Altered functional connectivity of right inferior frontal gyrus subregions in bipolar disorder: a resting state fMRI study

Local brain abnormalities in emotional disorders: Evidence from resting state fMRI studies

Emotional disorders inflict an enormous burden on society. Research on brain abnormalities implicated in emotional disorders has witnessed great progress over the past decades. Using cross-sectional and longitudinal designs, resting state functional magnetic resonance imaging (rs-fMRI) and its analytic approaches have been applied to characterize the local properties of patients with emotional disorders. Additionally, brain activity alterations of emotional disorders have shown frequency-specific. Despite the gains in understanding the roles of brain abnormalities in emotional disorders, the limitation of the small sample size needs to be highlighted. Lastly, we proposed that evidence from the positive psychology research stream presents it as a viable discipline, whose suggestions could be developed in future emotional disorders research. Such interdisciplinary research may produce novel treatments and intervention options. This article is categorized under: Psychology > Brain Function and Dysfunction.

The amplitude of low-frequency fluctuations is correlated with birth trauma in patients with postpartum post-traumatic stress disorder

Postpartum post-traumatic stress disorder (PP-PTSD) is a severe mental disorder worldwide. In recent years, some studies have reported that PP-PTSD stems from birth trauma. The present study was dedicated in finding ways to predict the occurrence of emergency caesarean section (ECS), trying to analyze the methods to reduce incidence of PP-PTSD on this basis, further exploring the neuroimaging changes in PP-PTSD. A total of 245 primiparas with intention of vaginal delivery were recruited. The internal tocodynamometry measurement was performed during labor for all mothers, and respectively taken at 3-5 cm, 5-8 cm, and 8-10 cm of cervical dilation. The receiver operating characteristic (ROC) curve and Binary logistic regression analyses were also performed to identify fetal head descending thrust that might help in the prediction of ECS. Resting-state magnetic resonance imaging (MRI) was performed on 26 patients diagnosed with PP-PTSD of 245 mothers, the amplitude of low-frequency fluctuations (ALFF) technology was used to observe the spontaneous neural activity of all PP-PTSD patients and correlation analyses were performed. We found that the natural delivery rate of mothers with fetal head descending thrust <16.29 N (5-8 cm), 26.36 N (8-10 cm) were respectively lower than other mothers with fetal head descending thrust ≥16.29 N (5-8 cm), 26.36 N (8-10 cm) (P < 0.05). The ROC curve analysis showed that the area under the receiver operating characteristic curve (AUC) value of thrust (5-8 cm) was 0.896 (95% CI: 0.854-0.938, p < 0.001), AUC of thrust(8-10 cm) was 0.786 (95% CI: 0.714-0.858, p < 0.001), which showed strong potential for predicting ECS. In addition, the Binary logistic regression analysis showed thrust (5-8 cm) and thrust (8-10 cm) were independent correlates of ECS. The resting-state functional magnetic resonance imaging (rs-fMRI) results indicated that PP-PTSD group showed decreased ALFF in the bilateral insula cortex (IC), right anterior cingulate cortex (ACC), and left midcingulate cortex (MCC) compared with healthy postpartum women (HPW) (false discovery rate (FDR) correction q-value < 0.05). The ALFF value of the right ACC was positively correlated with the Perinatal Post-traumatic stress disorder Questionnaire (PPQ) score (r = 0.4046 p = 0.0403) and Posttraumatic Stress Disorder Checklist-Civilian Version (PCL-C) score (r = 0.3909 p = 0.0483). The internal tocodynamometry measurement can serve as a predictive tool for ECS, on this basis, the implementation of effective emotional support may help to reduce the incidence of PP-PTSD. Besides, this study has verified the presence of altered ALFF in the brain regions of PP-PTSD patients, mainly involving the bilateral IC, right ACC, and left MCC, that might be associated with emotion, cognition, and memory disorders functions in PP-PTSD patients.

Harsh, unpredictable childhood environments are associated with inferior frontal gyrus connectivity and binge eating tendencies in late adolescents

Harsh, unpredictable childhood environments (HUCE) are associated with obesity older in life, but knowledge of how HUCE affect binge eating tendencies is lacking. Five hundred and one late adolescents aged 16-22 were recruited to finish resting state functional magnetic resonance imaging scan, behavioral measures including retrospective recall of childhood environmental harshness and unpredictability, binge eating tendencies and demographics. Three hundred and seventy-six of participants further completed the computerized visual probe task designed to evaluate attentional engagement towards high and low calorie food. As right inferior frontal gyrus (IFG) was the key nodes that related to both early life adversity and binge eating tendencies, it was treated as the interest region in the dynamic functional connectivity analyses. Results found that HUCE are associated with significant but modest decreases in connectivity of right inferior frontal gyrus (IFG)- bilateral medial frontal gyrus, right IFG - bilateral inferior parietal lobule (IPL), and right IFG - left superior frontal gyrus connectivity, as well as attentional engagement to high-calorie food and binge eating tendencies. A machine-learning method named linear support vector regression (SVR) and leave one out cross-validation (LOOCV) procedure used to examine the robustness of the brain-behavior relationship further confirm the findings. Mediation analyses suggested that right IFG - left IPL connectivity mediates the association of HUCE and binge eating tendencies. Findings suggest right IFG - left IPL connectivity may serve as a crucial neurobiological underpinning of HUCE to regulate binge eating behaviors. As such, these results contribute to a novel perspective and hypotheses in elucidating developmental neuro-mechanisms related to binge eating.

