Intrinsic inter-network brain dysfunction correlates with symptom dimensions in late-life depression

Challenges in Identifying Individualized Brain Biomarkers of Late Life Depression

Research into neuroimaging biomarkers for Late Life Depression (LLD) has identified neural correlates of LLD including increased white matter hyperintensities and reduced hippocampal volume. However, studies into neuroimaging biomarkers for LLD largely fail to converge. This lack of replicability is potentially due to challenges linked to construct variability, etiological heterogeneity, and experimental rigor. We discuss suggestions to help address these challenges, including improved construct standardization, increased sample sizes, multimodal approaches to parse heterogeneity, and the use of individualized analytical models.

Connectomics-based resting-state functional network alterations predict suicidality in major depressive disorder

Suicidal behavior is a major concern for patients who suffer from major depressive disorder (MDD). However, dynamic alterations and dysfunction of resting-state networks (RSNs) in MDD patients with suicidality have remained unclear. Thus, we investigated whether subjects with different severity of suicidal ideation and suicidal behavior may have different disturbances in brain RSNs and whether these changes could be used as the diagnostic biomarkers to discriminate MDD with or without suicidal ideation and suicidal behavior. Then a multicenter, cross-sectional study of 528 MDD patients with or without suicidality and 998 healthy controls was performed. We defined the probability of dying by the suicide of the suicidality components as a 'suicidality gradient'. We constructed ten RSNs, including default mode (DMN), subcortical (SUB), ventral attention (VAN), and visual network (VIS). The network connections of RSNs were analyzed among MDD patients with different suicidality gradients and healthy controls using ANCOVA, chi-squared tests, and network-based statistical analysis. And support vector machine (SVM) model was designed to distinguish patients with mild-to-severe suicidal ideation, and suicidal behavior. We found the following abnormalities with increasing suicidality gradient in MDD patients: within-network connectivity values initially increased and then decreased, and one-versus-other network values decreased first and then increased. Besides, within- and between-network connectivity values of the various suicidality gradients are mainly negatively correlated with HAMD anxiety and positively correlated with weight. We found that VIS and DMN-VIS values were affected by age (p < 0.05), cingulo-opercular network, and SUB-VAN values were statistically influenced by sex (p < 0.05). Furthermore, the SVM model could distinguish MDD patients with different suicidality gradients (AUC range, 0.73-0.99). In conclusion, we have identified that disrupted brain connections were present in MDD patients with different suicidality gradient. These findings provided useful information about the pathophysiological mechanisms of MDD patients with suicidality.

Task-based functional connectivity reveals aberrance with the salience network during emotional interference in late-life depression

OBJECTIVES

Late-life depression (LLD) is a common and debilitating disorder. Previously, resting-state studies have revealed abnormal functional connectivity (FC) of brain networks in LLD. Since LLD is associated with emotional-cognitive control deficits, the aim of this study was to compare FC of large-scale brain networks in older adults with and without a history of LLD during a cognitive control task with emotional stimuli.

METHODS

Cross-sectional case-control study. Twenty participants diagnosed with LLD and 37 never-depressed adults 60-88 years of age underwent functional magnetic resonance imaging during an emotional Stroop task. Network-region-to-region FC was assessed with seed regions in the default mode, the frontoparietal, the dorsal attention, and the salience networks.

RESULTS

FC between salience and sensorimotor network regions and between salience and dorsal attention network regions were reduced in LLD patients compared to controls during the processing of incongruent emotional stimuli. The normally positive FC between these networks were negative in LLD patients and inversely correlated with vascular risk and white matter hyperintensities.

CONCLUSIONS

Emotional-cognitive control in LLD is associated with aberrant functional coupling between salience and other networks. This expands on the network-based LLD model and proposes the salience network as a target for future interventions.

Relationships Among Short Self-Reported Sleep Duration, Cognitive Impairment, and Insular Functional Connectivity in Late-Life Depression

BACKGROUND

Both late-life depression (LLD) and short sleep duration increase the risk of cognitive impairment. Increased insular resting-state functional connectivity (FC) has been reported in individuals with short sleep duration and dementia.

OBJECTIVE

This study aimed to investigate whether short sleep duration is associated with impaired cognition and higher insular FC in patients with LLD.

METHODS

This case- control study recruited 186 patients with LLD and 83 normal controls (NC), and comprehensive psychometric assessments, sleep duration reports and resting-state functional MRI scans (81 LLD patients and 54 NC) were conducted.

RESULTS

Patients with LLD and short sleep duration (LLD-SS patients) exhibited more severe depressive symptoms and worse cognitive function than those with normal sleep duration (LLD-NS patients) and NC. LLD-SS patients exhibited higher FC between the bilateral insula and inferior frontal gyrus (IFG) pars triangularis than LLD-NS patients and NC, while LLD-NS patients exhibited lower FC than NC. Increased insular FC was correlated with short sleep duration, severe depressive symptoms, and slower information processing speeds. Furthermore, an additive effect was found between sleep duration and LLD on global cognition and insular FC.

CONCLUSION

LLD-SS patients exhibited impaired cognition and increased insular FC. Abnormal FC in LLD-SS patients may be a therapeutic target for neuromodulation to improve sleep and cognitive performance and thus decrease the risk of dementia.

