The salience network in the apathy of late-life depression

Investigating the Prevalence and Predictors of Apathy among the Canadian Long-Term Care Residents: A Secondary Data Analysis

BACKGROUND

In long-term care facilities (LTCF), apathy is a prevalent issue, leading to cognitive decline, functional impairment, and increased mortality risk. Despite its significance, apathy often remains underrecognized and undermanaged in these settings. Recognizing and addressing the predictors of apathy is critical for early intervention and improved care outcomes.

PURPOSE

This study aims to assess the prevalence of apathy and identify its associated risk factors among newly admitted residents in the Canadian LTCF, using the InterRAI Minimum Data Set (MDS 2.0).

METHODS

We conducted a cross-sectional analysis of MDS 2.0 admission assessment data between 2015 and 2019, covering 157,596 residents across six Canadian provinces and one territory. Apathy was measured using the Apathy Index of the MDS 2.0, with the biopsychosocial model guiding the analysis.

RESULTS

The prevalence of apathy was 12.5% (19,758 individuals). The most significant predictors include cognitive impairments, specific age groups, hearing impairments, vision impairments, facility size and location.

CONCLUSIONS

The findings of this study underscore the need for tailored strategies in LTCF to address apathy, considering individual, institutional, and regional variations. Emphasis on environmental and personal factors is crucial in the management and prevention of apathy in these settings.

The interplay between insomnia symptoms and Alzheimer's disease across three main brain networks

STUDY OBJECTIVES

Insomnia symptoms are prevalent along the trajectory of Alzheimer's disease (AD), but the neurobiological underpinning of their interaction is poorly understood. Here, we assessed structural and functional brain measures within and between the default mode network (DMN), salience network, and central executive network (CEN).

METHODS

We selected 320 participants from the ADNI database and divided them by their diagnosis: cognitively normal (CN), Mild Cognitive Impairment (MCI), and AD, with and without self-reported insomnia symptoms. We measured the gray matter volume (GMV), structural covariance (SC), degrees centrality (DC), and functional connectivity (FC), testing the effect and interaction of insomnia symptoms and diagnosis on each index. Subsequently, we performed a within-group linear regression across each network and ROI. Finally, we correlated observed abnormalities with changes in cognitive and affective scores.

RESULTS

Insomnia symptoms were associated with FC alterations across all groups. The AD group also demonstrated an interaction between insomnia and diagnosis. Within-group analyses revealed that in CN and MCI, insomnia symptoms were characterized by within-network hyperconnectivity, while in AD, within- and between-network hypoconnectivity was ubiquitous. SC and GMV alterations were nonsignificant in the presence of insomnia symptoms, and DC indices only showed network-level alterations in the CEN of AD individuals. Abnormal FC within and between DMN and CEN hubs was additionally associated with reduced cognitive function across all groups, and increased depressive symptoms in AD.

CONCLUSIONS

We conclude that patients with clinical AD present with a unique pattern of insomnia-related functional alterations, highlighting the profound interaction between both conditions.

Quantifying Apathy in Late-Life Depression: Unraveling Neurobehavioral Links Through Daily Activity Patterns and Brain Connectivity Analysis

BACKGROUND

Better understanding apathy in late-life depression would help improve prediction of poor prognosis of diseases such as dementia. Actimetry provides an objective and ecological measure of apathy from patients' daily motor activity. We aimed to determine whether patterns of motor activity were associated with apathy and brain connectivity in networks that underlie goal-directed behaviors.

METHODS

Resting-state functional magnetic resonance imaging and diffusion magnetic resonance imaging were collected from 38 nondemented participants with late-life depression. Apathy was evaluated using the diagnostic criteria for apathy, Apathy Evaluation Scale, and Apathy Motivation Index. Functional principal components (fPCs) of motor activity were derived from actimetry recordings taken for 72 hours. Associations between fPCs and apathy were estimated by linear regression. Subnetworks whose connectivity was significantly associated with fPCs were identified via threshold-free network-based statistics. The relationship between apathy and microstructure metrics was estimated along fibers by diffusion tensor imaging and a multicompartment model called neurite orientation dispersion and density imaging via tractometry.

RESULTS

We found 2 fPCs associated with apathy: mean diurnal activity, negatively associated with Apathy Evaluation Scale scores, and an early chronotype, negatively associated with Apathy Motivation Index scores. Mean diurnal activity was associated with increased connectivity in the default mode, cingulo-opercular, and frontoparietal networks, while chronotype was associated with a more heterogeneous connectivity pattern in the same networks. We did not find significant associations between microstructural metrics and fPCs.

CONCLUSIONS

Our findings suggest that mean diurnal activity and chronotype could provide indirect ambulatory measures of apathy in late-life depression, associated with modified functional connectivity of brain networks that underlie goal-directed behaviors.

Treatment resistant late-life depression: A narrative review of psychosocial risk factors, non-pharmacological interventions, and the role of clinical phenotyping

BACKGROUND

Treatment resistant depression (TRD) is a subset of major depressive disorder (MDD) in which symptoms do not respond to front line therapies. In older adults, the assessment and treatment of TRD is complicated by psychosocial risk factors unique to this population, as well as a relative paucity of research.

METHODS

Narrative review aimed at (1) defining TRLLD for clinical practice and research; (2) describing psychosocial risk factors; (3) reviewing psychological and non-pharmacological treatments; (4) discussing the role of clinical phenotyping for personalized treatment; and (5) outlining research priorities.

