Abnormal functional connectivity of the default mode network in remitted late-onset depression

Postpartum depression and major depressive disorder: the same or not? Evidence from resting-state functional MRI

Background

Although postpartum depression (PPD) and non-peripartum major depressive disorder (MDD) occurring within and outside the postpartum period share many clinical characteristics, whether PPD and MDD are the same or not remains controversial.

Methods

The current study was devoted to identify the shared and different neural circuits between PPD and MDD by resting-state functional magnetic resonance imaging data from 77 participants (22 first-episodic drug-naïve MDD, 26 drug-naïve PPD, and 29 healthy controls (HC)).

Results

Both the PPD and MDD groups exhibited higher fractional amplitude of low-frequency fluctuation (fALFF) in left temporal pole relative to the HC group; the MDD group showed specifically increased degree centrality in the right cerebellum while PPD showed specifically decreased fALFF in the left supplementary motor area and posterior middle temporal gyrus (pMTG_L), and specifically decreased functional connectivities between pMTG and precuneus and between left subgeneual anterior cingulate cortex (sgACC_L) and right sgACC. Moreover, sgACC and left thalamus showed abnormal regional homogeneity of functional activities between any pair of HC, MDD, and PPD.

Conclusions

These results provide initial evidence that PPD and MDD have common and distinct neural circuits, which may facilitate understanding the neurophysiological basis and precision treatment for PPD.

Thalamic abnormalities in older adults with remitted early-onset depression using structural magnetic resonance imaging

BACKGROUND

The thalamus is a key diencephalic structure involved in major depressive disorder (MDD). Studies have consistently revealed abnormalities in thalamic volumes in older adults with late-onset depression (LOD), however abnormalities in older adults with early-onset depression (EOD) have not yet been well-studied.

METHODS

Fifty-nine euthymic participants with a history of EOD and fifty-nine matched comparison participants without a lifetime history of depression underwent neuroimaging, medical and neuropsychological assessments. Thalamic volumes were compared between groups. To investigate the previously-proposed right hemispheric (RH) dominance theory of MDD, we explored the bilateral, right and left hemispheric (LH) thalamic volumes. Multiple regression analyses were used to evaluate between-group and within-group effects. Correlational analyses examined associations between group and cognitive performance.

RESULTS

Relative to the comparison group, those with EOD had significantly larger bilateral, LH and RH thalamic volumes. Those with EOD, those who were younger, and those who had fewer years of education demonstrated larger bilateral and LH thalamic volumes. For RH thalamic volumes, those with EOD and those who were younger demonstrated larger RH thalamic volumes. EOD within-group models were also run to assess associations between relevant depression variables. The results showed that only age was significant for bilateral and RH thalamic volumes. For the LH thalamic volumes, the model was not significant. No significant correlations were found between cognitive performance and EOD groups.

CONCLUSION

Older adults with a history of EOD showed significantly larger bilateral, RH and LH thalamic volumes. Further research is needed to delineate potential underlying mechanisms of this change.

A major depressive disorder classification framework based on EEG signals using statistical, spectral, wavelet, functional connectivity, and nonlinear analysis

BACKGROUND

Major depressive disorder (MDD) is a prevalent mental illness that is diagnosed through questionnaire-based approaches; however, these methods may not lead to an accurate diagnosis. In this regard, many studies have focused on using electroencephalogram (EEG) signals and machine learning techniques to diagnose MDD.

NEW METHOD

This paper proposes a machine learning framework for MDD diagnosis, which uses different types of EEG-derived features. The features are extracted using statistical, spectral, wavelet, functional connectivity, and nonlinear analysis methods. The sequential backward feature selection (SBFS) algorithm is also employed to perform feature selection. Various classifier models are utilized to select the best one for the proposed framework.

RESULTS

The proposed method is validated with a public EEG dataset, including the EEG data of 34 MDD patients and 30 healthy subjects. The evaluation of the proposed framework is conducted using 10-fold cross-validation, providing the metrics such as accuracy (AC), sensitivity (SE), specificity (SP), F1-score (F1), and false discovery rate (FDR). The best performance of the proposed method has provided an average AC of 99%, SE of 98.4%, SP of 99.6%, F1 of 98.9%, and FDR of 0.4% using the support vector machine with RBF kernel (RBFSVM) classifier.

COMPARISON WITH EXISTING METHODS

The obtained results demonstrate that the proposed method outperforms other approaches for MDD classification based on EEG signals.

CONCLUSIONS

According to the obtained results, a highly accurate MDD diagnosis would be provided using the proposed method, while it can be utilized to develop a computer-aided diagnosis (CAD) tool for clinical purposes.

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.

