Abnormal neural activities in first-episode, treatment-naïve, short-illness-duration, and treatment-response patients with major depressive disorder: a resting-state fMRI study

The association between gray matter volume in the hippocampal subfield and antidepressant efficacy mediated by abnormal dynamic functional connectivity

An abnormality of structures and functions in the hippocampus may have a key role in the pathophysiology of major depressive disorder (MDD). However, it is unclear whether structure factors of the hippocampus effectively impact antidepressant responses by hippocampal functional activity in MDD patients. We collected longitudinal data from 36 MDD patients before and after a 3-month course of antidepressant pharmacotherapy. Additionally, we obtained baseline data from 43 healthy controls matched for sex and age. Using resting-state functional magnetic resonance imaging (rs-fMRI), we estimated the dynamic functional connectivity (dFC) of the hippocampal subregions using a sliding-window method. The gray matter volume was calculated using voxel-based morphometry (VBM). The results indicated that patients with MDD exhibited significantly lower dFC of the left rostral hippocampus (rHipp.L) with the right precentral gyrus, left superior temporal gyrus and left postcentral gyrus compared to healthy controls at baseline. In MDD patients, the dFC of the rHipp.L with right precentral gyrus at baseline was correlated with both the rHipp.L volume and HAMD remission rate, and also mediated the effects of the rHipp.L volume on antidepressant performance. Our findings suggested that the interaction between hippocampal structure and functional activity might affect antidepressant performance, which provided a novel insight into the hippocampus-related neurobiological mechanism of MDD.

Multi-feature concatenation and multi-classifier stacking: An interpretable and generalizable machine learning method for MDD discrimination with rsfMRI

Major depressive disorder (MDD) is a serious and heterogeneous psychiatric disorder that needs accurate diagnosis. Resting-state functional MRI (rsfMRI), which captures multiple perspectives on brain structure, function, and connectivity, is increasingly applied in the diagnosis and pathological research of MDD. Different machine learning algorithms are then developed to exploit the rich information in rsfMRI and discriminate MDD patients from normal controls. Despite recent advances reported, the MDD discrimination accuracy has room for further improvement. The generalizability and interpretability of the discrimination method are not sufficiently addressed either. Here, we propose a machine learning method (MFMC) for MDD discrimination by concatenating multiple features and stacking multiple classifiers. MFMC is tested on the REST-meta-MDD data set that contains 2428 subjects collected from 25 different sites. MFMC yields 96.9% MDD discrimination accuracy, demonstrating a significant improvement over existing methods. In addition, the generalizability of MFMC is validated by the good performance when the training and testing subjects are from independent sites. The use of XGBoost as the meta classifier allows us to probe the decision process of MFMC. We identify 13 feature values related to 9 brain regions including the posterior cingulate gyrus, superior frontal gyrus orbital part, and angular gyrus, which contribute most to the classification and also demonstrate significant differences at the group level. The use of these 13 feature values alone can reach 87% of MFMC's full performance when taking all feature values. These features may serve as clinically useful diagnostic and prognostic biomarkers for MDD in the future.

Altered brain regional homogeneity is associated with cognitive dysfunction in first-episode drug-naive major depressive disorder: A resting-state fMRI study

BACKGROUND

Our study aimed to explore the abnormal spontaneous brain activity by regional homogeneity (ReHo) and its association with cognitive function to understand the neuropathology of major depressive disorder (MDD).

METHODS

ReHo was used to investigate brain activities of 60 patients with first-episode drug-naive MDD and 60 healthy controls (HCs). Partial correlation analysis was conducted on altered ReHo values and the severity of symptoms and cognitive deficits. Moreover, support vector machine analysis was used to evaluate the accuracy of abnormal ReHo values in distinguishing patients with MDD from HCs.

RESULTS

Compared with HCs, patients with MDD showed significantly increased ReHo values in the right cerebellum crus2 and right thalamus and decreased ReHo values in the right angular gyrus (AG) and right precuneus (PCUN). The ReHo values in right cerebellum crus2 and right AG were positively associated with working memory and visual learning, respectively. Furthermore, the combination of ReHo values in the right cerebellum crus2 and right PCUN discriminated the patients with MDD from HCs with specificity, sensitivity, and accuracy of 0.9688, 0.6250, and 0.90, respectively.

LIMITATIONS

The design of repeated cross-sectional surveys does not allow analyses of within individual changes.

CONCLUSIONS

Our study revealed that the pathophysiology mechanism of cognitive deficits in MDD may be related to abnormal spontaneous brain activity. Moreover, the combination of ReHo values in the right cerebellum crus2 and right PCUN can be used to discriminate patients with MDD from HCs effectively.

Deep Hashing Mutual Learning for Brain Network Classification

Recently, clinical phenotypic semantic information has begun to play an important role in some brain network classification methods based on deep learning. However, most current methods only consider the phenotypic semantic information of individual brain networks but ignore the potential phenotypic characteristics among group brain networks. To address this problem, we present a deep hashing mutual learning (DHML)-based brain network classification method. Specifically, we first design a separable CNN-based deep hashing learning to extract individual topological features of brain networks and map them into hash codes. Secondly, we construct a group brain network relationship graph based on the similarity of phenotypic semantic information, in which each node is a brain network, and the properties of the nodes are the individual features extracted in the previous step. Then, we adopt a GCN-based deep hashing learning to extract the group topological features of the brain network and map them to hash codes. Finally, the two deep hashing learning models perform mutual learning by measuring the distribution differences between the hash codes to achieve the interaction of individual and group features. The experimental results on the three commonly used brain atlases (AAL Atlas, Dosenbach160 Atlas, and CC200 Atlas) of the ABIDE I dataset show that our proposed DHML method achieves optimal classification performance compared with some state-of-the-art methods.

Deviant spontaneous neural activity as a potential early-response predictor for therapeutic interventions in patients with schizophrenia

Objective

Previous studies have established significant differences in the neuroimaging characteristics between healthy controls (HCs) and patients with schizophrenia (SCZ). However, the relationship between homotopic connectivity and clinical features in patients with SCZ is not yet fully understood. Furthermore, there are currently no established neuroimaging biomarkers available for the diagnosis of SCZ or for predicting early treatment response. The aim of this study is to investigate the association between regional homogeneity and specific clinical features in SCZ patients.

Methods

We conducted a longitudinal investigation involving 56 patients with SCZ and 51 HCs. The SCZ patients underwent a 3-month antipsychotic treatment. Resting-state functional magnetic resonance imaging (fMRI), regional homogeneity (ReHo), support vector machine (SVM), and support vector regression (SVR) were used for data acquisition and analysis.

Results

In comparison to HCs, individuals with SCZ demonstrated reduced ReHo values in the right postcentral/precentral gyrus, left postcentral/inferior parietal gyrus, left middle/inferior occipital gyrus, and right middle temporal/inferior occipital gyrus, and increased ReHo values in the right putamen. It is noteworthy that there was decreased ReHo values in the right inferior parietal gyrus after treatment compared to baseline data.

Conclusion

The observed decrease in ReHo values in the sensorimotor network and increase in ReHo values in the right putamen may represent distinctive neurobiological characteristics of patients with SCZ, as well as a potential neuroimaging biomarker for distinguishing between patients with SCZ and HCs. Furthermore, ReHo values in the sensorimotor network and right putamen may serve as predictive indicators for early treatment response in patients with SCZ.

Unbalanced amygdala communication in major depressive disorder

BACKGROUND

Previous studies suggested an association between functional alteration of the amygdala and typical major depressive disorder (MDD) symptoms. Examining whether and how the interaction between the amygdala and regions/functional networks is altered in patients with MDD is important for understanding its neural basis.

METHODS

Resting-state functional magnetic resonance imaging data were recorded from 67 patients with MDD and 74 age- and sex-matched healthy controls (HCs). A framework for large-scale network analysis based on seed mappings of amygdala sub-regions, using a multi-connectivity-indicator strategy (cross-correlation, total interdependencies (TI), Granger causality (GC), and machine learning), was employed. Multiple indicators were compared between the two groups. The altered indicators were ranked in a supporting-vector machine-based procedure and associated with the Hamilton Rating Scale for Depression scores.

RESULTS

The amygdala connectivity with the default mode network and ventral attention network regions was enhanced and that with the somatomotor network, dorsal frontoparietal network, and putamen regions in patients with MDD was reduced. The machine learning analysis highlighted altered indicators that were most conducive to the classification between the two groups.

LIMITATIONS

Most patients with MDD received different pharmacological treatments. It is difficult to illustrate the medication state's effect on the alteration model because of its complex situation.

CONCLUSION

The results indicate an unbalanced interaction model between the amygdala and functional networks and regions essential for various emotional and cognitive functions. The model can help explain potential aberrancy in the neural mechanisms that underlie the functional impairments observed across various domains in patients with MDD.