RESULTS

Our definition of TRLLD centers on response to medication and neuromodulation in primary depressive disorders. Psychosocial risk factors include trauma and early life adversity, chronic physical illness, social isolation, personality, and barriers to care. Promising non-pharmacological treatments include cognitive training, psychotherapy, and lifestyle interventions. The utility of clinical phenotyping is highlighted by studies examining the impact of comorbidities, symptom dimensions (e.g., apathy), and structural/functional brain changes.

LIMITATIONS

There is a relative paucity of TRLLD research. This limits the scope of empirical data from which to derive reliable patterns and complicates efforts to evaluate the literature quantitatively.

CONCLUSIONS

TRLLD is a complex disorder that demands further investigation given our aging population. While this review highlights the promising breadth of TRLLD research to date, more research is needed to help elucidate, for example, the optimal timing for implementing risk mitigation strategies, the value of collaborative care approaches, specific treatment components associated with more robust response, and phenotyping to help inform treatment decisions.

Apathy and Depression Among People Aging With Traumatic Brain Injury: Relationships to Cognitive Performance and Psychosocial Functioning

OBJECTIVE

Apathy and depression are both common after moderate to severe traumatic brain injury (TBI) and may be especially important to distinguish in older adults with TBI. The authors examined apathy and depression in relation to cognitive performance domains and their potentially unique contribution to psychosocial functioning in this patient population.

METHODS

A total of 106 participants (mean±SD age=64±8 years) with chronic moderate to severe TBI (≥1 year) completed questionnaires assessing severity of apathy (Frontal Systems Behavior Scale-apathy subscale) and depression (Geriatric Depression Scale-15) symptoms, health-related quality of life (HRQoL), and societal participation. Participants also completed neuropsychological tests of episodic memory, processing speed, and executive functioning.

RESULTS

Apathy symptom severity was significantly associated with all cognitive performances in correlations adjusted for the familywise error rate; a relationship with executive functioning remained after controlling for demographic and injury variables. Depression symptom severity was not significantly associated with cognition after statistical correction. Both symptomatologies uniquely contributed to HRQoL. Only depression symptoms contributed to societal participation. On the basis of clinical cutoffs, half the sample had neither depression nor apathy, approximately 25% met criteria for only apathy, and 25% had both apathy and depression. The combined presence of clinical depression and apathy was associated with worse HRQoL and societal participation.

CONCLUSIONS

This is the first study to examine apathy and depression in relation to cognition and psychosocial functioning in an older sample with a history of TBI. Findings suggest that the two syndromes can be dissociated in clinically meaningful ways, which may help to refine psychiatric and behavioral interventions in this vulnerable population.

Individualized prediction of cognitive test scores from functional brain connectome in patients with first-episode late-life depression

BACKGROUND

In the realm of cognitive screening, the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) are widely utilized for detecting cognitive deficits in patients with late-life depression (LLD), However, the interindividual variability in neuroimaging biomarkers contributing to individual-specific symptom severity remains poorly understood. In this study, we used a connectome-based predictive model (CPM) approach on resting-state functional magnetic resonance imaging data from patients with LLD to establish individualized prediction models for the MoCA and the MMSE scores.

METHODS

We recruited 135 individuals diagnosed with first-episode LLD for this research. Participants underwent the MMSE and MoCA tests, along with resting-state functional magnetic resonance imaging scans. Functional connectivity matrices derived from these scans were utilized in CPM models to predict MMSE or MoCA scores. Predictive precision was assessed by correlating predicted and observed scores, with the significance of prediction performance evaluated through a permutation test.

RESULTS

The negative model of the CPM procedure demonstrated a significant capacity to predict MoCA scores (r = -0.309, p = 0.002). Similarly, the CPM procedure could predict MMSE scores (r = -0.236, p = 0.016). The predictive models for cognitive test scores in LLD primarily involved the visual network, somatomotor network, dorsal attention network, and ventral attention network.

CONCLUSIONS

Brain functional connectivity emerges as a promising predictor of personalized cognitive test scores in LLD, suggesting that functional connectomes are potential neurobiological markers for cognitive performance in patients with LLD.

A novel biomarker selection method using multimodal neuroimaging data

Identifying biomarkers is essential to obtain the optimal therapeutic benefit while treating patients with late-life depression (LLD). We compare LLD patients with healthy controls (HC) using resting-state functional magnetic resonance and diffusion tensor imaging data to identify neuroimaging biomarkers that may be potentially associated with the underlying pathophysiology of LLD. We implement a Bayesian multimodal local false discovery rate approach for functional connectivity, borrowing strength from structural connectivity to identify disrupted functional connectivity of LLD compared to HC. In the Bayesian framework, we develop an algorithm to control the overall false discovery rate of our findings. We compare our findings with the literature and show that our approach can better detect some regions never discovered before for LLD patients. The Hub of our discovery related to various neurobehavioral disorders can be used to develop behavioral interventions to treat LLD patients who do not respond to antidepressants.

