs in the left superior frontal gyrus and HAMD and BSSI scores after ECT were negatively correlated with GMVs in the right superior temporal gyrus.

Conclusion

Frontal-temporal-precuneus structure changes may be a potential cause of depressive and suicidal symptoms in adolescents. ECT may improve depressive and suicidal symptoms in adolescents by regulating brain structures to compensate original defects.

Temporal Stability of Dynamic Default Mode Network Connectivity Negatively Correlates with Suicidality in Major Depressive Disorder

Previous studies have demonstrated that the suicidality in patients with major depressive disorder (MDD) is related to abnormal brain functional connectivity (FC) patterns. However, little is known about its relationship with dynamic functional connectivity (dFC) based on the assumption that brain FCs fluctuate over time. Temporal stabilities of dFCs within the whole brain and nine key networks were compared between 52 MDD patients and 21 age, sex-matched healthy controls (HCs) using resting-state functional magnetic resonance imaging and temporal correlation coefficients. The alterations in MDD were further correlated with the scores of suicidality item in the Hamilton Rating Scale for Depression (HAMD). Compared with HCs, the MDD patients showed a decreased temporal stability of dFC as indicated by a significantly decreased temporal correlation coefficient at the global level, as well as within the default mode network (DMN) and subcortical network. In addition, temporal correlation coefficients of the DMN were found to be significantly negatively correlated with the HAMD suicidality item scores in MDD patients. These results suggest that MDD may be characterized by excessive temporal fluctuations of dFCs within the DMN and subcortical network, and that decreased stability of DMN connectivity may be particularly associated with the suicidality in MDD.

Identification of suicidality in patients with major depressive disorder via dynamic functional network connectivity signatures and machine learning

Major depressive disorder (MDD) is a severe brain disease associated with a significant risk of suicide. Identification of suicidality is sometimes life-saving for MDD patients. We aimed to explore the use of dynamic functional network connectivity (dFNC) for suicidality detection in MDD patients. A total of 173 MDD patients, including 48 without suicide risk (NS), 74 with suicide ideation (SI), and 51 having attempted suicide (SA), participated in the present study. Thirty-eight healthy controls were also recruited for comparison. A sliding window approach was used to derive the dFNC, and the K-means clustering method was used to cluster the windowed dFNC. A linear support vector machine was used for classification, and leave-one-out cross-validation was performed for validation. Other machine learning methods were also used for comparison. MDD patients had widespread hypoconnectivity in both the strongly connected states (states 2 and 5) and the weakly connected state (state 4), while the dysfunctional connectivity within the weakly connected state (state 4) was mainly driven by suicidal attempts. Furthermore, dFNC matrices, especially the weakly connected state, could be used to distinguish MDD from healthy controls (area under curve [AUC] = 82), and even to identify suicidality in MDD patients (AUC = 78 for NS vs. SI, AUC = 88 for NS vs. SA, and AUC = 74 for SA vs. SI), with vision-related and default-related inter-network connectivity serving as important features. Thus, the dFNC abnormalities observed in this study might further improve our understanding of the neural substrates of suicidality in MDD patients.

Altered Regional Homogeneity and Amplitude of Low-Frequency Fluctuations Induced by Electroconvulsive Therapy for Adolescents with Depression and Suicidal Ideation

Resting-state functional magnetic resonance imaging (rs-fMRI) was used to investigate the effects of electroconvulsive therapy (ECT) causing brain function changes in adolescents who suffered from depression and suicidal ideation (SI). A total of 30 patients (MDDs) and 25 healthy controls (HCs) matched by gender, age, and education level were enrolled. The amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo) were used to compare differences between HCs and MDDs at baseline, and differences in ALFF and ReHo pre/post ECT in MDDs. Pearson correlation analysis was used to evaluate the relationship between altered brain function and clinical symptoms. At baseline, MDDs showed decreased ALFF in the left inferior temporal gyrus and right amygdala, decreased ReHo in left inferior temporal gyrus, and increased ReHo in the right inferior frontal gyrus, opercular part and left middle occipital gyrus. After ECT, MDDs showed increased ALFF in the right middle occipital gyrus, decreased ALFF in left temporal pole, left inferior frontal gyrus, opercular part, and right frontal middle gyrus, increased ReHo in the right middle occipital gyrus, and left inferior temporal gyrus. Pearson correlation found HAMD scores at baseline were negatively correlated with ALFF in the left inferior temporal gyrus, and HAMD and BSSI scores after ECT were negatively correlated with ALFF in the right middle occipital gyrus. The abnormal activities of amygdala, inferior temporal gyrus and middle occipital gyrus might be related to depressive and suicidal symptoms in adolescents.

High-order brain functional network for electroencephalography-based diagnosis of major depressive disorder

Brain functional network (BFN) based on electroencephalography (EEG) has been widely used to diagnose brain diseases, such as major depressive disorder (MDD). However, most existing BFNs only consider the correlation between two channels, ignoring the high-level interaction among multiple channels that contain more rich information for diagnosing brain diseases. In such a sense, the BFN is called low-order BFN (LO-BFN). In order to fully explore the high-level interactive information among multiple channels of the EEG signals, a scheme for constructing a high-order BFN (HO-BFN) based on the “correlation’s correlation” strategy is proposed in this paper. Specifically, the entire EEG time series is firstly divided into multiple epochs by sliding window. For each epoch, the short-term correlation between channels is calculated to construct a LO-BFN. The correlation time series of all channel pairs are formulated by these LO-BFNs obtained from all epochs to describe the dynamic change of short-term correlation along the time. To construct HO-BFN, we cluster all correlation time series to avoid the problems caused by high dimensionality, and the correlation of the average correlation time series from different clusters is calculated to reflect the high-order correlation among multiple channels. Experimental results demonstrate the efficiency of the proposed HO-BFN in MDD identification, and its integration with the LO-BFN can further improve the recognition rate.