Beta-informativeness-diffusion multilayer graph embedding for brain network analysis

Brain network analysis provides essential insights into the diagnosis of brain disease. Integrating multiple neuroimaging modalities has been demonstrated to be more effective than using a single modality for brain network analysis. However, a majority of existing brain network analysis methods based on multiple modalities often overlook both complementary information and unique characteristics from various modalities. To tackle this issue, we propose the Beta-Informativeness-Diffusion Multilayer Graph Embedding (BID-MGE) method. The proposed method seamlessly integrates structural connectivity (SC) and functional connectivity (FC) to learn more comprehensive information for diagnosing neuropsychiatric disorders. Specifically, a novel beta distribution mapping function (beta mapping) is utilized to increase vital information and weaken insignificant connections. The refined information helps the diffusion process concentrate on crucial brain regions to capture more discriminative features. To maximize the preservation of the unique characteristics of each modality, we design an optimal scale multilayer brain network, the inter-layer connections of which depend on node informativeness. Then, a multilayer informativeness diffusion is proposed to capture complementary information and unique characteristics from various modalities and generate node representations by incorporating the features of each node with those of their connected nodes. Finally, the node representations are reconfigured using principal component analysis (PCA), and cosine distances are calculated with reference to multiple templates for statistical analysis and classification. We implement the proposed method for brain network analysis of neuropsychiatric disorders. The results indicate that our method effectively identifies crucial brain regions associated with diseases, providing valuable insights into the pathology of the disease, and surpasses other advanced methods in classification performance.

Brain functional changes across mood states in bipolar disorder: from a large-scale network perspective

BACKGROUND

Exploring the neural basis related to different mood states is a critical issue for understanding the pathophysiology underlying mood switching in bipolar disorder (BD), but research has been scarce and inconsistent.

METHODS

Resting-state functional magnetic resonance imaging data were acquired from 162 patients with BD: 33 (hypo)manic, 64 euthymic, and 65 depressive, and 80 healthy controls (HCs). The differences of large-scale brain network functional connectivity (FC) between the four groups were compared and correlated with clinical characteristics. To validate the generalizability of our findings, we recruited a small longitudinal independent sample of BD patients (n = 11). In addition, we examined topological nodal properties across four groups as exploratory analysis.

RESULTS

A specific strengthened pattern of network FC, predominantly involving the default mode network (DMN), was observed in (hypo)manic patients when compared with HCs and bipolar patients in other mood states. Longitudinal observation revealed an increase in several network FCs in patients during (hypo)manic episode. Both samples evidenced an increase in the FC between the DMN and ventral attention network, and between the DMN and limbic network (LN) related to (hypo)mania. The altered network connections were correlated with mania severity and positive affect. Bipolar depressive patients exhibited decreased FC within the LN compared with HCs. The exploratory analysis also revealed an increase in degree in (hypo)manic patients.

CONCLUSIONS

Our findings identify a distributed pattern of large-scale network disturbances in the unique context of (hypo)mania and thus provide new evidence for our understanding of the neural mechanism of BD.

Enhanced Dynamic Laterality Based on Functional Subnetworks in Patients with Bipolar Disorder

An ocean of studies have pointed to abnormal brain laterality changes in patients with bipolar disorder (BD). Determining the altered brain lateralization will help us to explore the pathogenesis of BD. Our study will fill the gap in the study of the dynamic changes of brain laterality in BD patients and thus provide new insights into BD research. In this work, we used fMRI data from 48 BD patients and 48 normal controls (NC). We constructed the dynamic laterality time series by extracting the dynamic laterality index (DLI) at each sliding window. We then used k-means clustering to partition the laterality states and the Arenas-Fernandez-Gomez (AFG) community detection algorithm to determine the number of states. We characterized subjects' laterality characteristics using the mean laterality index (MLI) and laterality fluctuation (LF). Compared with NC, in all windows and state 1, BD patients showed higher MLI in the attention network (AN) of the right hemisphere, and AN in the left hemisphere showed more frequent laterality fluctuations. AN in the left hemisphere of BD patients showed higher MLI in all windows and state 3 compared to NC. In addition, in the AN of the right hemisphere in state 1, higher MLI in BD patients was significantly associated with patient symptoms. Our study provides new insights into the understanding of BD neuropathology in terms of brain dynamic laterality.

Intrinsic functional connectivity correlates of cognitive deficits involving sustained attention and executive function in bipolar disorder

BACKGROUND

The neural correlate of cognitive deficits in bipolar disorder (BD) is an issue that warrants further investigation. However, relatively few studies have examined the intrinsic functional connectivity (FC) underlying cognitive deficits involving sustained attention and executive function at both the region and network levels, as well as the different relationships between connectivity patterns and cognitive performance, in BD patients and healthy controls (HCs).