"Brain-breath" interactions: respiration-timing-dependent impact on functional brain networks and beyond

Breathing is a natural daily action that one cannot do without, and it sensitively and intensely changes under various situations. What if this essential act of breathing can impact our overall well-being? Recent studies have demonstrated that breathing oscillations couple with higher brain functions, i.e., perception, motor actions, and cognition. Moreover, the timing of breathing, a phase transition from exhalation to inhalation, modulates specific cortical activity and accuracy in cognitive tasks. To determine possible respiratory roles in attentional and memory processes and functional neural networks, we discussed how breathing interacts with the brain that are measured by electrophysiology and functional neuroimaging: (i) respiration-dependent modulation of mental health and cognition; (ii) respiratory rhythm generation and respiratory pontomedullary networks in the brainstem; (iii) respiration-dependent effects on specific brainstem regions and functional neural networks (e.g., glutamatergic PreBötzinger complex neurons, GABAergic parafacial neurons, adrenergic C1 neurons, parabrachial nucleus, locus coeruleus, temporoparietal junction, default-mode network, ventral attention network, and cingulo-opercular salience network); and (iv) a potential application of breathing manipulation in mental health care. These outlines and considerations of "brain-breath" interactions lead to a better understanding of the interoceptive and cognitive mechanisms that underlie brain-body interactions in health conditions and in stress-related and neuropsychiatric disorders.

Brain multi-contrast, multi-atlas segmentation of diffusion tensor imaging and ensemble learning automatically diagnose late-life depression

We investigated the potential of machine learning for diagnostic classification in late-life major depression based on an advanced whole brain white matter segmentation framework. Twenty-six late-life depression and 12 never depressed individuals aged > 55 years, matched for age, MMSE, and education underwent brain diffusion tensor imaging and a multi-contrast, multi-atlas segmentation in MRIcloud. Fractional anisotropy volume, mean fractional anisotropy, trace, axial and radial diffusivity (RD) extracted from 146 white matter parcels for each subject were used to train and test the AdaBoost classifier using stratified 12-fold cross validation. Performance was evaluated using various measures. The statistical power of the classifier was assessed using label permutation test. Statistical analysis did not yield significant differences in DTI measures between the groups. The classifier achieved a balanced accuracy of 71% and an Area Under the Receiver Operator Characteristic Curve (ROC-AUC) of 0.81 by trace, and a balanced accuracy of 70% and a ROC-AUC of 0.80 by RD, in limbic, cortico-basal ganglia-thalamo-cortical loop, brainstem, external and internal capsules, callosal and cerebellar structures. Both indices shared important structures for classification, while fornix was the most important structure for classification by both indices. The classifier proved statistically significant, as trace and RD ROC-AUC scores after permutation were lower than those obtained with the actual data (P = 0.022 and P = 0.024, respectively). Similar results were obtained with the Gradient Boosting classifier, whereas the RBF-kernel Support Vector Machine with k-best feature selection did not exceed the chance level. Finally, AdaBoost significantly predicted the class using all features together. Limitations are discussed. The results encourage further investigation of the implemented methods for computer aided diagnostics and anatomically informed therapeutics.

Cognitive, Disability, and Treatment Outcome Implications of Symptom-Based Phenotyping in Late-Life Depression

OBJECTIVE

Late-life depression is associated with substantial heterogeneity in clinical presentation, disability, and response to antidepressant treatment. We examined whether self-report of severity of common symptoms, including anhedonia, apathy, rumination, worry, insomnia, and fatigue were associated with differences in presentation and response to treatment. We also examined whether these symptoms improved during treatment with escitalopram.

DESIGN

Eighty-nine older adults completed baseline assessments, neuropsychological testing and providing self-reported symptom and disability scales. They then entered an 8-week, placebo-controlled randomized trial of escitalopram, and self-report scales were repeated at the trial's end. Raw symptom scale scores were combined into three standardized symptom phenotypes and models examined how symptom phenotype severity was associated with baseline measures and depression improvement over the trial.

RESULTS

While rumination/worry appeared independent, severity of apathy/anhedonia and fatigue/insomnia were associated with one another and with greater self-reported disability. Greater fatigue/insomnia was also associated with slower processing speed, while rumination/worry was associated with poorer episodic memory. No symptom phenotype severity score predicted a poorer overall response to escitalopram. In secondary analyses, escitalopram did not improve most phenotypic symptoms more than placebo, aside for greater reductions in worry and total rumination severity.

CONCLUSION

Deeper symptom phenotype characterization may highlight differences in the clinical presentation of late-life depression. However, when compared to placebo, escitalopram did not improve many of the symptoms assessed. Further work is needed to determine whether symptom phenotypes inform longer-term course of illness, and which treatments may best benefit specific symptoms.

Connectivity patterns of the core resting-state networks associated with apathy in late-life depression

BACKGROUND

Apathy is associated with reduced antidepressant response and dementia in late-life depression (LLD). However, the functional cerebral basis of apathy is understudied in LLD. We investigated the functional connectivity of 5 resting-state networks (RSN) hypothesized to underlie apathy in LLD.

METHODS

Resting-state functional MRI data were collected from individuals with LLD who did not have dementia as well as healthy older adults between October 2019 and April 2022. Apathy was evaluated using the diagnostic criteria for apathy (DCA), the Apathy Evaluation Scale (AES) and the Apathy Motivation Index (AMI). Subnetworks whose connectivity was significantly associated with each apathy measure were identified via the threshold-free network-based statistics. Regions that were consistently associated with apathy across the measures were reported as robust findings.

RESULTS

Our sample included 39 individuals with LLD who did not have dementia and 26 healthy older adults. Compared with healthy controls, individuals with LLD had an altered intra-RSN and inter-RNS connectivity in the default mode, the cingulo-opercular and the frontoparietal networks. All 3 apathy measurements showed associations with modified intra-RSN connectivity in these networks, except for the DCA in the cingulo-opercular network. The AMI scores showed stronger associations with the cingulo-opercular and frontoparietal networks, whereas the AES had stronger associations with the default mode network and the goal-oriented behaviour network.

