Abnormal Default Mode Network Homogeneity in Treatment-Naive Patients With First-Episode Depression

Knowledge, attitude, and practice of depression among university students

INTRODUCTION

This study aimed to investigate the knowledge, attitude, and practice (KAP) of depression among university students.

METHODS

A cross-sectional survey was carried out across randomly selected universities in Shandong Province from October 25, 2023, to November 8, 2023. Demographic information and KAP scores were assessed through the administration of questionnaires. The reliability of the questionnaire was confirmed with a Cronbach's alpha coefficient of 0.816 and the Kaiser-Meyer-Olkin measure of 0.894.

RESULTS

This study included 2448 university students, with 1489 (60.8%) females. The median scores for KAP were 20 (Interquartile Range (IQR): 17-21), 26 (IQR: 23-28), and 35 (IQR: 32-38), respectively. Multivariate regression analysis indicated that being a junior (odds ratio [OR] = 0.720, 95% Confidence Interval (CI): 0.538-0.965, p = .028), senior or above (OR = 0.474, 95% CI: 0.325-0.691, p < .001), having divorced parents (OR = 0.618, 95% CI: 0.409-0.933, p = .022), having direct relatives with depression (OR = 0.710, 95% CI: 0.589-0.856, p < .001), and lacking intimate friends (OR = 0.344, 95% CI: 0.245-0.484, p < .001) were negatively associated with practice. Only having an attitude score of ≥26 (OR = 5.076, 95% CI: 4.230-6.091, p < .001) was significantly and positively associated with practice.

CONCLUSION

University students had insufficient knowledge, positive attitude, and passive practice toward depression. Clinical interventions should focus on enhancing the understanding and management of depression among university students, particularly through targeted educational programs and support groups, to bridge the gap between knowledge and practice and foster a proactive approach to mental health care.

Morinda officinalis oligosaccharides modulate the default-mode network homogeneity in major depressive disorder at rest

BACKGROUND

While prior studies have explored the efficacy of Morinda officinalis oligosaccharides (MOs) as a treatment for patients with major depressive disorder (MDD), the mechanistic basis for the effects of MOs on brain function or the default-mode network (DMN) has yet to be characterized. The objective of this was to examine the effects of MOs treatment on functional connectivity in different regions of the DMN.

METHODS

In total, 27 MDD patients and 29 healthy control subjects (HCs) underwent resting-state functional magnetic resonance imaging. The patients were then treated with MOs for 8 weeks, and scanning was performed at baseline and the end of the 8-week treatment period. Changes in DMN homogeneity associated with MOs treatment were assessed using network homogeneity (NH) analyses of the imaging data, and pattern classification approaches were employed to determine whether abnormal baseline NH deficits could differentiate between MDD patients and controls. The ability of NH abnormalities to predict patient responses to MOs treatment was also evaluated.

RESULTS

Relative to HCs, patients exhibited a baseline reduction in NH values in the right precuneus (PCu). At the end of the 8-week treatment period, the MDD patients showed reduced and increased NH values in the right PCu and left superior medial frontal gyrus (SMFG), respectively. Compared to these patients at baseline, the 8-week MOs treatment was associated with reduced NH values in the right angular gyrus and increased NH values in the left middle temporal gyrus and the right PCu. Support vector machine (SVM) analyses revealed that NH abnormalities in the right PCu and left SMFG were the most accurate (87.50%) for differentiating between MDD patients and HCs.

CONCLUSION

These results indicated that MOs treatment could alter default-mode NH in patients with MDD. The results provide a foundation for elucidation of the effects of MOs on brain function and suggest that the distinctive NH patterns observed in this study may be useful as imaging biomarkers for distinguishing between patients with MDD and healthy subjects.

Intelligent classification of major depressive disorder using rs-fMRI of the posterior cingulate cortex

Major Depressive Disorder (MDD) is a widespread psychiatric condition that affects a significant portion of the global population. The classification and diagnosis of MDD is crucial for effective treatment. Traditional methods, based on clinical assessment, are subjective and rely on healthcare professionals' expertise. Recently, there's growing interest in using Resting-State Functional Magnetic Resonance Imaging (rs-fMRI) to objectively understand MDD's neurobiology, complementing traditional diagnostics. The posterior cingulate cortex (PCC) is a pivotal brain region implicated in MDD which could be used to identify MDD from healthy controls. Thus, this study presents an intelligent approach based on rs-fMRI data to enhance the classification of MDD. Original rs-fMRI data were collected from a cohort of 430 participants, comprising 197 patients and 233 healthy controls. Subsequently, the data underwent preprocessing using DPARSF, and the amplitudes of low-frequency fluctuation values were computed to reduce data dimensionality and feature count. Then data associated with the PCC were extracted. After eliminating redundant features, various types of Support Vector Machines (SVMs) were employed as classifiers for intelligent categorization. Ultimately, we compared the performance of each algorithm, along with its respective optimal classifier, based on classification accuracy, true positive rate, and the area under the receiver operating characteristic curve (AUC-ROC). Upon analyzing the comparison results, we determined that the Random Forest (RF) algorithm, in conjunction with a sophisticated Gaussian SVM classifier, demonstrated the highest performance. Remarkably, this combination achieved a classification accuracy of 81.9 % and a true positive rate of 92.9 %. In conclusion, our study improves the classification of MDD by supplementing traditional methods with rs-fMRI and machine learning techniques, offering deeper neurobiological insights and aiding accuracy, while emphasizing its role as an adjunct to clinical assessment.