METHODS

Patients with BD (n = 59) and HCs (n = 52) underwent structural and resting-state functional magnetic resonance imaging and completed the Wisconsin Card Sorting Test (WCST), the continuous performance test and a clinical assessment. A seed-based approach was used to evaluate the intrinsic FC alterations in three core neurocognitive networks (the default mode network [DMN], the central executive network [CEN] and the salience network [SN]). Finally, we examined the relationship between FC and cognitive performance by using linear regression analyses.

RESULTS

Decreased FC was observed within the DMN, in the DMN-SN and DMN-CEN and increased FC was observed in the SN-CEN in BD. The alteration direction of regional FC was consistent with that of FC at the brain network level. Decreased FC between the left posterior cingulate cortex and right anterior cingulate cortex was associated with longer WCST completion time in BD patients (but not in HCs).

CONCLUSIONS

These findings emphasize the dominant role of the DMN in the psychopathology of BD and provide evidence that cognitive deficits in BD may be associated with aberrant FC between the anterior and posterior DMN.

Evidence of functional abnormalities in the default mode network in bipolar depression: A coordinate-based activation likelihood estimation meta-analysis

BACKGROUND

The default mode network (DMN) is thought to be involved in the pathophysiology of bipolar depression (BD). However, the findings of prior studies on DMN alterations in BD are inconsistent. Thus, this study aimed to systematically investigate functional abnormalities of the DMN in BD patients.

METHODS

We systematically searched PubMed, Ovid, and Web of Science for functional neuroimaging studies on regional homogeneity, amplitude of low frequency fluctuations (ALFF), and functional connectivity of the DMN in BD patients published before March 18, 2022. The stereotactic coordinates of the reported altered brain regions were extracted and incorporated into a brain map using the coordinate-based activation likelihood estimation approach.

RESULTS

A total of 43 original research studies were included in the meta-analysis. BD patients showed specific changes in the DMN including decreased ALFF/fractional ALFF in the left cingulate gyrus (CG) and bilateral precuneus (PCUN); increased functional connectivity (FC) in the left CG, left posterior CG, left PCUN, bilateral medial frontal gyrus, and bilateral superior frontal gyrus; and decreased FC in the left CG, left PCUN, left inferior parietal lobule, and left postcentral gyrus.

LIMITATIONS

Conclusions are limited by the small number of studies, additional meta-analyses are needed to obtain more data in BD subgroup.

CONCLUSION

This meta-analysis supports specific changes in DMN activity and FC in BD patients, which may be powerful biomarkers for the diagnosis of BD. The CG and PCUN were the most affected regions and are thus potential targets for clinical interventions to delay BD progression.

Predicting depressed and elevated mood symptomatology in bipolar disorder using brain functional connectomes

BACKGROUND

The study is aimed to identify brain functional connectomes predictive of depressed and elevated mood symptomatology in individuals with bipolar disorder (BD) using the machine learning approach Connectome-based Predictive Modeling (CPM).

METHODS

Functional magnetic resonance imaging data were obtained from 81 adults with BD while they performed an emotion processing task. CPM with 5000 permutations of leave-one-out cross-validation was applied to identify functional connectomes predictive of depressed and elevated mood symptom scores on the Hamilton Depression and Young Mania rating scales. The predictive ability of the identified connectomes was tested in an independent sample of 43 adults with BD.

RESULTS

CPM predicted the severity of depressed [concordance between actual and predicted values (r = 0.23, pperm (permutation test) = 0.031) and elevated (r = 0.27, pperm = 0.01) mood. Functional connectivity of left dorsolateral prefrontal cortex and supplementary motor area nodes, with inter- and intra-hemispheric connections to other anterior and posterior cortical, limbic, motor, and cerebellar regions, predicted depressed mood severity. Connectivity of left fusiform and right visual association area nodes with inter- and intra-hemispheric connections to the motor, insular, limbic, and posterior cortices predicted elevated mood severity. These networks were predictive of mood symptomatology in the independent sample (r ⩾ 0.45, p = 0.002).

CONCLUSIONS

This study identified distributed functional connectomes predictive of depressed and elevated mood severity in BD. Connectomes subserving emotional, cognitive, and psychomotor control predicted depressed mood severity, while those subserving emotional and social perceptual functions predicted elevated mood severity. Identification of these connectome networks may help inform the development of targeted treatments for mood symptoms.

Consequences of General Anesthesia in Infancy on Behavior and Brain Structure

BACKGROUND

One in 7 children will need general anesthesia (GA) before the age of 3. Brain toxicity of anesthetics is controversial. Our objective was to clarify whether exposure of GA to the developing brain could lead to lasting behavioral and structural brain changes.