LIMITATIONS

The study was limited by the small number of participants without apathy according to the DCA, which may have reduced the statistical power of between-group comparisons. Additionally, the reliance on specific apathy measures may have influenced the observed overlap in brain regions.

CONCLUSION

Our findings indicate that apathy in LLD is consistently associated with changes in both intra-RSN and inter-RSN connectivity of brain regions implicated in goal-oriented behaviours. These results corroborate previous findings of altered functional RSN connectivity in severe LLD.

Changes in brain functional networks in remitted major depressive disorder: a six-month follow-up study

BACKGROUND

Patients with remitted major depressive disorder (rMDD) show abnormal functional connectivity of the central executive network (CEN), salience networks (SN) and default mode network (DMN). It is unclear how these change during remission, or whether changes are related to function.

METHODS

Three spatial networks in 17 patients with rMDD were compared between baseline and the six-month follow-up, and to 22 healthy controls. Correlations between these changes and psychosocial functioning were also assessed.

RESULTS

In the CEN, patients at baseline had abnormal functional connectivity in the right anterior cingulate, right dorsolateral prefrontal cortex (DLPFC) and inferior parietal lobule (IPL) compare with HCs. There were functional connection differences in the right DLPFC and left IPL at baseline during follow-up. Abnormal connectivity in the right DLPFC and medial prefrontal cortex (mPFC) were found at follow-up. In the SN, patients at baseline had abnormal functional connectivity in the insula, left anterior cingulate, left IPL, and right precuneus; compared with baseline, patients had higher connectivity in the right DLPFC at follow-up. In the DMN, patients at baseline had abnormal functional connectivity in the right mPFC. Resting-state functional connectivity of the IPL and DLPFC in the CEN correlated with psychosocial functioning.

CONCLUSIONS

At six-month follow-up, the CEN still showed abnormal functional connectivity in those with rMDD, while anomalies in the SN and DMN has disappeared. Resting-state functional connectivity of the CEN during early rMDD is associated with psychosocial function.

CLINICAL TRIALS REGISTRATION

Pharmacotherapy and Psychotherapy for MDD after Remission on Psychology and Neuroimaging. https://www.

CLINICALTRIALS

gov/ , registration number: NCT01831440 (15/4/2013).

Functional MRI-specific alterations in frontoparietal network in mild cognitive impairment: an ALE meta-analysis

Background

Mild cognitive impairment (MCI) depicts a transitory phase between healthy elderly and the onset of Alzheimer's disease (AD) with worsening cognitive impairment. Some functional MRI (fMRI) research indicated that the frontoparietal network (FPN) could be an essential part of the pathophysiological mechanism of MCI. However, damaged FPN regions were not consistently reported, especially their interactions with other brain networks. We assessed the fMRI-specific anomalies of the FPN in MCI by analyzing brain regions with functional alterations.

Methods

PubMed, Embase, and Web of Science were searched to screen neuroimaging studies exploring brain function alterations in the FPN in MCI using fMRI-related indexes, including the amplitude of low-frequency fluctuation, regional homogeneity, and functional connectivity. We integrated distinctive coordinates by activating likelihood estimation, visualizing abnormal functional regions, and concluding functional alterations of the FPN.

Results

We selected 29 studies and found specific changes in some brain regions of the FPN. These included the bilateral dorsolateral prefrontal cortex, insula, precuneus cortex, anterior cingulate cortex, inferior parietal lobule, middle temporal gyrus, superior frontal gyrus, and parahippocampal gyrus. Any abnormal alterations in these regions depicted interactions between the FPN and other networks.

Conclusion

The study demonstrates specific fMRI neuroimaging alterations in brain regions of the FPN in MCI patients. This could provide a new perspective on identifying early-stage patients with targeted treatment programs.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023432042, identifier: CRD42023432042.

The neural correlates of apathy in the context of aging and brain disorders: a meta-analysis of neuroimaging studies

Introduction

Apathy is a prevalent mood disturbance that occurs in a wide range of populations, including those with normal cognitive aging, mental disorders, neurodegenerative disorders and traumatic brain injuries. Recently, neuroimaging technologies have been employed to elucidate the neural substrates underlying brain disorders accompanying apathy. However, the consistent neural correlates of apathy across normal aging and brain disorders are still unclear.

Methods

This paper first provides a brief review of the neural mechanism of apathy in healthy elderly individuals, those with mental disorders, neurodegenerative disorders, and traumatic brain injuries. Further, following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines, the structural and functional neuroimaging meta-analysis using activation likelihood estimation method is performed on the apathy group with brain disorders and the healthy elderly, aiming at exploring the neural correlates of apathy.

Results

The structural neuroimaging meta-analysis showed that gray matter atrophy is associated with apathy in the bilateral precentral gyrus (BA 13/6), bilateral insula (BA 47), bilateral medial frontal gyrus (BA 11), bilateral inferior frontal gyrus, left caudate (putamen) and right anterior cingulate, while the functional neuroimaging meta-analysis suggested that the functional connectivity in putamen and lateral globus pallidus is correlated with apathy.

Discussion

Through the neuroimaging meta-analysis, this study has identified the potential neural locations of apathy in terms of brain structure and function, which may offer valuable pathophysiological insights for developing more effective therapeutic interventions for affected patients.

