Abnormal default-mode network in angiotensin converting enzyme D allele carriers with remitted geriatric depression

Hyperconnectivity between the posterior cingulate and middle frontal and temporal gyrus in depression: Based on functional connectivity meta-analyses

Disrupted whole-brain resting-state functional connectivity (RSFC) of the posterior cingulate (PCC) has been highlighted to associate with cognitive and affective dysfunction in major depressive disorder (MDD). However, prior findings showed certain inconsistency about the RSFC of the PCC in MDD. This study aims to investigate the aberrant RSFC of the PCC in MDD using anisotropic effect-size version of seed-based d mapping (AES-SDM). Web of Science and PubMed were searched for studies investigating PCC-based RSFC in MDD. A total of 17 studies, involving 804 patients and 724 healthy controls (HCs), fit our selection criteria. Additionally, to seek for the link between functional and structural differences, we did a meta-analysis on the studies in conjunction with voxel-based morphology (VBM) analysis. The PCC showed higher RSFC with the left middle temporal gyrus (MTG) and the right middle frontal gyrus (MFG), and lower RSFC with the left superior frontal gyrus (SFG) and the left precuneus in patients with MDD than HCs. Moreover, the meta-regression analysis revealed a negative correlation between the FC alteration of the right MFG with the PCC and depression severity. Notably, the left MTG and the left MFG demonstrated gray matter deviations in conjunction analysis. Our results indicated that the aberrant RSFC between the PCC and brain regions sub-serving cognitive control and emotional regulation in patients with MDD. And such functional alterations may have structural basis. These findings may underlie the mechanisms of deficits in cognitive control and emotional regulation of MDD.

Intrinsic connectivity identifies the sensory-motor network as a main cross-network between remitted late-life depression- and amnestic mild cognitive impairment-targeted networks

Remitted late-life depression (rLLD) and amnestic mild cognitive impairment (aMCI) are both associated with a high risk of developing Alzheimer's disease (AD). Neurodegeneration is considered to spread within pre-existing networks. To investigate whether, in the healthy brain, there was a pre-existing cross-network between the intrinsic networks that are vulnerable to rLLD and aMCI. We performed functional connectivity analyses based on brain areas with the greatest brain neuronal activity differences in 55 rLLD, 87 aMCI, and 114 healthy controls. Intrinsic networks that were differentially vulnerable to rLLD and aMCI converged onto the sensory-motor network (SMN) in the healthy brain. These regions in the SMN within the aMCI- and rLLD-vulnerable networks played different roles in the cognitive functions. This study identifies the SMN as a cross-network between rLLD- and aMCI-vulnerable networks. The common susceptibility of these diseases to AD is likely due to the breakdown of the cross-network. The results further suggest that interventions targeting the amelioration of sensory-motor deficits in the early course of disease in individuals with AD risk may enhance patient function as AD pathology progresses.

Neural substrates for late-life depression: A selective review of structural neuroimaging studies

Recent neuroimaging studies have characterized the pathophysiology of late-life depression (LLD) as a dysfunction of the brain networks involved in the regulation of emotion, motivational behavior, cognitive control, executive function, and self-referential thinking. In this article, we reviewed LLD-associated structural neuroimaging markers such as white matter hyperintensity (WMH), white matter integrity measured by diffusion tensor imaging, cortical and subcortical volumes, and cortical thickness, which may provide a structural basis for brain network dysfunction in LLD. LLD was associated with greater severity or volumes of deep, periventricular, or overall WMH and with decreased white matter integrity in the brain regions belonging to the fronto-striatal-limbic circuits and reduced white matter tract integrity which connects these circuits, such as the cingulum, corpus callosum, or uncinate fasciculus. Decreased volumes or cortical thickness in the prefrontal cortex, orbitofrontal cortex, anterior and posterior cingulate cortex, several temporal and parietal regions, hippocampus, amygdala, striatum, thalamus, and the insula were associated with LLD. These structural neuroimaging findings were also associated with cognitive dysfunction, which is a prominent clinical feature in LLD. Several structural neuroimaging markers including the WMH burden, white matter integrity, and cortical and subcortical volumes predicted antidepressant response in LLD. These structural neuroimaging findings support the hypothesis that disruption of the brain networks involved in emotion regulation and cognitive processing by impaired structural connectivity is strongly associated with the pathophysiology of LLD.