METHODS

A first study was performed in mice. The behaviors (fear conditioning, Y-maze, and actimetry) and brain anatomy (high-resolution magnetic resonance imaging) of 6- to 8-week-old Swiss mice exposed or not exposed to GA from 4 to 10 days old were evaluated. A second study was a complementary analysis from the preexisting APprentissages EXécutifs et cerveau chez les enfants d'âge scolaire (APEX) cohort to assess the replicability of our data in humans. The behaviors (behavior rating inventory of executive function, emotional control, and working memory score, Backward Digit Span, and Raven 36) and brain anatomy (high-resolution magnetic resonance imaging) were compared in 102 children 9 to 10 years of age exposed or not exposed to a single GA (surgery) during infancy.

RESULTS

The animal study revealed chronic exacerbated fear behavior in the adult mice (95% confidence interval [CI], 4-80; P = .03) exposed to postnatal GA; this was associated with an 11% (95% CI, 7.5-14.5) reduction of the periaqueductal gray matter (P = .046). The study in humans suggested lower emotional control (95% CI, 0.33-9.10; P = .06) and a 6.1% (95% CI, 4.3-7.8) reduction in the posterior part of the right inferior frontal gyrus (P = .019) in the children who had been exposed to a single GA procedure.

CONCLUSIONS

The preclinical and clinical findings of these independent studies suggest lasting effects of early life exposure to anesthetics on later emotional control behaviors and brain structures.

The atypical functional connectivity of Broca's area at multiple frequency bands in autism spectrum disorder

As a developmental disorder, autism spectrum disorder (ASD) has drawn much attention due to its severe impacts on one's language capacity. Broca's area, an important brain region of the language network, is largely involved in language-related functions. Using the Autism Brain Image Data Exchange (ABIDE) dataset, a mega-analysis was performed involving a total of 1454 participants (including 618 individuals with ASD and 836 healthy controls (HCs). To detect the neural pathophysiological mechanism of ASD from the perspective of language, we conducted a functional connectivity (FC) analysis with Broca's area as the seed in multiple frequency bands (conventional: 0.01-0.08 Hz; slow-4: 0.027-0.073 Hz; slow-5: 0.01-0.027 Hz). We found that compared with HC, ASD patients demonstrated increased FC in the left thalamus, left precuneus, left anterior cingulate and paracingulate gyri, and left medial orbital of the superior frontal gyrus in the conventional frequency band (0.01-0.08 Hz). The results of the slow-5 frequency band (0.01-0.027 Hz) presented increased FC values of the left precuneus, left medial orbital of the superior frontal gyrus, right medial orbital of the superior frontal gyrus and right thalamus. No significant cluster was detected in the slow-4 frequency band (0.027-0.073 Hz). In conclusion, the abnormal functional connectivity in patients with ASD has frequency-specific properties. Furthermore, the slow-5 frequency band (0.01-0.027 Hz) mainly contributed to the findings of the conventional frequency band (0.01-0.08 Hz). The current study might shed new light on the neural pathophysiological mechanism of language impairments in people with ASD.

Altered frequency-specific/universal amplitude characteristics of spontaneous brain oscillations in patients with bipolar disorder

The human brain is a dynamic system with intrinsic oscillations in spontaneous neural activity. Whether the dynamic characteristics of these spontaneous oscillations are differentially altered across different frequency bands in patients with bipolar disorder (BD) remains unclear. This study recruited 65 patients with BD and 85 healthy controls (HCs). The entire frequency range of resting-state fMRI data was decomposed into four frequency intervals. Two-way repeated-measures ANCOVA was employed to detect frequency-specific/universal alterations in the dynamic oscillation amplitude in BD. The patients were then divided into two subgroups according to their mood states to explore whether these alterations were independent of their mood states. Finally, other window sizes, step sizes, and window types were tested to replicate all analyses. Frequency-specific abnormality of the dynamic oscillation amplitude was detected within the posterior medial parietal cortex (centered at the precuneus extending to the posterior cingulate cortex). This specific profile indicates decreased amplitudes in the lower frequency bands (slow-5/4) and no amplitude changes in the higher frequency bands (slow-3/2) compared with HCs. Frequency-universal abnormalities of the dynamic oscillation amplitude were also detectable, indicating increased amplitudes in the thalamus and left cerebellum anterior lobe but decreased amplitudes in the medial superior frontal gyrus. These alterations were independent of the patients' mood states and replicable across multiple analytic and parametric settings. In short, frequency-specific/universal amplitude characteristics of spontaneous oscillations were observed in patients with BD. These abnormal characteristics have important implications for specific functional changes in BD from multiple frequency and dynamic perspectives.

Altered dynamic amplitude of low-frequency fluctuation between bipolar type I and type II in the depressive state

BACKGROUND

Bipolar disorder is a chronic and highly recurrent mental disorder that can be classified as bipolar type I (BD I) and bipolar type II (BD II). BD II is sometimes taken as a milder form of BD I or even doubted as an independent subtype. However, the fact that symptoms and severity differ in patients with BD I and BD II suggests different pathophysiologies and underlying neurobiological mechanisms. In this study, we aimed to explore the shared and unique functional abnormalities between subtypes.