Structural and functional differences in the brains of patients with MCI with and without depressive symptoms and their relations with Alzheimer's disease: an MRI study

Background

The mild cognitive impairment (MCI) stage among elderly individuals is very complex, and the level of diagnostic accuracy is far from ideal. Some studies have tried to improve the 'MCI due to Alzheimer's disease (AD)' classification by further stratifying these patients into subgroups. Depression-related symptoms may play an important role in helping to better define the MCI stage in elderly individuals.

Objective

In this work, we explored functional and structural differences in the brains of patients with nondepressed MCI (nDMCI) and patients with MCI with depressive symptoms (DMCI), and we examined how these groups relate to AD atrophy patterns and cognitive functioning.

Methods

Sixty-five participants underwent MRI exams and were divided into four groups: cognitively normal, nDMCI, DMCI, and AD. We compared the regional brain volumes, cortical thickness, and white matter microstructure measures using diffusion tensor imaging among groups. Additionally, we evaluated changes in functional connectivity using fMRI data.

Results

In comparison to the nDMCI group, the DMCI patients had more pronounced atrophy in the hippocampus and amygdala. Additionally, DMCI patients had asymmetric damage in the limbic-frontal white matter connection. Furthermore, two medial posterior regions, the isthmus of cingulate gyrus and especially the lingual gyrus, had high importance in the structural and functional differentiation between the two groups.

Conclusion

It is possible to differentiate nDMCI from DMCI patients using MRI techniques, which may contribute to a better characterization of subtypes of the MCI stage.

Individualized fMRI connectivity defines signatures of antidepressant and placebo responses in major depression

Though sertraline is commonly prescribed in patients with major depressive disorder (MDD), its superiority over placebo is only marginal. This is in part due to the neurobiological heterogeneity of the individuals. Characterizing individual-unique functional architecture of the brain may help better dissect the heterogeneity, thereby defining treatment-predictive signatures to guide personalized medication. In this study, we investigate whether individualized brain functional connectivity (FC) can define more predictable signatures of antidepressant and placebo treatment in MDD. The data used in the present work were collected by the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study. Patients (N = 296) were randomly assigned to antidepressant sertraline or placebo double-blind treatment for 8 weeks. The whole-brain FC networks were constructed from pre-treatment resting-state functional magnetic resonance imaging (rs-fMRI). Then, FC was individualized by removing the common components extracted from the raw baseline FC to train regression-based connectivity predictive models. With individualized FC features, the established prediction models successfully identified signatures that explained 22% variance for the sertraline group and 31% variance for the placebo group in predicting HAMD17 change. Compared with the raw FC-based models, the individualized FC-defined signatures significantly improved the prediction performance, as confirmed by cross-validation. For sertraline treatment, predictive FC metrics were predominantly located in the left middle temporal cortex and right insula. For placebo, predictive FC metrics were primarily located in the bilateral cingulate cortex and left superior temporal cortex. Our findings demonstrated that through the removal of common FC components, individualization of FC metrics enhanced the prediction performance compared to raw FC. Associated with previous MDD clinical studies, our identified predictive biomarkers provided new insights into the neuropathology of antidepressant and placebo treatment.

Development of a Bayesian multimodal model to detect biomarkers in neuroimaging studies

In this article, we developed a Bayesian multimodal model to detect biomarkers (or neuromarkers) using resting-state functional and structural data while comparing a late-life depression group with a healthy control group. Biomarker detection helps determine a target for treatment intervention to get the optimal therapeutic benefit for treatment-resistant patients. The borrowing strength of the structural connectivity has been quantified for functional activity while detecting the biomarker. In the biomarker searching process, thousands of hypotheses are generated and tested simultaneously using our novel method to control the false discovery rate for small samples. Several existing statistical approaches, frequently used in analyzing neuroimaging data have been investigated and compared via simulation with the proposed approach to show its excellent performance. Results are illustrated with a live data set generated in a late-life depression study. The role of detected biomarkers in terms of cognitive function has been explored.

How past trauma impacts emotional intelligence: Examining the connection

Backed by both research and practice, the organizational psychology field has come to value emotional intelligence (EI) as being vital for leader and employee effectiveness. While this field values EI, it has paid little attention to the antecedents of emotional intelligence, leaving the EI domain without clarity on (1) why EI might vary across individuals, and (2) how to best develop EI. In this article, we rely on neuroscience and psychology research to make the case that past psychological trauma impacts later EI capabilities. Specifically, we present evidence that psychological trauma impairs the brain areas and functions that support EI. Establishing psychological trauma has valuable theoretical and practical implications that include providing an explanation of why EI might vary across individuals and providing a focus for improving EI: healing from past trauma. Further theoretical and practical implications for the field of organizational psychology are provided.

Altered Resting-State Brain Activity and Functional Connectivity in Post-Stroke Apathy: An fMRI Study