Frontoparietal network homogeneity as a biomarker for mania and remitted bipolar disorder and a predictor of early treatment response in bipolar mania patient

OBJECTIVE

Previous studies have revealed the frontoparietal network (FPN) plays a key role in the imaging pathophysiology of bipolar disorder (BD). However, network homogeneity (NH) in the FPN among bipolar mania (BipM), remitted bipolar disorder (rBD), and healthy controls (HCs) remains unknown. The present study aimed to explore whether NH within the FPN can be used as an imaging biomarker to differentiate BipM from rBD and to predict treatment efficacy for patients with BipM.

METHODS

Sixty-six patients with BD (38 BipM and 28 rBD) and 60 HCs participated in resting-state functional magnetic resonance imaging and neuropsychological tests. Independent component analysis and NH analysis were applied to analyze the imaging data.

RESULTS

Relative to HCs, BipM patients displayed increased NH in the left middle frontal gyrus (MFG), and rBD patients displayed increased NH in the right inferior parietal lobule (IPL). Compared to rBD patients, BipM patients displayed reduced NH in the right IPL. Furthermore, support vector machine results exhibited that NH values in the right IPL could distinguish BipM patients from rBD patients with 69.70 %, 57.89 %, and 91.67 % for accuracy, sensitivity, and specificity, respectively, and support vector regression results exhibited a significant association between predicted and actual symptomatic improvement based on the reduction ratio of the Young` Mania Rating Scale total scores (r = 0.466, p < 0.01).

CONCLUSION

The study demonstrated distinct NH values in the FPN could serve as a valuable neuroimaging biomarker capable of differentiating patients with BipM and rBD, and NH values of the left MFG as a potential predictor of early treatment response in patients with BipM.

The Ripple Effect: Unveiling the Bidirectional Relationship Between Negative Life Events and Depressive Symptoms in Medical Cadets

Background

Previous studies have explored the relationship between negative life events and depression, but little is known about the bidirectional relationship between negative life events and depression, particularly in specific groups of medical cadets.

Purpose

This study aimed to explore the relationship between negative life events and depressive symptoms among medical cadets during their four years of college.

Methods

An analysis of 4-wave longitudinal data collected from 2015-2018 was conducted using a cross-lagged panel network (CLPN) model to explore the complex causal relationship between negative life events and depressive symptoms in medical cadets (N=433).

Results

We found differences in negative life events and depressive symptoms among medical cadets across four network models over four years of university. Nodes A-21, A-20, A-23 and A-24, and depressive symptoms D-6 showed greater lagged effect values.

Conclusion

Our findings suggest that there is a lagged and mutually causal interaction between negative life events and depressive symptoms in medical cadets over 4 years of college, but that the predictability of negative life events is more important. However, more attention needs to be paid to the predictive role of depressive symptoms, especially those in early life which are often overlooked. Our study provides new insights into the relationship between negative life events and depressive symptoms in university students and helps to refine strategies for prevention and intervention of depression.

Hypoconnectivity within the cingulo-opercular network in patients with mild cognitive impairment in Chinese communities

INTRODUCTION

At rest, the brain's higher cognitive systems engage in correlated activity patterns, forming networks. With mild cognitive impairment (MCI), it is essential to understand how functional connectivity within and between resting-state networks changes. This study used resting-state functional connectivity to identify significant differences within and between the cingulo-opercular network (CON) and default mode network (DMN).

METHODS

We assessed cognitive function in patients using the Chinese version of the Alzheimer's disease assessment scale-Cognitive subscale (ADAS-Cog). A group of MCI subjects (ages 60-83 years, n = 45) was compared to age-matched healthy controls (n = 70). Resting-state functional connectivity was used to determine functional connectivity strength within and between the CON and DMN.

RESULTS

Compared to healthy controls, the MCI group showed significantly lower functional connectivity within the CON (F = 10.76, df = 1, p = 0.001, FDR adjusted p = 0.003). Additionally, the MCI group displayed no distinct differences in functional connectivity within DMN (F = 0.162, df = 1, p = 0.688, FDR adjusted p = 0.688) and between CON and DMN (F = 2.270, df = 1, p = 0.135, FDR adjusted p = 0.262). Moreover, we found no correlation between ADAS-Cog and within- or between-connectivity metrics among subjects with MCI.