Transcriptional signatures of the cortical morphometric similarity network gradient in first-episode, treatment-naive major depressive disorder

Recent studies have shown that major depressive disorder (MDD) is accompanied by alterations in functional and structural network gradients. However, whether changes are present in the cortical morphometric similarity (MS) network gradient, and the relationship between alterations of the gradient and gene expression remains largely unknown. In this study, the MS network was constructed, and its gradient was calculated in 71 patients with first-episode, treatment-naive MDD, and 69 demographically matched healthy controls. Between-group comparisons were performed to investigate abnormalities in the MS network gradient, and partial least squares regression analysis was conducted to explore the association between gene expression profiles and MS network gradient-based alternations in MDD. We found that the gradient was primarily significantly decreased in sensorimotor regions in patients with MDD compared with healthy controls, and increased in visual-related regions. In addition, the altered principal MS network gradient in the left postcentral cortex and right lingual cortex exhibited significant correlations with symptom severity. The abnormal gradient pattern was spatially correlated with the brain-wide expression of genes enriched for neurobiologically relevant pathways, downregulated in the MDD postmortem brain, and preferentially expressed in different cell types and cortical layers. These results demonstrated alterations of the principal MS network gradient in MDD and suggested the molecular mechanisms for structural alternations underlying MDD.

Multiple examinations indicated associations between abnormal regional homogeneity and cognitive dysfunction in major depressive disorder

Background

This study aimed to investigate the relationships between regional neural activity and multiple related indicators in patients with major depressive disorder (MDD).

Methods

Forty-two patients and 42 healthy controls (HCs) were enrolled. Pearson/Spearman correlation analyses were applied to examine the associations between abnormal regional homogeneity (ReHo) and different indicators in the patients.

Results

Compared with HCs, patients with MDD had increased ReHo in the left inferior temporal gyrus (ITG) and decreased ReHo values in the left putamen, anterior cingulate cortex (ACC), and precentral gyrus. The ReHo of the left putamen was positively correlated with the PR interval, Repeatable Battery for the Assessment of Neuropsychological Status 4A, and Discriminant analysis (D), and negatively correlated with Ae (block) and Ae (total) in the patients. The ReHo value of the left ACC was positively correlated with the severity of depression, Stroop Color Word Test of C - 2B + 100 in reaction time, and negatively correlated with Ce (Missay) and Perseverative Responses in the patients. The ReHo of the left ITG was positively correlated with the Neuroticism scores and negatively correlated with the Lie scores in the patients.

Conclusion

These results suggested that the decreased ReHo of the salience network might be the underpinning of cognitive impairments in patients with MDD.

Disrupted interhemispheric coordination of sensory-motor networks and insula in major depressive disorder

Objective

Prior researches have identified distinct differences in neuroimaging characteristics between healthy controls (HCs) and patients with major depressive disorder (MDD). However, the correlations between homotopic connectivity and clinical characteristics in patients with MDD have yet to be fully understood. The present study aimed to investigate common and unique patterns of homotopic connectivity and their relationships with clinical characteristics in patients with MDD.

Methods

We recruited 42 patients diagnosed with MDD and 42 HCs. We collected a range of clinical variables, as well as exploratory eye movement (EEM), event-related potentials (ERPs) and resting-state functional magnetic resonance imaging (rs-fMRI) data. The data were analyzed using correlation analysis, support vector machine (SVM), and voxel-mirrored homotopic connectivity (VMHC).

Results

Compared with HCs, patients with MDD showed decreased VMHC in the insula, and increased VMHC in the cerebellum 8/vermis 8/vermis 9 and superior/middle occipital gyrus. SVM analysis using VMHC values in the cerebellum 8/vermis 8/vermis 9 and insula, or VMHC values in the superior/middle occipital gyrus and insula as inputs can distinguish HCs and patients with MDD with high accuracy, sensitivity, and specificity.

Conclusion

The study demonstrated that decreased VMHC in the insula and increased VMHC values in the sensory-motor networks may be a distinctive neurobiological feature for patients with MDD, which could potentially serve as imaging markers to discriminate HCs and patients with MDD.

Disrupted local functional connectivity in schizophrenia: An updated and extended meta-analysis

Neuroimaging studies have shown that schizophrenia is associated with disruption of resting-state local functional connectivity. However, these findings vary considerably, which hampers our understanding of the underlying pathophysiological mechanisms of schizophrenia. Here, we performed an updated and extended meta-analysis to identify the most consistent changes of local functional connectivity measured by regional homogeneity (ReHo) in schizophrenia. Specifically, a systematic search of ReHo studies in patients with schizophrenia in PubMed, Embase, and Web of Science identified 18 studies (20 datasets), including 652 patients and 596 healthy controls. In addition, we included three whole-brain statistical maps of ReHo differences calculated based on independent datasets (163 patients and 194 controls). A voxel-wise meta-analysis was then conducted to investigate ReHo alterations and their relationship with clinical characteristics using the newly developed seed-based d mapping with permutation of subject images (SDM-PSI) meta-analytic approach. Compared with healthy controls, patients with schizophrenia showed significantly higher ReHo in the bilateral medial superior frontal gyrus, while lower ReHo in the bilateral postcentral gyrus, right precentral gyrus, and right middle occipital gyrus. The following sensitivity analyses including jackknife analysis, subgroup analysis, heterogeneity test, and publication bias test demonstrated that our results were robust and highly reliable. Meta-regression analysis revealed that illness duration was negatively correlated with ReHo abnormalities in the right precentral/postcentral gyrus. This comprehensive meta-analysis not only identified consistent and reliably aberrant local functional connectivity in schizophrenia but also helped to further deepen our understanding of its pathophysiology.

Functional Brain Network Classification Based on Deep Graph Hashing Learning

Brain network classification using resting-state functional magnetic resonance imaging (rs-fMRI) is an effective analytical method for diagnosing brain diseases. In recent years, brain network classification methods based on deep learning have attracted increasing attention. However, these methods only consider the spatial topological characteristics of the brain network but ignore its proximity relationships in semantic space. To overcome this problem, we propose a novel brain network classification method based on deep graph hashing learning named BNC-DGHL. Specifically, we first extract the deep features of the brain network and then learn a graph hash function based on clinical phenotype labels and the similarity of diagnostic labels. Secondly, we use the learned graph hash function to convert deep features into hash codes, which can maintain the original semantic spatial relationships. Finally, we calculate the distance between hash codes to obtain the predicted category of the brain network. Experimental results on ABIDE I, ABIDE II, and ADHD-200 datasets demonstrate that our method achieves better classification performance of brain diseases compared with some state-of-the-art methods, and the abnormal functional connectivities between brain regions identified may serve as biomarkers associated with related brain diseases.

Brain Response of Major Depressive Disorder Patients to Emotionally Positive and Negative Music

Depression is characterized by poor emotion regulation that makes it difficult to escape the effects of emotional pain, but the neuromodulation behind these symptoms is still unclear. This study investigated the neural mechanism of emotional state-related responses during music stimuli in participants with major depressive disorder (MDD) compared to never-depressed (ND) controls. A novel two-level feature selection method, integrating recursive feature elimination based on support vector machine (SVM-RFE) and random forest algorithm (RF), was proposed to screen emotional recognition brain regions (ERBRs). On this basis, the differences of functional connectivity (FC) were systematically analyzed by two-sample t-test. The results demonstrate that ND participants show eight pairs of FCs with a significant difference between positive emotional music stimuli (pEMS) versus negative emotional music stimuli (nEMS) in 15 ERBRs of MDD, but the participants with MDD show one pair of significant difference in FC. The decreased number reflects the fuzzy response to positive and negative emotions in MDD, which appears to arise from obstacle to emotional cognition and regulation. Furthermore, there was no significant difference in FC between MDDs and NDs under pEMS, but a significant difference was detected between the two groups under nEMS (p < 0.01), revealing a 'bias' against the negative state in MDD. The current study may help to better comprehend the abnormal evolution from normal to depression and inform the utilization of pEMS in formal treatment for depression.

Intrinsic brain abnormalities in female major depressive disorder patients with childhood trauma: A resting-state functional magnetic resonance imaging study

Objective

Childhood trauma is a strong predictor of major depressive disorder (MDD). Women are more likely to develop MDD than men. However, the neural basis of female MDD patients with childhood trauma remains unclear. We aimed to identify the specific brain regions that are associated with female MDD patients with childhood trauma.

Methods

We recruited 16 female MDD patients with childhood trauma, 16 female MDD patients without childhood trauma, and 20 age- and education level-matched healthy controls. All participants underwent resting-state functional magnetic resonance imaging (MRI). Regional brain activity was evaluated as the amplitude of low-frequency fluctuation (ALFF). Furthermore, functional connectivity (FC) analyses were performed on areas with altered ALFF to explore alterations in FC patterns.

Results

There was increased ALFF in the left middle frontal gyrus (MFG) and the right postcentral gyrus (PoCG) in MDD with childhood trauma compared with MDD without childhood trauma. The areas with significant ALFF discrepancies were selected as seeds for the FC analyses. There was increased FC between the left MFG and the bilateral putamen gyrus. Moreover, ALFF values were correlated with childhood trauma severity.