Apathy is a common neuropsychiatric disease after stroke and is linked to a lower quality of life while undergoing rehabilitation. However, it is still unknown what are the underlying neural mechanisms of apathy. This research aimed to explore differences in the cerebral activity and functional connectivity (FC) of subjects with post-stroke apathy and those without it. A total of 59 individuals with acute ischemic stroke and 29 healthy subjects with similar age, sex, and education were recruited. The Apathy Evaluation Scale (AES) was used to evaluate apathy at 3 months after stroke. Patients were split into two groups-PSA (n = 21) and nPSA (n = 38)-based on their diagnosis. The fractional amplitude of low-frequency fluctuation (fALFF) was used to measure cerebral activity, as well as region-of-interest to region-of-interest analysis to examine functional connectivity among apathy-related regions. Pearson correlation analysis between fALFF values and apathy severity was performed in this research. The values of fALFF in the left middle temporal regions, right anterior and middle cingulate regions, middle frontal region, and cuneus region differed significantly among groups. Pearson correlation analysis showed that the fALFF values in the left middle temporal region (p < 0.001, r = 0.66) and right cuneus (p < 0.001, r = 0.48) were positively correlated with AES scores in stroke patients, while fALFF values in the right anterior cingulate (p < 0.001, r = -0.61), right middle frontal gyrus (p < 0.001, r = -0.49), and middle cingulate gyrus (p = 0.04, r = -0.27) were negatively correlated with AES scores in stroke patients. These regions formed an apathy-related subnetwork, and functional connectivity analysis unveiled that altered connectivity was linked to PSA (p < 0.05). This research found that abnormalities in brain activity and FC in the left middle temporal region, right middle frontal region, right cuneate region, and right anterior and middle cingulate regions in stroke patients were associated with PSA, revealing a possible neural mechanism and providing new clues for the diagnosis and treatment of PSA.

Brain signatures in children who contemplate suicide: learning from the large-scale ABCD study

BACKGROUND

Suicide is the second-leading cause of death in youth. Understanding the neural correlates of suicide ideation (SI) in children is crucial to ongoing efforts to understand and prevent youth suicide. This study characterized key neural networks during rest and emotion task conditions in an epidemiologically informed sample of children who report current, past, or no SI.

METHODS

Data are from the adolescent brain cognitive development study, including 8248 children (ages 9-10; mean age = 119.2 months; 49.2% female) recruited from the community. Resting-state functional connectivity (RSFC) and activation to emotional stimuli in the salience (SN) and default mode (DMN) networks were measured through fMRI. Self-reported SI and clinical profiles were gathered. We examined the replicability of our model results through repeated sub-sample reliability analyses.

RESULTS

Children with current SI (2.0%), compared to those without any past SI, showed lower DMN RSFC (B = -0.267, p < 0.001) and lower DMN activation in response to negative as compared to neutral faces (B = -0.204, p = 0.010). These results were robust to the effects of MDD, ADHD, and medication use. Sub-sample analysis further supported the robustness of these results. We did not find support for differences in SN RSFC or in SN activation to positive or negative stimuli for children with or without SI.

CONCLUSIONS

Results from a large brain imaging study using robust statistical approaches suggest aberrant DMN functioning in children with current suicide ideation. Findings suggest potential mechanisms that may be targeted in suicide prevention efforts.

[Late-life depression and frailty-Epidemiological, clinical and neurobiological associations]

BACKGROUND

Depression is the most common mental disorder in older adults and is influenced by age-related processes. Frailty is a well-established clinical expression of ageing that implies a state of increased vulnerability to stressor events as well as increased risks of disability, hospitalization and death. Neurobiological findings will disentangle the comorbidity of frailty and depression and may inform future management of depression in old age.

OBJECTIVE

This narrative review provides an overview of the comorbidity of late-life depression and frailty, with a focus on neuroscientific findings that are organized within the research domain criteria (RDoC) framework.

RESULTS

More than one third of old people with depression are affected by frailty, which results in more chronic depression and in poorer efficacy and tolerability of antidepressant medication. Depression and frailty share motivational and psychomotor characteristics, particularly apathy, decreased physical activity and fatigue. In patients with frailty, altered activity of the supplementary motor cortex is associated with motor performance deficits. Patients with late-life depression and apathy are characterized by abnormal structure and altered functional connectivity of the reward network and the salience network, along with altered functional connectivity of these networks with premotor brain areas.

CONCLUSION

Identifying frailty in older adults with depression is relevant for prognostic assessment and treatment. A better understanding of the neuronal mechanisms of comorbidity will provide potential targets for future personalized therapeutic interventions.

Strengths and Weaknesses of the Vascular Apathy Hypothesis: A Narrative Review

The vascular apathy hypothesis states that cerebral small vessel disease (CSVD) can cause apathy, even when no other symptoms of CSVD are present. In order to examine this hypothesis, the objectives of this narrative review are to evaluate the evidence for a pathophysiological mechanism linking CSVD to apathy and to examine whether CSVD can be a sole cause of apathy. The nature of the CSVD-apathy relationship was evaluated using the Bradford Hill criteria as a method for research on the distinction between association and causation. Pathological, neuroimaging, and behavioral studies show that CSVD can cause lesions in the reward network, which causes an apathy syndrome. Studies in healthy older individuals, stroke patients and cognitively impaired persons consistently show an association between CSVD markers and apathy, although studies in older persons suffering from depression are inconclusive. A biological gradient is confirmed, as well as a temporal relationship, although the evidence for the latter is still weak. The specificity of this causal relationship is low given there often are other contributing factors in CSVD patients with apathy, particularly depression and cognitive deterioration. Differentiating between vascular apathy and other apathy syndromes on the basis of clinical features is not yet possible, while in-depth knowledge about differences in the prognosis and efficacy of treatment options for apathy caused by CSVD and other apathy syndromes is lacking. Since we cannot differentiate between etiologically different apathy syndromes as yet, it is premature to use the term vascular apathy which would suggest a distinct clinical apathy syndrome.

Functional connectivity and mild behavioral impairment in dementia-free elderly

Background

Mild behavioral impairment (MBI) is a syndrome that uses later-life emergent and persistent neuropsychiatric symptoms (NPS) to identify a group at high risk for incident dementia. MBI is associated with neurodegenerative disease markers in advance of syndromic dementia. Functional connectivity (FC) correlates of MBI are understudied and could provide further insights into mechanisms early in the disease course. We used resting-state functional magnetic resonance imaging (rs-fMRI) to test the hypothesis that FC within the default mode network (DMN) and salience network (SN) of persons with MBI (MBI+) is reduced, relative to those without (MBI-).