CONCLUSIONS

Our findings indicate that specific patterns of hypoconnectivity within CON circuitry may characterize MCI relative to healthy controls. This work improves our understanding of network dysfunction underlying MCI and could inform more targeted treatment.

Electroconvulsive therapy-induced neuroimaging alterations measured by cerebral blood flow in adolescents with major depressive disorder

BACKGROUND

Electroconvulsive therapy (ECT) is a novel treatment strategy for adolescents with major depressive disorder (MDD). However, its related neurobiological changes associated with ECT remain undetermined.

OBJECTIVE

To elucidate the impact of ECT on the regional cerebral blood flow (CBF), and to identify alterations in the CBF associated with clinical outcomes in adolescents with MDD.

METHODS

Fifty-two treatment-naive adolescents who had experienced their first episode of MDD and 36 healthy controls (HCs) were recruited. To assess baseline parameters, all subjects were scanned with arterial spin labeling resting-state functional magnetic resonance imaging (ASL-fMRI) at the beginning of the study. Subsequently, 27 MDD adolescents were re-scanned after 2 weeks after ECT. CBF imaging was used for the prediction of specific clinical outcomes. Lastly, the associations between alterations seen on brain imaging alterations after ECT and ECT clinical efficacy (ΔHAMD scores) were determined.

RESULTS

Relative to HCs, adolescents with MDD exhibited reduced CBF in the left medial superior frontal gyrus (SFGmed) (cluster = 243, peak t = -3.9373, and P < 0.001) and augmented CBF in the right percental gyrus (PerCG) (cluster = 321, peak t = 4.3332, and P < 0.001) at baseline. Following ECT, MDD adolescents exhibited reduced CBF in the right fusiform gyrus (FFG) (cluster = 309, peak t = -4.346, and P < 0.001) and left hippocampus (HIP) (cluster = 290, peak t = -4.706, and P < 0.001), and enhanced CBF in the left orbital part of the inferior frontal gyrus (ORBinf) (cluster = 214, peak t = 4.073, and P < 0.001). Correlation analysis suggested an inverse association between ΔHAMD scores and CBF values in the left ORBinf (R² = 0.196, P = 0.021).

CONCLUSIONS

It was found that ECT resulted in alterations in CBF in specific brain areas, highlighting the significance of ORBinf in ECT pathophysiology in MDD adolescents.

Transcutaneous Electrical Cranial-Auricular Acupoint Stimulation Modulating the Brain Functional Connectivity of Mild-to-Moderate Major Depressive Disorder: An fMRI Study Based on Independent Component Analysis

Evidence has shown the roles of taVNS and TECS in improving depression but few studies have explored their synergistic effects on MDD. Therefore, the treatment responsivity and neurological effects of TECAS were investigated and compared to escitalopram, a commonly used medication for depression. Fifty patients with mild-to-moderate MDD (29 in the TECAS group and 21 in another) and 49 demographically matched healthy controls were recruited. After an eight-week treatment, the outcomes of TECAS and escitalopram were evaluated by the effective rate and reduction rate based on the Montgomery-Asberg Depression Rating Scale, Hamilton Depression Rating Scale, and Hamilton Anxiety Rating Scale. Altered brain networks were analyzed between pre- and post-treatment using independent component analysis. There was no significant difference in clinical scales between TECAS and escitalopram but these were significantly decreased after each treatment. Both treatments modulated connectivity of the default mode network (DMN), dorsal attention network (DAN), right frontoparietal network (RFPN), and primary visual network (PVN), and the decreased PVN-RFPN connectivity might be the common brain mechanism. However, there was increased DMN-RFPN and DMN-DAN connectivity after TECAS, while it decreased in escitalopram. In conclusion, TECAS could relieve symptoms of depression similarly to escitalopram but induces different changes in brain networks.

Decreased degree centrality values as a potential neuroimaging biomarker for migraine: A resting-state functional magnetic resonance imaging study and support vector machine analysis

OBJECTIVE

Misdiagnosis and missed diagnosis of migraine are common in clinical practice. Currently, the pathophysiological mechanism of migraine is not completely known, and its imaging pathological mechanism has rarely been reported. In this study, functional magnetic resonance imaging (fMRI) technology combined with a support vector machine (SVM) was employed to study the imaging pathological mechanism of migraine to improve the diagnostic accuracy of migraine.

METHODS

We randomly recruited 28 migraine patients from Taihe Hospital. In addition, 27 healthy controls were randomly recruited through advertisements. All patients had undergone the Migraine Disability Assessment (MIDAS), Headache Impact Test - 6 (HIT-6), and 15 min magnetic resonance scanning. We ran DPABI (RRID: SCR_010501) on MATLAB (RRID: SCR_001622) to preprocess the data and used REST (RRID: SCR_009641) to calculate the degree centrality (DC) value of the brain region and SVM (RRID: SCR_010243) to classify the data.