Conclusion

Our findings revealed abnormal intrinsic brain activity and FC patterns in female MDD patients with childhood trauma, which provides new possibilities for exploring the pathophysiology of this disorder in women.

Local dynamic spontaneous brain activity changes in first-episode, treatment-naïve patients with major depressive disorder and their associated gene expression profiles

BACKGROUND

Major depressive disorder (MDD) is a common debilitating disorder characterized by impaired spontaneous brain activity, yet little is known about its alterations in dynamic properties and the molecular mechanisms associated with these changes.

METHODS

Based on the resting-state functional MRI data of 65 first-episode, treatment-naïve patients with MDD and 66 healthy controls, we compared dynamic regional homogeneity (dReHo) of spontaneous brain activity between the two groups, and we investigated gene expression profiles associated with dReHo alterations in MDD by leveraging transcriptional data from the Allen Human Brain Atlas and weighted gene co-expression network analysis.

RESULTS

Compared with healthy controls, patients with MDD consistently showed reduced dReHo in both fusiform gyri and in the right temporal pole and hippocampus. The expression profiles of 16 gene modules were correlated with dReHo alterations in MDD. These gene modules were enriched for various biological process terms, including immune, synaptic signalling, ion channels, mitochondrial function and protein metabolism, and were preferentially expressed in different cell types.

CONCLUSIONS

Patients with MDD have reduced dReHo in brain areas associated with emotional and cognitive regulation, and these changes may be related to complex polygenetic and polypathway mechanisms.

Early Fractional Amplitude of Low Frequency Fluctuation Can Predict the Efficacy of Transcutaneous Auricular Vagus Nerve Stimulation Treatment for Migraine Without Aura

Migraine is a common primary headache disorder. Transcutaneous auricular vagus nerve stimulation (taVNS) has been verified to be effective in patients with migraine without aura (MWoA). However, there are large interindividual differences in patients’ responses to taVNS. This study aimed to explore whether pretreatment fractional amplitude of low frequency fluctuation (fALFF) features could predict clinical outcomes in MWoA patients after 4-week taVNS. Sixty MWoA patients and sixty well-matched healthy controls (HCs) were recruited, and migraineurs received 4-week taVNS treatment. Resting-state functional magnetic resonance imaging (rs-fMRI) data were collected, and the significant differences of fALFF were detected between MWoA patients and HCs using two-sample t-test. A mask of these significant regions was generated and used for subsequent analysis. The abnormal fALFF in the mask was used to predict taVNS efficacy for MWoA using a support vector regression (SVR) model combining with feature select of weight based on the LIBSVM toolbox. We found that (1) compared with HCs, MWoA patients exhibited increased fALFF in the left thalamus, left inferior parietal gyrus (IPG), bilateral precentral gyrus (PreCG), right postcentral gyrus (PoCG), and bilateral supplementary motor areas (SMAs), but decreased in the bilateral precuneus and left superior frontal gyrus (SFG)/medial prefrontal cortex (mPFC); (2) after 4-week taVNS treatment, the fALFF values significantly decreased in these brain regions based on the pretreatment comparison. Importantly, the decreased fALFF in the bilateral precuneus was positively associated with the reduction in the attack times (r = 0.357, p = 0.005, Bonferroni correction, 0.05/5), whereas the reduced fALFF in the right PoCG was negatively associated with reduced visual analog scale (VAS) scores (r = −0.267, p = 0.039, uncorrected); (3) the SVR model exhibited a good performance for prediction (r = 0.411, p < 0.001),which suggests that these extracted fALFF features could be used as reliable biomarkers to predict the treatment response of taVNS for MWoA patients. This study demonstrated that the baseline fALFF features have good potential for predicting individualized treatment response of taVNS in MWoA patients, and those weight brain areas are mainly involved in the thalamocortical (TC) circuits, default mode network (DMN), and descending pain modulation system (DPMS). This will contribute to well understanding the mechanism of taVNS in treating MWoA patients and may help to screen ideal patients who respond well to taVNS treatment.

Abnormal regional spontaneous brain activities in white matter in patients with autism spectrum disorder

Previous studies have demonstrated patients with autism spectrum disorder (ASD) are accompanied by alterations of spontaneous brain activity in gray matter. However, whether the alterations of spontaneous brain activity exist in white matter remains largely unclear. In this study, 88 ASD patients and 87 typical controls (TCs) were included and regional homogeneity (ReHo) was calculated to characterize spontaneous brain activity in white matter. Voxel-wise two-sample t-tests were performed to investigate ReHo alterations, and cluster-level analyses were conducted to examine structural-functional coupling changes. Compared with TCs, the ASD group showed significantly decreased ReHo in the left superior corona radiata and left posterior limb of internal capsule, and decreased ReHo in the left anterior corona radiata with a trend level of significance. In addition, significantly weaker structural-functional coupling was observed in the left superior corona radiata and left posterior limb of internal capsule in ASD patients. Taken together, these findings highlighted abnormalities of white matter's regional spontaneous brain activity in ASD, which may provide new insights into the pathophysiological mechanisms of this disorder.

Test-retest stability of spontaneous brain activity and functional connectivity in the core resting-state networks assessed with ultrahigh field 7-Tesla resting-state functional magnetic resonance imaging

The growing demand for precise and reliable biomarkers in psychiatry is fueling research interest in the hope that identifying quantifiable indicators will improve diagnoses and treatment planning across a range of mental health conditions. The individual properties of brain networks at rest have been highlighted as a possible source for such biomarkers, with the added advantage that they are relatively straightforward to obtain. However, an important prerequisite for their consideration is their reproducibility. While the reliability of resting‐state (RS) measurements has often been studied at standard field strengths, they have rarely been investigated using ultrahigh‐field (UHF) magnetic resonance imaging (MRI) systems. We investigated the intersession stability of four functional MRI RS parameters—amplitude of low‐frequency fluctuations (ALFF) and fractional ALFF (fALFF; representing the spontaneous brain activity), regional homogeneity (ReHo; measure of local connectivity), and degree centrality (DC; measure of long‐range connectivity)—in three RS networks, previously shown to play an important role in several psychiatric diseases—the default mode network (DMN), the central executive network (CEN), and the salience network (SN). Our investigation at individual subject space revealed a strong stability for ALFF, ReHo, and DC in all three networks, and a moderate level of stability in fALFF. Furthermore, the internetwork connectivity between each network pair was strongly stable between CEN/SN and moderately stable between DMN/SN and DMN/SN. The high degree of reliability and reproducibility in capturing the properties of the three major RS networks by means of UHF‐MRI points to its applicability as a potentially useful tool in the search for disease‐relevant biomarkers.

Altered brain network in first-episode, drug-naive patients with major depressive disorder

BACKGROUND

Resting-state functional magnetic resonance imaging has been widely used for the assessment of brain functional network, yet with inconsistent results. The present study aimed to investigate intranetwork and internetwork connectivity differences between patients with major depressive disorder (MDD) and healthy controls at the integrity, network and edge levels of 8 well-defined resting state networks.

METHODS

Thirty patients with MDD and sixty-three healthy control subjects were recruited in this study.

RESULTS

Compared with healthy controls, patients with MDD showed increased node degree in the right amygdala and putamen, increased connectivity strength in the deep gray matter network (DGN) and increased functional connectivity in intranetwork and internetwork. Meanwhile, MDD showed decreased connectivity strength in visual network-DGN pair.

LIMITATIONS

The sample size was small, and all patients in this study were of Asian ethnicity, especially Han individuals.

CONCLUSIONS

These findings demonstrate that MDD cases and healthy controls may have divergent intranetwork and internetwork connectivity at an early stage without confounding influence of medication. These differences may underlie cognitive and behavioral alterations in patients with MDD. And these differences may help with the discrimination of patients and healthy people at an early stage of MDD. More studies in the future are warranted to assist in the diagnosis of this burdensome disease.

Vortioxetine Modulates the Regional Signal in First-Episode Drug-Free Major Depressive Disorder at Rest

BACKGROUND

Previous studies on brain functional alterations associated with antidepressants for major depressive disorder (MDD) have produced conflicting results because they involved short treatment periods and a variety of compounds.

METHODS

Resting-state functional magnetic resonance imaging scans were obtained from 25 first-episode drug-free patients with MDD and 25 healthy controls. The patients, who were treated with vortioxetine for 8 weeks, were scanned at two-time points (baseline and week 8 of treatment). The amplitude of low-frequency fluctuation (ALFF) in the imaging data was used to analyze local brain signal alterations associated with antidepressant treatment.

RESULTS

Compared with the controls, the patients at baseline showed decreased ALFF values in the right inferior temporal gyrus and increased ALFF values in the left inferior cerebellum, right cingulate gyrus and postcentral gyrus. After 8 weeks of vortioxetine treatment, patients showed increased ALFF values in the bilateral cingulate gyrus, middle temporal gyrus, medial superior frontal gyrus, and inferior cerebellum.