The early postpartum period - Differences between women with and without a history of depression

Depression is a highly recurrent disorder. When in remission, it affords an important opportunity to understand the state-independent neurobiological alterations, as well as the socio-demographic characteristics, that likely contribute to the recurrence of major depressive disorder (MDD). The present study examined 110 euthymic women in their early postpartum period. A comparison was made between participants with (n = 20) and without (n = 90) a history of MDD by means of a multimodal approach including an fMRI experiment, assessment of hair cortisol concentration (HCC) and a clinical anamnestic interview. Women with a personal history of MDD were found to have decreased resting-state functional connectivity (RSFC) between the lateral parietal cortex (LPC) and the posterior cingulate cortex (PCC), and their Edinburgh Postnatal Depression Scale (EPDS) scores were significantly higher shortly after childbirth. More often than not, these women also had a family history of MDD. While women with no history of depression showed a negative association between hair cortisol concentration (HCC) and gray matter volume (GMV) in the medial orbitofrontal cortex (mOFC), the opposite trend was seen in women with a history of depression. This implies that women with remitted depression show distinctive neural phenotypes with subclinical residual symptoms, which likely predispose them to later depressive episodes.

Functional connectivity of major depression disorder using ongoing EEG during music perception

OBJECTIVE

The functional connectivity (FC) of major depression disorder (MDD) has not been well studied under naturalistic and continuous stimuli conditions. In this study, we investigated the frequency-specific FC of MDD patients exposed to conditions of music perception using ongoing electroencephalogram (EEG).

METHODS

First, we applied the phase lag index (PLI) method to calculate the connectivity matrices and graph theory-based methods to measure the topology of brain networks across different frequency bands. Then, classification methods were adopted to identify the most discriminate frequency band for the diagnosis of MDD.

RESULTS

During music perception, MDD patients exhibited a decreased connectivity pattern in the delta band but an increased connectivity pattern in the beta band. Healthy people showed a left hemisphere-dominant phenomenon, but MDD patients did not show such a lateralized effect. Support vector machine (SVM) achieved the best classification performance in the beta frequency band with an accuracy of 89.7%, sensitivity of 89.4% and specificity of 89.9%.

CONCLUSIONS

MDD patients exhibited an altered FC in delta and beta bands, and the beta band showed a superiority in the diagnosis of MDD.

SIGNIFICANCE

Our study provided a promising reference for the diagnosis of MDD, and revealed a new perspective for understanding the topology of MDD brain networks during music perception.

Evidence for Structural and Functional Alterations of Frontal-Executive and Corticolimbic Circuits in Late-Life Depression and Relationship to Mild Cognitive Impairment and Dementia: A Systematic Review

Depression is a risk factor for developing Alzheimer's disease and Related Dementia (ADRD). We conducted a systematic review between 2008 and October 2018, to evaluate the evidence for a conceptual mechanistic model linking depression and ADRD, focusing on frontal-executive and corticolimbic circuits. We focused on two neuroimaging modalities: diffusion-weighted imaging measuring white matter tract disruptions and resting-state functional MRI measuring alterations in network dynamics in late-life depression (LLD), mild cognitive impairment (MCI), and LLD+MCI vs. healthy control (HC) individuals. Our data synthesis revealed that in some but not all studies, impairment of both frontal-executive and corticolimbic circuits, as well as impairment of global brain topology was present in LLD, MCI, and LLD+MCI vs. HC groups. Further, posterior midline regions (posterior cingulate cortex and precuneus) appeared to have the most structural and functional alterations in all patient groups. Future cohort and longitudinal studies are required to address the heterogeneity of findings, and to clarify which subgroups of people with LLD are at highest risk for developing MCI and ADRD.

Quantitative Identification of Major Depression Based on Resting-State Dynamic Functional Connectivity: A Machine Learning Approach

Introduction

Developing a machine learning-based approach which could provide quantitative identification of major depressive disorder (MDD) is essential for the diagnosis and intervention of this disorder. However, the performances of traditional algorithms using static functional connectivity (SFC) measures were unsatisfactory. In the present work, we exploit the hidden information embedded in dynamic functional connectivity (DFC) and developed an accurate and objective image-based diagnosis system for MDD.

Methods

MRI images were collected from 99 participants including 56 healthy controls and 43 MDD patients. DFC was calculated using a sliding-window algorithm. A non-linear support vector machine (SVM) approach was then used with the DFC matrices as features to distinguish MDD patients from healthy controls. The spatiotemporal characteristics of the most discriminative features were then investigated.

Results

The area under the curve (AUC) of the SVM classifier with DFC measures reached 0.9913, while this value is only 0.8685 for the algorithm using SFC measures. Spatially, the most discriminative 28 connections distributed in the visual network (VN), somatomotor network (SMN), dorsal attention network (DAN), ventral attention network (VAN), limbic network (LN), frontoparietal network (FPN), and default mode network (DMN), etc. Notably, a large portion of these connections were associated with the FPN, DMN, and VN. Temporally, the most discriminative connections transited from the cortex to deeper regions.

Conclusion

The results clearly suggested that DFC is superior to SFC and provide a reliable quantitative identification method for MDD. Our findings may furnish a better understanding of the neural mechanisms of MDD as well as improve accurate diagnosis and early intervention of this disorder.