RESULTS

Compared with the healthy controls (HCs), the DC value of bilateral inferior temporal gyrus (ITG) in patients with migraine was significantly lower and that of left ITG showed a positive linear correlation with MIDAS scores. The SVM results showed that the DC value of left ITG has the potential to be a diagnostic biomarker for imaging, with the highest diagnostic accuracy, sensitivity, and specificity for patients with migraine of 81.82, 85.71, and 77.78%, respectively.

CONCLUSION

Our findings demonstrate abnormal DC values in the bilateral ITG among patients with migraine, and the present results provide insights into the neural mechanism of migraines. The abnormal DC values can be used as a potential neuroimaging biomarker for the diagnosis of migraine.

Hyperconnectivity and altered interactions of a nucleus accumbens network in post-stroke depression

Post-stroke depression is a common complication of stroke. To date, no consistent locus of injury is associated with this complication. Here, we probed network dynamics and structural alterations in post-stroke depression in four functional circuits linked to major depressive disorder and a visual network, which served as a control network. Forty-four participants with recent stroke (mean age = 69.03, standard deviation age = 8.59, age range = 51–86 and gender: female = 10) and 16 healthy volunteers (mean age = 71.53, standard deviation age = 10.62, age range = 51–84 and gender: female = 11) were imaged with 3-Tesla structural, diffusion and resting-state functional MRI. The Geriatric Depression Scale was administered to measure depression severity. Associations between depression severity and functional connectivity were investigated within networks seeded from nucleus accumbens, amygdala, dorsolateral prefrontal cortex and primary visual cortex. In addition, the default mode network was identified by connectivity with medial prefrontal cortex and posterior cingulate cortex. Circuits that exhibited altered activity associated with depression severity were further investigated by extracting within-network volumetric and microstructural measures from structural images. In the stroke group, functional connectivity within the nucleus accumbens-seeded network (left hemisphere: P = 0.001; and right hemisphere: P = 0.004) and default mode network (cluster one: P &lt; 0.001; and cluster two: P &lt; 0.001) correlated positively with depressive symptoms. Normal anticorrelations between these two networks were absent in patients with post-stroke depression. Grey matter volume of the right posterior cingulate cortex (Pearson correlation coefficient = −0.286, P = 0.03), as well as microstructural measures in the posterior cingulate cortex (right: Pearson correlation coefficient = 0.4, P = 0.024; and left: Pearson correlation coefficient = 0.3, P = 0.048), right medial prefrontal cortex (Pearson correlation coefficient = 0.312, P = 0.039) and the medial forebrain bundle (Pearson correlation coefficient = 0.450, P = 0.003), a major projection pathway interconnecting the nucleus accumbens-seeded network and linking to medial prefrontal cortex, were associated with depression severity. Depression after stroke is marked by reduced mutual inhibition between functional circuits involving nucleus accumbens and default mode network as well as volumetric and microstructural changes within these networks. Aberrant network dynamics present in patients with post-stroke depression are therefore likely to be influenced by secondary, pervasive alterations in grey and white matter, remote from the site of injury.

Abnormal Ventral Somatomotor Network Homogeneity in Patients With Temporal Lobe Epilepsy

BACKGROUND

Abnormalities of functional connectivity in the somatomotor network have been thought to play an essential role in the pathophysiology of epilepsy. However, there has been no network homogeneity (NH) study about the ventral somatomotor network (VSN) in patients with temporal lobe epilepsy (TLE). Therefore, we explored the NH of the VSN in TLE patients in this study.

METHODS

The sample included 52 patients with left temporal lobe epilepsy, 83 patients with right temporal lobe epilepsy, and 68 healthy controls. The NH method was utilized to analyze the resting-state functional magnetic resonance imaging data.

RESULTS

Compared to the controls, rTLE patients had significantly higher NH in the bilateral postcentral gyrus, and significantly lower NH in the bilateral Rolandic operculum and the right superior temporal gyrus (STG). The NH values of the left postcentral gyrus were significantly higher in lTLE patients than in the healthy controls, and lTLE patients had lower NH in the right Rolandic operculum. The altered NH in the postcentral gyrus was negatively correlated with the illness duration, and the decreased NH in the left Rolandic operculum was negatively correlated with the executive control reaction time (ECRT).

CONCLUSION

Our findings suggest that altered NH of the postcentral gyrus, Rolandic operculum and STG might be associated with the pathophysiology of TLE, and thus, highlight the contribution of the VSN to the pathophysiology of TLE.

The Bilateral Precuneus as a Potential Neuroimaging Biomarker for Right Temporal Lobe Epilepsy: A Support Vector Machine Analysis

Background and Objective

While evidence has demonstrated that the default-mode network (DMN) plays a key role in the broad-scale cognitive problems that occur in right temporal lobe epilepsy (rTLE), little is known about alterations in the network homogeneity (NH) of the DMN in TLE. In this study, we used the NH method to investigate the NH of the DMN in TLE at rest, and an support vector machine (SVM) method for the diagnosis of rTLE.