The heterogeneity of late-life depression and its pathobiology: a brain network dysfunction disorder

Depression is frequent in older individuals and is often associated with cognitive impairment and increasing risk of subsequent dementia. Late-life depression (LLD) has a negative impact on quality of life, yet the underlying pathobiology is still poorly understood. It is characterized by considerable heterogeneity in clinical manifestation, genetics, brain morphology, and function. Although its diagnosis is based on standard criteria, due to overlap with other age-related pathologies, the relationship between depression and dementia and the relevant structural and functional cerebral lesions are still controversial. LLD has been related to a variety of pathogenic mechanisms associated with the underlying age-related neurodegenerative and cerebrovascular processes. In addition to biochemical abnormalities, involving serotonergic and GABAergic systems, widespread disturbances of cortico-limbic, cortico-subcortical, and other essential brain networks, with disruption in the topological organization of mood- and cognition-related or other global connections are involved. Most recent lesion mapping has identified an altered network architecture with "depressive circuits" and "resilience tracts", thus confirming that depression is a brain network dysfunction disorder. Further pathogenic mechanisms including neuroinflammation, neuroimmune dysregulation, oxidative stress, neurotrophic and other pathogenic factors, such as β-amyloid (and tau) deposition are in discussion. Antidepressant therapies induce various changes in brain structure and function. Better insights into the complex pathobiology of LLD and new biomarkers will allow earlier and better diagnosis of this frequent and disabling psychopathological disorder, and further elucidation of its complex pathobiological basis is warranted in order to provide better prevention and treatment of depression in older individuals.

Resting state connectivity predictors of symptom change during gaze-contingent music reward therapy of social anxiety disorder

BACKGROUND

Social anxiety disorder (SAD) is common, first-line treatments are often only partially effective, and reliable predictors of treatment response are lacking. Here, we assessed resting state functional connectivity (rsFC) at pre-treatment and during early treatment as a potential predictor of response to a novel attention bias modification procedure, gaze-contingent music reward therapy (GC-MRT).

METHODS

Thirty-two adults with SAD were treated with GC-MRT. rsFC was assessed with multi-voxel pattern analysis of fMRI at pre-treatment and after 2-3 weeks. For comparison, 20 healthy control (HC) participants without treatment were assessed twice for rsFC over the same time period. All SAD participants underwent clinical evaluation at pre-treatment, early-treatment (week 2-3), and post-treatment.

RESULTS

SAD and depressive symptoms improved significantly from pre-treatment to post-treatment. After 2-3 weeks of treatment, decreased connectivity between the executive control network (ECN) and salience network (SN), and increased connectivity within the ECN predicted improvement in SAD and depressive symptoms at week 8. Increased connectivity between the ECN and default mode network (DMN) predicted greater improvement in SAD but not depressive symptoms at week 8. Connectivity within the DMN decreased significantly after 2-3 weeks of treatment in the SAD group, while no changes were found in HC over the same time interval.

CONCLUSION

We identified early changes in rsFC during a course of GC-MRT for SAD that predicted symptom change. Connectivity changes within the ECN, ECN-DMN, and ECN-SN may be related to mechanisms underlying the clinical effects of GC-MRT and warrant further study in controlled trials.

Association of functional connectivity of the executive control network or default mode network with cognitive impairment in older adults with remitted major depressive disorder or mild cognitive impairment

Major depressive disorder (MDD) is associated with an increased risk of developing dementia. The present study aimed to better understand this risk by comparing resting state functional connectivity (rsFC) in the executive control network (ECN) and the default mode network (DMN) in older adults with MDD or mild cognitive impairment (MCI). Additionally, we examined the association between rsFC in the ECN or DMN and cognitive impairment transdiagnostically. We assessed rsFC alterations in ECN and DMN in 383 participants from five groups at-risk for dementia-remitted MDD with normal cognition (MDD-NC), non-amnestic mild cognitive impairment (naMCI), remitted MDD + naMCI, amnestic MCI (aMCI), and remitted MDD + aMCI-and from healthy controls (HC) or individuals with Alzheimer's dementia (AD). Subject-specific whole-brain functional connectivity maps were generated for each network and group differences in rsFC were calculated. We hypothesized that alteration of rsFC in the ECN and DMN would be progressively larger among our seven groups, ranked from low to high according to their risk for dementia as HC, MDD-NC, naMCI, MDD + naMCI, aMCI, MDD + aMCI, and AD. We also regressed scores of six cognitive domains (executive functioning, processing speed, language, visuospatial memory, verbal memory, and working memory) on the ECN and DMN connectivity maps. We found a significant alteration in the rsFC of the ECN, with post hoc testing showing differences between the AD group and the HC, MDD-NC, or naMCI groups, but no significant alterations in rsFC of the DMN. Alterations in rsFC of the ECN and DMN were significantly associated with several cognitive domain scores transdiagnostically. Our findings suggest that a diagnosis of remitted MDD may not confer functional brain risk for dementia. However, given the association of rs-FC with cognitive performance (i.e., transdiagnostically), rs-FC may help in stratifying this risk among people with MDD and varying degrees of cognitive impairment.

Automatic diagnosis of late-life depression by 3D convolutional neural networks and cross-sample Entropy analysis from resting-state fMRI

Resting-state fMRI has been widely used in investigating the pathophysiology of late-life depression (LLD). Unlike the conventional linear approach, cross-sample entropy (CSE) analysis shows the nonlinear property in fMRI signals between brain regions. Moreover, recent advances in deep learning, such as convolutional neural networks (CNNs), provide a timely application for understanding LLD. Accurate and prompt diagnosis is essential in LLD; hence, this study aimed to combine CNN and CSE analysis to discriminate LLD patients and non-depressed comparison older adults based on brain resting-state fMRI signals. Seventy-seven older adults, including 49 patients and 28 comparison older adults, were included for fMRI scans. Three-dimensional CSEs with volumes corresponding to 90 seed regions of interest of each participant were developed and fed into models for disease classification and depression severity prediction. We obtained a diagnostic accuracy > 85% in the superior frontal gyrus (left dorsolateral and right orbital parts), left insula, and right middle occipital gyrus. With a mean root-mean-square error (RMSE) of 2.41, three separate models were required to predict depressive symptoms in the severe, moderate, and mild depression groups. The CSE volumes in the left inferior parietal lobule, left parahippocampal gyrus, and left postcentral gyrus performed best in each respective model. Combined complexity analysis and deep learning algorithms can classify patients with LLD from comparison older adults and predict symptom severity based on fMRI data. Such application can be utilized in precision medicine for disease detection and symptom monitoring in LLD.