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.

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.

The Dose-Dependent Effects of Vascular Risk Factors on Dynamic Compensatory Neural Processes in Mild Cognitive Impairment

Background/Objectives: Mild cognitive impairment (MCI) has been associated with risk for Alzheimer's Disease (AD). Previous investigations have suggested that vascular risk factors (VRFs) were associated with cognitive decline and AD pathogenesis, and the intervention of VRFs may be a possible way to prevent dementia. However, in MCI, little is known about the potential impacts of VRFs on neural networks and their neural substrates, which may be a neuroimaging biomarker of the disease progression.

Methods: 128 elderly Han Chinese participants (67 MCI subjects and 61 matched normal elderly) with or without VRFs (hypertension, diabetes mellitus, hypercholesterolemia, smoking and alcohol drinking) underwent the resting-state functional magnetic resonance imaging (fMRI) and neuropsychological tests. We obtained the default mode network (DMN) to identify alterations in MCI with the varying number of the VRF and analyzed the significant correlation with behavioral performance.

Results: The effects of VRF on the DMN were primarily in bilateral dorsolateral prefrontal cortex (DLPFC) (i.e., middle frontal gyrus). Normal elderly showed the gradually increased functional activity of DLPFC, while a fluctuant activation of DLPFC was displayed in MCI with the growing number of the VRF. Interestingly, the left DLPFC further displayed significantly dynamic correlation with executive function as the variation of VRF loading. Initial level of compensation was observed in normal aging and none-vascular risk factor (NVRF) MCI, while these compensatory neural processes were suppressed in One-VRF MCI and were subsequently re-aroused in Over-One-VRF MCI.

Conclusions: These findings suggested that the dose-dependent effects of VRF on DLPFC were highlighted in MCI, and the dynamic compensatory neural processes that fluctuated along with variations of VRF loading could be key role in the progression of MCI.

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.

The renin-angiotensin system: a possible new target for depression

Depression remains a debilitating condition with an uncertain aetiology. Recently, attention has been given to the renin-angiotensin system. In the central nervous system, angiotensin II may be important in multiple pathways related to neurodevelopment and regulation of the stress response. Studies of drugs targeting the renin-angiotensin system have yielded promising results. Here, we review the potential beneficial effects of angiotensin blockers in depression and their mechanisms of action. Drugs blocking the angiotensin system have efficacy in several animal models of depression. While no randomised clinical trials were found, case reports and observational studies showed that angiotensin-converting enzyme inhibitors or angiotensin receptor blockers had positive effects on depression, whereas other antihypertensive agents did not. Drugs targeting the renin-angiotensin system act on inflammatory pathways implicated in depression. Both preclinical and clinical data suggest that these drugs possess antidepressant properties. In light of these results, angiotensin system-blocking agents offer new horizons in mood disorder treatment.

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.

Targeting Ruminative Thinking in Adolescents at Risk for Depressive Relapse: Rumination-Focused Cognitive Behavior Therapy in a Pilot Randomized Controlled Trial with Resting State fMRI

This pilot randomized control trial was designed to examine whether Rumination-Focused Cognitive Behavior Therapy (RFCBT) reduces rumination and residual depressive symptoms among adolescents with a history of Major Depressive Disorder (MDD) who are at risk for relapse. We also examined whether these changes in symptoms were associated with changes in functional connectivity of the posterior cingulate cortex (PCC), a key node in the default mode network (DMN). Thirty-three adolescents (ages 12–18) were randomized to eight weeks of RFCBT or an assessment only (AO) control. Twenty two adolescents successfully completed fMRI scans pre- and post-intervention. Adolescents were recruited from the clinic and community and met criteria for at least one previous episode of MDD and were currently in full or partial remission. An Independent Evaluator interviewed parent and child before and after the eight-week intervention. The left PCC (-5, -50, 36) seed was used to probe resting state functional connectivity of the DMN. Adolescents who received RFCBT demonstrated reduced rumination (F = -2.76, df = 112, p < .01, 95% CI [-4.72,-0.80]) and self-report depression across eight weeks (F = -2.58, df = 113, p < .01, 95% CI [-4.21, -0.94]). Youth who received RFCBT also demonstrated significant decreases in connectivity between the left PCC and the right inferior frontal gyrus (IFG) and bilateral inferior temporal gyri (ITG). Degree of change in connectivity was correlated with changes in self-report depression and rumination. These data suggest that rumination can be reduced over eight weeks and that this reduction is associated with parallel decreases in residual depressive symptoms and decreased functional connectivity of the left PCC with cognitive control nodes. These changes may enhance the ability of vulnerable youth to stay well during the transition to adulthood.