Resting-State fMRI in Predicting Response to Treatment With SSRIs in First-Episode, Drug-Naive Patients With Major Depressive Disorder

Objective

For major depressive disorder (MDD), there has been a lack of neuroimaging markers of efficacy of pharmacological treatment. In this study, we aimed to explore the neuroimaging mechanisms in patients with first-episode MDD and identify markers that predict the efficacy of 5-hydroxytryptamine reuptake inhibitors (SSRIs) with the use of resting-state brain imaging technology.

Methods

A total of 101 patients with first-episode MDD and 53 normal controls were finally included in this study. Based on the reduction rate of the score of Hamilton Depression Rating Scale (HAMD-17) during the 2-week SSRI treatment, 31 patients were assigned into the unresponsive group and 32 were assigned into the responsive group. The brain function was compared between patients with MDD and normal controls, and the diagnostic value of brain function was analyzed. With brain regions showing differences between patients with MDD and normal controls as a mask, and the brain function between the responsive and unresponsive groups were compared. Correlations between brain function the HAMD-17 score reduction rate during the 2-week SSRI treatment were analyzed.

Results

Compared to normal controls, patients with MDD showed increased ReHo in the left parahippocampal gyrus and right parahippocampal gyrus, decreased ReHo in the right middle occipital gyrus, and decreased functional connectivity between the right and left parahippocampal gyri, right middle occipital gyrus and middle temporal gyrus. Receiver operator characteristic (ROC) curve analysis showed that the area under the curve (AUC) was 0.544 (95% CI: 0.445–0.644) for ReHo and 0.822 (95% CI: 0.734–0.909) for functional connectivity. Logistic regression pooling of the differences in ReHo mean time series with the functional connectivity mean time series was performed for the ROC curve analysis, which showed an AUC of 0.832 (95% CI: 0.752–0.911). Compared to the responsive group, the unresponsive group showed elevated ReHo in the right parahippocampal gyrus and lower functional connectivity in the middle temporal gyrus. We also found that the ReHo value was negatively correlated with the HAMD-17 score reduction after 2 weeks of SSRI treatment.

Conclusion

Altered resting-state brain function in some regions might be a neurobiological marker for the diagnosis of MDD, and ReHo values are expected to be predictors of patient response to treatment with SSRIs.

Clinical Trial Registration

[http://www.chictr.org.cn/], identifier [ChiCTR1900028722].

Changes of functional connectivity of the subgenual anterior cingulate cortex and precuneus after cognitive behavioral therapy combined with fluoxetine in young depressed patients with suicide attempt

This single-center, randomized, single-blind, parallel-controlled study aimed to analyze the changes in resting-state functional connectivity (RSFC) in young patients with a suicide attempt caused by depression before and after cognitive-behavioral therapy (CBT) combined with fluoxetine or fluoxetine alone by functional magnetic resonance imaging (fMRI). Before treatment, functional connectivity of the right subgenual anterior cingulate cortex (R-sgACC), left subgenual anterior cingulate cortex (L-sgACC) and right precuneus (R-PCu) was lower in depressed patients with a suicide attempt than that of healthy controls. After treatment, compared with the fluoxetine group, functional connectivity between the R-sgACC and left posterior cerebellar lobe in the CBT group was increased, while this group also showed increased RSFC between the L-sgACC and right anterior cingulate cortex/ medial prefrontal cortex. On the contrary, the functional connectivity between the R-PCu and right parietal lobe was reduced (P < 0.001). It was also found there were some changes in different brain regions in pre- and post-treatment within both the CBT and MG group. The functional connectivity of the R-sgACC and the left posterior cerebellum lobe was negatively correlated with the SSI score. The functional connectivity of the R-PCu and right middle frontal cortex was negatively correlated with the HAMD score before treatment. After treatment, functional connectivity between the R-PCu and right superior frontal gyrus was positively correlated with the SSI scores in the CBT group. After 8 weeks of combined CBT, the strength of the functional connectivity in the bilateral sgACC and bilateral PCu was significantly changed.

Alteration of Whole Brain ALFF/fALFF and Degree Centrality in Adolescents With Depression and Suicidal Ideation After Electroconvulsive Therapy: A Resting-State fMRI Study

Major depressive disorder (MDD) is one of the most widespread mental disorders and can result in suicide. Suicidal ideation (SI) is strongly predictive of death by suicide, and electroconvulsive therapy (ECT) is effective for MDD, especially in patients with SI. In the present study, we aimed to determine differences in resting-state functional magnetic resonance imaging (rs-fMRI) in 14 adolescents aged 12–17 with MDD and SI at baseline and after ECT. All participants were administered the Hamilton Depression Scale (HAMD) and Beck Scale for Suicide Ideation (BSSI) and received rs-fMRI scans at baseline and after ECT. Following ECT, the amplitude of low frequency fluctuation (ALFF) and fractional ALFF (fALFF) significantly decreased in the right precentral gyrus, and the degree centrality (DC) decreased in the left triangular part of the inferior frontal gyrus and increased in the left hippocampus. There were significant negative correlations between the change of HAMD (ΔHAMD) and ALFF in the right precentral gyrus at baseline, and between the change of BSSI and the change of fALFF in the right precentral gyrus. The ΔHAMD was positively correlated with the DC value of the left hippocampus at baseline. We suggest that these brain regions may be indicators of response to ECT in adolescents with MDD and SI.