Methods

A total of 43 rTLE cases and 42 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (rs-fMRI). Imaging data were analyzed with the NH and SVM methods.

Results

rTLE patients have a decreased NH in the right inferior temporal gyrus (ITG) and left middle temporal gyrus (MTG), but increased NH in the bilateral precuneus (PCu) and right inferior parietal lobe (IPL), compared with HCs. We found that rTLE had a longer performance reaction time (RT). No significant correlation was found between abnormal NH values and clinical variables of the patients. The SVM results showed that increased NH in the bilateral PCu as a diagnostic biomarker distinguished rTLE from HCs with an accuracy of 74.12% (63/85), a sensitivity 72.01% (31/43), and a specificity 72.81% (31/42).

Conclusion

These findings suggest that abnormal NH of the DMN exists in rTLE, and highlights the significance of the DMN in the pathophysiology of cognitive problems occurring in rTLE, and the bilateral PCu as a neuroimaging diagnostic biomarker for rTLE.

Decreased Connectivity in Precuneus of the Ventral Attentional Network in First-Episode, Treatment-Naïve Patients With Major Depressive Disorder: A Network Homogeneity and Independent Component Analysis

BACKGROUND AND OBJECTIVE

The ventral attentional network (VAN) can provide quantitative information on cognitive problems in patients with major depressive disorder (MDD). Nevertheless, little is known about network homogeneity (NH) changes in the VAN of these patients. The aim of this study was to examine the NH values in the VAN by independent component analysis (ICA) and compare the NH values between MDD patients and the normal controls (NCs).

METHODS

Attentional network test and resting-state functional magnetic resonance imaging (rs-fMRI) data were collected from 73 patients, and 70 NCs matched by gender, age, and education years. ICA and NH were employed to evaluate the data. Moreover, the NH values were compared, and Spearman's rank correlation analysis was used to assess the correlations with the executive control reaction time (ECRT).

RESULTS

Our results showed that the first-episode, treatment-naive MDD patients had decreased NH in the right precuneus (PCu) and abnormal ECRT compared with NCs. However, no significant correlation was found between the NH values and measured clinical variables.

CONCLUSION

Our results highlight the potential importance of VAN in the pathophysiology of cognitive problems in MDD, thus offering new directions for future research on MDD.

The Prominent Role of the Temporal Lobe in Premenstrual Syndrome and Premenstrual Dysphoric Disorder: Evidence From Multimodal Neuroimaging

Premenstrual syndrome (PMS) is a group of psychological, physical, and behavioral symptoms that recur with the menstrual cycle, usually occurring a few days before menstruation and ceasing with the onset of menstruation. Premenstrual dysphoric disorder (PMDD) is a severe form of PMS that has been included in a subcategory of depression in the Diagnostic and Statistical Manual of Mental Disorders (DSM-V) according to the latest diagnostic criteria. Patients usually present with mild to moderate emotional and physical symptoms that affect their routine work, social activities, and family lives. The pathogenesis of PMDD remains unclear, and some researchers believe that it is related to fluctuations in ovarian hormone levels. However, the details of the interrelationships and regulating effects between ovarian hormones, symptoms, and the brain need to be more comprehensively determined. Recent studies have revealed some novel findings on PMS and PMDD based on brain morphology, function, and metabolism. Additionally, multiple studies have suggested that PMS and PMDD are closely related to brain structural and functional variations in certain core temporal lobe regions, such as the amygdala and hippocampus. We summarized neuroimaging studies of PMS and PMDD related to the temporal lobe by retrospectively reviewing relevant literature over the past decade. This review contributes to further clarifying the significant role of the temporal lobe in PMS and PMDD and understanding the neurochemical links between hormones, symptoms, and the brain.

Abnormal regional signal in the left cerebellum as a potential neuroimaging biomarker of sudden sensorineural hearing loss

OBJECTIVE

While prior reports have characterized visible changes in neuroimaging findings in individuals suffering from sudden sensorineural hearing loss (SSNHL), the utility of regional homogeneity (ReHo) as a means of diagnosing SSNHL has yet to be established. The present study was thus conducted to assess ReHo abnormalities in SSNHL patients and to establish whether these abnormalities offer value as a diagnostic neuroimaging biomarker of SSNHL through a support vector machine (SVM) analysis approach.

METHODS

Resting-state functional magnetic resonance imaging (rs-fMRI) analyses of 27 SSNHL patients and 27 normal controls were conducted, with the resultant imaging data then being analyzed based on a combination of ReHo and SVM approaches.