Trial Registration: ClinicalTrials.gov NCT01905267

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.

The Current Situation on Major Depressive Disorder in China: Research on Mechanisms and Clinical Practice

Depression is the most disabling disorder worldwide that accounts for the highest proportion of global burden attributable to mental disorders. Major depressive disorder (MDD) is characterized by deep sadness, reduced energy, vegetative nervous system dysregulation, cognitive dysfunction, and even a high suicidal tendency. Although other treatment choices are available, antidepressant medication is the front-line treatment option for MDD. Regarding clinical efficacy, only ~50% of patients respond to frontline antidepressants, and <33% obtain remission. Currently, objective indexes to guide clinical decisions are still lacking. Furthermore, knowledge about the neurobiological mechanisms underlying discrepant antidepressant outcomes is still also fragmentary. In the present review, we discuss the current research progress and clinical opinions on MDD in China.

The Clinical Applicability of Functional Connectivity in Depression: Pathways Toward More Targeted Intervention

Resting-state functional magnetic resonance imaging provides a noninvasive method to rapidly map large-scale brain networks affected in depression and other psychiatric disorders. Dysfunctional connectivity in large-scale brain networks has been consistently implicated in major depressive disorder (MDD). Although advances have been made in identifying neural circuitry implicated in MDD, this information has yet to be translated into improved diagnostic or treatment interventions. In the first section of this review, we discuss dysfunctional connectivity in affective salience, cognitive control, and default mode networks observed in MDD in association with characteristic symptoms of the disorder. In the second section, we address neurostimulation focusing on transcranial magnetic stimulation and evidence that this approach may directly modulate circuit abnormalities. Finally, we discuss possible avenues of future research to develop more precise diagnoses and targeted interventions within the heterogeneous diagnostic category of MDD as well as the methodological limitations to clinical implementation. We conclude by proposing, with cautious optimism, the future incorporation of neuroimaging into clinical practice as a tool to aid in more targeted diagnosis and treatment guided by circuit-level connectivity dysfunction in patients with depression.

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.

LORETA Neurofeedback in the Precuneus: Operant Conditioning in Basic Mechanisms of Self-Regulation

Low-resolution brain electomagnetic tomography (LORETA) neurofeedback provides a mechanism to influence the electrical activity of the brain in intracranial space. The aim of this study was to determine the effects of LORETA neurofeedback (LNFB) in the precuneus as a mechanism for improving self-regulation in controls and a heterogeneous diagnostic group (DX). Thirteen participants completed between 10 and 20 sessions of LNFB training in a 3-voxel cluster in the left precuneus. The participants included 5 nonclinical university students, and 8 adults with heterogeneous psychiatric diagnoses. We assessed the effects of LNFB with neurophysiological measures as well as pre- and post-Personality Assessment Inventory (PAI) subscales and selected subtests from the Delis-Kaplan Executive Function System (DKEFS). There was a significant total relative power increase at the precuneus for baseline contrasts for the control group. The DX group did not reach significant levels. All participants showed improvements in executive functions and tended to report significantly less psychopathology. The basic neural mechanisms of self-regulation are poorly understood. The data obtained in this study demonstrate that LNFB in a heterogeneous population enhances executive functions while concordantly decreasing endorsement of psychological symptoms. The alpha frequency in the brain may represent integrative functioning relative to operant efficiency and self-regulatory mechanisms.

Increased coupling of intrinsic networks in remitted depressed youth predicts rumination and cognitive control

Objective

Functional connectivity MRI (fcMRI) studies of individuals currently diagnosed with major depressive disorder (MDD) document hyperconnectivities within the default mode network (DMN) and between the DMN and salience networks (SN) with regions of the cognitive control network (CCN). Studies of individuals in the remitted state are needed to address whether effects derive from trait, and not state or chronic burden features of MDD.