METHODS

The dynamic amplitude of low-frequency fluctuation (dALFF) was performed to compare 31 patients with BD I, 32 with BD II, and 79 healthy controls (HCs). Global dALFF was calculated using sliding-window analysis. Group differences in dALFF among the 3 groups were compared using analysis of covariance (ANCOVA), with covariates of age, sex, years of education, and mean FD, and Bonferroni correction was applied for post hoc analysis. Pearson and Spearman's correlations were conducted between clusters with significant differences and clinical features in the BD I and BD II groups, after which false error rate (FDR) was used for correction.

RESULTS

We found a significant decrease in dALFF values in BD patients compared with HCs in the following brain regions: the bilateral-side inferior frontal gyrus (including the triangular, orbital, and opercular parts), inferior temporal gyrus, the medial part of the superior frontal gyrus, middle frontal gyrus, anterior cingulum, insula gyrus, lingual gyrus, calcarine gyrus, precuneus gyrus, cuneus gyrus, left-side precentral gyrus, postcentral gyrus, inferior parietal gyrus, superior temporal pole gyrus, middle temporal gyrus, middle occipital gyrus, superior occipital gyrus and right-side fusiform gyrus, parahippocampal gyrus, hippocampus, middle cingulum, orbital part of the medial frontal gyrus and superior frontal gyrus. Unique alterations in BD I were observed in the right-side supramarginal gyrus and postcentral gyrus. In addition, dALFF values in BD II were significantly higher than those in BD I in the right superior temporal gyrus and middle temporal gyrus. The variables of dALFF correlated with clinical characteristics differently according to the subtypes, but no correlations survived after FDR correction.

LIMITATIONS

Our study was cross-sectional. Most of our patients were on medication, and the sample was limited.

CONCLUSIONS

Our findings demonstrated neurobiological characteristics of BD subtypes, providing evidence for BD II as an independent existence, which could be the underlying explanation for the specific symptoms and/or severity and point to potential biomarkers for the differential diagnosis of bipolar subtypes.

The alterations of brain functional connectivity networks in major depressive disorder detected by machine learning through multisite rs-fMRI data

BACKGROUND

The current diagnosis of major depressive disorder (MDD) is mainly based on the patient's self-report and clinical symptoms. Machine learning methods are used to identify MDD using resting-state functional magnetic resonance imaging (rs-fMRI) data. However, due to large site differences in multisite rs-fMRI data and the difficulty of sample collection, most of the current machine learning studies use small sample sizes of rs-fMRI datasets to detect the alterations of functional connectivity (FC) or network attribute (NA), which may affect the reliability of the experimental results.

METHODS

Multisite rs-fMRI data were used to increase the size of the sample, and then we extracted the functional connectivity (FC) and network attribute (NA) features from 1611 rs-fMRI data (832 patients with MDD (MDDs) and 779 healthy controls (HCs)). ComBat algorithm was used to harmonize the data variances caused by the multisite effect, and multivariate linear regression was used to remove age and sex covariates. Two-sample t-test and wrapper-based feature selection methods (support vector machine recursive feature elimination with cross-validation (SVM-RFECV) and LightGBM's "feature_importances_" function) were used to select important features. The Shapley additive explanations (SHAP) method was used to assign the contribution of features to the best classification effect model.

RESULTS

The best result was obtained from the LinearSVM model trained with the 136 important features selected by SVMRFE-CV. In the nested five-fold cross-validation (consisting of an outer and an inner loop of five-fold cross-validation) of 1611 data, the model achieved the accuracy, sensitivity, and specificity of 68.90 %, 71.75 %, and 65.84 %, respectively. The 136 important features were tested in a small dataset and obtained excellent classification results after balancing the ratio between patients with depression and HCs.

CONCLUSIONS

The combined use of FC and NA features is effective for classifying MDDs and HCs. The important FC and NA features extracted from the large sample dataset have some generalization performance and may be used as a reference for the altered brain functional connectivity networks in MDD.

Convergent functional changes of the episodic memory impairment in mild cognitive impairment: An ALE meta-analysis

Background

Mild cognitive impairment (MCI) is considered to be an intermediate stage between normal aging and Alzheimer's disease (AD). The earliest and most common symptom of MCI is impaired episodic memory. When episodic memory is impaired in MCI patients, specific functional changes occur in related brain areas. However, there is currently a lack of a unified conclusion on this change. Therefore, the purpose of this meta-analysis is to find MRI-specific functional changes in episodic memory in MCI patients.

Methods

Based on three commonly used indicators of brain function: functional connectivity (FC), the amplitude of low-frequency fluctuation /fractional amplitude of low-frequency fluctuation (ALFF/fALFF), and regional homogeneity (ReHo), we systematically searched PubMed, Web of Science and Ovid related literature and conducted the strict screening. Then we use the activation likelihood estimation (ALE) algorithm to perform the coordinate-based meta-analysis.

Results

Through strict screening, this meta-analysis finally included 21 related functional neuroimaging research articles. The final result displays that functional changes of episodic memory in MCI patients are mainly located in the parahippocampal gyrus, precuneus, posterior cingulate gyrus, cuneus, middle temporal gyrus, middle frontal gyrus, lingual gyrus, and thalamus.