CONCLUSION

This study provided evidence that vortioxetine modulates brain signals in MDD sufferers. These findings contribute to the understanding of how antidepressants effect brain function.

Abnormal causal connectivity of left superior temporal gyrus in drug-naïve first- episode adolescent-onset schizophrenia: A resting-state fMRI study

This study aimed to investigate the alterations of causal connectivity between the brain regions in Adolescent-onset schizophrenia (AOS) patients. Thirty-two first-episode drug-naïve AOS patients and 27 healthy controls (HC) were recruited for resting-state functional MRI scanning. The brain region with the between-group difference in regional homogeneity (ReHo) values was chosen as a seed to perform the Granger causality analysis (GCA) and further detect the alterations of causal connectivity in AOS. AOS patients exhibited increased ReHo values in left superior temporal gyrus (STG) compared with HCs. Significantly decreased values of outgoing Granger causality from left STG to right superior frontal gyrus and right angular gyrus were observed in GC mapping for AOS. Significantly stronger causal outflow from left STG to right insula and stronger causal inflow from right middle occipital gyrus (MOG) to left STG were also observed in AOS patients. Based on assessments of the two strengthened causal connectivity of the left STG with insula and MOG, a discriminant model could identify all patients from controls with 94.9% accuracy. This study indicated that alterations of directional connections in left STG may play an important role in the pathogenesis of AOS and serve as potential biomarkers for the disease.

Shared and distinct homotopic connectivity changes in melancholic and non-melancholic depression

OBJECTIVE

Previous studies have revealed different neuroimaging features between melancholic and non-melancholic major depressive disorder (MDD). However, homotopic connectivity of melancholic and non-melancholic MDD remains unknown. The present study aimed to explore common and distinct homotopic connectivity patterns of melancholic and non-melancholic MDD and their associations with clinical characteristics.

METHODS

Sixty-four patients with MDD and thirty-two healthy controls were scanned by resting-state functional magnetic resonance imaging (fMRI). Voxel-mirrored homotopic connectivity (VMHC) and pattern classification were applied to analyze the imaging data.

RESULTS

Relative to healthy controls, melancholic patients displayed decreased VMHC in the fusiform gyrus, posterior cingulate cortex (PCC), superior occipital gyrus (SOG), postcentral gyrus and precentral/postcentral gyrus, and non-melancholic patients displayed decreased VMHC in the PCC. Compared with non-melancholic patients, melancholic patients displayed reduced VMHC in the precentral gyrus and precentral/postcentral gyrus. Support vector machine (SVM) results exhibited VMHC in the precentral gyrus could distinguish melancholic patients from non-melancholic patients with more than 0.6 for specificity, sensitivity and accuracy.

CONCLUSION

The study demonstrated common and distinct homotopic connectivity patterns in melancholic and non-melancholic patients. Decreased VMHC in the PCC may be a state-related change for depression, and reduced VMHC in the precentral gyrus and postcentral gyrus may be a distinctive neurobiological feature for melancholic MDD. VMHC in precentral gyrus might be served as potential imaging markers to discriminate melancholic patients from non-melancholic MDD.

Abnormal Default-Mode Network Homogeneity in Melancholic and Nonmelancholic Major Depressive Disorder at Rest

Background

Melancholic depression has been assumed as a severe type of major depressive disorder (MDD). We aimed to explore if there were some distinctive alterations in melancholic MDD and whether the alterations could be used to discriminate the melancholic MDD and nonmelancholic MDD.

Methods

Thirty-one outpatients with melancholic MDD, thirty-three outpatients with nonmelancholic MDD, and thirty-two age- and gender-matched healthy controls were recruited. All participants were scanned by resting-state functional magnetic resonance imaging (fMRI). Imaging data were analyzed with the network homogeneity (NH) and support vector machine (SVM) methods.

Results

Both patient groups exhibited increased NH in the right PCC/precuneus and right angular gyrus and decreased NH in the right middle temporal gyrus compared with healthy controls. Compared with nonmelancholic patients and healthy controls, melancholic patients exhibited significantly increased NH in the bilateral superior medial frontal gyrus and decreased NH in the left inferior temporal gyrus. But merely for melancholic patients, the NH of the right middle temporal gyrus was negatively correlated with TEPS total and contextual anticipatory scores. SVM analysis showed that a combination of NH values in the left superior medial frontal gyrus and left inferior temporal gyrus could distinguish melancholic patients from nonmelancholic patients with accuracy, sensitivity, and specificity of 79.66% (47/59), 70.97% (22/31), and 89.29%(25/28), respectively.

Conclusion

Our findings showed distinctive network homogeneity alterations in melancholic MDD which may be potential imaging markers to distinguish melancholic MDD and nonmelancholic MDD.

Altered dynamic regional homogeneity in patients with conduct disorder

Conduct disorder (CD) is a psychiatric condition characterized by severe aggressive and antisocial behaviors. Prior neuroimaging work reported that CD is associated with abnormal resting-state local intrinsic brain activity (IBA). However, few studies detected the time-varying brain activity patterns in CD. In this study, eighteen adolescent patients with CD and 18 typically developing controls underwent resting-state functional magnetic resonance imaging scans. We then compared the dynamic characteristics of IBA by calculating the dynamic regional homogeneity (dReHo) through a sliding-window approach between the two groups, and the correlations between the dReHo variability and clinical symptoms in CD were further examined. Moreover, the statistical between-group differences in dReHo were selected as classification features to help distinguish CD patients from controls by adopting a linear support vector machine (SVM) classifier. CD patients showed increased dReHo variability in the left precuneus, right postcentral gyrus, right precentral gyrus, left middle cingulate gyrus, and left paracentral lobule compared to controls, and dReHo variability in the left precuneus was significantly positively associated with impulsiveness scores in CD patients. Importantly, SVM combined with the leave-one-out cross-validation method results demonstrated that 75% (p < 0.001) subjects were correctly classified with sensitivity of 61% and specificity of 89%. Our results provided the initial evidence that CD is characterized by abnormal dynamic IBA patterns, giving novel insights into the neuropathological mechanisms of CD. Further, our findings exhibited that the dReHo variability may distinguish CD patients from controls with high accuracy.

Cell-Type-Specific Gene Modules Related to the Regional Homogeneity of Spontaneous Brain Activity and Their Associations With Common Brain Disorders

Mapping gene expression profiles to neuroimaging phenotypes in the same anatomical space provides opportunities to discover molecular substrates for human brain functional properties. Here, we aimed to identify cell-type-specific gene modules associated with the regional homogeneity (ReHo) of spontaneous brain activity and their associations with brain disorders. Fourteen gene modules were consistently associated with ReHo in the three datasets, five of which showed cell-type-specific expression (one neuron-endothelial module, one neuron module, one astrocyte module and two microglial modules) in two independent cell series of the human cerebral cortex. The neuron-endothelial module was mainly enriched for transporter complexes, the neuron module for the synaptic membrane, the astrocyte module for amino acid metabolism, and microglial modules for leukocyte activation and ribose phosphate biosynthesis. In enrichment analyses of cell-type-specific modules for 10 common brain disorders, only the microglial module was significantly enriched for genes obtained from genome-wide association studies of multiple sclerosis (MS) and Alzheimer’s disease (AD). The ReHo of spontaneous brain activity is associated with the gene expression profiles of neurons, astrocytes, microglia and endothelial cells. The microglia-related genes associated with MS and AD may provide possible molecular substrates for ReHo abnormality in both brain disorders.

Age-Related Hearing Loss and the Development of Cognitive Impairment and Late-Life Depression: A Scoping Overview

Age-related hearing loss (ARHL) has been connected to both cognitive decline and late-life depression. Several mechanisms have been offered to explain both individual links. Causal and common mechanisms have been theorized for the relationship between ARHL and impaired cognition, including dementia. The causal mechanisms include increased cognitive load, social isolation, and structural brain changes. Common mechanisms include neurovascular disease as well as other known or as-yet undiscovered neuropathologic processes. Behavioral mechanisms have been used to explain the potentially causal association of ARHL with depression. Behavioral mechanisms include social isolation, loneliness, as well as decreased mobility and impairments of activities of daily living, all of which can increase the risk of depression. The mechanisms underlying the associations between hearing loss and impaired cognition, as well as hearing loss and depression, are likely not mutually exclusive. ARHL may contribute to both impaired cognition and depression through overlapping mechanisms. Furthermore, ARHL may contribute to impaired cognition which may, in turn, contribute to depression. Because ARHL is highly prevalent and greatly undertreated, targeting this condition is an appealing and potentially influential strategy to reduce the risk of developing two potentially devastating diseases of later life. However, further studies are necessary to elucidate the mechanistic relationship between ARHL, depression, and impaired cognition.