Method

fcMRI data from two 3.0 Tesla GE scanners were collected from 30 unmedicated (47% medication naïve) youth (aged 18–23, modal depressive episodes = 1, mean age of onset = 16.2, SD = 2.6) with remitted MDD (rMDD; modal years well = 4) and compared with data from 23 healthy controls (HCs) using four bilateral seeds in the DMN and SN (posterior cingulate cortex (PCC), subgenual anterior cingulate (sgACC), and amygdala), followed by voxel-based comparisons of the whole brain.

Results

Compared to HCs, rMDD youth exhibited hyperconnectivities from both PCC and sgACC seeds with lateral, parietal, and frontal regions of the CCN, extending to the dorsal medial wall. A factor analysis reduced extracted data and a PCC factor was inversely correlated with rumination among rMDD youth. Two factors from the sgACC hyperconnectivity clusters were related to performance in cognitive control on a Go/NoGo task, one positively and one inversely.

Conclusions

Findings document hyperconnectivities of the DMN and SN with the CCN (BA 8/10), which were related to rumination and sustained attention. Given these cognitive markers are known predictors of response and relapse, hyperconnectivities may increase relapse risk or represent compensatory mechanisms.

Imbalanced hippocampal functional networks associated with remitted geriatric depression and apolipoprotein E ε4 allele in nondemented elderly: a preliminary study

BACKGROUND

Apolipoprotein E (APOE) ε4 allele and a history of geriatric depression are confirmed risk factors of Alzheimer׳s disease (AD). Coexistence of both factors could notably enhance the risk of cognitive impairment in nondemented elderly. However, neural basis of the association remains unclear.

METHODS

Thirty-one remitted geriatric depression (RGD) patients and 29 cognitively normal subjects were recruited and underwent resting-state functional MRI scans. They were further divided into four groups according to their APOE genotypes. Hippocampal seed-based network analysis and two-way factorial analysis of covariance were employed to detect the main effects and interactive effects of RGD and APOE ε4 allele on the hippocampal functional connectivity (HFC) networks. Partial correlation analysis was applied to examine the cognitive significance of these altered HFC networks.

RESULTS

The HFC networks of RGD patients were decreased in the dorsal frontal and increased in the right temporal-occipital regions. For APOE ε4 carriers, the HFC networks were reduced primarily in medial prefrontal regions and enhanced in the bilateral insula. Additionally, when both factors coexisted, the left HFC network was significantly disrupted in the dorsal anterior cingulate cortex and increased in somatomotor and occipital regions. Importantly, the extent of network alterations was linked to inferior cognitive performances in RGD patients and APOE ε4 carriers.

LIMITATIONS

The small sample size may limit the generalizability of our findings.

CONCLUSIONS

RGD and APOE ε4 allele, and their interaction, are associated with the imbalanced HFC network, which may contribute to cognitive deterioration for subjects with a high risk of AD.

Abnormally altered patterns of whole brain functional connectivity network of posterior cingulate cortex in remitted geriatric depression: a longitudinal study

AIMS

A longitudinal study investigated the remitted geriatric depression (RGD) patients' persistent cognitive impairment and potential correlation with their PCC functional connectivity network.

METHODS

A total of 14 RGD patients and 18 matched controls were recruited. All subjects finished the neuropsychological tests and functional magnetic resonance imaging scan at baseline and follow-up. A spherical region of interest was placed in PCC to calculate the functional connectivity, and further analysis was employed to detect correlations between longitudinal changes in the brain regions and neuropsychological data.

RESULTS

There were significant cognitive declines in RGD patients at baseline and follow-up. Altered patterns of functional connectivity were detected within the RGD group showing correlations with neuropsychological tests. The longitudinal change in functional connectivity between PCC and cerebellum posterior lobe was correlated with longitudinal changes in auditory verbal memory test-recall (r=0.550, P=0.042). The longitudinal change in functional connectivity between PCC and right parahippocampal gyrus was correlated with Trail Making Test-A (r=0.631, P=0.015). The longitudinal change in functional connectivity between PCC and supramarginal_R was correlated with Mini-Mental State Examination (r=-0.630, P=0.016).