Analysis of Functional Brain Network in MDD Based on Improved Empirical Mode Decomposition With Resting State EEG Data

At present, most brain functional studies are based on traditional frequency bands to explore the abnormal functional connections and topological organization of patients with depression. However, they ignore the characteristic relationship of electroencephalogram (EEG) signals in the time domain. Therefore, this paper proposes a network decomposition model based on Improved Empirical Mode Decomposition (EMD), it is suitable for time-frequency analysis of brain functional network. On the one hand, it solves the problem of mode mixing on original EMD method, especially on high-density EEG data. On the other hand, by building brain function networks on different intrinsic mode function (IMF), we can perform time-frequency analysis of brain function connections. It provides a new insight for brain function connectivity analysis of major depressive disorder (MDD). Experimental results found that the IMFs waveform decomposed by Improved EMD was more stable and the difference between IMFs was obvious, it indicated that the mode mixing can be effectively solved. Besides, the analysis of the brain network, we found that the changes in MDD functional connectivity on different IMFs, it may be related to the pathological changes for MDD. More statistical results on three network metrics proved that there were significant differences between MDD and normal controls (NC) group. In addition, the aberrant brain network structure of MDDs was also confirmed in the hubs characteristic. These findings may provide potential biomarkers for the clinical diagnosis of MDD patients.

Functional alterations of the suicidal brain: a coordinate-based meta-analysis of functional imaging studies

Altered brain activities in suicidal subjects have been reported in a number of neuroimaging studies. However, the activity aberrances were inconsistent in previous investigations. Thus, we aimed to address activity abnormalities in suicidal individuals. Databases were searched to perform a meta-analysis of whole-brain functional MRI studies of suicidal individuals through January 14, 2020. Meta-analyses were conducted using Seed-based d Mapping software. Based on a meta-analysis of 17 studies comprising 381 suicidal individuals and 642 controls, we mainly found that increased activity in the bilateral superior temporal gyrus, left middle temporal gyrus, and bilateral middle occipital gyrus, along with decreased activity in the right putamen and left insula, were detected in suicidal individuals compared with nonsuicidal subjects. To reduce methodological heterogeneity between the included studies, subanalyses of behavioral domains were conducted, and the right superior temporal gyrus was found to increase in all subanalyses of domains. In subanalyses of suicidal attempters and ideators, suicide attempters displayed hyperactivation in the bilateral superior temporal gyrus and left middle temporal gyrus and blunted responses in the left insula relative to controls. Suicidal ideators demonstrated elevated activation in the right middle occipital gyrus and reduced activity in the right putamen relative to controls. The bilateral superior temporal gyrus was the most robust finding, replicable in all data sets in the jackknife sensitive analysis. Moreover, increased activity in the right superior temporal gyrus, left middle temporal gyrus, and right middle occipital gyrus was found to be involved with higher suicide ideation scores. This study revealed several brain regions associated with suicidality. These findings may contribute to our understanding of the pathophysiology of suicide and have important implications for suicide prevention and interventions.

Temporal dynamics alterations of spontaneous neuronal activity in anterior cingulate cortex predict suicidal risk in bipolar II patients

Bipolar disorder type II (BD-II) is linked to an increased suicidal risk. Since a prior suicide attempt (SA) is the single most important risk factor for sequent suicide, the elucidation of involved neural substrates is critical for its prevention. Therefore, we examined the spontaneous brain activity and its temporal variabilities in suicide attempters with bipolar II during a major depressive episode. In this cross-sectional study, 101 patients with BD-II, including 44 suicidal attempters and 57 non-attempters, and 60 non-psychiatric controls underwent a resting-state functional magnetic resonance imaging (fMRI). Participants were assessed with Hamilton Rating Scale for Depression (HAMD) and Nurses^, Global Assessment of Suicide Risk (NGASR). The dynamics of low-frequency fluctuation (dALFF) was measured using sliding-window analysis and its correlation with suicidal risk was conducted using Pearson correlation. Compared to non-attempters, suicidal attempters showed an increase in brain activity and temporal dynamics in the anterior cingulate cortex (ACC). In addition, the temporal variabilities of ACC activity positively correlated with suicidal risk (R = 0.45, p = 0.004), while static ACC activity failed to (R = 0.08, p > 0.05). Our findings showed that an aberrant static ALFF and temporal variability could affect suicidal behavior in BD-II patients. However, temporal variability of neuronal activity was more sensitive than static amplitude in reflecting diathesis for suicide in BD-II. Dynamics of brain activity could be considered in developing neuromarkers for suicide prevention.

Altered cortical morphology in major depression disorder patients with suicidality

Background

Major depressive disorder (MDD) is associated with high risk of suicide, but the biological underpinnings of suicidality in MDD patients are far from conclusive. Previous neuroimaging studies using voxel-based morphometry (VBM) demonstrated that depressed individuals with suicidal thoughts or behaviors exhibit specific cortical structure alterations. To complement VBM findings, surface-based morphometry (SBM) can provide more details into gray matter structure, including the cortical complexity, cortical thickness and sulcal depth for brain images.

Objective

This study aims to use SBM to investigate cortical morphology alterations to obtain evidence for neuroanatomical alterations in depressed patients with suicidality.

Methods

Here, 3D T1-weighted MR images of brain from 39 healthy controls, 40 depressed patients without suicidality (patient controls), and 39 with suicidality (suicidal groups) were analyzed based on SBM to estimate the fractal dimension, gyrification index, sulcal depth, and cortical thickness using the Computational Anatomy Toolbox. Correlation analyses were performed between clinical data and cortical surface measurements from patients.

Results

Surface-based morphometry showed decreased sulcal depth in the parietal, frontal, limbic, occipital and temporal regions and decreased fractal dimension in the frontal regions in depressed patients with suicidality compared to both healthy and patient controls. Additionally, in patients with depression, the sulcal depth of the left caudal anterior cingulate cortex was negatively correlated with Hamilton Depression Rating Scale scores.

Conclusions

Depressed patients with suicidality had abnormal cortical morphology in some brain regions within the default mode network, frontolimbic circuitry and temporal regions. These structural deficits may be associated with the dysfunction of emotional processing and impulsivity control. This study provides insights into the underlying neurobiology of the suicidal brain.