Methods

From two harmonized dementia-free cohort studies, using a score of ≥6 on the MBI Checklist to define MBI status, 32 MBI+ and 63 MBI- individuals were identified (mean age: 71.7 years; 54.7% female). Seed-based connectivity analysis was implemented in each MBI group using the CONN fMRI toolbox (v20.b), with the posterior cingulate cortex (PCC) as the seed region within the DMN and anterior cingulate cortex (ACC) as the seed within the SN. The average time series from the PCC and ACC were used to determine FC with other regions within the DMN (medial prefrontal cortex, lateral inferior parietal cortex) and SN (anterior insula, supramarginal gyrus, rostral prefrontal cortex), respectively. Age, sex, years of education, and Montreal Cognitive Assessment scores were included as model covariates. The false discovery rate approach was used to correct for multiple comparisons, with a p-value of .05 considered significant.

Results

For the DMN, MBI+ individuals exhibited reduced FC between the PCC and the medial prefrontal cortex, compared to MBI-. For the SN, MBI+ individuals exhibited reduced FC between the ACC and left anterior insula.

Conclusion

MBI in dementia-free older adults is associated with reduced FC in networks known to be disrupted in dementia. Our results complement the evidence linking MBI with Alzheimer's disease biomarkers.

Highlights

Resting-state functional magnetic resonance imaging was completed in 95 dementia-free persons from FAVR and COMPASS-ND studies.Participants were stratified by informant-rated Mild Behavioral Impairment Checklist (MBI-C) score, ≥6 for MBI+.MBI+ participants showed reduced functional connectivity (FC) within the default mode network and salience network.These FC changes are consistent with those seen in early-stage Alzheimer's disease.MBI may help identify persons with early-stage neurodegenerative disease.

Shared and distinct patterns of dynamic functional connectivity variability of thalamo-cortical circuit in bipolar depression and major depressive disorder

Evidence has indicated abnormalities of thalamo-cortical functional connectivity (FC) in bipolar disorder during a depressive episode (BDD) and major depressive disorder (MDD). However, the dynamic FC (dFC) within this system is poorly understood. We explored the thalamo-cortical dFC pattern by dividing thalamus into 16 subregions and combining with a sliding-window approach. Correlation analysis was performed between altered dFC variability and clinical data. Classification analysis with a linear support vector machine model was conducted. Compared with healthy controls (HCs), both patients revealed increased dFC variability between thalamus subregions with hippocampus (HIP), angular gyrus and caudate, and only BDD showed increased dFC variability of the thalamus with superior frontal gyrus (SFG), HIP, insula, middle cingulate gyrus, and postcentral gyrus. Compared with MDD and HCs, only BDD exhibited enhanced dFC variability of the thalamus with SFG and superior temporal gyrus. Furthermore, the number of depressive episodes in MDD was significantly positively associated with altered dFC variability. Finally, the disrupted dFC variability could distinguish BDD from MDD with 83.44% classification accuracy. BDD and MDD shared common disrupted dFC variability in the thalamo-limbic and striatal-thalamic circuitries, whereas BDD exhibited more extensive and broader aberrant dFC variability, which may facilitate distinguish between these 2 mood disorders.

Apathy in depression: An arterial spin labeling perfusion MRI study

INTRODUCTION

Apathy, as defined as a deficit in goal-directed behaviors, is a critical clinical dimension in depression associated with chronic impairment. Little is known about its cerebral perfusion specificities in depression. To explore neurovascular mechanisms underpinning apathy in depression by pseudo-continuous arterial spin labeling (pCASL) magnetic resonance imaging (MRI).

METHODS

Perfusion imaging analysis was performed on 90 depressed patients included in a prospective study between November 2014 and February 2017. Imaging data included anatomical 3D T1-weighted and perfusion pCASL sequences. A multiple regression analysis relating the quantified cerebral blood flow (CBF) in different regions of interest defined from the FreeSurfer atlas, to the Apathy Evaluation Scale (AES) total score was conducted.

RESULTS

After confound adjustment (demographics, disease and clinical characteristics) and correction for multiple comparisons, we observed a strong negative relationship between the CBF in the left anterior cingulate cortex (ACC) and the AES score (standardized beta = -0.74, corrected p value = 0.0008).

CONCLUSION

Our results emphasized the left ACC as a key region involved in apathy severity in a population of depressed participants. Perfusion correlates of apathy in depression evidenced in this study may contribute to characterize different phenotypes of depression.