CONCLUSIONS

RGD patients performed worse cognitive function, and altered PCC functional connectivity network might have a role in these cognitive declines.

Phenotypic variability in resting-state functional connectivity: current status

We reviewed the extant literature with the goal of assessing the extent to which resting-state functional connectivity is associated with phenotypic variability in healthy and disordered populations. A large corpus of work has accumulated to date (125 studies), supporting the association between intrinsic functional connectivity and individual differences in a wide range of domains-not only in cognitive, perceptual, motoric, and linguistic performance, but also in behavioral traits (e.g., impulsiveness, risky decision making, personality, and empathy) and states (e.g., anxiety and psychiatric symptoms) that are distinguished by cognitive and affective functioning, and in neurological conditions with cognitive and motor sequelae. Further, intrinsic functional connectivity is sensitive to remote (e.g., early-life stress) and enduring (e.g., duration of symptoms) life experience, and it exhibits plasticity in response to recent experience (e.g., learning and adaptation) and pharmacological treatment. The most pervasive associations were observed with the default network; associations were also widespread between the cingulo-opercular network and both cognitive and affective behaviors, while the frontoparietal network was associated primarily with cognitive functions. Associations of somatomotor, frontotemporal, auditory, and amygdala networks were relatively restricted to the behaviors linked to their respective putative functions. Surprisingly, visual network associations went beyond visual function to include a variety of behavioral traits distinguished by affective function. Together, the reviewed evidence sets the stage for testing causal hypothesis about the functional role of intrinsic connectivity and augments its potential as a biomarker for healthy and disordered brain function.

The vascular depression hypothesis: mechanisms linking vascular disease with depression

The 'Vascular Depression' hypothesis posits that cerebrovascular disease may predispose, precipitate or perpetuate some geriatric depressive syndromes. This hypothesis stimulated much research that has improved our understanding of the complex relationships between late-life depression (LLD), vascular risk factors, and cognition. Succinctly, there are well-established relationships between LLD, vascular risk factors and cerebral hyperintensities, the radiological hallmark of vascular depression. Cognitive dysfunction is common in LLD, particularly executive dysfunction, a finding predictive of poor antidepressant response. Over time, progression of hyperintensities and cognitive deficits predicts a poor course of depression and may reflect underlying worsening of vascular disease. This work laid the foundation for examining the mechanisms by which vascular disease influences brain circuits and influences the development and course of depression. We review data testing the vascular depression hypothesis with a focus on identifying potential underlying vascular mechanisms. We propose a disconnection hypothesis, wherein focal vascular damage and white matter lesion location is a crucial factor, influencing neural connectivity that contributes to clinical symptomatology. We also propose inflammatory and hypoperfusion hypotheses, concepts that link underlying vascular processes with adverse effects on brain function that influence the development of depression. Testing such hypotheses will not only inform the relationship between vascular disease and depression, but also provide guidance on the potential repurposing of pharmacological agents that may improve LLD outcomes.

Resting-state functional connectivity in normal brain aging

The world is aging and, as the elderly population increases, age-related cognitive decline emerges as a major concern. Neuroimaging techniques, such as functional magnetic resonance imaging (fMRI), allow the investigation of the neural bases of age-related cognitive changes in vivo. Typically, fMRI studies map brain activity while subjects perform cognitive tasks, but such paradigms are often difficult to implement on a wider basis. Resting-state fMRI (rs-fMRI) has emerged as an important alternative modality of fMRI data acquisition, during which no specific task is required. Due to such simplicity and the reliability of rs-fMRI data, this modality presents increased feasibility and potential for clinical application in the future. With rs-fMRI, fluctuations in regional brain activity can be detected across separate brain regions and the patterns of intercorrelation between the functioning of these regions are measured, affording quantitative indices of resting-state functional connectivity (RSFC). This review article summarizes the results of recent rs-fMRI studies that have documented a variety of aging-related RSFC changes in the human brain, discusses the neurophysiological hypotheses proposed to interpret such findings, and provides an overview of the future, highly promising perspectives in this field.