EEG microstate in first-episode drug-naive adolescents with depression

BACKGROUND

A growing number of studies have revealed significant abnormalities in EEG microstate in patients with depression, but these findings may be affected by medication. Therefore, how the EEG microstates abnormally change in patients with depression in the early stage and without the influence of medication has not been investigated so far.

METHODS

Resting-state EEG data and Hamilton Depression Rating Scale (HDRS) were collected from 34 first-episode drug-naïve adolescent with depression and 34 matched healthy controls. EEG microstate analysis was applied and nonlinear characteristics of EEG microstate sequences were studied by sample entropy and Lempel-Ziv complexity (LZC). The microstate temporal parameters and complexity were tried to train a SVM for classification of patients with depression.

RESULTS

Four typical EEG microstate topographies were obtained in both groups, but microstate C topography was significantly abnormal in depression patients. The duration of microstate B, C, D and the occurrence and coverage of microstate B significantly increased, the occurrence and coverage of microstate A, C reduced significantly in depression group. Sample entropy and LZC in the depression group were abnormally increased and were negatively correlated with HDRS. When the combination of EEG microstate temporal parameters and complexity of microstate sequence was used to classify patients with depression from healthy controls, a classification accuracy of 90.9% was obtained.

CONCLUSION

Abnormal EEG microstate has appeared in early depression, reflecting an underlying abnormality in configuring neural resources and transitions between distinct brain network states. EEG microstate can be used as a neurophysiological biomarker for early auxiliary diagnosis of depression.

A Comparative Study of Regional Homogeneity of Resting-State fMRI Between the Early-Onset and Late-Onset Recurrent Depression in Adults

Background

Neurobiological mechanisms underlying the recurrence of major depressive disorder (MDD) at different ages are unclear, and this study used the regional homogeneity (ReHo) index to compare whether there are differences between early onset recurrent depression (EORD) and late onset recurrent depression (LORD).

Methods

Eighteen EORD patients, 18 LORD patients, 18 young healthy controls (HCs), and 18 older HCs were included in the rs-fMRI scans. ReHo observational metrics were used for image analysis and further correlation of differential brain regions with clinical symptoms was analyzed.

Results

ANOVA analysis revealed significant differences between the four groups in ReHo values in the prefrontal, parietal, temporal lobes, and insula. Compared with EORD, the LORD had higher ReHo in the right fusiform gyrus/right middle temporal gyrus, left middle temporal gyrus/left angular gyrus, and right middle temporal gyrus/right angular gyrus, and lower ReHo in the right inferior frontal gyrus/right insula and left superior temporal gyrus/left insula. Compared with young HCs, the EORD had higher ReHo in the right inferior frontal gyrus/right insula, left superior temporal gyrus/left insula, and left rolandic operculum gyrus/left superior temporal gyrus, and lower ReHo in the left inferior parietal lobule, right inferior parietal lobule, and left middle temporal gyrus/left angular gyrus. Compared with old HCs, the LORD had higher ReHo in the right fusiform gyrus/right middle temporal gyrus, right middle temporal gyrus/right angular gyrus, and left rolandic operculum gyrus/left superior temporal gyrus, and lower ReHo in the right inferior frontal gyrus/right insula. ReHo in the right inferior frontal gyrus/right insula of patients with LORD was negatively correlated with the severity of 17-item Hamilton Rating Scale for Depression (HAMD-17) scores (r = −0.5778, p = 0.0120).

Conclusion

Adult EORD and LORD patients of different ages have abnormal neuronal functional activity in some brain regions, with differences closely related to the default mode network (DMN) and the salience network (SN), and patients of each age group exhibit ReHo abnormalities relative to matched HCs.

Clinical Trial Registration

[http://www.chictr.org.cn/], [ChiCTR1800014277].

Role of Stress-Related Dopamine Transmission in Building and Maintaining a Protective Cognitive Reserve

This short review presents the hypothesis that stress-dependent dopamine (DA) transmission contributes to developing and maintaining the brain network supporting a cognitive reserve. Research has shown that people with a greater cognitive reserve are better able to avoid symptoms of degenerative brain changes. The paper will review evidence that: (1) successful adaptation to stressors involves development and stabilization of effective but flexible coping strategies; (2) this process requires dynamic reorganization of functional networks in the adult brain; (3) DA transmission is amongst the principal mediators of this process; (4) age- and disease-dependent cognitive impairment is associated with dysfunctional connectivity both between and within these same networks as well as with reduced DA transmission.