Characterizing the subtype of anhedonia in major depressive disorder: A symptom-specific multimodal MRI study

Anhedonia is a core symptom of major depressive disorder (MDD). Two subtypes of anhedonia: anticipatory anhedonia and consummatory anhedonia has been recognized in MDD patients. However, our knowledge regarding the distinction of anticipatory anhedonia and consummatory anhedonia in MDD remains limited. This study aimed to characterize the anticipatory anhedonia and consummatory anhedonia in first-episode, drug-naïve MDD patients. Resting-state functional MRI and T1-structural MRI were acquired for 38 MDD patients and 65 matched healthy controls (HCs). The ALFF and cortical surface indexes were compared between MDD and HCs. Then the correlations between the ALFF and cortical surface indexes alternations and the scores of anticipatory and consummatory pleasure measured by Temporal Experience of Pleasure Scale were evaluated. The elevated ALFF of left dorsal anterior cingulate cortex (dACC) and the reduced cortical thickness (CT) of left rostral ACC and lateral orbitofrontal cortex (lOFC) were respectively correlated with anticipatory anhedonia and consummatory anhedonia in MDD patients. These findings suggested the dissociated pathophysiological basis and imaging characteristics of anticipatory anhedonia and consummatory anhedonia. The ALFF and CT values of ACC and lOFC might serve as the imaging biomarker of the subtypes of anhedonia in early onset of MDD.

Functional network alterations differently associated with suicidal ideas and acts in depressed patients: an indirect support to the transition model

The transition from suicidal ideas to a suicide act is an important topic of research for the identification of those patients at risk of acting out. We investigated here whether specific brain activity and connectivity measures at rest may be differently associated with suicidal thoughts and behaviors. A large sample of acutely depressed patients with major depressive disorder was recruited in three different centers (Montreal/Canada, Stanford/USA, and Jena/Germany), covering four different phenotypes: patients with a past history of suicide attempt (n = 53), patients with current suicidal ideas but no past history of suicide attempt (n = 40), patients without current suicidal ideation nor past suicide attempts (n = 42), and healthy comparison subjects (n = 107). 3-T resting-state functional magnetic resonance imaging (fMRI) measures of the amplitude of low-frequency fluctuation (ALFF) and degree centrality (DC) were obtained and examined in a whole-brain data-driven analysis. Past suicide attempt was associated with a double cortico-subcortical dissociation in ALFF values. Decreased ALFF and DC values mainly in a frontoparietal network and increased ALFF values in some subcortical regions (hippocampus and thalamus) distinguished suicide attempters from suicide ideators, patient controls, and healthy controls. No clear neural differences were identified in relation to suicidal ideas. Suicide attempters appear to be a distinct subgroup of patients with widespread brain alterations in functional activity and connectivity that could represent factors of vulnerability. Our results also indirectly support at the neurobiological level the relevance of the transition model described at the psychological and clinical levels. The brain bases of suicidal ideas occurrence in depressed individuals needs further investigations.

Machine Learning-Based Identification of Suicidal Risk in Patients With Schizophrenia Using Multi-Level Resting-State fMRI Features

BACKGROUND

Some studies suggest that as much as 40% of all causes of death in a group of patients with schizophrenia can be attributed to suicides and compared with the general population, patients with schizophrenia have an 8.5-fold greater suicide risk (SR). There is a vital need for accurate and reliable methods to predict the SR among patients with schizophrenia based on biological measures. However, it is unknown whether the suicidal risk in schizophrenia can be related to alterations in spontaneous brain activity, or if the resting-state functional magnetic resonance imaging (rsfMRI) measures can be used alongside machine learning (ML) algorithms in order to identify patients with SR.

METHODS

Fifty-nine participants including patients with schizophrenia with and without SR as well as age and gender-matched healthy underwent 13 min resting-state functional magnetic resonance imaging. Both static and dynamic indexes of the amplitude of low-frequency fluctuation (ALFF), the fractional amplitude of low-frequency fluctuations (fALFF), regional homogeneity as well as functional connectivity (FC) were calculated and used as an input for five machine learning algorithms: Gradient boosting (GB), LASSO, Logistic Regression (LR), Random Forest and Support Vector Machine.

RESULTS

All groups revealed different intra-network functional connectivity in ventral DMN and anterior SN. The best performance was reached for the LASSO applied to FC with an accuracy of 70% and AUROC of 0.76 (p < 0.05). Significant classification ability was also reached for GB and LR using fALFF and ALFF measures.

CONCLUSION

Our findings suggest that SR in schizophrenia can be seen on the level of DMN and SN functional connectivity alterations. ML algorithms were able to significantly differentiate SR patients. Our results could be useful in developing neuromarkers of SR in schizophrenia based on non-invasive rsfMRI.

Gray matter volume alterations associated with suicidal ideation and suicide attempts in patients with mood disorders

BACKGROUND

Mood disorders are severe mental disorders related to increased suicidal behavior. Finding neural features for suicidal behavior, including suicide attempts (SAs) and suicidal ideation (SI), in mood disorders may be helpful in preventing suicidal behavior.

METHODS

Subjects consisted of 70 patients with mood disorders and suicidal behavior, 128 patients with mood disorders without suicidal behavior (mood disorders control, MC), and 145 health control (HC) individuals. All participants underwent structural magnetic resonance imaging (MRI). We used voxel-based morphometry (VBM) techniques to examine gray matter volumes (GMVs).

RESULTS

Significant differences were found in GMVs of the left and right middle frontal gyrus among the patients with mood disorders and suicidal behavior, MC, and HC. Post hoc comparisons showed significant differences in the GMVs of the above regions across all three groups (P < 0.01): HC > MC > mood disorders with suicidal behavior. However, there were no significant differences in the GMVs of the left and right middle frontal gyrus between the mood disorders with SI and mood disorders with SAs groups.