Conclusions

There are specific functional changes in episodic memory brain regions in MCI patients, and the brain functional network can regulate episodic memory through these brain regions. And these specific changes can assist in the early diagnosis of MCI, providing new ideas and directions for early identification and intervention in the process of MCI.

Resting-state fMRI in depressive and (hypo)manic mood states in bipolar disorders: A systematic review

OBJECTIVE

Abnormalities in spontaneous brain activity, measured with resting-state functional magnetic resonance imaging (rs-fMRI), may be key biomarkers for bipolar disorders. This systematic review compares rs-fMRI findings in people experiencing a bipolar depressive or (hypo)manic episode to bipolar euthymia and/or healthy participants.

METHODS

Medline, Web of Science and Embase were searched up until April 2021. Studies without control group, or including minors, neurological co-morbidities or mixed episodes, were excluded. Qualitative synthesis was used to report results and risk of bias was assessed using the National Heart, Lung and Blood Institute tool for case-control studies.

RESULTS

Seventy-one studies were included (3167 bipolar depressed/706 (hypo)manic). In bipolar depression, studies demonstrated default-mode (DMN) and frontoparietal network (FPN) dysfunction, altered baseline activity in the precuneus, insula, striatum, cingulate, frontal and temporal cortex, and disturbed regional homogeneity in parietal, temporal and pericentral areas. Functional connectivity was altered in thalamocortical circuits and between the cingulate cortex and precuneus. In (hypo)mania, studies reported altered functional connectivity in the amygdala, frontal and cingulate cortex. Finally, rs-fMRI disturbances in the insula and putamen correlate with depressive symptoms, cerebellar resting-state alterations could evolve with disease progression and altered amygdala connectivity might mediate lithium effects.

CONCLUSIONS

Our results suggest DMN and FPN dysfunction in bipolar depression, whereas local rs-fMRI alterations might differentiate mood states. Future studies should consider controlling rs-fMRI findings for potential clinical confounding factors such as medication. Considerable heterogeneity of methodology between studies limits conclusions. Standardised clinical reporting and consistent analysis approaches would increase coherence in this promising field.

Altered regional brain activity and functional connectivity patterns in major depressive disorder: A function of childhood trauma or diagnosis?

Childhood trauma (CT) is a non-specific risk factor for major depressive disorder (MDD). However, the neurobiological mechanisms of MDD with CT remain unclear. In the present study, we sought to determine the specific brain regions associated with CT and MDD etiology. Fractional amplitude of low-frequency fluctuation (fALFF) and functional connectivity (FC) analyses were performed to assess alterations of intrinsic brain activity in MDD with CT, MDD without CT, healthy controls with CT, and healthy controls without CT. Two-by-two factorial analyses were performed to examine the effects of the factors "MDD" and "CT" on fALFF and FC. Moderator analysis was used to explore whether the severity of depression moderated the relationship between CT and aberrant fALFF. We found that the etiological effects of MDD and CT exhibited negative impacts on brain dysfunction including altered fALFF in the left postcentral gyrus, left lingual gyrus, left paracentral lobule (PCL), and left cuneus. Decreased FC was observed in the following regions: (i) the left lingual gyrus seed and the left fusiform gyrus as well as the right calcarine cortex; (ii) the left PCL seed and the left supplementary motor area, left calcarine cortex, left precentral gyrus, and right cuneus; (iii) the left postcentral gyrus seed and left superior parietal lobule, right postcentral gyrus, and left precentral gyrus. Furthermore, the severity of depression acted as a moderator in the relationship between CT and aberrant fALFF in the left PCL. These data indicate that MDD patients with and without trauma exposure are clinically and neurobiologically distinct.

Diurnal mood variation symptoms in major depressive disorder associated with evening chronotype: Evidence from a neuroimaging study

BACKGROUND

Major depressive disorder (MDD) is often accompanied with classic diurnal mood variation (DMV) symptoms. Patients with DMV symptoms feel a mood improvement and prefer activities at dusk or in the evening, which is consistent with the evening chronotype. Their neural alterations are unclear. In this study, we aimed to explore the neuropathological mechanisms underlying the circadian rhythm of mood and the association with chronotype in MDD.

METHODS

A total of 126 depressed patients, including 48 with DMV, 78 without, and 67 age/gender-matched healthy controls (HC) were recruited and underwent a resting-state functional magnetic resonance imaging. Spontaneous neural activity was investigated using amplitude of low-frequency fluctuation (ALFF) and region of interest (ROI)-based functional connectivity (FC) analyses were conducted. The Morningness-Eveningness Questionnaire (MEQ) was utilized to evaluate participant chronotypes and Pearson correlations were calculated between altered ALFF/FC values and MEQ scores in patients with MDD.

RESULTS

Compared with NMV, DMV group exhibited lower MEQ scores, and increased ALFF values in the right orbital superior frontal gyrus (oSFG). We observed that increased FC between the left suprachiasmatic nucleus (SCN) and supramarginal gyrus (SMG). ALFF in the oSFG and FC of rSCN-SMG were negatively correlated with MEQ scores.