Treating Depression With Tai Chi: State of the Art and Future Perspectives

Major depressive disorder (MDD) is one of the most prevalent mental illnesses in America. Current treatments for MDD are unsatisfactory given high non-response rates, high relapse rates, and undesirable side effects. Accumulating evidence suggests that Tai Chi, a popular mind-body intervention that originated as a martial art, can significantly regulate emotion and relieve the symptoms of mood disorders. In addition, the availability of instructional videos and the development of more simplified and less structured Tai Chi has made it a promising low-intensity mind-body exercise. In this article, we first examine a number of clinical trials that implemented Tai Chi as a treatment for depression. Then, we explore several mechanisms by which Tai Chi may alleviate depressive symptoms, hypothesizing that the intervention may modulate the activity and connectivity of key brain regions involved in mood regulation, reduce neuro-inflammatory sensitization, modulate the autonomic nervous system, and regulate hippocampal neurogenesis. Finally, we discuss common challenges of the intervention and possible ways to address them. Specifically, we pose developing a simplified and tailored Tai Chi protocol for patients with depression, comparatively investigating Tai Chi with other mind-body interventions such as yoga and Baduanjin, and developing new mind-body interventions that merge the advantages of multiple mind-body exercises.

Effect of 5-HTTLPR on current source density, connectivity, and topological properties of resting state EEG networks

The S allele of serotonin transporter gene (5-HTTLPR) has been found to increase the risk of depression and other mental health problems, but some evidence suggests that S-allele carriers outperform subjects carrying the long allele in an array of cognitive tasks. Evidence linking this polymorphism with individual variation in electrophysiological properties of resting state brain networks is very limited. This study investigated the effect of 5-HTTLPR polymorphism on EEG current source density, connectivity, and topological properties of resting state networks. We collected genetic and resting state EEG data in 113 Caucasians. As compared to L-homozygotes, S-allele carriers showed lower current source density and connectivity in most frequency bands in areas overlapping with the default mode and emotion regulation regions. The analysis of graph-theoretical measures showed that S-allele carriers, as compared to L-homozygotes, have less optimal topological properties of brain networks in theta, but more optimal in alpha band. This dissociation may reflect the predisposition to emotional disorders, which is inherent to S-allele carriers, and, on the other hand, their superior functioning in some cognitive domains.

Aberrant Default Mode Network Underlying the Cognitive Deficits in the Patients With Late-Onset Depression

Late-onset depression (LOD) is regarded as a risk factor or a prodrome of Alzheimer’s disease (AD). Moreover, LOD patients with cognitive deficits have the higher risk of subsequent AD. Thus, it is necessary to understand the neural underpinnings of cognitive deficits and its pathological implications in LOD. Consistent findings show that the default mode network (DMN) is an important and potentially useful brain network for the cognitive deficits in LOD patients. In recent years, genetics has been actively researched as a possible risk factor in the pathogenesis of LOD. So, in this review, we discuss the current research progress on the cognitive deficits and DMN in LOD through a combined view of brain network and genetics. We find that different structural and functional impairments of the DMN might be involved in the etiological mechanisms of different cognitive impairments in LOD patients.

Resting state functional connectivity in patients with remitted psychotic depression: A multi-centre STOP-PD study

Background

There is paucity of neurobiological knowledge about major depressive disorder with psychotic features (“psychotic depression”). This study addresses this knowledge gap by using resting state functional magnetic resonance imaging (R-fMRI) to compare functional connectivity in patients with psychotic depression and healthy controls.

Methods

We scanned patients who participated in a randomized controlled trial as well as healthy controls. All patients achieved remission from depressive and psychotic symptoms with sertraline and olanzapine. We employed Independent Component Analysis in independent samples to isolate the default mode network (DMN) and compared patients and controls.

Findings

The Toronto sample included 28 patients (mean [SD], age 56·2 [13·7]) and 39 controls (age 55·1 [13·5]). The Replication sample included 29 patients (age 56·1 [17·7]) and 36 controls (age 48·3 [17·9]). Patients in the Toronto sample demonstrated decreased between-network functional connectivity between the DMN and bilateral insular, somatosensory/motor, and auditory cortices with peak activity in the right planum polare (t = 4·831; p = 0·001, Family Wise Error (FWE) corrected). A similar pattern of between-network functional connectivity was present in our Replication sample with peak activity in the right precentral gyrus (t = 4·144; p = 0·003, FWE corrected).

Interpretation

Remission from psychotic depression is consistently associated with an absence of increased DMN-related functional connectivity and presence of decreased between-network functional connectivity. Future research will evaluate this abnormal DMN-related functional connectivity as a potential biomarker for treatment trajectories.

Funding

National Institute of Mental Health.

Neuroimaging genomic studies in major depressive disorder: A systematic review

Genetic-neuroimaging studies could identify new potential endophenotypes of major depressive disorder (MDD). Morphological and functional alterations may be attributable to genetic factors that regulate neurogenesis and neurodegeneration. Given that the association between gene polymorphisms and brain morphology or function has varied across studies, this systematic review aims at evaluating and summarizing all available genetic-neuroimaging studies. Twenty-eight gene variants were evaluated in 64 studies by structural or functional magnetic resonance imaging. Significant genetic-neuroimaging associations were found in monoaminergic genes, BDNF genes, glutamatergic genes, HPA axis genes, and the other common genes, which were consistent with common hypotheses of the pathogenesis of MDD.