OUP accepted manuscript

The Coronavirus disease of 2019 (COVID-19) and measures to curb it created population-level changes in male-dominant impulsive and risky behaviors such as violent crimes and gambling. One possible explanation for this is that the pandemic has been stressful, and males, more so than females, tend to respond to stress by altering their focus on immediate versus delayed rewards, as reflected in their delay discounting rates. Delay discounting rates from healthy undergraduate students were collected twice during the pandemic. Discounting rates of males (n=190) but not of females (n=493) increased during the pandemic. Using machine learning, we show that prepandemic functional connectome predict increased discounting rates in males (n=88). Moreover, considering that delay discounting is associated with multiple psychiatric disorders, we found the same neural pattern that predicted increased discounting rates in this study, in secondary datasets of patients with major depression and schizophrenia. The findings point to sex-based differences in maladaptive delay discounting under real-world stress events, and to connectome-based neuromarkers of such effects. They can explain why there was a population-level increase in several impulsive and risky behaviors during the pandemic and point to intriguing questions about the shared underlying mechanisms of stress responses, psychiatric disorders and delay discounting.

Default mode network dissociation linking cerebral beta amyloid retention and depression in cognitively normal older adults

Cerebral beta amyloid (Aβ) deposition and late-life depression (LLD) are known to be associated with the trajectory of Alzheimer's disease (AD). However, their neurobiological link is not clear. Previous studies showed aberrant functional connectivity (FC) changes in the default mode network (DMN) in early Aβ deposition and LLD, but its mediating role has not been elucidated. This study was performed to investigate the distinctive association pattern of DMN FC linking LLD and Aβ retention in cognitively normal older adults. A total of 235 cognitively normal older adults with (n = 118) and without depression (n = 117) underwent resting-state functional magnetic resonance imaging and ¹⁸F-flutemetamol positron emission tomography to investigate the associations between Aβ burden, depression, and DMN FC. Independent component analysis showed increased anterior DMN FC and decreased posterior DMN FC in the depression group compared with the no depression group. Global cerebral Aβ retention was positively correlated with anterior and negatively correlated with posterior DMN FC. Anterior DMN FC was positively correlated with severity of depression, whereas posterior DMN FC was negatively correlated with cognitive function. In addition, the effects of global cerebral Aβ retention on severity of depression were mediated by subgenual anterior cingulate FC. Our results of anterior and posterior DMN FC dissociation pattern may be pivotal in linking cerebral Aβ pathology and LLD in the course of AD progression. Further longitudinal studies are needed to confirm the causal relationships between cerebral Aβ retention and LLD.

Be Fit, Be Sharp, Be Well: The Case for Exercise as a Treatment for Cognitive Impairment in Late-life Depression

OBJECTIVE

To lay out the argument that exercise impacts neurobiological targets common to both mood and cognitive functioning, and thus more research should be conducted on its use as an alternative or adjunctive treatment for cognitive impairment in late-life depression (LLD).

METHOD

This narrative review summarizes the literature on cognitive impairment in LLD, describes the structural and functional brain changes and neurochemical changes that are linked to both cognitive impairment and mood disruption, and explains how exercise targets these same neurobiological changes and can thus provide an alternative or adjunctive treatment for cognitive impairment in LLD.

RESULTS

Cognitive impairment is common in LLD and predicts recurrence of depression, poor response to antidepressant treatment, and overall disability. Traditional depression treatment with medication, psychotherapy, or both, is not effective in fully reversing cognitive impairment for most depressed older adults. Physical exercise is an ideal treatment candidate based on evidence that it 1) is an effective treatment for depression, 2) enhances cognitive functioning in normal aging and in other patient populations, and 3) targets many of the neurobiological mechanisms that underlie mood and cognitive functioning. Results of the limited existing clinical trials of exercise for cognitive impairment in depression are mixed but overall support this contention.

CONCLUSIONS

Although limited, existing evidence suggests exercise may be a viable alternative or adjunctive treatment to address cognitive impairment in LLD, and thus more research in this area is warranted. Moving forward, additional research is needed in large, diverse samples to translate the growing research findings into clinical practice.

Crosstalk between Existential Phenomenological Psychotherapy and Neurological Sciences in Mood and Anxiety Disorders

Psychotherapy is a comprehensive biological treatment modifying complex underlying cognitive, emotional, behavioral, and regulatory responses in the brain, leading patients with mental illness to a new interpretation of the sense of self and others. Psychotherapy is an art of science integrated with psychology and/or philosophy. Neurological sciences study the neurological basis of cognition, memory, and behavior as well as the impact of neurological damage and disease on these functions, and their treatment. Both psychotherapy and neurological sciences deal with the brain; nevertheless, they continue to stay polarized. Existential phenomenological psychotherapy (EPP) has been in the forefront of meaning-centered counseling for almost a century. The phenomenological approach in psychotherapy originated in the works of Martin Heidegger, Ludwig Binswanger, Medard Boss, and Viktor Frankl, and it has been committed to accounting for the existential possibilities and limitations of one's life. EPP provides philosophically rich interpretations and empowers counseling techniques to assist mentally suffering individuals by finding meaning and purpose to life. The approach has proven to be effective in treating mood and anxiety disorders. This narrative review article demonstrates the development of EPP, the therapeutic methodology, evidence-based accounts of its curative techniques, current understanding of mood and anxiety disorders in neurological sciences, and a possible converging path to translate and integrate meaning-centered psychotherapy and neuroscience, concluding that the EPP may potentially play a synergistic role with the currently prevailing medication-based approaches for the treatment of mood and anxiety disorders.