Default mode network activity in depression subtypes

Depression continues to carry a major disease burden worldwide, with limitations on the success of traditional pharmacological or psychological treatments. Recent approaches have therefore focused upon the neurobiological underpinnings of depression, and on the "individualization" of depression symptom profiles. One such model of depression has divided the standard diagnostic criteria into four "depression subtypes", with neurological and behavioral pathways. At the same time, attention has been focused upon the region of the brain known as the "default mode network" (DMN) and its role in attention and problem-solving. However, to date, no review has been published of the links between the DMN and the four subtypes of depression. By searching the literature studies from the last 20 years, 62 relevant papers were identified, and their findings are described for the association they demonstrate between aspects of the DMN and the four depression subtypes. It is apparent from this review that there are potential positive clinical and therapeutic outcomes from focusing upon DMN activation and connectivity, via psychological therapies, transcranial magnetic stimulation, and some emerging pharmacological models.

Abnormal regional homogeneity and its relationship with symptom severity in cervical dystonia: a rest state fMRI study

BACKGROUND

Although several brain networks play important roles in cervical dystonia (CD) patients, regional homogeneity (ReHo) changes in CD patients have not been clarified. We investigated to explore ReHo in CD patients at rest and analyzed its correlations with symptom severity as measured by Tsui scale.

METHODS

A total of 19 CD patients and 21 gender-, age-, and education-matched healthy controls underwent fMRI scans at rest state. Data were analyzed by ReHo method.

RESULTS

Patients showed increased ReHo in the right cerebellum crus I and decreased ReHo in the right superior medial prefrontal cortex (MPFC). Moreover, the right precentral gyrus, right insula, and bilateral middle cingulate gyrus also showed increased ReHo values. A significantly positive correlation was observed between ReHo value in the right cerebellum crus I and symptom severity (p < 0.05).

CONCLUSIONS

Our investigation suggested abnormal ReHo existed in brain regions of the "pain matrix" and salience network (the right insula and bilateral middle cingulate gyrus), the motor network (the right precentral gyrus), the cerebellum and MPFC and further highlighted the significance of these networks in the pathology of CD.

Altered Fractional Amplitude of Low-Frequency Fluctuation in Major Depressive Disorder and Bipolar Disorder

Background: Discriminating between major depressive disorder (MDD) and bipolar disorder (BD) remains challenging and cognitive deficits in MDD and BD are generally recognized. In this study, the fractional amplitude of low-frequency fluctuation (fALFF) approach was performed to explore neural activity and cognition in first-episode, drug-naïve BD and MDD patients, as well as the relationship between altered fALFF values and clinical or psychometric variables. Methods: A total of 21 BD patients, 25 MDD patients, and 41 healthy controls (HCs) completed clinical assessments and resting-state functional magnetic resonance imaging (rs-fMRI) scans in this study. The rs-fMRI data were analyzed by fALFF method and Pearson correlation analyses were performed between altered fALFF values and clinical variables or cognition. Support vector machine (SVM) was adopted to identify the three groups from each other with abnormal fALFF values in the brain regions obtained by group comparisons. Results: (1) The fALFF values were significantly different in the frontal lobe, temporal lobe, and left precuneus among three groups. In comparison to HCs, BD showed increased fALFF values in the right inferior temporal gyrus (ITG) and decreased fALFF values in the right middle temporal gyrus, while MDD showed decreased fALFF values in the right cerebellar lobule IV/V. In comparison to MDD, BD showed decreased fALFF values in bilateral posterior cingulate gyrus and the right cerebellar lobule VIII/IX. (2) In the BD group, a negative correlation was found between increased fALFF values in the right ITG and years of education, and a positive correlation was found between decreased fALFF values in the right cerebellar lobule VIII/IX and visuospatial abilities. (3) The fALFF values in the right cerebellar lobule VIII/IX may have the ability to discriminate BD patients from MDD patients, with sensitivity, specificity, and accuracy all over 0.70. Conclusions: Abnormal brain activities were observed in BD and MDD and were related with cognition in BD patients. The abnormality in the cerebellum can be potentially used to identify BD from MDD patients.

Increased regional homogeneity modulated by metacognitive training predicts therapeutic efficacy in patients with schizophrenia

Previous studies have demonstrated the efficacy of metacognitive training (MCT) in schizophrenia. However, the underlying mechanisms related to therapeutic effect of MCT remain unknown. The present study explored the treatment effects of MCT on brain regional neural activity using regional homogeneity (ReHo) and whether these regions' activities could predict individual treatment response in schizophrenia. Forty-one patients with schizophrenia and 20 healthy controls were scanned using resting-state functional magnetic resonance imaging. Patients were randomly divided into drug therapy (DT) and drug plus psychotherapy (DPP) groups. The DT group received only olanzapine treatment, whereas the DPP group received olanzapine and MCT for 8 weeks. The results revealed that ReHo in the right precuneus, left superior medial prefrontal cortex (MPFC), right parahippocampal gyrus and left rectus was significantly increased in the DPP group after 8 weeks of treatment. Patients in the DT group showed significantly increased ReHo in the left ventral MPFC/anterior cingulate cortex (ACC), left superior MPFC/middle frontal gyrus (MFG), left precuneus, right rectus and left MFG, and significantly decreased ReHo in the bilateral cerebellum VIII and left inferior occipital gyrus (IOG) after treatment. Support vector regression analyses showed that high ReHo levels at baseline in the right precuneus and left superior MPFC could predict symptomatic improvement of Positive and Negative Syndrome Scale (PANSS) after 8 weeks of DPP treatment. Moreover, high ReHo levels at baseline and alterations of ReHo in the left ventral MPFC/ACC could predict symptomatic improvement of PANSS after 8 weeks of DT treatment. This study suggests that MCT is associated with the modulation of ReHo in schizophrenia. ReHo in the right precuneus and left superior MPFC may predict individual therapeutic response for MCT in patients with schizophrenia.

Shared and Distinct Fractional Amplitude of Low-Frequency Fluctuation Patterns in Major Depressive Disorders With and Without Gastrointestinal Symptoms

Objective: Gastrointestinal (GI) symptoms are fairly common somatic symptoms in depressed patients. The purpose of this study was to explore the influence of concomitant GI symptoms on the fractional amplitude of low-frequency fluctuation (fALFF) patterns in patients with major depressive disorder (MDD) and investigate the connection between aberrant fALFF and clinical characteristics. Methods: This study included 35 MDD patients with GI symptoms (GI-MDD patients), 17 MDD patients without GI symptoms (nGI-MDD patients), and 28 healthy controls (HCs). The fALFF method was used to analyze the resting-state functional magnetic resonance imaging data. Correlation analysis and pattern classification were employed to investigate the relationship of the fALFF patterns with the clinical characteristics of patients. Results: GI-MDD patients exhibited higher scores in the HRSD-17 and suffered more severe insomnia, anxiety/somatization, and weight loss than nGI-MDD patients. GI-MDD patients showed higher fALFF in the right superior frontal gyrus (SFG)/middle frontal gyrus (MFG) and lower fALFF in the left superior medial prefrontal cortex (MPFC) compared with nGI-MDD patients. A combination of the fALFF values of these two clusters could be applied to discriminate GI-MDD patients from nGI-MDD patients, with accuracy, sensitivity, and specificity of 86.54, 94.29, and 70.59%, respectively. Conclusion: GI-MDD patients showed more severe depressive symptoms. Increased fALFF in the right SFG/MFG and decreased fALFF in the left superior MPFC might be distinctive neurobiological features of MDD patients with GI symptoms.

Changes in Regional Homogeneity of Medication-Free Major Depressive Disorder Patients With Different Onset Ages

Background: Neurobiological mechanisms underlying the development of major depressive disorder (MDD) may differ depending on onset ages. Our aim was to determine whether regional homogeneity (ReHo) changes in early-onset depression (EOD) and late-onset depression (LOD) are different, which could also delineate EOD and LOD. Methods: Ninety-one MDD patients and 115 healthy controls (HCs) were recruited, and resting-state functional magnetic resonance imaging data were collected. The ReHo comparison was conducted using analysis of variance. Results: Compared with HCs, MDD patients showed decreased ReHo in the left precentral gyrus and the left middle cingulum area, and increased ReHo in the left middle orbital frontal gyrus and superior temporal gyrus. Compared with LOD patients, young HC separately, EOD patients had significantly increased ReHo in the right inferior frontal triangular gyrus and the left postcentral gyrus. However, compared with young HC, EOD patients showed decreased ReHo in the right superior frontal gyrus/supplementary motor area and the right medial frontal gyrus. ReHo in the right inferior frontal triangular gyrus was negatively correlated with the severity of cognitive disturbance in LOD patients (r = -0.47, p = 0.002), but not in EOD patients (r = 0.21, p = 0.178). Conclusion: MDD patients with different onset ages may have different pathophysiological mechanisms; the EOD patients had more abnormal ReHo than LOD patients in the prefrontal lobe, especially the right inferior frontal triangular gyrus.