Treating Depression with Transcutaneous Auricular Vagus Nerve Stimulation: State of the Art and Future Perspectives

Depression is a highly prevalent disorder, and its treatment is far from satisfactory. There is an urgent need to develop a new treatment for depression. Although still at its early stage, transcutaneous auricular vagus nerve stimulation (taVNS) has shown promising potential for treating depression. In this article, we first summarize the results of clinical studies on the treatment effect of taVNS on depression. Then, we re-analyze a previous study to identify the specific symptoms taVNS can relieve as indicated by subscores of the 24-item Hamilton Depression Scale in patients with depression. We found that taVNS can significantly reduce multiple symptoms of depression patients, including anxiety, psychomotor retardation, sleep disturbance, and hopelessness. Next, we pose several hypotheses on the mechanism of taVNS treatment of depression, including directly and indirectly modulating the activity and connectivity of key brain regions involved in depression and mood regulation; inhibiting neuro-inflammatory sensitization; modulating hippocampal neurogenesis; and regulating the microbiome-brain-gut axis. Finally, we outline current challenges and lay out the future directions of taVNS treatment of depression, which include (1) intensively comparing stimulation parameters and "dose effect" (treatment frequency and duration) to maximize the treatment effect of taVNS; (2) exploring the effect of taVNS on disorders comorbid with depression (such as chronic pain disorders, cardiovascular disorder, and autism) to provide new "two-for-one" treatment approaches for patients with these disorders; and (3) applying multiple scale methods to explore the underlying mechanism of taVNS.

Neuropsychiatric Disturbances in Alzheimer's Disease: What Have We Learned from Neuropathological Studies?

Neuropsychiatric symptoms (NPS) are an integral part of the dementia syndrome and were therefore recently included in the core diagnostic criteria of dementia. The near universal prevalence of NPS in Alzheimer's disease (AD), combined with their disabling effects on patients and caregivers, is contrasted by the fact that few effective and safe treatments exist, which is in part to be attributed to our incomplete understanding of the neurobiology of NPS. In this review, we describe the pathological alterations typical for AD, including spreading and evolution of burden, effect on the molecular and cellular integrity, functional consequences and atrophy of NPS-relevant brain regions and circuits in correlation with specific NPS assessments. It is thereby clearly established that NPS are fundamental expressions of the underlying neurodegenerative brain disease and not simply reflect the patients' secondary response to their illness. Neuropathological studies, moreover, include a majority of end-stage patient samples, which may not correctly represent the pathophysiological environment responsible for particular NPS that may already be present in an early stage, or even prior to AD diagnosis. The burdensome nature and high prevalence of NPS, in combination with the absence of effective and safe pharmacotherapies, provide a strong incentive to continue neuropathological and neurochemical, as well as imaging and other relevant approaches to further improve our apprehension of the neurobiology of NPS.

Abnormal functional connectivity of the posterior cingulate cortex is associated with depressive symptoms in patients with Alzheimer's disease

BACKGROUND

Depressive symptoms are significant and very common psychiatric complications in patients with Alzheimer's disease (AD), which can aggravate the decline in social function. However, changes in the functional connectivity (FC) of the brain in AD patients with depressive symptoms (D-AD) remain unclear.

OBJECTIVE

To investigate whether any differences exist in the FC of the posterior cingulate cortex (PCC) between D-AD patients and non-depressed AD patients (nD-AD).

MATERIALS AND METHODS

We recruited 15 D-AD patients and 17 age-, sex-, educational level-, and Mini-Mental State Examination (MMSE)-matched nD-AD patients to undergo tests using the Neuropsychiatric Inventory, Hamilton Depression Rating Scale, and 3.0T resting-state functional magnetic resonance imaging. Bilateral PCC were selected as the regions of interest and between-group differences in the PCC FC network were assessed using Student's t-test.

RESULTS

Compared with the nD-AD group, D-AD patients showed increased PCC FC in the right amygdala, right parahippocampus, right superior temporal pole, right middle temporal lobe, right middle temporal pole, and right hippocampus (AlphaSim correction; P<0.05). In the nD-AD group, MMSE scores were positively correlated with PCC FC in the right superior temporal pole and right hippocampus (false discovery rate corrected; P<0.05).

CONCLUSION

Differences were detected in PCC FC between nD-AD and D-AD patients, which may be related to depressive symptoms. Our study provides a significant enhancement to our understanding of the functional mechanisms underlying D-AD.