Crosstalk between Depression and Dementia with Resting-State fMRI Studies and Its Relationship with Cognitive Functioning

Alzheimer’s disease (AD) is the most common type of dementia, and depression is a risk factor for developing AD. Epidemiological studies provide a clinical correlation between late-life depression (LLD) and AD. Depression patients generally remit with no residual symptoms, but LLD patients demonstrate residual cognitive impairment. Due to the lack of effective treatments, understanding how risk factors affect the course of AD is essential to manage AD. Advances in neuroimaging, including resting-state functional MRI (fMRI), have been used to address neural systems that contribute to clinical symptoms and functional changes across various psychiatric disorders. Resting-state fMRI studies have contributed to understanding each of the two diseases, but the link between LLD and AD has not been fully elucidated. This review focuses on three crucial and well-established networks in AD and LLD and discusses the impacts on cognitive decline, clinical symptoms, and prognosis. Three networks are the (1) default mode network, (2) executive control network, and (3) salience network. The multiple properties emphasized here, relevant for the hypothesis of the linkage between LLD and AD, will be further developed by ongoing future studies.

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.

Topological reorganization of the default mode network in patients with poststroke depressive symptoms: A resting-state fMRI study

OBJECTIVE

This study mapped the topological configuration of the default mode network (DMN) in patients with depressive symptoms after acute ischemic stroke.

METHODS

The study sample comprised 63 patients: 36 with poststroke depressive symptoms (PSD) and 37 without PSD matched according to age, gender and the severity of stroke. PSD was defined by a cutoff of ≥ 7 on the 15-item Geriatric Depression Scale (GDS). Resting-state functional magnetic resonance imaging (fMRI) was used to examine functional connectivity (FC) to reconstruct the DMN. Network based statistics estimated the FC differences of the DMN between the PSD and non-PSD groups. Graph theoretical approaches were used to characterize the topological properties of this network.

RESULTS

The study sample mainly comprised patients with mild to moderate stroke. A widespread hyper-connected configuration of the functional DMN was characterized in PSD group. The orbital frontal, dorsolateral prefrontal, dorsal medial prefrontal and, ventromedial prefrontal corticis, the middle temporal gyrus and the inferior parietal lobule were the functional hubs related to PSD. The nodal topology in inferior parietal lobule and superior frontal gyrus, overlapping with dorsal medial prefrontal and, ventromedial prefrontal cortices, tended to be functionally integrated in patients with PSD. After False Discovery Rate correction, no significant difference between the PSD and non-PSD groups was found with respect to the global and nodal metrics of the DMN. However, the correlations between these altered network metrics and severity of PSD were lacking.

LIMITATIONS

The diagnosis of PSD was based on the GDS score rather than established with a structured clinical interview.

CONCLUSIONS

The DMN in PSD was functionally integrated and more specialized in some core hubs such as the inferior parietal lobule and dorsal prefrontal cortex. The configuration of the subnetwork like DMN may be more essential in the pathogenesis of PSD than single stroke lesions.

Persistent Intrinsic Functional Network Connectivity Alterations in Middle-Aged and Older Women With Remitted Depression

BACKGROUND

In younger adults, residual alterations in functional neural networks persist during remitted depression. However, there are fewer data for midlife and older adults at risk of recurrence. Such residual network alterations may contribute to vulnerability to recurrence. This study examined intrinsic network functional connectivity in midlife and older women with remitted depression.

METHODS

A total of 69 women (24 with a history of depression, 45 with no psychiatric history) over 50 years of age completed 3T fMRI with resting-state acquisition. Participants with remitted depression met DSM-IV-TR criteria for an episode in the last 10 years but not the prior year. Whole-brain seed-to-voxel resting-state functional connectivity analyses examined the default mode network (DMN), executive control network (ECN), and salience network (SN), plus bilateral hippocampal seeds. All analyses were adjusted for age and used cluster-level correction for multiple comparisons with FDR < 0.05 and a height threshold of p < 0.001, uncorrected.

RESULTS

Women with a history of depression exhibited decreased functional connectivity between the SN (right insula seed) and ECN regions, specifically the left superior frontal gyrus. They also exhibited increased functional connectivity between the left hippocampus and the left postcentral gyrus. We did not observe any group differences in functional connectivity for DMN or ECN seeds.

CONCLUSIONS

Remitted depression in women is associated with connectivity differences between the SN and ECN and between the hippocampus and the postcentral gyrus, a region involved in interoception. Further work is needed to determine whether these findings are related to functional alterations or are predictive of recurrence.

Association of anxiety with subcortical amyloidosis in cognitively normal older adults

Late-life anxiety has been associated with increased progression from normal cognition to amnestic MCI, suggesting that anxiety may be a neuropsychiatric symptom of Alzheimer's disease (AD) pathological changes and a possible marker of anatomical progression in preclinical AD. This study examined whether cortical or subcortical amyloidosis, indicating earlier or later stages of preclinical AD, was associated with greater self-reported anxiety among 118 cognitively normal volunteers, aged 65-90 years, and whether this association was stronger in APOEε4 carriers. Participants underwent Pittsburgh Compound B Positron Emission Tomography (PiB-PET) to assess fibrillar amyloid-β burden in cortical and subcortical regions, and measurement of anxiety using the Hospital Anxiety and Depression Scale-anxiety subscale. Higher PiB-PET measures in the subcortex (striatum, amygdala, and thalamus), but not in the cortex, were associated with greater anxiety, adjusting for demographics, cognition, and depression. Findings were similar using a cortico-striatal staging system and continuous PET measurements. Anxiety was highest in APOEε4 carriers with subcortical amyloidosis. This work supports in vivo staging of amyloid-β deposition in both cortical and subcortical regions as a promising approach to the study of neuropsychiatric symptoms such as anxiety in cognitively normal older individuals. Elevated anxiety symptoms in combination with high-risk biological factors such as APOEε4 and subcortical amyloid-β may identify participants closest to MCI for secondary prevention trials.