CONCLUSIONS

These findings provide evidence that abnormal regional GMV in the middle frontal gyrus is associated with suicidal behavior in mood disorders. Further investigation is warranted to determine whether the GMV alterations in mood disorders with SI are different from these in mood disorders with SAs.

Characteristics of temporal dynamics of intrinsic brain activity in unmedicated bipolar disorder with suicidality

BACKGROUND

Bipolar disorder is associated with a high risk of suicide. Routine neuroimaging examination exhibited that bipolar disorder with suicidality was associated with brain structural and functional changes. However, the alterations of brain dynamics have still remained elusive.

PURPOSE

To investigate the alterations of brain dynamics in unmedicated bipolar disorder II depression with suicidality and predict the severity of suicidality.

MATERIALS AND METHODS

This prospective study included 106 bipolar disorder II participants (20 with suicidal attempt, 35 with suicidal ideation, 51 without suicidal ideation) and 50 healthy controls who underwent resting-state functional magnetic resonance imaging between February 2016 and December 2017. We first used sliding window analysis to evaluate the dynamic amplitude of low-frequency fluctuations. Then, we predicted the severity of suicidality using a multivariate regression model.

RESULTS

One-way analysis of covariance revealed that the dynamic amplitude of low-frequency fluctuations in the right temporal pole, inferior temporal gyrus, superior temporal gyrus and the bilateral precuneus/posterior cingulate cortex was significantly different among the four groups. Post hoc pairwise comparisons revealed that dynamic amplitude of low-frequency fluctuations was remarkably decreased in the bilateral precuneus/posterior cingulate cortex in the three bipolar disorder II groups compared with that in healthy controls group. Increased dynamic amplitude of low-frequency fluctuations was found in the right superior temporal gyrus and inferior temporal gyrus in the suicidal attempt group compared with that in the other groups, and in the right temporal pole in the suicidal attempt group compared with that in the suicidal ideation and healthy controls groups. Importantly, these temporal variabilities could be used to predict the severity of suicidality (r = 0.330, p = 0.036), whereas static amplitude of low-frequency fluctuations couldn't (r = -0.050, p = 0.532).

CONCLUSION

Our findings indicated that alterations of temporal variability in the precuneus/posterior cingulate cortex are such a common feature of bipolar disorder patients. Besides, the severity of suicidality could be predicted by the dynamic amplitude of low-frequency fluctuations abnormalities rather than static amplitude of low-frequency fluctuations abnormalities, which is the first evidence of dynamic brain alterations in bipolar disorder patients with suicidality. The proposed predictive model may be advantageous for clinical applications.

Common and distinct patterns of intrinsic brain activity alterations in major depression and bipolar disorder: voxel-based meta-analysis

Identification of intrinsic brain activity differences and similarities between major depression (MDD) and bipolar disorder (BD) is necessary. However, results have not yet yielded consistent conclusions. A meta-analysis of whole-brain resting-state functional MRI (rs-fMRI) studies that explored differences in the amplitude of low-frequency fluctuation (ALFF) between patients (including MDD and BD) and healthy controls (HCs) was conducted using seed-based d mapping software. Systematic literature search identified 50 studies comparing 1399 MDD patients and 1332 HCs, and 15 studies comparing 494 BD patients and 593 HCs. MDD patients displayed increased ALFF in the right superior frontal gyrus (SFG) (including the medial orbitofrontal cortex, medial prefrontal cortex [mPFC], anterior cingulate cortex [ACC]), bilateral insula extending into the striatum and left supramarginal gyrus and decreased ALFF in the bilateral cerebellum, bilateral precuneus, and left occipital cortex compared with HCs. BD showed increased ALFF in the bilateral inferior frontal gyrus, bilateral insula extending into the striatum, right SFG, and right superior temporal gyrus (STG) and decreased ALFF in the bilateral precuneus, left cerebellum (extending to the occipital cortex), left ACC, and left STG. In addition, MDD displayed increased ALFF in the left lingual gyrus, left ACC, bilateral precuneus/posterior cingulate gyrus, and left STG and decreased ALFF in the right insula, right mPFC, right fusiform gyrus, and bilateral striatum relative to BD patients. Conjunction analysis showed increased ALFF in the bilateral insula, mPFC, and decreased ALFF in the left cerebellum in both disorders. Our comprehensive meta-analysis suggests that MDD and BD show a common pattern of aberrant regional intrinsic brain activity which predominantly includes the insula, mPFC, and cerebellum, while the limbic system and occipital cortex may be associated with spatially distinct patterns of brain function, which provide useful insights for understanding the underlying pathophysiology of brain dysfunction in affective disorders, and developing more targeted and efficacious treatment and intervention strategies.

Alterations in functional brain networks in depressed patients with a suicide attempt history

Suicide is a major challenge in public health and is strongly associated with major depressive disorder (MDD). Despite recent neuroimaging developments, the neural correlates of suicide behavior in patients with MDD remain unclear. Independent component analysis (ICA) for neuroimaging data allows the identification of functional brain networks without prior regions of interest and may help to identify neurobiological markers of specific disorders. Using ICA, we investigated the differences in resting-state brain networks in patients with MDD who had or did not have a history of suicide attempts and in healthy controls (HCs). Suicidal depressed (SD) patients, non-suicidal depressed (NSD) patients, and HCs significantly differed from each other in the pattern of connectivity of multiple functional networks, network synchronization, and functional network connectivity (FNC). The patient groups had a decreased network synchronization in the insular, cerebellum, basal ganglia, thalamus, operculum, frontoparietal cortices, and sensory cortices relative to the HCs. The decreased FNC between these networks (insular-default mode network and insular-cerebellum) was found in the SD group compared to the NSD and HC groups. These differences were not related to illness duration and medication status differences between SD and NSD. Furthermore, the degree of FNC in these networks was associated with the suicide ideation and stress level. Our results demonstrated that widespread but discrete network changes in brain networks and their interconnectivity was associated with suicide attempts in patients with MDD. Our results suggest that the neural basis underlying the psychopathology of attempted suicide in patients with MDD involves multiple brain networks and their interaction.