LIMITATION

Some people's chronotypes information is missing.

CONCLUSION

Patients with DMV tended to be evening type and exhibited abnormal brain functions in frontal lobes. The synergistic changes between frontotemporal lobe, SCN-SMG maybe the characteristic of patients with DMV symptoms.

The colors of our brain: an integrated approach for dimensionality reduction and explainability in fMRI through color coding (i-ECO)

Several systematic reviews have highlighted the role of multiple sources in the investigation of psychiatric illness. For what concerns fMRI, the focus of recent literature preferentially lies on three lines of research, namely: functional connectivity, network analysis and spectral analysis. Data was gathered from the UCLA Consortium for Neuropsychiatric Phenomics. The sample was composed by 130 neurotypicals, 50 participants diagnosed with Schizophrenia, 49 with Bipolar disorder and 43 with ADHD. Single fMRI scans were reduced in their dimensionality by a novel method (i-ECO) averaging results per Region of Interest and through an additive color method (RGB): local connectivity values (Regional Homogeneity), network centrality measures (Eigenvector Centrality), spectral dimensions (fractional Amplitude of Low-Frequency Fluctuations). Average images per diagnostic group were plotted and described. The discriminative power of this novel method for visualizing and analyzing fMRI results in an integrative manner was explored through the usage of convolutional neural networks. The new methodology of i-ECO showed between-groups differences that could be easily appreciated by the human eye. The precision-recall Area Under the Curve (PR-AUC) of our models was > 84.5% for each diagnostic group as evaluated on the test-set – 80/20 split. In conclusion, this study provides evidence for an integrative and easy-to-understand approach in the analysis and visualization of fMRI results. A high discriminative power for psychiatric conditions was reached. This proof-of-work study may serve to investigate further developments over more extensive datasets covering a wider range of psychiatric diagnoses.

Default-mode and fronto-parietal network connectivity during rest distinguishes asymptomatic patients with bipolar disorder and major depressive disorder

Bipolar disorder (BD) is commonly misdiagnosed as major depressive disorder (MDD). This is understandable, as depression often precedes mania and is otherwise indistinguishable in both. It is therefore imperative to identify neural mechanisms that can differentiate the two disorders. Interrogating resting brain neural activity may reveal core distinguishing abnormalities. We adopted an a priori approach, examining three key networks documented in previous mood disorder literature subserving executive function, salience and rumination that may differentiate euthymic BD and MDD patients. Thirty-eight patients with BD, 39 patients with MDD matched for depression severity, and 39 age-gender matched healthy controls, completed resting-state fMRI scans. Seed-based and data-driven Independent Component analyses (ICA) were implemented to examine group differences in resting-state connectivity (pFDR < 0.05). Seed analysis masks were target regions identified from the fronto-parietal (FPN), salience (SN) and default-mode (DMN) networks. Seed-based analyses identified significantly greater connectivity between the subgenual cingulate cortex (DMN) and right dorsolateral prefrontal cortex (FPN) in BD relative to MDD and controls. The ICA analyses also found greater connectivity between the DMN and inferior frontal gyrus, an FPN region in BD relative to MDD. There were also significant group differences across the three networks in both clinical groups relative to controls. Altered DMN-FPN functional connectivity is thought to underlie deficits in the processing, management and regulation of affective stimuli. Our results suggest that connectivity between these networks could potentially distinguish the two disorders and could be a possible trait mechanism in BD persisting even in the absence of symptoms.

Inferior frontal gyrus seed-based resting-state functional connectivity and sustained attention across manic/hypomanic, euthymic and depressive phases of bipolar disorder

OBJECTIVE

Seed-based resting-state functional connectivity (rs-FC) of inferior frontal gyrus (IFG), as well as sustained attention cognitive deficit are consistently reported to be impaired in bipolar disorders. However, whether these deficits exist across mood states and euthymic state are lacking. We compared rs-FC of IFG and sustained attention of bipolar patients in (hypo) mania, depression and euthymia, with controls. We also explored the interrelationships between clinical, cognitive, and imaging measurements.

METHODS

Participants included 110 bipolar subjects: 46 manic/hypomanic, 35 euthymic, and 29 depressed, matched with 41 healthy controls (HCs) underwent structural magnetic resonance imaging (MRI) and resting-state functional MRI scans. Seed-based functional connectivity analyses were performed focused on bilateral IFG seeds. Clinical symptoms and sustained attention function were measured. Stepwise linear regression analysis was conducted to explore predictors of sustained attention measurements.

RESULTS

Increased rs-FC between right IFG and bilateral frontal pole/superior frontal gyrus, precuneus, and posterior cingulate gyrus, as well as decreased rs-FC between right IFG and sensorimotor areas, anterior middle cingulate gyrus were found in all three bipolar subgroups compared with HCs. Impaired sustained attention measurement was found in bipolar manic/hypomanic and depressive subgroups compared with HCs. Linear regression analyses revealed a significant impact of the manic symptoms and psychotic symptoms on the performance of sustained attention task.