Disruption of Neural Homeostasis as a Model of Relapse and Recurrence in Late-Life Depression

The significant public health burden associated with late-life depression (LLD) is magnified by the high rates of recurrence. In this manuscript, we review what is known about recurrence risk factors, conceptualize recurrence within a model of homeostatic disequilibrium, and discuss the potential significance and challenges of new research into LLD recurrence. The proposed model is anchored in the allostatic load theory of stress. We review the allostatic response characterized by neural changes in network function and connectivity and physiologic changes in the hypothalamic-pituitary-adrenal axis, autonomic nervous system, immune system, and circadian rhythm. We discuss the role of neural networks' instability following treatment response as a source of downstream disequilibrium, triggering and/or amplifying abnormal stress response, cognitive dysfunction and behavioral changes, ultimately precipitating a full-blown recurrent episode of depression. We propose strategies to identify and capture early change points that signal recurrence risk through mobile technology to collect ecologically measured symptoms, accompanied by automated algorithms that monitor for state shifts (persistent worsening) and variance shifts (increased variability) relative to a patient's baseline. Identifying such change points in relevant sensor data could potentially provide an automated tool that could alert clinicians to at-risk individuals or relevant symptom changes even in a large practice.

Diagnosing and Treating Depression in Patients with Alzheimer's Disease

Although cognitive and functional impairment are the hallmark features of Alzheimer's disease (AD), neuropsychiatric symptoms associated with AD account for increased rates of disability and profoundly impact the quality of life of both patients and their caregivers. This narrative review of current evidence provides practical guidance in diagnosing and managing depression in patients with AD using pharmacological and nonpharmacological interventions. After apathy, depression is the second most common neuropsychiatric symptom in AD. Diagnosing late-life depression (LLD), particularly in those affected by AD, is complicated because older patients may not meet the criteria for a major depressive disorder. Clinically, late-life depression and dementia can be indistinguishable. Although these two entities are now thought to be related, the pathologic mechanisms remain unclear. Evidence suggests that LLD may be a prodromal symptom of neurodegenerative disease. The various geropsychiatric measures currently used to diagnose, rate the severity of, and monitor the progress of treatment for depression are imperfect. Neuroimaging represents a promising avenue toward understanding the complex pathophysiologic relationships between dementia and LLD, and will support the pursuit of biomarker-driven diagnosis and treatment. Nonpharmacologic interventions to relieve depression in persons with cognitive impairment and dementia include emotion-oriented therapies, behavioral and cognitive-behavioral modification programs, and structured activity programs. Sensory-stimulation therapies and multisensory approaches show some promise for successfully treating depression in patients with dementia, but further rigorous research is needed to establish their validity. Clinical consensus and research appear to support selective serotonin reuptake inhibitors as a first choice for the pharmacological treatment of depression in patients with dementia. However, initial support for these therapies remains variable, and further investigation is needed. Extra care is required in prescribing to this population because of the generally high level of medical and psychiatric comorbidity and the potential difficulty in assessing the cognitively impaired patient's response.

Brain structural abnormalities in emotional regulation and sensory processing regions associated with anxious depression

BACKGROUND

Considerable patients with major depressive disorder (MDD) comorbid with anxious symptoms, referred as anxious depression. The neural structural basis of this MDD specifier remains largely unknown.

METHODS

104 patients with anxious depression, 57 MDD patients without significant anxious symptoms, and 160 healthy controls from single research center participated in the study with age and sex well-matched. We investigated gray matter alterations in anxious and non-anxious depression, explored different brain alterations between these two patient groups, and possible relationships between brain structural parameter and clinical information in patients.

RESULTS

Gray matter volumes differed in the right inferior frontal gyrus, right orbital frontal gyrus, left postcentral gyrus, bilateral culmen and left cuneus among the three groups. Anxious depression had smaller gray matter volumes in the right inferior frontal gyrus and orbital frontal gyrus relative to both non-anxious depression and healthy controls. Patients with anxious depression presented larger gray matter volumes in the left postcentral gyrus than non-anxious depression, and larger gray matter volumes in the left cuneus than healthy controls. In addition, both patient groups showed larger gray matter volumes in bilateral culmen relative to healthy controls. Gray matter volumes in the left postcentral gyrus were positively associated with overall depression severity and anxiety factor scores in anxious depression.

CONCLUSION

Our study revealed brain structural abnormalities in emotional regulation and sensory processing regions of anxious depression, which may suggested distinct neurobiological mechanisms of this MDD specifier and could help explain different clinical manifestations in anxious depression from pure depression.

Recent advances in the use of imaging in psychiatry: functional magnetic resonance imaging of large-scale brain networks in late-life depression

Advances in neuroimaging have identified neural systems that contribute to clinical symptoms that occur across various psychiatric disorders. This transdiagnostic approach to understanding psychiatric illnesses may serve as a precise guide to identifying disease mechanisms and informing successful treatments. While this work is ongoing across multiple psychiatric disorders, in this article we emphasize recent findings pertaining to major depression in the elderly, or late-life depression (LLD), a common and debilitating neuropsychiatric illness. We discuss how neural functioning of three networks is linked to symptom presentation, illness course, and cognitive decline in LLD. These networks are (1) an executive control network responsible for complex cognitive processing, (2) a default mode network normally deactivated during cognitive demanding when individuals are at rest, and a (3) salience network relevant to attending to internal and external emotional and physiological sensations. We discuss how dysfunction in multiple networks contributes to common behavioral syndromes, and we present an overview of the cognitive control, default mode, and salience networks observed in LLD.