Default mode dysfunction underpins suicidal activity in mood disorders

BACKGROUND

Suicide is a serious and not uncommon consequence of mood disorders that occurs primarily when individuals are depressed. Understanding the neurobiology of suicidal activity (thoughts or behaviors) is likely to facilitate prevention.

METHOD

Seventy-nine adult depressed mood disorder patients (MDP), of which 25 had attempted suicide at least once, and 66 healthy controls (HC) participated in this study. Resting-state functional MRI was used to identify neural activity differences between suicide attempters (SA) and non-attempters (NA). Specifically, differences were examined in functional connectivity both within and between four large cognitive networks [Executive Control (ECN), Default Mode (DMN), Salience (SN), and Basal Ganglia (BGN)] and their respective associations with suicidal activity.

RESULTS

Compared to HCs, patients had greater posterior DMN activity, but less activity in the BGN, and less low-frequency spectral power in the dorso-medial DMN. Furthermore, increased posterior DMN activity in SA was associated with recent suicidal activity, whereas NA had reduced BGN activity and less dorso-medial DMN spectral power, the latter being associated with lifelong suicidal thinking. SA also had greater activity in midline circuitry compared to both HC and NA, and the pattern of BGN and DMN co-activity differed between SA and NA.

CONCLUSIONS

DMN engagement raises the possibility that suicidal activity in mood disorder patients may be a consequence of impaired self-referential thought processing. Furthermore, differential BGN and DMN co-activation according to suicide attempt status suggests that attempting suicide perhaps alters cognitive flexibility. These insights are potentially useful for understanding the neural basis of suicide activity.

Understanding the Complex of Suicide in Depression: from Research to Clinics

OBJECTIVE

Amongst psychiatric disorders, major depressive disorder (MDD) is the most prevalent, by affecting approximately 15-17% of the population and showing a high suicide risk rate equivalent to around 15%. The present comprehensive overview aims at evaluating main research studies in the field of MDD at suicide risk, by proposing as well as a schematic suicide risk stratification and useful flow-chart for planning suicide preventive and therapeutic interventions for clinicians.

METHODS

A broad and comprehensive overview has been here conducted by using PubMed/Medline, combining the search strategy of free text terms and exploded MESH headings for the topics of 'Major Depressive Disorder' and 'Suicide' as following: ((suicide [Title/Abstract]) AND (major depressive disorder [Title/Abstract])). All articles published in English through May 31, 2019 were summarized in a comprehensive way.

RESULTS

Despite possible pathophysiological factors which may explain the complexity of suicide in MDD, scientific evidence supposed the synergic role of genetics, exogenous and endogenous stressors (i.e., interpersonal, professional, financial, as well as psychiatric disorders), epigenetic, the hypothalamic-pituitary-adrenal stress-response system, the involvement of the monoaminergic neurotransmitter systems, particularly the serotonergic ones, the lipid profile, neuro-immunological biomarkers, the Brain-derived neurotrophic factor and other neuromodulators.

CONCLUSION

The present overview reported that suicide is a highly complex and multifaceted phenomenon in which a large plethora of mechanisms could be variable implicated, particularly amongst MDD subjects. Beyond these consideration, modern psychiatry needs a better interpretation of suicide risk with a more careful assessment of suicide risk stratification and planning of clinical and treatment interventions.

Altered Static and Dynamic Functional Connectivity of Habenula Associated With Suicidal Ideation in First-Episode, Drug-Naïve Patients With Major Depressive Disorder

Investigating the neurobiological mechanism of suicidal ideation (SI) in major depressive disorder (MDD) may be beneficial to prevent the suicidal behavior. Mounting evidence showed that habenula contributed to the etiology of MDD. The habenula is a key brain region that links the forebrain to midbrain, crucial for the processing of reward and aversion. The aim of the present study was to identify whether first-episode, drug-naive MDD patients with SI displayed altered habenula neural circuitry. Forty-three and 38 drug-naïve patients with first-episode MDD with or without SI (SI+/- group) and 35 healthy control subjects (HC) underwent resting-state functional magnetic resonance imaging. The whole-brain habenula static (sFC) and dynamic functional connectivity (dFC) were calculated to identify regions showing significant difference among these three groups followed by region of interest to region of interest post hoc analysis. For sFC, compared with SI- and HC groups, SI+ group showed decreased sFC from habenula to the precuneus and the inferior frontal gyrus. Patients with MDD displayed increased sFC from habenula to the putamen but decreased sFC to the precentral gyrus. For dFC, SI+ group showed increased dFC from habenula to the superior temporal gyrus, the precuneus, but decreased dFC to the lingual gyrus, the postcentral gyrus, when comparing with SI- and HC groups. Patients with MDD, regardless of SI, displayed decreased dFC from the habenula to the angular gyrus. These findings provide evidence that SI in first-episode, drug-naïve patients with MDD may be related to an abnormality in habenula neural circuitry, which may provide the theoretical basis of novel treatments.