CONCLUSIONS

Our results revealed that IFG seed-based resting-state functional networks involved in emotion regulation and cognitive function were trait-like deficit in bipolar patients. Higher manic levels and psychotic symptoms were predictors of a worse sustained attention performance.

Altered Regional Cerebral Blood Flow and Brain Function Across the Alzheimer's Disease Spectrum: A Potential Biomarker

Objective: To investigate variation in the characteristics of regional cerebral blood flow (rCBF), brain activity, and intrinsic functional connectivity (FC) across the Alzheimer's disease spectrum (ADS).

Methods: The study recruited 20 individuals in each of the following categories: Alzheimer's disease (AD), mild cognitive impairment (MCI), subjective cognitive decline (SCD), and healthy control (HC). All participants completed the 3.0T resting-state functional MRI (rs-fMRI) and arterial spin labeling scans in addition to neuropsychological tests. Additionally, the normalized CBF, regional homogeneity (ReHo), and amplitude of low-frequency fluctuation (ALFF) of individual subjects were compared in the ADS. Moreover, the changes in intrinsic FC were investigated across the ADS using the abnormal rCBF regions as seeds and behavioral correlations. Finally, a support-vector classifier model of machine learning was used to distinguish individuals with ADS from HC.

Results: Compared to the HC subjects, patients with AD showed the poorest level of rCBF in the left precuneus (LPCUN) and right middle frontal gyrus (RMFG) among all participants. In addition, there was a significant decrease in the ALFF in the bilateral posterior cingulate cortex (PCC) and ReHo in the right PCC. Moreover, RMFG- and LPCUN-based FC analysis revealed that the altered FCs were primarily located in the posterior brain regions. Finally, a combination of altered rCBF, ALFF, and ReHo in posterior cingulate cortex/precuneus (PCC/PCUN) showed a better ability to differentiate ADS from HC, AD from SCD and MCI, but not MCI from SCD.

Conclusions: The study demonstrated the significance of an altered rCBF and brain activity in the early stages of ADS. These findings, therefore, present a potential diagnostic neuroimaging-based biomarker in ADS. Additionally, the study provides a better understanding of the pathophysiology of AD.

Altered dynamic functional connectivity across mood states in bipolar disorder

BACKGROUND

This study aims to identify how the large-scale brain dynamic functional connectivity (dFC) differs between mood states in bipolar disorder (BD). The authors analyzed dFC in subjects with BD in depressed and euthymic states using resting-state functional magnetic resonance imaging (rsfMRI) data, and compared these states to healthy controls (HCs).

METHOD

20 subjects with BD in a depressive episode, 23 euthymic BD subjects, and 31 matched HCs underwent rsfMRI scans. Using an existing parcellation of the whole brain, we measured dFC between brain regions and identified the different patterns of brain network connections between groups.

RESULTS

In the analysis of whole brain dFC, the connectivity between the left Superior Temporal Gyrus (STG) in the somatomotor network (SMN), the right Middle Temporal Gyrus (MTG) in the default mode network (DMN) and the bilateral Postcentral Gyrus (PoG) in the DMN of depressed BD was greater than that of euthymic BD, while there was no significant difference between euthymic BD and HCs in these brain regions. Euthymic BD patients had abnormalities in the frontal-striatal-thalamic (FST) circuit compared to HCs.

CONCLUSIONS

Differences in dFC within and between DMN and SMN can be used to distinguish depressed and euthymic states in bipolar patients. The hyperconnectivity within and between DMN and SMN may be a state feature of depressed BD. The abnormal connectivity of the FST circuit can help identify euthymic BD from HCs.

Functional MRI-Specific Alterations in Executive Control Network in Mild Cognitive Impairment: An ALE Meta-Analysis

Background: Mild cognitive impairment (MCI) is regarded as a transitional stage between normal aging and Alzheimer's disease (AD) dementia. MCI individuals with deficits in executive function are at higher risk for progressing to AD dementia. Currently, there is no consistent result for alterations in the executive control network (ECN) in MCI, which makes early prediction of AD conversion difficult. The aim of the study was to find functional MRI-specific alterations in ECN in MCI patients by expounding on the convergence of brain regions with functional abnormalities in ECN.

Methods: We searched PubMed, Embase, and Web of Science to identify neuroimaging studies using methods including the amplitude of low frequency fluctuation/fractional amplitude of low-frequency fluctuation, regional homogeneity, and functional connectivity in MCI patients. Based on the Activation Likelihood Estimation algorithm, the coordinate-based meta-analysis and functional meta-analytic connectivity modeling were conducted.

Results: A total of 25 functional imaging studies with MCI patients were included in a quantitative meta-analysis. By summarizing the included articles, we obtained specific brain region changes, mainly including precuneus, cuneus, lingual gyrus, middle frontal gyrus, posterior cingulate cortex, and cerebellum posterior lobe, in the ECN based on these three methods. The specific abnormal brain regions indicated that there were interactions between the ECN and other networks.

Conclusions: This study confirms functional imaging specific abnormal markers in ECN and its interaction with other networks in MCI. It provides novel targets and pathways for individualized and precise interventions to delay the progression of MCI to AD.