Disrupted Regional Homogeneity in Melancholic and Non-melancholic Major Depressive Disorder at Rest

Background: Melancholic depression has been viewed as one severe subtype of major depressive disorder (MDD). However, it is unclear whether melancholic depression has distinct changes in brain imaging. We aimed to explore specific or distinctive alterations in melancholic MDD and whether the alterations could be used to separate melancholic MDD from non-melancholic MDD or healthy controls. Materials and Methods: Thirty-one outpatients with melancholic MDD and thirty-three outpatients with non-melancholic MDD and thirty-two age- and gender-matched healthy controls were recruited. All participants were scanned by resting-state functional magnetic resonance imaging (fMRI). Imaging data were analyzed with the regional homogeneity (ReHo) and support vector machine (SVM) methods. Results: Melancholic MDD patients exhibited lower ReHo in the right superior occipital gyrus/middle occipital gyrus than non-melancholic MDD patients and healthy controls. Merely for non-melancholic MDD patients, decreased ReHo in the right middle frontal gyrus was negatively correlated with the total HRSD-17 scores. SVM analysis results showed that a combination of abnormal ReHo in the right fusiform gyrus/cerebellum Crus I and the right superior occipital gyrus/middle occipital gyrus exhibited the highest accuracy of 83.05% (49/59), with a sensitivity of 90.32% (28/31), and a specificity of 75.00% (21/28) for discriminating patients with melancholic MDD from patients with non-melancholic MDD. And a combination of abnormal ReHo in the right fusiform gyrus/cerebellum VI and left postcentral gyrus/precentral gyrus exhibited the highest accuracy of 98.41% (62/63), with a sensitivity of 96.77% (30/31), and a specificity of 100.00%(32/32) for separating patients with melancholic MDD from healthy controls. Conclusion: Our findings showed the distinctive ReHo pattern in patients with melancholic MDD and found brain area that may be associated with the pathophysiology of non-melancholic MDD. Potential imaging markers for discriminating melancholic MDD from non-melancholic MDD or healthy controls were reported.

Diagnosis of major depressive disorder using whole-brain effective connectivity networks derived from resting-state functional MRI

OBJECTIVE

It is important to improve identification accuracy for possible early intervention of major depressive disorder (MDD). Recently, effective connectivity (EC), defined as the directed influence of spatially distant brain regions on each other, has been used to find the dysfunctional organization of brain networks in MDD. However, little is known about the ability of whole-brain resting-state EC features in identification of MDD. Here, we employed EC by whole-brain analysis to perform MDD diagnosis.

APPROACH

In this study, we proposed a high-order EC network capturing high-level relationship among multiple brain regions to discriminate 57 patients with MDD from 60 normal controls (NC). In high-order EC networks and traditional low-order EC networks, we utilized the network properties and connection strength for classification. Meanwhile, the support vector machine (SVM) was employed for model training. Generalization of the results was supported by 10-fold cross-validation.

MAIN RESULTS

The classification results showed that the high-order EC network performed better than the low-order EC network in diagnosing MDD, and the integration of these two networks yielded the best classification precision with 95% accuracy, 98.83% sensitivity, and 91% specificity. Furthermore, we found that the abnormal connections of high-order EC in MDD patients involved multiple widely concerned functional subnets, particularly the default mode network and the cerebellar network.

SIGNIFICANCE

The current study indicates whole-brain EC networks, measured by our high-order method, may be promising biomarkers for clinical diagnosis of MDD, and the complementary between high-order and low-order EC will better guide patients to get early interventions as well as treatments.

Dynamic alterations of spontaneous neural activity in patients with amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a multi-system disease featured by movement disorder. Studies on ALS using static neuroimaging indexes demonstrated inconsistent results. However, recent work indicated that the intrinsic brain activity was time-varying, and the abnormal temporal dynamics of brain activity in ALS remains unknown. Resting-state functional magnetic resonance imaging data were first obtained from 54 patients with ALS and 54 healthy controls (HCs). Then the dynamic regional homogeneity (d-ReHo) was calculated and compared between the two groups. Correlation analyses between altered d-ReHo and clinical scores were further performed. Compared with HCs, ALS patients showed higher d-ReHo in the left lingual gyrus while lower d-ReHo in the left rectus gyrus and left parahippocampal gyrus. Moreover, the d-ReHo in the left lingual gyrus exhibited correlation with disease progression rate in ALS at a trend level. Our findings suggested that altered dynamics in intrinsic brain activity might be a potential biomarker for diagnosing of ALS.

Altered brain function and clinical features in patients with first-episode, drug naïve major depressive disorder: A resting-state fMRI study

Major depressive disorder (MDD) is characterized by heterogeneous clinical performance and neurocognitive impairment. It is important to explore the correlation between global functioning and regional homogeneity (ReHo)/amplitude of low-frequency fluctuation (ALFF) values in MDD patients. 67 first-episode, drug naïve MDD patients and 69 healthy subjects were enrolled in the study. The MATRICS Consensus Cognitive Battery (MCCB) and the Functioning Assessment Short Test (FAST) were used to assess functional impairment in patients. Brain activity was assessed using ReHo and ALFF measurements. The relationship between the clinical features and altered brain function was evaluated using correlation analysis. There were significant differences in the ReHo and ALFF values between MDD patients and healthy subjects. The reduction in ReHo in the left calcarine/lingual gyrus/cuneus was negatively correlated with occupational functioning and the total FAST scores. The reduction in ALFF in the right calcarine/lingual gyrus was positively correlated with the verbal learning aspects of the MCCB. These findings suggest that the altered brain function in the default mode network (DMN) may be related to functional impairments in patients with first-episode, drug naïve major depressive disorder.

Altered Intrinsic Brain Activity and Functional Connectivity Before and After Knee Arthroplasty in the Elderly: A Resting-State fMRI Study

Objective: This study aimed to investigate the brain functional alterations with resting-state functional magnetic resonance imaging (rs-fMRI) in older patients with knee osteoarthritis (KOA) before and after total knee arthroplasty (TKA) and to assess the causal relationship of the brain function and neuropsychological changes.

Methods: We performed rs-fMRI to investigate brain function of 23 patients aged ≥65 with KOA and 23 healthy matched controls. Of the KOA patients, 15 completed postoperative rs-fMRI examinations. Analyzes of the amplitude of low-frequency fluctuation (ALFF) and functional connectivity (FC) were used to estimate differences in brain functional parameters between KOA patients, postoperative patients, and the controls. The relationship between changes of pre- and post-surgical status in ALFF and neuropsychological test results was analyzed.

Results: Compared with the controls, all patients with KOA exhibited decreased ALFF in the default mode network (bilateral angular gyrus, precuneus gyrus, medial superior frontal gyrus) and increased ALFF in the bilateral amygdala and cerebellum posterior lobe before surgery (P < 0.001). Altered ALFF persisted in the same brain regions 1 week postoperatively. The decreased ALFF in the left precuneus gyrus and middle temporal gyrus was found after surgery when compared with preoperative data (P < 0.01). Preoperatively, the KOA patients exhibited increased FC between the left precuneus gyrus and the right supplementary motor area compared to the controls (P < 0.001), but this connectivity became no significant difference after TKA. The left Cerebelum_9 was found to have decreased FC with the right precuneus gyrus postoperatively (P < 0.001) although this was not significantly different before surgery. The significantly altered ALFF values were not correlated with changes in cognitive assessment scores.

Conclusion: In older patients with end-stage KOA, functional alterations in important brain regions were detected with the persistence and further changes observed at an early stage after knee replacement. Our data further our understanding of brain functional abnormalities and cognitive impairment in older patients following knee replacement, which may provide therapeutic targets for preventive/treatment strategy to be developed.

Trial registration: Clinical Trial Registration: http://www.chictr.org.cn/index.aspx, ChiCTR1800016437; Registered June 1, 2018.

Disrupted Regional Homogeneity in Drug-Naive Patients With Bipolar Disorder

OBJECTIVE

Studies on alterations in the regional neural activity in the brain of patients with bipolar disorder (BD) have provided conflicting results because of different medications used and study designs. A low bone mineral density (BMD) is also observed in patients with BD. This study aimed to further explore regional neural activities in unmedicated patients with BD and their association with BMD.

METHODS

In this study, 40 patients with BD and 42 healthy controls were scanned through resting-state functional magnetic resonance imaging (fMRI). Imaging data were analyzed with regional homogeneity (ReHo) and pattern classification. Pearson's correlation analyses were performed to explore the correlations between abnormal ReHo and BMD.

RESULTS

A significant increase in ReHo values in the left inferior frontal gyrus (IFG)/temporal pole, left cerebellum vermis I/vermis II/parahippocampal gyrus/brainstem, and right superior temporal gyrus (STG) and a decrease in ReHo in the occipital gyrus (OG; left middle OG/superior OG/bilateral cuneus) were found in the patients with BD (p < 0.05) compared with those in the healthy controls. No significant correlation was observed between the abnormal ReHo values in any of the brain regions of the patients with BMD.Support vector machine (SVM) analyses revealed that the ReHo values in the right STG for distinguishing patients from healthy controls showed an accuracy of 91.89%, a sensitivity of 75.68%, and a specificity of 83.78%. The ReHo values in the left cerebellum vermis I/vermis II/parahippocampal gyrus/brainstem indicated an accuracy of 78.38%, a sensitivity of 75.68%, and a specificity of 81.08%.