RESULTS

Relative to normal control individuals, patients diagnosed with SSNHL exhibited significant reductions in ReHo values in the left cerebellum, bilateral inferior temporal gyrus (ITG), left superior temporal pole (STP), right parahippocampal gyrus (PHG), left posterior cingulum cortex (PCC), and right superior frontal gyrus (SFG). SVM analyses suggested that reduced ReHo values in the left cerebellum were associated with high levels of diagnostic accuracy (96.30%, 52/54), sensitivity (92.59%, 25/27), and specificity (100.00%, 27/27) when distinguishing between SSNHL patients and control individuals.

CONCLUSION

These data suggest that SSNHL patients exhibit abnormal resting-state neurological activity, with changes in the ReHo of the left cerebellum offering value as a diagnostic neuroimaging biomarker associated with this condition.

Altered voxel-mirrored homotopic connectivity in right temporal lobe epilepsy as measured using resting-state fMRI and support vector machine analyses

BACKGROUND

Prior reports revealed abnormalities in voxel-mirrored homotopic connectivity (VMHC) when analyzing neuroimaging data from patients with various psychiatric conditions, including temporal lobe epilepsy (TLE). Whether these VHMC changes can be leveraged to aid in the diagnosis of right TLE (rTLE), however, remains to be established. This study was thus developed to examine abnormal VMHC findings associated with rTLE to determine whether these changes can be used to guide rTLE diagnosis.

METHODS

The resultant imaging data of resting-state functional MRI (rs-fMRI) analyses of 59 patients with rTLE and 60 normal control individuals were analyzed using VMHC and support vector machine (SVM) approaches.

RESULTS

Relative to normal controls, patients with rTLE were found to exhibit decreased VMHC values in the bilateral superior and the middle temporal pole (STP and MTP), the bilateral middle and inferior temporal gyri (MTG and ITG), and the bilateral orbital portion of the inferior frontal gyrus (OrbIFG). These patients further exhibited increases in VMHC values in the bilateral precentral gyrus (PreCG), the postcentral gyrus (PoCG), and the supplemental motor area (SMA). The ROC curve of MTG VMHC values showed a great diagnostic efficacy in the diagnosis of rTLE with AUCs, sensitivity, specificity, and optimum cutoff values of 0.819, 0.831, 0.717, and 0.465. These findings highlight the value of the right middle temporal gyrus (rMTG) when differentiating between rTLE and control individuals, with a corresponding SVM analysis yielding respective accuracy, sensitivity, and specificity values of 70.59% (84/119), 78.33% (47/60), and 69.49% (41/59).

CONCLUSION

In summary, patients with rTLE exhibit various forms of abnormal functional connectivity, and SVM analyses support the potential value of abnormal VMHC values as a neuroimaging biomarker that can aid in the diagnosis of this condition.

The decreased connectivity in middle temporal gyrus can be used as a potential neuroimaging biomarker for left temporal lobe epilepsy

OBJECTIVE

We aimed to explore voxel-mirrored homotopic connectivity (VMHC) abnormalities between the two brain hemispheres in left temporal lobe epilepsy (lTLE) patients and to determine whether these alterations could be leveraged to guide lTLE diagnosis.

MATERIALS AND METHODS

Fifty-eight lTLE patients and sixty healthy controls (HCs) matched in age, sex, and education level were recruited to receive resting state functional magnetic resonance imaging (rs-fMRI) scan. Then VHMC analyses of bilateral brain regions were conducted based on the results of these rs-fMRI scans. The resultant imaging data were further analyzed using support vector machine (SVM) methods.

RESULTS

Compared to HCs, patients with lTLE exhibited decreased VMHC values in the bilateral middle temporal gyrus (MTG) and middle cingulum gyrus (MCG), while no brain regions in these patients exhibited increased VMHC values. SVM analyses revealed the diagnostic accuracy of reduced bilateral MTG VMHC values to be 75.42% (89/118) when differentiating between lTLE patients and HCs, with respective sensitivity and specificity values of 74.14% (43/58) and 76.67% (46/60).

CONCLUSION

Patients with lTLE exhibit abnormal VMHC values corresponding to the impairment of functional coordination between homotopic regions of the brain. These altered MTG VMHC values may also offer value as a robust neuroimaging biomarker that can guide lTLE patient diagnosis.

Abnormal Fractional Amplitude of Low-Frequency Fluctuation as a Potential Imaging Biomarker for First-Episode Major Depressive Disorder: A Resting-State fMRI Study and Support Vector Machine Analysis