An inverse relationship between cortical plasticity and cognitive inhibition in late-life depression

Executive dysfunction is a common and disabling component of late-life depression (LLD), yet its neural mechanisms remain unclear. In particular, it is not yet known how executive functioning in LLD relates to measures of cortical physiology that may change with age and illness, namely cortical inhibition/excitation and plasticity. Here, we used transcranial magnetic stimulation (TMS) to measure cortical inhibition/excitation (n = 51), and the potentiation of cortical activity following paired associative stimulation, which is thought to reflect long-term potentiation (LTP)-like cortical plasticity (n = 32). We assessed the correlation between these measures of cortical physiology and two measures of executive functioning: cognitive inhibition, assessed using the Delis-Kaplan Executive Function System Color-Word Interference ["Stroop"] Test, and cognitive flexibility, assessed using the Trail Making Test. Correlations with recall memory and processing speed were also performed to assess the specificity of any associations to executive functioning. A significant correlation was found between greater LTP-like cortical plasticity and poorer cognitive inhibition, a core executive function (rp = -0.56, p < 0.001). We did not observe significant associations between cortical inhibition/excitation and executive functioning, or between any neurophysiological measure and cognitive flexibility, memory, or processing speed. Our finding that elevated cortical plasticity is associated with diminished cognitive inhibition emphasizes the importance of balanced synaptic strengthening to healthy cognition. More specifically, our findings suggest that hyper-excitability of cortical circuits following repeated cortical activation may promote inappropriate prepotent responses in LLD. LTP-like cortical plasticity might therefore represent a neural mechanism underlying an inhibitory control cognitive endophenotype of LLD.

Functional plasticity of the dorsomedial prefrontal cortex in depression reorganized by electroconvulsive therapy: Validation in two independent samples

Previous studies have implied a key role for the prefrontal cortex in the antidepressive effect of electroconvulsive therapy (ECT). However, there is still ubiquitous inconsistency across these studies, partly due to several confounding effects induced by the use of different samples. Studies with independent samples are necessary for validations to minimize confounding effects. In the current study, resting-state magnetic resonance imaging of 84 participants was collected using two scanners and two types of scanning parameters. One sample consisted of 28 patients and 23 healthy controls, and the other sample consisted of 33 patients. The local activity (indexed by the amplitude of low-frequency fluctuations) and functional connectivity were used to examine functional plasticity in the two independent samples before and after ECT. Both samples showed increased local activity of the dorsomedial prefrontal cortex (DMPFC) and enhanced connectivity of the DMPFC with the posterior cingulate cortex (PCC) following ECT. The enhanced connectivity between the DMPFC and PCC was positively associated with clinical improvement for both samples. These findings provide relatively strong evidence to support the functional plasticity of the dorsomedial prefrontal cortex and reorganization by ECT. The functional plasticity of the DMPFC-PCC may underlie the antidepressive effect of ECT.

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.

Intrinsic Functional Network Connectivity Is Associated With Clinical Symptoms and Cognition in Late-Life Depression

BACKGROUND

Late-life depression (LLD) has been associated with alterations in intrinsic functional networks, best characterized in the default mode network (DMN), cognitive control network (CCN), and salience network. However, these findings often derive from small samples, and it is not well understood how network findings relate to clinical and cognitive symptomatology.

METHODS

We studied 100 older adults (n = 79 with LLD, n = 21 nondepressed) and collected resting-state functional magnetic resonance imaging, clinical measures of depression, and performance on cognitive tests. We selected canonical network regions for each intrinsic functional network (DMN, CCN, and salience network) as seeds in seed-to-voxel analysis. We compared connectivity between the depressed and nondepressed groups and correlated connectivity with depression severity among depressed subjects. We then investigated whether the observed connectivity findings were associated with greater severity of common neuropsychiatric symptoms or poorer cognitive performance.

RESULTS

LLD was characterized by decreased DMN connectivity to the frontal pole, a CCN region (Wald χ²₁ = 22.33, p < .001). No significant group differences in connectivity were found for the CCN or salience network. However, in the LLD group, increased CCN connectivity was associated with increased depression severity (Wald χ²₁ > 20.14, p < .001), greater anhedonia (Wald χ²₁ = 7.02, p = .008) and fatigue (Wald χ²₁ = 6.31, p = .012), and poorer performance on tests of episodic memory (Wald χ²₁ > 4.65, p < .031), executive function (Wald χ²₁ = 7.18, p = .007), and working memory (Wald χ²₁ > 4.29, p < .038).

CONCLUSIONS

LLD is characterized by differences in DMN connectivity, while CCN connectivity is associated with LLD symptomology, including poorer performance in several cognitive domains.

Multiple cortical thickness sub-networks and cognitive impairments in first episode, drug naïve patients with late life depression: A graph theory analysis

BACKGROUND

Coordinated and pattern-wise changes in large scale gray matter structural networks reflect neural circuitry dysfunction in late life depression (LLD), which in turn is associated with emotional dysregulation and cognitive impairments. However, due to methodological limitations, there have been few attempts made to identify individual-level structural network properties or sub-networks that are involved in important brain functions in LLD.

METHODS

In this study, we sought to construct individual-level gray matter structural networks using average cortical thicknesses of several brain areas to investigate the characteristics of the gray matter structural networks in normal controls and LLD patients. Additionally, we investigated the structural sub-networks correlated with several clinical measurements including cognitive impairment and depression severity.

RESULTS

We observed that small worldness, clustering coefficients, global and local efficiency, and hub structures in the brains of LLD patients were significantly different from healthy controls. We further found that a sub-network including the anterior cingulate, dorsolateral prefrontal cortex and superior prefrontal cortex is significantly associated with attention control and executive function. The severity of depression was associated with the sub-networks comprising the salience network, including the anterior cingulate and insula.