CONCLUSION

This study further confirms the abnormal brain activities in extensive regions, and these brain regions are primarily located in the fronto-temporal-occipital circuit and the cerebellum vermis of patients with BD. The regional neural activity in the right STG and the left cerebellum vermis I/vermis II/parahippocampal gyrus/brainstem may serve as potential imaging markers to distinguish patients with BD from healthy controls.

Brain structural and functional alterations in MDD patient with gastrointestinal symptoms: A resting-state MRI study

OBJECTIVE

It is common for major depressive disorder (MDD) to be accompanied by gastrointestinal (GI) symptoms, which are known to negatively impact the course and severity of the disease. Although previous studies have attempted to explore the neuropathology of MDD, few studies have focused on the pathogenesis of GI symptoms in MDD. In this study, we investigated the changes in regional gray matter volume (GMV) and regional homogeneity (ReHo) present in MDD accompanied by GI symptoms.

METHOD

The following images were obtained and analyzed: Structural and functional magnetic resonance images (MRI) of 36 patients with MDD accompanied by GI symptoms (GI symptoms group), 22 patients without GI symptoms (Non-GI symptoms group), and 27 healthy controls (HC. The 24-item Hamilton Depression Rating Scale (HAMD) was administered. A correlation analysis was used to identify the possible associations between altered regional GMV, ReHo symptoms, GI symptoms, and depressive symptoms.

RESULTS

The total scores from the HAMD-24 in the GI symptoms group were significantly higher than in the Non-GI symptoms group (P<0.05). Significant differences in both GMV and ReHo were observed among the three groups for the right parahippocampal gyrus, left precentral gyrus, left middle frontal gyrus, right superior frontal gyrus, right middle frontal gyrus, and left inferior orbitofrontal gyrus (AlphaSim correction, P <0.001). The GI symptoms group exhibited significantly decreased GMV and ReHo in the left middle frontal gyrus, precentral gyrus, right superior frontal gyrus, and middle frontal gyrus. Additionally, the GI symptoms group exhibited increased ReHo in the left superior temporal gyrus at a higher level than the non-GI symptoms group. (AlphaSim correction, P <0.001). These altered brain areas were correlated with GI symptoms (P<0.001) but not depressive symptoms (P>0.05).

CONCLUSION

Patients with MDD accompanied by GI symptoms have more severe depressive symptoms. The structural and functional changes of the brain may be the pathogenesis for the GI symptoms in patients with MDD.

Abnormal functional connectivity strength in first-episode, drug-naïve adult patients with major depressive disorder

BACKGROUND

The pathogenesis of major depressive disorder (MDD) is complicated and equivocal. Previous studies have found an incidence of abnormal changes of neural networks, with plentiful evidence pointing the finger of suspicion firmly at the default mode network (DMN) and cortico-limbic networks. The aim of the present study was to use the approach of functional connectivity strength (FCS) to directly investigate the features of spontaneous brain activity in the case of first-episode, drug-naïve adult patients with MDD at rest.

METHODS

Resting-state functional magnetic resonance imaging (MRI) scans were performed on 23 first-episode drug-naïve major depressive disorder (MDD) patients and 20 healthy controls (HCs). In this study, using graph-theory approaches(FCS), we computed the characteristics of brain connectivity. Simultaneously, we used a series of validated test procedures to evaluate the patients' cognitive function. Subsequently, the results were compared with the peak of FCS value and a correlation analysis was conducted.

RESULTS

Compared with the HCs group, MDD patients showed significantly decreased FCS in bilateral posterior cingulate cortex (PCC)/precuneus and bilateral prefrontal cortex(PFC) and increased FCS in right posterior central gyrus, left thalamus and left temporal lobe. These brain regions belongs to the default-mode network and cortico-limbic networks. Finally, the correlation analyses showed the negative correlation of the FCS values in the left posterior cingulate cortex (PCC)/precuneus and Hamilton Anxiety Rating Scale (HAMA, r = -0.472, p = .023), Stroop Color Word Test-A(SCWT-A, r = -0.451, p = .031), Stroop Color Word Test-B(SCWT-B, r = -0.588, p = .003).Meanwhile, there was negative correlation between the FCS values in the left thalamus and SCWT-A(r = -0.473, p = .023), SCWT-B(r = -0.465, p = .025), SCWTC(r = -0.524, p = .010).In addition, the FCS values in the right PCC has negative correlation with Montgomery Asberg Depression Rating Scale (MADRS) (r = -0.433, p = .039).

CONCLUSIONS

DMN is an important node of MDD. FCS within the default mode network and cortico-limbic networks in patients with major depressive disorder has been changed in the early stage of MDD. FCS can provide favourable and additional evidence in the investigation of brain pathophysiology and therapy in depression.

Common and distinct neural activities in frontoparietal network in first-episode bipolar disorder and major depressive disorder: Preliminary findings from a follow-up resting state fMRI study

BACKGROUND

It is difficult to distinguish bipolar disorder (BD) from major depressive disorder (MDD), especially with the initial depressive episode. In this study, we compared neural activities of BD and MDD patients during the first-episode (FE) to investigate common and distinct neural activities and further explore predictive indicators in the two diseases.

METHODS

FE-MDD patients were performed resting state functional magnetic resonance imaging and followed up after scanning. After follow-up, FE-MDD patients were regrouped into FE-BD and FE-MDD patients. The study included 24 FE-BD patients, 28 FE-MDD patients, and 30 age- and sex-matched healthy controls (HC) to investigate neural activities with regional homogeneity (ReHo) analysis among the 3 groups.

RESULTS

Compared to HC, FE-BD patients displayed significantly higher ReHo values in the superior frontal gyrus, the medial superior frontal gyrus within right-side cerebral hemisphere than FE-MDD patients and HC. Compared to HC, FE-BD and FE-MDD patients displayed significant decreased ReHo values in the paracentral lobule, the precuneus and the median cingulate and paracingulate gyrus within bilateral cerebral hemisphere, and the postcentral gyrus and the precentral gyrus within the right-side. FE-BD displayed significant lower ReHo values than FE-MDD patients in these regions.

LIMITATIONS

The potential effects of medicine, age, course of disease and handedness on results could not be ignored.

CONCLUSIONS

Abnormal neural activities of frontoparietal network may provide common and distinct markers to affective disorders and scientific basis for further prediction researches of affective disorders.

Abnormal spontaneous neural activity of brain regions in patients with primary blepharospasm at rest

BACKGROUND

Primary blepharospasm (BSP) is characterized by excessive involuntary eyelid spasms without significant morphological brain abnormalities. Its neural bases remain unclear. Resting-state functional magnetic resonance imaging (rs-fMRI) is a powerful tool for exploring cerebral function mechanisms in BSP.

METHODS

Two subject groups (24 patients with BSP and 24 healthy controls) underwent rs-fMRI scans. The rs-fMRI images were analyzed using the regional homogeneity (ReHo) method to assess the local features of spontaneous brain activity. Correlation analysis was carried out to explore the relationship between the ReHo values of abnormal brain areas and clinical variables including illness duration, symptom severity, and depression/anxiety symptoms.

RESULTS

Relative to healthy controls, patients with BSP showed significantly decreased ReHo in the left superior temporal pole/left insula, left calcarine cortex, and bilateral superior medial frontal gyrus (mSFG), and increased ReHo in the bilateral supplementary motor area (SMA). There were no significant correlations between ReHo values in these brain regions and clinical variables in the patients.

CONCLUSIONS

Our results suggest that abnormal spontaneous brain activity in multiple brain regions not limited to the basal ganglia may be trait alterations in the patients, which provides more insights into the pathogenesis of BSP.

The neural markers of MRI to differentiate depression and panic disorder

Depression and panic disorder (PD) share the common pathophysiology from the perspectives of neurotransmitters. The relatively high comorbidity between depression and PD contributes to the substantial obstacles to differentiate from depression and PD, especially for the brain pathophysiology. There are significant differences in the diagnostic criteria between depression and PD. However, the paradox of similar pathophysiology and different diagnostic criteria in these two disorders were still the issues needing to be addressed. Therefore the clarification of potential difference in the field of neuroscience and pathophysiology between depression and PD can help the clinicians and scientists to understand more comprehensively about significant differences between depression and PD. The researchers should be curious about the underlying difference of pathophysiology beneath the significant distinction of clinical symptoms. In this review article, I tried to find some evidences for the differences between depression and PD, especially for neural markers revealed by magnetic resonance imaging (MRI). The distinctions of structural and functional alterations in depression and PD are reviewed. From the structural perspectives, PD seems to have less severe gray matter alterations in frontal and temporal lobes than depression. The study of white matter microintegrity reveals more widespread alterations in fronto-limbic circuit of depression patients than PD patients, such as the uncinate fasciculus and anterior thalamic radiation. PD might have a more restrictive pattern of structural alterations when compared to depression. For the functional perspectives, the core site of depression pathophysiology is the anterior subnetwork of resting-state network, such as anterior cingulate cortex, which is not significantly altered in PD. A possibly emerging pattern of fronto-limbic distinction between depression and PD has been revealed by these explorative reports. The future trend for machine learning and pattern recognition might confirm the differentiation pattern between depression and PD based on the explorative results.