Objective: Major depressive disorder (MDD) is a psychiatric disorder with serious negative health outcomes; however, there is no reliable method of diagnosis. This study explored the clinical diagnostic value of the fractional amplitude of low-frequency fluctuation (fALFF) based on the support vector machine (SVM) method for the diagnosis of MDD. Methods: A total of 198 first-episode MDD patients and 234 healthy controls were involved in this study, and all participants underwent resting-state functional magnetic resonance imaging (fMRI) scanning. Imaging data were analyzed with the fALFF and SVM methods. Results: Compared with the healthy controls, the first-episode MDD patients showed higher fALFF in the left mid cingulum, right precuneus, and left superior frontal gyrus (SFG). The increased fALFF in these three brain regions was positively correlated with the executive control reaction time (ECRT), and the increased fALFF in the left mid cingulum and left SFG was positively correlated with the 17-item Hamilton Rating Scale for Depression (HRSD-17) scores. The SVM results showed that increased fALFF in the left mid cingulum, right precuneus, and left SFG exhibited high diagnostic accuracy of 72.92% (315/432), 71.76% (310/432), and 73.84% (319/432), respectively. The highest diagnostic accuracy of 76.39% (330/432) was demonstrated for the combination of increased fALFF in the right precuneus and left SFG, along with a sensitivity of 84.34% (167/198), and a specificity of 70.51% (165/234). Conclusion: Increased fALFF in the left mid cingulum, right precuneus, and left SFG may serve as a neuroimaging marker for first-episode MDD. The use of the increased fALFF in the right precuneus and left SFG in combination showed the best diagnostic value.

Abnormal Network Properties and Fiber Connections of DMN across Major Mental Disorders: A Probability Tracing and Graph Theory Study

The default mode network (DMN) is related to brain functions and its abnormalities were associated with mental disorders' pathophysiology. To further understand the common and distinct DMN alterations across disorders, we capitalized on the probability tracing method and graph theory to analyze the role of DMN across three major mental disorders. A total of 399 participants (156 schizophrenia [SCZ], 90 bipolar disorder [BP], 58 major depression disorder [MDD], and 95 healthy controls [HC]) completed magnetic resonance imaging (MRI)-scanning, clinical, and cognitive assessment. The MRI preprocessing of diffusion-tensor-imaging was conducted in FMRIB Software Library and probabilistic fiber tracking was applied by PANDA. This study had three main findings. First, patient groups showed significantly lower cluster coefficient in whole-brain compared with HC. SCZ showed significantly longer characteristic path compared with HC. Second, patient groups showed inter-group specificity in abnormalities of DMN connections. Third, SCZ was sensitive to left_medial_superior_frontal_gyrus (L_SFGmed)-right_anterior_cingulate_gyrus (R_ACG) connection relating to positive symptoms; left_ACG-right_ACG connection was the mania's antagonistic factor in BP. This trans-diagnostic study found disorder-specific structural abnormalities in the fiber connection of R_SFGmed-L_SFGmed-R_ACG_L_ACG within DMN, where SCZ showed more disconnections compared with other disorders. And these connections are diagnosis-specifically correlated to phenotypes. The current study may provide further evidence of shared and distinct endo-phenotypes across psychopathology.

Altered gray matter structural covariance networks in postpartum depression: a graph theoretical analysis

BACKGROUND

Postpartum depression (PPD) is a serious postpartum mental health problem worldwide. To date, minimal is known about the alteration of topographical organization in the brain structural covariance network of patients with PPD. This study investigates the brain structural covariance networks of patients with PPD by using graph theoretical analysis.

METHODS

High-resolution 3D T1 structural images were acquired from 21 drug-naive patients with PPD and 18 healthy postpartum women. Cortical thickness was extracted from 64 brain regions to construct the whole-brain structural covariance networks by calculating the Pearson correlation coefficients, and their topological properties (e.g., small-worldness, efficiency, and nodal centrality) were analyzed by using graph theory. Nonparametric permutation tests were further used for group comparisons of topological metrics. A node was set as a hub if its betweenness centrality (BC) was at least two standard deviations higher than the mean nodal centrality. Network-based statistic (NBS) was used to determine the connected subnetwork.

RESULTS

The PPD and control groups showed small-worldness of group networks, but the small-world network was more evidently in the PPD group. Moreover, the PPD group showed increased network local efficiency and almost similar network global efficiency. However, the difference of the network metrics was not significant across the range of network densities. The hub nodes of the patients with PPD were right inferior parietal lobule (BC = 13.69) and right supramarginal gyrus (BC = 13.15), whereas those for the HCs were left cuneus (BC = 14.96), right caudal anterior-cingulate cortex (BC = 15.51), and right precuneus gyrus (BC = 15.74). NBS demonstrated two disrupted subnetworks that are present in PPD: the first subnetwork with decreased internodal connections is mainly involved in the cognitive-control network and visual network, and the second subnetwork with increased internodal connections is mainly involved in the default mode network, cognitive-control network and visual network.

CONCLUSIONS

This study demonstrates the alteration of topographical organization in the brain structural covariance network of patients with PPD, providing in sight on the notion that PPD could be characterized as a systems-level disorder.

Alterations in intrinsic functional networks in Parkinson's disease patients with depression: A resting-state functional magnetic resonance imaging study

Aims

The aim of this research was to investigate the alterations in functional brain networks and to assess the relationship between depressive impairment and topological network changes in Parkinson's disease (PD) patients with depression (DPD).