Connectome Analysis of Brain Functional Network Alterations in Depressive Patients with Suicidal Attempt

Our study aimed to clarify the neuroimaging correlates of suicide attempt by comparing differences in functional magnetic resonance imaging (fMRI) among depressed suicide attempters, depressed patients without suicide attempt history, and healthy controls through comprehensive and novel fMRI analyses and methods in the same study population. The association between depression severity and aspects of the brain imaging was also discussed. Our study recruited 109 participants who were assigned to three groups: 33 depressed patients with suicide attempt (SA), 32 depressed patients without suicide attempt (NS), and 44 healthy controls (HC). All participants were scanned using a 3 T MRI imaging system to obtain resting-state functional images. In seed-based correlation analysis, we found altered functional connectivity in some brain regions of the SA compared with the NS or HC, especially in the hippocampus and thalamus. In the voxel-based analysis, our results showed differential activation and regional homogeneity of the temporal lobe and several brain regions in the SA compared with the NS and HC. We also found that some brain areas correlated with the Hamilton Depression Rating Scale (HAM-D), anxiety, and depression scores, especially in the frontal and temporal lobes. Graph theoretical analysis (GTA) and network-based statistical (NBS) analyses revealed different topological organization as well as slightly better global integration and worse local segregation of the brain network (i.e., more like a random network) in depressed participants compared with healthy participants. We concluded that the brain function of major depressive disorders with and without suicide attempts changed compared with healthy participants.

Connectomics-Based Functional Network Alterations in both Depressed Patients with Suicidal Behavior and Healthy Relatives of Suicide Victims

Understanding the neural mechanisms of suicidal behavior is crucial. While regional brain alterations have previously been reported, knowledge about brain functional connectomics is currently limited. Here, we investigated differences in global topologic network properties and local network-based functional organization in both suicide attempters and suicide relatives. Two independent samples of depressed suicide attempters (N = 42), depressed patient controls (N = 43), healthy controls (N = 66) as well as one sample of healthy relatives of suicide victims (N = 16) and relatives of depressed patients (N = 16) were investigated with functional magnetic resonance imaging in the resting-state condition. Graph theory analyses were performed. Assortativity, clustering coefficients, global efficiency, and rich-club coefficients were calculated. A network-based statistic approach was finally used to examine functional connectivity matrices. In comparison to healthy controls, both patient groups showed significant reduction in assortativity, and decreased functional connectivity in largely central and posterior brain networks. Suicide attempters only differed from patient controls in terms of higher rich-club coefficients for the highest degree nodes. Compared to patient relatives and healthy controls, suicide relatives showed reduced assortativity, reduced clustering coefficients, increased global efficiency, and increased rich-club coefficients for the highest degree nodes. Suicide relatives also showed reduced functional connectivity in one anterior and one posterior sub-network in comparison to healthy controls, and in a largely anterior brain network in comparison to patient relatives. In conclusion, these results suggest that the vulnerability to suicidal behavior may be associated with heritable deficits in global brain functioning – characterized by weak resilience and poor segregation - and in functional organization with reduced connectivities affecting the ventral and dorsal prefrontal cortex, the anterior cingulate, thalamus, striatum, and possibly the insula, fusiform gyrus and the cerebellum.

Classifying suicidal behavior with resting-state functional connectivity and structural neuroimaging

OBJECTIVE

About 80% of patients who commit suicide do not report suicidal ideation the last time they speak to their mental health provider, highlighting the need to identify biomarkers of suicidal behavior. Our goal is to identify suicidal behavior neural biomarkers to classify suicidal psychiatric inpatients.

METHODS

Eighty percent of our sample [suicidal (n = 63) and non-suicidal psychiatric inpatients (n = 65)] was used to determine significant differences in structural and resting-state functional connectivity measures throughout the brain. These measures were used in a random forest classification model on 80% of the sample for training the model.

RESULTS

The model built on 80% of the patients had sensitivity = 79.4% and specificity = 72.3%. This model was tested on an independent sample (20%; n = 32) with sensitivity = 81.3% and specificity = 75.0% for confirming the generalizability of the model. Altered resting-state functional connectivity features from frontal and middle temporal regions, as well as the amygdala, parahippocampus, putamen, and vermis were found to generalize best.

CONCLUSION

This work demonstrates neuroimaging (an unbiased biomarker) can be used to classify suicidal behavior in psychiatric inpatients without observing any clinical features.

Neural Correlates of Suicidality in Adolescents with Major Depression: Resting-State Functional Connectivity of the Precuneus and Posterior Cingulate Cortex

OBJECTIVE

Major depressive disorder (MDD) is associated with suicidal thoughts and behaviors ("suicidality"). Of the three components of Joiner's interpersonal theory of suicide, two involve negatively valenced, self-related beliefs: perceived burdensomeness and thwarted belongingness. However, the neurocircuitry underlying self-processing and suicidality has not been fully explored. This study examined the association between suicidality and the neurocircuitry of regions relevant to self-referential processing in adolescents with depression.

METHOD

Fifty-eight adolescents underwent assessment and a resting-state fMRI scan. Resting-state functional connectivity (RSFC) analyses included two brain regions implicated in self-referential processing: precuneus and posterior cingulate cortex (PCC). Suicidality was measured using the Index of Depression and Anxiety Symptoms. While controlling for depression severity, we conducted whole-brain correlation analyses between suicidality and left and right precuneus and PCC connectivity maps.

RESULTS

Suicidality was positively associated with RSFC between left precuneus and left primary motor and somatosensory cortices, and middle and superior frontal gyri. Suicidality was negatively associated with RSFC between left PCC and left cerebellum, lateral occipital cortex, and temporal-occipital fusiform gyrus.

CONCLUSIONS

Findings of hyperconnectivity stemming from the precuneus and hypoconnectivity from the PCC may reflect maladaptive self-reflection and mentalization. However, additional investigation is warranted to further clarify these relationships.