Structural and Functional Connectivity of Default Mode Network underlying the Cognitive Impairment in Late-onset Depression

To identify the association between the functional and structural changes of default mode network (DMN) underlying the cognitive impairment in Late-onset depression (LOD), 32 LOD patients and 39 normal controls were recruited and underwent resting-state fMRI, DTI scans, and cognitive assessments. Seed-based correlation analysis was conducted to explore the functional connectivity (FC) of the DMN. Deterministic tractography between FC-impaired regions was performed to examine the structural connectivity (SC). Partial correlation analyses were employed to evaluate the cognitive association of those altered FC and SC. Compared with controls, LOD patients showed decreased FC between DMN and the cingulo-opercular network (CON), as well as the thalamus. Decreased FA and increased RD of these fiber tracts connecting DMN with CON were found in LOD patient. The DMN-CON FC and the FA, RD of the fiber tracts were both significantly correlated with the cognitive performance. Therefore, the cognitive impairment in LOD might be associated with the decreased FC between the DMN and the CON, which probably resulted from the demyelination of the white matter.

Depression, marijuana use and early-onset marijuana use conferred unique effects on neural connectivity and cognition

OBJECTIVE

Marijuana (MJ) use is common. Research shows risks for psychiatric illnesses, including major depressive disorder (MDD) and cognitive deficits with MJ use, particularly early-onset use. We investigated cognitive function, functional connectivity, and genetic risk with MDD alone and combined with MJ use, and differences between early-vs. late-onset/non-MJ use in youth.

METHOD

A total of 74 youth in four groups were studied: healthy control, MDD, frequent MJ use and current/past MDD plus frequent MJ use. Psychiatric symptoms, cognitive performance and demographics were measured. Default mode network (DMN) brain connectivity was determined. Risk alleles in six genes of interest were evaluated.

RESULTS

DMN differences among groups in reward-processing and motor control regions were found; the effects of MJ use and MDD were distinct. Early-onset MJ use was associated with lower IQ and hyperconnectivity within areas of the DMN. Early-onset MJ use was associated with the BDNF risk allele.

CONCLUSIONS

Cognitive deficits linked with early-onset MJ use were present within several years after MJ use began and may result from, predispose to, or share a common cause with early-onset MJ use. The DMN was affected by MDD, MJ and their combination, as well as by early-onset MJ use. BDNF carrier state may predispose to early-onset MJ use.

Abnormal resting-state functional connectivity study in unilateral pulsatile tinnitus patients with single etiology: A seed-based functional connectivity study

OBJECTIVE

Previous studies demonstrated altered regional neural activations in several brain areas in patients with pulsatile tinnitus (PT), especially indicating an important role of posterior cingulate cortex (PCC). However, few studies focused on the degree of functional connectivity (FC) of this area in PT patients. In this study, we will compare the FC of PCC in patients affected with this condition and normal controls by using resting-state functional magnetic resonance imaging (fMRI).

METHODS

Structural and functional MRI data were obtained from 36 unilateral PT patients with single etiology and 36 matched healthy controls. FC feature of the region of interest (PCC) were characterized using a seed-based correlation method with the voxels in the whole-brain.

RESULTS

Compared with healthy controls, patients showed significant decreased FC to the right middle temporal gyrus (MTG), right thalamus and bilateral insula. By contrast, PCC demonstrated increased functional connectivity between the precuneus, bilateral inferior parietal lobule and middle occipital gyrus. We also found correlations between the disease duration of PT and FC of PCC-right MTG (r=-0.616, p<0.001).

CONCLUSIONS

Unilateral PT patients could have abnormal FC to the PCC bilaterally in the brain. PCC, as a highly integrated brain area, is an example of nucleus that was involved in mediation between different neural networks. It might be a modulation core between visual network and auditory network. The decreased FC of MTG to PCC may indicate a down regulation of activity between PCC and auditory associated brain cortex. Decreased FC between limbic system (bilateral AI) and PCC may reflect the emotional message control in patient group. This study facilitated understanding of the underlying neuropathological process in patients with pulsatile tinnitus.

Disrupted Interhemispheric Synchrony in Default Mode Network Underlying the Impairment of Cognitive Flexibility in Late-Onset Depression

The intuitive association between cognitive impairment and aberrant functional activity in the brain network has prompted interest in exploring the role of functional connectivity in late-onset depression (LOD). The relationship of altered voxel-mirrored homotopic connectivity (VMHC) and cognitive dysfunction in LOD is not yet well understood. This study was designed to examine the implicit relationship between the disruption of interhemispheric functional coordination and cognitive impairment in LOD. LOD patients (N = 31) and matched healthy controls (HCs; N = 37) underwent neuropsychological tests and functional magnetic resonance imaging (fMRI) in this study. The intergroup difference of interhemispheric coordination was determined by calculating VMHC value in the whole brain. The neuro-behavioral relevancy approach was applied to explore the association between disrupted VMHC and cognitive measures. Receiver operating characteristic (ROC) curve analysis was used to determine the capability of disrupted regional VMHC to distinguish LOD. Compared to the HC group, significantly attenuated VMHC in the superior frontal gyrus (SFG), superior temporal gyrus (STG), posterior cerebellar lobe (CePL) and post- and precentral gyri were observed in the bilateral brain of LOD patients. The interhemispheric asynchrony in bilateral CePLs was positively correlated with the performance of trail making test B (TMT-B) in LOD patients (r = 0.367, P = 0.040). ROC analysis revealed that regions with abnormal VMHC could efficiently distinguish LOD from HCs (Area Under Curve [AUC] = 0.90, P < 0.001). Altered linkage patterns of intrinsic homotopic connectivity and impaired cognitive flexibility was first investigated in LOD, and it would provide a novel clue for revealing the neural substrates underlying cognitive impairment in LOD.