Methods

Twenty‐two DPD patients, 23 PD patients without depression (NDPD), and 25 matched healthy controls (HCs) were enrolled. All participants were examined by resting‐state functional magnetic resonance imaging scans. Graph theoretical analysis and network‐based statistic methods were used to analyze brain network topological properties and abnormal subnetworks, respectively.

Results

The DPD group showed significantly decreased local efficiency compared with the HC group (P = .008, FDR corrected). In nodal metrics analyses, the degree of the right inferior occipital gyrus (P = .0001, FDR corrected) was positively correlated with the Hamilton Depression Rating Scale scores in the DPD group. Meanwhile, the temporal visual cortex, including the bilateral middle temporal gyri and right inferior temporal gyrus in the HC and NDPD groups and the left posterior cingulate gyrus in the NDPD group, was defined as hub region, but not in the DPD group. Compared with the HC group, the DPD group had extensive weakening of connections between the temporal‐occipital visual cortex and the prefrontal‐limbic network.

Conclusions

These results suggest that PD depression is associated with disruptions in the topological organization of functional brain networks, mainly involved the temporal‐occipital visual cortex and the posterior cingulate gyrus and may advance our current understanding of the pathophysiological mechanisms underlying DPD.

Aberrant dorsal attention network homogeneity in patients with right temporal lobe epilepsy

The dorsal attention network (DAN) is involved in the process that causes wide-ranging cognitive damage resulted in right temporal lobe epilepsy (rTLE). Nevertheless, few studies have evaluated the relationship between DAN and rTLE. There has been little research on alterations in the network homogeneity (NH) of the DAN in rTLE. The aim of the present study was to investigate NH changes in DAN in patients with rTLE. We included 85 patients with rTLE and 69 healthy controls in this study, and resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired. The NH method was used for data analysis. All subjects took the attention network test (ANT). Network homogeneity in the right superior parietal lobule (SPL) and right precuneus (PCU) was significantly higher in patients with rTLE than in healthy controls. The reaction time (RT) was significantly longer in patients with rTLE than in controls. Notably, we observed no significant relationship between the clinical variables and the abnormal NH. These results indicated that abnormal alterations in DAN existed in patients with rTLE and highlighted the crucial role of DAN in the pathophysiology of cognitive damage in rTLE. Our findings suggested that the executive function (EF) significantly weakened in patients with rTLE.

A bayesian approach to examining default mode network functional connectivity and cognitive performance in major depressive disorder

To reconcile the inconsistency of the association between the resting-state functional connectivity (RSFC) and cognitive performance in healthy and depressed groups due to high variance of both measures, we proposed a Bayesian spatio-temporal model to precisely and accurately estimate the RSFC in depressed and nondepressed participants. This model was employed to estimate spatially-adjusted functional connectivity (saFC) in the extended default mode network (DMN) that was hypothesized to correlate with cognitive performance in both depressed and nondepressed. Multiple linear regression models were used to study the relationship between DMN saFC and cognitive performance scores measured in the following four cognitive domains while adjusting for age, sex, and education. In ROI pairs including the posterior cingulate (PCC) and anterior cingulate (ACC) cortex regions, the relationship between connectivity and cognition was found only with the Bayesian approach. Moreover, only the Bayesian approach was able to detect a significant diagnostic difference in the association in ROI pairs, including both PCC and ACC regions, due to smaller variance for the saFC estimator. The results confirm that a reliable and precise saFC estimator, based on the Bayesian model, can foster scientific discovery that may not be feasible with the conventional ROI-based FC estimator (denoted as 'AVG-FC').

Changes in Global and Nodal Networks in Patients With Unipolar Depression After 3-Week Repeated Transcranial Magnetic Stimulation Treatment

Objectives: Repeated transcranial magnetic stimulation (rTMS) therapy has been applied in depressive disorders, but its neurobiological effect has not been well understood. Changes in cortical source network after treatment need to be confirmed. The present study investigated the effect of 3-week rTMS therapy on the symptom severity and cortical source network in patients with unipolar depression. Methods: Thirty-five patients with unipolar major depressive disorder participated in the study. High-frequency (10 Hz) rTMS was applied at the left dorsolateral prefrontal cortex during 3 weeks (five consecutive weekdays every week). Clinical symptoms were examined using the Hamilton Rating Scale for Depression and Anxiety. The resting state electroencephalography was recorded with 62 scalp channels before and after rTMS treatment. Results: Clinical symptoms significantly improved after rTMS treatment in both the active (p = 0.001) and sham groups (p = 0.002). However, an increased cortical source network in global and nodal levels was observed only in the active group after a 3-week treatment. Conclusions: The present study indicates that rTMS treatment leads to improved symptoms in patients with unipolar depression. Furthermore, treatment outcome of real effect was assured in changes of cortical source network.