LIMITATIONS

We investigated cortico-cortical connectivity, but omitted the subcortical structures such as the striatum and thalamus.

CONCLUSION

We report differences in patterns between several clinical measurements and sub-networks from large-scale and individual-level cortical thickness networks in LLD.

Advances and Barriers for Clinical Neuroimaging in Late-Life Mood and Anxiety Disorders

PURPOSE OF REVIEW

Mood and anxiety disorders are very commonly experienced by older adults and are becoming a growing concern due to the rapidly aging global population. Recent advances in neuroimaging may help in improving outcomes in late-life mood and anxiety disorders. The elucidation of mechanisms contributing to late-life mental health disorders may ultimately lead to the identification of novel therapeutic interventions. Alternatively, clinically validated imaging biomarkers may allow for the prediction of treatment response and identification of better therapeutic approaches in late-life mood and anxiety disorders.

RECENT FINDINGS

In community samples, late-life depression and late-life generalized anxiety disorder occur up to 38 and 15%, respectively, while late-life bipolar disorder is less common and occur in approximately 0.5% of the population. There are significant challenges in treating and improving outcome in late-life mood and anxiety disorders. Time to treatment response and treatment resistance are increased in older adults. Novel neuroimaging techniques have the potential to improve diagnostic and therapeutic outcome in late-life mood and anxiety disorders either through "personalized pharmacotherapy" or through identifying dysfunction regions/networks to be subsequently used for direct interventions such as transcranial magnetic stimulation. This review will provide an overview of recent literature that substantiates the potential role of neuroimaging in clinical practice, as well as the barriers that must be overcome prior to clinical translation.

Patients with anxious depression: overview of prevalence, pathophysiology and impact on course and treatment outcome

PURPOSE OF REVIEW

Major depressive disorder with a comorbid anxiety disorder or with significant anxiety symptoms (here called anxious depression) is common and has been associated with poor clinical course trajectories. However, various dichotomous as well as dimensional definitions have been used to label anxious depression and it remains unclear to which extent these result in inconsistent findings. This review provides an overview of recent literature on the impact of anxiety in depressed patients on clinical course trajectories, treatment outcomes, and underlying neurobiological dysregulations.

RECENT FINDINGS

Anxious depression seems associated with poorer clinical course trajectories and treatment nonresponse as compared with 'pure' depression, regardless of which definition is used. Recent studies have attempted to determine specific efficacy of novel pharmacological treatments for anxious depressed patients, but have not been conclusive because of the insufficient number of studies and differences in definitions and assessment of anxious depression. Neurobiology studies suggest that anxious depression is associated with increased immune dysregulation, more cortical thinning, and corticolimbic dysfunctions as compared with 'pure' depression.

SUMMARY

Anxious depression appears to be a common and clinically relevant subtype of depression as it predicts poorer course trajectories. As populations with anxious depression may benefit from specific treatment regimens, further research is necessary to better delineate its definition and neurobiology. The relatively new Diagnostic and Statistical Manual of Mental Disorders-5 anxious distress specifier is a welcome development and should be further investigated and compared against other anxiety constructs.

Nicotine and networks: Potential for enhancement of mood and cognition in late-life depression

Late-life depression is characterized by both lower mood and poor cognitive performance, symptoms that often do not fully respond to current antidepressant medications. Nicotinic acetylcholine receptor (nAChR) agonists such as nicotine may serve as a novel therapeutic approach for this population. Both preclinical and preliminary clinical studies suggest that nAChR agonists can improve depressive behavior in animal models and improve mood in depressed individuals. Substantial literature also supports that nAChR agonists benefit cognitive performance, particularly in older populations. These potential benefits may be mediated by the effects of nAChR stimulation on neural network function and connectivity. Functional neuroimaging studies detail effects of nAChR agonists on the default mode network, central-executive network, and salience network that may oppose or reverse network changes seen in depression. We propose that, given the existent literature and the clinical presentation of late-life depression, nicotine or other nAChR agonists may have unique therapeutic benefits in this population and that clinical trials examining nicotine effects on mood, cognition, and network dynamics in late-life depression are justified.

Cerebral blood flow changes in remitted early- and late-onset depression patients

Abnormal cerebral blood flow (CBF) is reportedly associated with major depressive disorder (MDD). We have investigated CBF changes in early-onset depression (EOD) and late-onset depression (LOD), and their impact on cognitive function. Thirty-two remitted EOD patients, 32 remitted LOD patients, and 43 age-matched healthy controls were recruited, and the pulsed arterial spin labeling data were scanned under 3.0T MRI and processed through voxel-by-voxel statistical analysis. Compared to healthy controls, LOD patients had decreased normalized CBF in the bilateral precuneus, cuneus, right fronto-cingulate-striatal areas, and right temporal, occipital and parietal lobes, but increased normalized CBF in the left frontal and temporal cortices and the cingulate gyrus. EOD patients had decreased normalized CBF in the left cerebellum and right calcarine/lingual/fusiform gyrus, and increased normalized CBF in right angular gyrus. LOD patients displayed hemispheric asymmetry in CBF, and had more regions with abnormal CBF than EOD patients. A significant correlation between abnormal CBF and impaired cognitive function was detected in LOD patients, but not EOD patients. These results demonstrate greater CBF abnormalities in LOD patients than EOD patients, and suggest these CBF changes may be associated with progressive degradation of cognitive function in LOD patients.