Aberrant topographical organization of the default mode network underlying the cognitive impairment of remitted late-onset depression

To investigate the alteration of resting-state functional connectivity (FC) and topological organization of the default mode network (DMN), and their contribution to the cognitive impairment in remitted late-onset depression (rLOD) patients. Thirty-three rLOD patients and thirty-one healthy controls underwent clinical and cognitive evaluations as well as resting-state functional magnetic resonance imaging (R-fMRI) scans. The FC networks were constructed by thresholding Pearson correlation metrics of the DMN regions, and their topological properties were analyzed using graph theory-based approaches. Nonparametric permutation tests were further used for group comparisons of topological metrics. Finally, multiple linear regression analyses were performed to examine the relationships between the network measures and cognitive performances. Patients displayed universally decreased FC of DMN and abnormal global topology of the DMN (i.e., increased characteristic path length Lp and reduced global efficiency Eglob) compared with healthy controls. According to the distance-dependent FC results, the long-distance connections were mainly involved in the connectivity between anterior and posterior hubs, and the short-distance connections were primarily located in the frontal lobe. There were significant correlations between the global topology and the episodic memory performance in rLOD patients. In conclusion, the present study indicated that the disrupted topological organization of the DMN might be considered as a potential biomarker of the episodic memory deficits in rLOD patients.

Enhanced default mode network connectivity with ventral striatum in subthreshold depression individuals

Subthreshold depression (StD) is a highly prevalent condition associated with increased service utilization and social morbidity. Nevertheless, due to limitations in current diagnostic systems that set the boundary for major depressive disorder (MDD), very few brain imaging studies on the neurobiology of StD have been carried out, and its underlying neurobiological mechanism remains unclear. In recent years, accumulating evidence suggests that the disruption of the default mode network (DMN), a network involved in self-referential processing, affective cognition, and emotion regulation, is involved in major depressive disorder. Using independent component analysis, we investigated resting-state default mode network (DMN) functional connectivity (FC) changes in two cohorts of StD patients with different age ranges (young and middle-aged, n = 57) as well as matched controls (n = 79). We found significant FC increase between the DMN and ventral striatum (key region in the reward network), in both cohorts of StD patients in comparison with controls. In addition, we also found the FC between the DMN and ventral striatum was positively and significantly associated with scores on the Center for Epidemiologic Studies Depression Scale (CES-D), a measurement of depressive symptomatology. We speculate that this enhanced FC between the DMN and the ventral striatum may reflect a self-compensation to ameliorate the lowered reward function.

Transcutaneous Vagus Nerve Stimulation Modulates Default Mode Network in Major Depressive Disorder

BACKGROUND

Depression is the most common form of mental disorder in community and health care settings and current treatments are far from satisfactory. Vagus nerve stimulation (VNS) is a Food and Drug Administration approved somatic treatment for treatment-resistant depression. However, the involvement of surgery has limited VNS only to patients who have failed to respond to multiple treatment options. Transcutaneous VNS (tVNS) is a relatively new, noninvasive VNS method based on the rationale that there is afferent/efferent vagus nerve distribution on the surface of the ear. The safe and low-cost characteristics of tVNS have the potential to significantly expand the clinical application of VNS.

METHODS

In this study, we investigated how tVNS can modulate the default mode network (DMN) functional connectivity (FC) in mild or moderate major depressive disorder (MDD) patients. Forty-nine MDD patients were recruited and received tVNS or sham tVNS (stVNS) treatments.

RESULTS

Thirty-four patients completed the study and were included in data analysis. After 1 month of tVNS treatment, the 24-item Hamilton Depression Rating Scale score reduced significantly in the tVNS group as compared with the stVNS group. The FC between the DMN and anterior insula and parahippocampus decreased; the FC between the DMN and precuneus and orbital prefrontal cortex increased compared with stVNS. All these FC increases are also associated with 24-item Hamilton Depression Rating Scale reduction.

CONCLUSIONS

tVNS can significantly modulate the DMN FC of MDD patients; our results provide insights to elucidate the brain mechanism of tVNS treatment for MDD patients.

Corticostriatal pathways contribute to the natural time course of positive mood

The natural time course of mood includes both acute responses to stimuli and spontaneous fluctuations. To date, neuroimaging studies have focused on either acute affective responses or spontaneous neural fluctuations at rest but no prior study has concurrently probed both components, or how mood disorders might modulate these processes. Here, using fMRI, we capture the acute affective and neural responses to naturalistic positive mood induction, as well as their spontaneous fluctuations during resting states. In both healthy controls and individuals with a history of depression, our manipulation acutely elevates positive mood and ventral striatum activation. Only controls, however, sustain positive mood over time, and this effect is accompanied by the emergence of a reciprocal relationship between the ventral striatum and medial prefrontal cortex during ensuing rest. Findings suggest that corticostriatal pathways contribute to the natural time course of positive mood fluctuations, while disturbances of those neural interactions may characterize mood disorder.