Brain functional connectivity is altered in patients with Takotsubo Syndrome

Takotsubo syndrome (TTS) is an acute, reversible cardiomyopathy. The central autonomic nervous system (ANS) is believed to play a role in this disease. The aim of the present study was to investigate the patterns of brain functional connectivity in a sample of patients who had experienced a previous episode of TTS. Brain functional connectivity, both at rest and in response to the stressful stimulus of topical cold stimulation, was explored using functional magnetic resonance imaging (fMRI), network-based statistics (NBS) and graph theory analysis (GTA) in a population consisting of eight patients with a previous episode of TTS and eight sex- and age-matched controls. At rest, a network characterized by increased connectivity in the TTS group compared to controls and comprising elements of the central ANS was identified. GTA revealed increased local efficiency, clustering and strength in regions of the bilateral hippocampus in subjects with a previous episode of TTS. When stressed by local exposure to cold, the TTS group differed significantly from both a pre-stress baseline interval and from the control group, showing increased connectivity in a network that included the left amygdala and the right insula. Based on the results, patients with TTS display a reorganization of cortical and subcortical networks, including areas associated with the emotional response and autonomic regulation. The findings tend to support the hypothesis that a deregulation of autonomic control at the central level plays a significant role in this syndrome.

Graph Theory Analysis of Functional Connectivity in Major Depression Disorder With High-Density Resting State EEG Data

Existing studies have shown functional brain networks in patients with major depressive disorder (MDD) have abnormal network topology structure. But the methods to construct brain network still exist some issues to be solved. This paper is to explore reliable and robust construction methods of functional brain network using different coupling methods and binarization approaches, based on high-density 128-channel resting state EEG recordings from 16 MDD patients and 16 normal controls (NC). It was found that the combination of imaginary part of coherence and cluster-span threshold outperformed other methods. Based on this combination, right hemisphere function deficiency, symmetry breaking and randomized network structure were found in MDD, which confirmed that MDD had aberrant cognitive processing. Furthermore, clustering coefficient in left central region in theta band and node betweenness centrality in right temporal region in alpha band were significantly negatively correlated with depressive level. And these network metrics had the ability to discriminate MDD from NC, which indicated that these network metrics might be served as the electrophysiological characteristics for probable MDD identification. Hence, this paper may provide reliable methods to construct functional brain network and offer potential biomarkers in MDD.

Abnormal resting state activity of left middle occipital gyrus and its functional connectivity in female patients with major depressive disorder

BACKGROUND

Women are more susceptible to major depressive disorder (MDD). A possible explanation is that women have a trait tendency to engage in a ruminative response style. Depending on cognitive model of depression, attention bias, memory bias and self-referential bias were closely related among depressed patients. Previous studies have explored the neural mechanism of the cognitive biases by using amplitude of low frequency fluctuations (ALFF) or functional connectivity (FC), and few combined these two metrics, especially focusing on female patients.

METHODS

We assessed 25 female patients diagnosed with MDD and 13 well matched healthy controls (HCs) using Rs-fMRI. Two metrics ALFF and FC based on abnormal ALFF were explored and made comparisons.

RESULTS

Compared with HCs, female patients with MDD showed that one cluster with significantly decreased ALFF in the left middle occipital gyrus(L-MOG). Furtherly we founded depressed female subjects showed significantly lower FC between the L-MOG seed and left orbitofrontal cortex, and significantly higher FC between the L-MOG seed and left medial prefrontal gyrus and left hippocampus.

CONCLUSIONS

Our results showed L-MOG may act as a connection, which involved in the processing of cognitive biases of MDD by connected with limbic-cortical regions in resting state. These findings may enhance the understanding of the neurobiological mechanism in female patients with MDD.

Structural and functional alterations of the suicidal brain: An updated review of neuroimaging studies

Brain imaging is a non-invasive and in vivo direct estimation of detailed brain structure, regional brain functioning and estimation of molecular processes in the brain. The main objective of this review was to analyze functional and structural neuroimaging studies of individuals at risk for suicide. We reviewed articles published between 2005 and 2018, indexed in PubMed and Medline, assessing structural and functional alterations of the brain of individuals at high risk for suicide and at low risk for suicide. We reviewed functional and structural neuroimaging studies which included individuals with a history of suicidal ideation or attempt in major depressive disorder (MDD), bipolar disorder (BD), psychosis, and borderline personality disorder (BPD). We selected 45 papers that focused on suicidality in MDD, 17 papers on BD, 11 papers on psychosis, and 5 papers on BPD. The suicidal brain across psychiatric diagnoses seems to heavily involve dysfunction of the fronto-temporal network, primarily involving reductions of gray and white matter volumes in the pre-frontal cortex (PFC), anterior cingulate, and superior temporal gyrus. Nonetheless, there are several ways to define suicidal behaviour and ideation. Therefore, it still remains difficult to combine the evidence from imaging studies that used different definitions of suicidality.

The dynamic characteristics of the anterior cingulate cortex in resting-state fMRI of patients with depression

BACKGROUND

The anterior cingulate cortex (ACC) is part of the limbic system of the brain. It is a bridge between attentional and emotional processing, which is responsible for the integration of visceral, attentional, and affective information. Lesioning of the ACC, which produces striking changes, is used to treat major depression disorder (MDD). Moreover, the brain dynamically integrates and coordinates functions of its different subparts to realize its cognitive capability. Hence, the spatio-temporal community distribution of the ACC is necessary to completely understand MDD.

METHODS

First, community structure detection was used to reveal the community distribution of brain regions. Thereafter, the flexibility, i.e., the frequency of community assignment changes of the ACC in such a community, and the module allegiance matrix (MAM) between the ACC and other brain regions, were analyzed.

RESULTS

Our analysis demonstrated significant differences in the distribution of community assignment and flexibility of the ACC in MDD, compared to healthy controls (HC). The results also showed that the pairwise values of the MAMs between the ACC and the amygdala, insula, precuneus, and thalamus were significantly lower in patients with MDD compared to those in HC.

LIMITATIONS

The data collected is subject to patient-specific noise because (1) the medication effect varies from patient to patient, and (2) with most fMRI studies, the thoughts of the participants during imaging are difficult to control.

CONCLUSION

ACC exhibits abnormal flexibility in community structures in MDD. The pairwise abnormal entries in the MAM for the ACC with four other brain regions, i.e., amygdala, insula, precuneus, and thalamus, quantified the role played by the ACC in MDD.