Altered Local and Large-Scale Dynamic Functional Connectivity Variability in Posttraumatic Stress Disorder: A Resting-State fMRI Study

Posttraumatic stress disorder (PTSD) is a psychiatric condition that can emerge after exposure to an exceedingly traumatic event. Previous neuroimaging studies have indicated that PTSD is characterized by aberrant resting-state functional connectivity (FC). However, few existing studies on PTSD have examined dynamic changes in resting-state FC related to network formation, interaction, and dissolution over time. In this study, we compared the dynamic resting-state local and large-scale FC between PTSD patients (n = 22) and healthy controls (HC; n = 22; conducted as standard deviation in resting-state local and large-scale FC over a series of sliding windows). Local dynamic FC was examined by calculating the dynamic regional homogeneity (dReHo), and large-scale dynamic FC (dFC) was investigated between regions with significant dReHo group differences. For the PTSD patients, we also investigated the relationship between symptom severity and dFC/dReHo. Our results showed that PTSD patients were characterized by I) increased dynamic (more variable) dReHo in left precuneus (PCu); II) increased dynamic (more variable) dFC between the left PCu and left insula; and III) decreased dFC between left PCu and left inferior parietal lobe (IPL), and decreased dFC between left PCu and right PCu. However, there is no significant correlation between the clinical indicators and dReHo/dFC after the family-wise-error (FWE) correction. These findings provided the initial evidence that PTSD is characterized by aberrant patterns of fluctuating communication within brain system such as the default mode network (DMN) and among different brain systems such as the salience network and the DMN.

Aberrant brain regional homogeneity in first-episode drug-naïve patients with major depressive disorder: A voxel-wise meta-analysis

BACKGROUND

Resting-state functional magnetic resonance imaging studies have reported aberrant brain regional homogeneity (ReHo) in patients with major depressive disorder (MDD). However, the findings across studies were confounded by medication status and different depressive episodes.

METHODS

A systematic literature search of the PubMed, Embase, and Web of Science databases was conducted. We conducted a quantitative voxel-wise meta-analysis of ReHo studies, using the Seed-based d Mapping approach, in first-episode drug-naïve patients with MDD.

RESULTS

We identified 10 studies with 12 datasets suitable for inclusion, consisting of 402 first-episode drug-naïve patients with MDD and 330 healthy controls. The most consistent and robust findings were that patients with MDD relative to healthy controls exhibited increased ReHo in the left hippocampus and decreased ReHo in the left orbitofrontal cortex.

LIMITATIONS

The patient samples included in our meta-analysis were all Chinese, thus limiting the applicability of the present findings to other populations.

CONCLUSIONS

ReHo alterations in these brain regions are likely to reflect the core disease-related functional abnormalities, which are implicated in emotional dysregulation and cognitive impairment that are seen in the early stage of MDD. These findings contribute to a better understanding of the neurobiological underpinnings of MDD, and the left hippocampus and orbitofrontal cortex could serve as specific regions of interest for further investigations.

Disrupted Regional Spontaneous Neural Activity in Mild Cognitive Impairment Patients with Depressive Symptoms: A Resting-State fMRI Study

Depressive symptoms are common in individuals with mild cognitive impairment (MCI) who have an increased risk of dementia. It is currently unclear whether the pattern of spontaneous brain activity in patients with MCI differs between subjects with and without depressive symptoms. The current study sought to investigate the features of spontaneous brain activity in MCI patients with depressive symptoms (D-MCI) using coherence regional homogeneity (CReHo) analysis with resting-state functional magnetic resonance imaging (rsfMRI). We obtained rsfMRI data in 16 MCI patients with depressive symptoms and 18 nondepressed MCI patients (nD-MCI) using a 3 T scanner. Statistical analyses were performed to determine the regions in which ReHo differed between the two groups in specific frequency bands, slow-4 (0.027–0.073 Hz) and slow-5 (0.010–0.027 Hz), and typical bands (0.01–0.08 Hz). Correlation analyses were performed between the CReHo index of these regions and clinical variables to evaluate the relationship between CReHo and pathophysiological measures in the two groups. Our results showed that D-MCI patients exhibited significantly higher CReHo in the left Heschl's gyrus and left thalamus and lower CReHo in the left postcentral gyrus in the typical frequency band. In the slow-4 frequency band, D-MCI patients showed significantly higher CReHo in the left Heschl's gyrus and left thalamus. In the slow-5 frequency band, D-MCI patients exhibited significantly lower CReHo in the superior medial prefrontal gyrus. In addition, the results revealed that CReHo values in the left thalamus were positively correlated with Hamilton Depression Rating Scale (HAMD) scores in D-MCI patients. These results suggest that the sensorimotor network may be one of the main pathophysiological factors in D-MCI.

Gray Matter Volume Changes in Patients With Acute Eye Pain: A Voxel-Based Morphometry Study

PURPOSE

The present study was attempted to compare the differences in gray matter volume (GMV) between the acute eye pain (EP) patients and the healthy controls (HCs) using voxel-based morphometry (VBM), and to explore the relationship with clinical features and behavioral performance.

METHODS

A total of 24 patients (17 males, 7 females) with acute EP and 24 (17 males, 7 females) age-, sex-, and education-matched HCs were recruited from the Ophthalmology Department of the First Affiliated Hospital of Nanchang University. Functional magnetic resonance imaging (fMRI) scans were conducted in all subjects. We analyzed the original three-dimensional (3D) T1 brain images by VBM and compared the GMV values with the HCs. The acute EP patients can be distinguished from the HCs by receiver operating characteristic (ROC) curve.

RESULTS

Compared with HCs, the acute EP patients had significantly lower GMV values in the brain regions of the left cerebellum posterior lobe, the left limbic lobe, the right insula, the left insula, the left thalamus, the left caudate, and the right cuneus. In addition, the WMV values of the whole brain in acute EP patients decreased slightly.

CONCLUSIONS

These results demonstrated that the acute EP patients showed an abnormal reduction in GMV in some brain regions, which might provide valuable information for further exploration of underlying neural mechanisms. These abnormal brain regions may reflect the functional disorders of acute EP patients in somatosensory, motor, cognitive functions, and so on.

TRANSLATIONAL RELEVANCE

The VBM study provides a diagnostic method for identifying the cause of acute EP, additionally, a novel direction was presented for further exploration of underlying neural mechanisms of acute EP.

Cerebellar Cortex as a Therapeutic Target for Neurostimulation

Non-invasive stimulation of the cerebellum is growingly applied both in the clinic and in research settings to modulate the activities of cerebello-cerebral loops. The anatomical location of the cerebellum, the high responsiveness of the cerebellar cortex to magnetic/electrical stimuli, and the implication of the cerebellum in numerous cerebello-cerebral networks make the cerebellum an ideal target for investigations and therapeutic purposes. In this mini-review, we discuss the potentials of cerebellar neuromodulation in major brain disorders in order to encourage large-scale sham-controlled research and explore this therapeutic aid further.

Increased coherence-based regional homogeneity in resting-state patients with first-episode, drug-naive somatization disorder

BACKGROUND

Abnormal neural activity has been observed in patients with somatization disorder (SD), especially in brain regions of the default-mode network (DMN). In this study, a coherence-based regional homogeneity (Cohe-ReHo) approach was used to detect abnormal regional synchronization in patients with SD, which might be used to differentiate the patients from the controls.

METHODS

We recruited 25 patients with SD and 28 healthy controls. The imaging data of the participants were analyzed using the Cohe-ReHo approach. LIBSVM (a library for support vector machines) was utilized to verify whether abnormal Cohe-ReHo values could be applied to separate patients with SD from healthy controls.

RESULTS

Compared with healthy controls, patients with SD showed an increased Cohe-ReHo in the left medial prefrontal cortex/anterior cingulate cortex (MPFC/ACC) (t = 5.5017, p < 0.001). No correlations were detected between the increased Cohe-ReHo values and clinical variables of the patients. The Cohe-ReHo values in the left MPFC/ACC could be applied to distinguish patients from controls with a sensitivity and a specificity of 84.00% and 85.71%, respectively.

CONCLUSIONS

An increased Cohe-ReHo was observed in the anterior DMN of the patients and could be applied as a marker to distinguish patients from healthy controls. These results highlighted the importance of the DMN in the pathophysiology of SD.