Positive mood can occur as a result of a stimulus or spontaneously. Admon and Pizzagalli measure variations in neural responses to a positive stimulus over time, and identify cortico-striatal interactions associated with sustained positive mood which are reduced in individuals with a history of depression.

Subthreshold depression is associated with impaired resting-state functional connectivity of the cognitive control network

Subthreshold depression (StD) is a prevalent condition associated with social morbidity and increased service utilization, as well as a high risk of developing into a major depressive disorder (MDD). The lack of well-defined diagnostic criteria for StD has limited research on this disorder, with very few brain-imaging studies examining the neurobiology of StD. Yet, identifying the neural pathology of StD has the potential to elucidate risk factors and prognostic markers for major depression and is crucial for developing tailored treatments for patients at mild stages of depression. We investigated resting-state functional connectivity (rs-FC) of the cognitive control network (CCN), known to be dysregulated in MDD, using the bilateral dorsolateral prefrontal cortex (DLPFC) as a seed, focusing on two cohorts of StD subjects (young and middle aged) as well as matched controls. Irrespective of age, we found a significant rs-FC decrease in the CCN of the StD subjects, compared with matched controls, particularly between the DLPFC and the brain regions associated with the representation of self and other mental states (temporo-parietal junction (TPJ) and precuneus), as well as salience detection and orienting (insula). The functional connectivity between the DLPFC and the left TPJ was also associated with depressive symptom scores measured by the Center for Epidemiologic Studies Depression Scale. This finding may shed light on the neural pathology of StD, leading to better understanding of mild stages of depression, its diagnosis and the development of new treatments.

Aberrant connectivity within the default mode network in first-episode, treatment-naïve major depressive disorder

BACKGROUND

Convergent studies have highlighted the dysfunction of default mode network (DMN) in major depressive disorder (MDD). The altered connectivity in posterior cingulate cortex (PCC) and medial prefrontal cortex (mPFC) was especially found to be of interest in the resting state functional connectivity analysis. Recently, more attention has turned to the internal functional connectivity within the DMN. However, the internal connection patterns within the DMN remain unclear at the initial onset of MDD.

METHODS

Resting-state fMRI was performed on 38 first-episode, treatment-naïve MDD patients along with 38 matched healthy controls. Seed-based analysis was used to define the DMN and then a region-to-region connectivity analysis was performed to inspect the functional connectivity within the DMN. Spearman׳s rank correlation analysis was performed between significantly abnormal connectivities in MDD patients and clinical measurements.

RESULTS

Decreased region-to-region connectivities within DMN were found between the PCC and dorsal medial prefrontal cortex (dmPFC), between PCC and the right inferior parietal gyrus/angular, as well as between the left thalamus and cerebellar tonsil. No significant increase in connectivity was found. Moreover, functional connectivity between the left thalamus and cerebellar tonsil revealed a marginal significant negative correlation with clinical Hamilton Depression Rating Scale (HDRS) scores.

LIMITATIONS

Noteworthiness in morbidity, a high risk of mortality, and a high rate of medical service utilization of MDD make the current results uncertain to apply to the more complicated situations.

CONCLUSIONS

Each region within DMN may have a specific, individual functional role. The reason to identify the pathological mechanism of MDD may not lie in the abnormal DMN functional connectivity, but rather in the abnormal functional connectivity within DMN.

Resting-state functional connectivity of antero-medial prefrontal cortex sub-regions in major depression and relationship to emotional intelligence

BACKGROUND

Major depressive disorder has been associated with abnormal resting-state functional connectivity (FC), especially in cognitive processing and emotional regulation networks. Although studies have found abnormal FC in regions of the default mode network (DMN), no study has investigated the FC of specific regions within the anterior DMN based on cytoarchitectonic subdivisions of the antero-medial pre-frontal cortex (PFC). Studies from different areas in the field have shown regions within the anterior DMN to be involved in emotional intelligence. Although abnormalities in this region have been observed in depression, the relationship between the ventromedial PFC (vmPFC) function and emotional intelligence has yet to be investigated in depressed individuals.

METHODS

Twenty-one medication-free, non-treatment resistant, depressed patients and 21 healthy controls underwent a resting state functional magnetic resonance imaging session. The participants also completed an ability-based measure of emotional intelligence: the Mayer-Salovey-Caruso Emotional Intelligence Test. FC maps of Brodmann areas (BA) 25, 10 m, 10r, and 10p were created and compared between the two groups.

RESULTS

Mixed-effects analyses showed that the more anterior seeds encompassed larger areas of the DMN. Compared to healthy controls, depressed patients had significantly lower connectivity between BA10p and the right insula and between BA25 and the perigenual anterior cingulate cortex. Exploratory analyses showed an association between vmPFC connectivity and emotional intelligence.

CONCLUSIONS

These results suggest that individuals with depression have reduced FC between antero-medial PFC regions and regions involved in emotional regulation compared to control subjects. Moreover, vmPFC functional connectivity appears linked to emotional intelligence.

Depression, neuroimaging and connectomics: a selective overview

Depression is a multifactorial disorder with clinically heterogeneous features involving disturbances of mood and cognitive function. Noninvasive neuroimaging studies have provided rich evidence that these behavioral deficits in depression are associated with structural and functional abnormalities in specific regions and connections. Recent advances in brain connectomics through the use of graph theory highlight disrupted topological organization of large-scale functional and structural brain networks in depression, involving global topology (e.g., local clustering, shortest-path lengths, and global and local efficiencies), modular structure, and network hubs. These system-level disruptions show important correlates with genetic and environmental factors, which provide an integrative perspective on mood and cognitive deficits in depressive syndrome. Moreover, research suggests that the pathologic networks associated with depression represent potentially valuable biomarkers for early detection of this disorder and they are likely to be regulated and recalibrated by using pharmacologic, psychological, and brain stimulation therapies. These connectome-based imaging studies present new opportunities to reconceptualize the pathogenesis of depression, improve our knowledge of the biological mechanisms of therapeutic effects, and identify appropriate stimulation targets to optimize the clinical response in depression treatment. Here, we summarize the current findings and historical understanding of structural and functional connectomes in depression, focusing on graph analyses of depressive brain networks. We also consider methodological factors such as sample heterogeneity and poor test-retest reliability of recordings due to physiological, head motion, and imaging artifacts to discuss result inconsistencies among studies. We conclude with suggestions for future research directions on the emerging field of imaging connectomics in depression.

Characterization of resting-state fMRI-derived functional connectivity in patients with deficiency versus excess patterns of major depression

OBJECTIVE

Patients with major depression (MD) experience a variety of emotional and mental problems accompanied by characteristic clinical symptoms. Based on traditional Chinese medicine (TCM) notions, the clinical appearance of MD can be divided into two syndromes, namely a deficiency pattern (DP) and an excess pattern (EP), depending on the patient's clinical symptoms, pulse, and lingual signs. Brain functional neuroimaging has demonstrated cerebral activity abnormalities in MD patients. However, such abnormalities have not been linked to particular symptoms of MD. The objective of this work was to compare functional connectivity of the posterior cingulate cortex (PCC) across MD patients with DP, MD patients with EP, and normal control (NC) subjects in a resting-state functional magnetic resonance imaging (rs-fMRI) study.

METHODS

Participants (24 DP patients, 21 EP patients, and 20 NCs) underwent rs-fMRI scans. Whole-brain functional connectivity of a seed in the PCC was then mapped for each subject. Functional connectivity differences among the three studied groups were analyzed statistically.

RESULTS

Compared to the NC group, DP patients had decreased functional connectivity of the PCC with the right middle temporal gyrus and bilateral precuneus, as well as increased functional connectivity of the PCC with the bilateral middle frontal gyrus. Meanwhile, compared to the NC group, the EP group had decreased functional connectivity of the PCC with both the middle temporal gyrus and bilateral precuneus, as well as increased functional connectivity of the PCC with the bilateral superior frontal gyrus. Relative to the DP group, the EP group had reduced functional connectivity of the PCC with the bilateral cerebellum and left superior frontal gyrus.

CONCLUSION

Functional connectivity changes differ between MD patients with different TCM syndrome types, suggesting that the TCM clinical syndromes of MD are associated with correlates in cerebral functional activity.

Depressive Symptoms and Biomarkers of Alzheimer's Disease in Cognitively Normal Older Adults

Even low levels of depressive symptoms are associated with an increased risk of cognitive decline in older adults without overt cognitive impairment (CN). Our objective was to examine whether very low, "subthreshold symptoms of depression" are associated with Alzheimer's disease (AD) biomarkers of neurodegeneration in CN adults and whether these associations are specific to particular depressive symptoms. We analyzed data from 248 community-dwelling CN older adults, including measurements of cortical amyloid burden, neurodegeneration markers of hippocampal volume (HV) and cerebral 18F-fluorodeoxyglucose (FDG) metabolism in a composite of AD-related regions and the 30-item Geriatric Depression Scale (GDS). Participants with GDS >10 were excluded. General linear regression models evaluated the cross-sectional relations of GDS to HV or FDG in separate backward elimination models. Predictors included GDS total score, age, gender, premorbid intelligence, a binary amyloid variable and its interaction with GDS. Principal component analyses of GDS item scores revealed three factors (the Dysphoria, Apathy-Anhedonia, and Anxiety-Concentration Factors). In secondary analyses, GDS total score was replaced with the three factor scores in repeated models. Higher GDS score (p = 0.03) was significantly associated with lower HV and was marginally related (p = 0.06) to FDG hypometabolism. In secondary models, higher Dysphoria (p = 0.02) and Apathy-Anhedonia (p = 0.05) were related to lower HV while higher Apathy-Anhedonia (p = 0.003) was the sole factor related to FDG hypometabolism. Amyloid was not a significant predictor in any model. In conclusion, very low-level dysphoria, apathy and anhedonia may point to neurodegeneration in AD-related regions but this association appears to be independent of amyloid burden.