The neurobiology of apathy in depression and neurocognitive impairment in older adults: a review of epidemiological, clinical, neuropsychological and biological research

Apathy is a common condition that involves diminished initiative, diminished interest and diminished emotional expression or responsiveness. It is highly prevalent in the context of a variety of neuropsychiatric disorders and is related to poor health outcomes. Presence of apathy is associated with cognitive and functional decline in dementia. Despite its negative impact on health, there is no definitive treatment for apathy, a clinical reality that may be due in part to lack of knowledge about assessment, neuropsychological features and neurobiological underpinnings. Here, we review and synthesize evidence from clinical, epidemiological, neuropsychological, peripheral biomarker and neuroimaging research. Apathy is a common feature of depression and cognitive disorders and is associated with impairment in executive function. Neuropsychological and neuroimaging studies point to dysfunction of brain circuitry involving the prefrontal cortex, especially the dorsolateral prefrontal cortex circuit, the dorsomedial prefrontal cortex circuit, and the ventromedial prefrontal cortex circuit. However, inconsistent findings, particularly in neuroimaging may be due to heterogeneity of apathy symptoms (with a need to better elucidate subtypes), neuropsychiatric comorbidities, the severity of cognitive impairment and other factors. These factors need to be accounted for in future studies so that biomarker research can make progress. On the whole, the literature on apathy has identified likely neurocognitive, peripheral biomarker and neuroimaging targets for understanding apathy, but also points to the need to address methodological issues that will better inform future studies. In turn, as we learn more about the underpinning of apathy and its subtypes, subsequent research can focus on new neurally based interventions that will strengthen the clinical management of apathy in the context of its comorbidities.

Functional connectivity correlates of reduced goal-directed behaviors in behavioural variant frontotemporal dementia

We explored the resting state functional connectivity correlates of apathy assessed as a multidimensional construct, using behavioral metrics, in behavioral variant frontotemporal dementia (bvFTD). We recorded the behavior of 20 bvFTD patients and 16 healthy controls in a close-to-real-life situation including a free phase (FP-in which actions were self-initiated) and a guided phase (GP-in which initiation of actions was facilitated by external guidance). We investigated the activity time and walking episode features as quantifiers of apathy. We used the means ((FP + GP)/2) and the differences (FP-GP) calculated for these metrics as well as measures by questionnaires to extract apathy dimensions by factor analysis. We assessed two types of fMRI-based resting state connectivity measures (local activity and seed-based connectivity) and explored their relationship with extracted apathy dimensions. Apathy in bvFTD was associated with lower time spent in activity combined with walking episodes of higher frequency, lower acceleration and higher duration. Using these behavioral metrics and apathy measures by questionnaires, we disentangled two dimensions: the global reduction of goal-directed behaviors and the specific deficit of self-initiation. Global apathy was associated with lower resting state activity within prefrontal cortex and lower connectivity of salience network hubs while the decrease in self-initiation was related to increased connectivity of parietal default-mode network hubs. Through a novel dimensional approach, we dissociated the functional connectivity correlates of global apathy and self-initiation deficit. We discussed in particular the role of the modified connectivity of lateral parietal cortex in the volitional process.

Ambient air pollution exposure and increasing depressive symptoms in older women: The mediating role of the prefrontal cortex and insula

Exposures to fine particulate matter (PM_2.5) and nitrogen dioxide (NO₂) have been associated with the emergence of depressive symptoms in older adulthood, although most studies used cross-sectional outcome measures. Elucidating the brain structures mediating the adverse effects can strengthen the causal role between air pollution and increasing depressive symptoms. We evaluated whether smaller volumes of brain structures implicated in late-life depression mediate associations between ambient air pollution exposure and changes in depressive symptoms. This prospective study included 764 community-dwelling older women (aged 81.6 ± 3.6 in 2008-2010) from the Women's Health Initiative Memory Study (WHIMS) Magnetic Resonance Imaging study (WHIMS-MRI; 2005-06) and WHIMS-Epidemiology of Cognitive Health Outcomes (WHIMS-ECHO; 2008-16). Three-year average annual mean concentrations (scaled by interquartile range [IQR]) of ambient PM_2.5 (in μg/m³; IQR = 3.14 μg/m³) and NO₂ (in ppb; IQR = 7.80 ppb) before WHIMS-MRI were estimated at participants' addresses via spatiotemporal models. Mediators included structural brain MRI-derived grey matter volumes of the prefrontal cortex and structures of the limbic-cortical-striatal-pallidal-thalamic circuit. Depressive symptoms were assessed annually by the 15-item Geriatric Depression Scale. Structural equation models were constructed to estimate associations between exposure, structural brain volumes, and depressive symptoms. Increased exposures (by each IQR) were associated with greater annual increases in depressive symptoms (β_PM2.5 = 0.022; 95% Confidence Interval (CI) = 0.003, 0.042; β_NO2 = 0.019; 95% CI = 0.001, 0.037). The smaller volume of prefrontal cortex associated with exposures partially mediated the associations of increased depressive symptoms with NO₂ (8%) and PM_2.5 (13%), and smaller insula volume associated with NO₂ contributed modestly (13%) to the subsequent increase in depressive symptoms. We demonstrate the first evidence that the smaller volumes of the prefrontal cortex and insula may mediate the subsequent increases in depressive symptoms associated with late-life exposures to NO₂ and PM_2.5.

Dissociable Functional Brain Networks Associated With Apathy in Subcortical Ischemic Vascular Disease and Alzheimer’s Disease

Few studies have investigated differences in functional connectivity (FC) between patients with subcortical ischemic vascular disease (SIVD) and Alzheimer’s disease (AD), especially in relation to apathy. Therefore, the aim of this study was to compare apathy-related FC changes among patients with SIVD, AD, and cognitively normal subjects. The SIVD group had the highest level of apathy as measured using the Apathy Evaluation Scale-clinician version (AES). Dementia staging, volume of white matter hyperintensities (WMH), and the Beck Depression Inventory were the most significant clinical predictors for apathy. Group-wise comparisons revealed that the SIVD patients had the worst level of “Initiation” by factor analysis of the AES. FCs from four resting state networks (RSNs) were compared, and the connectograms at the level of intra- and inter-RSNs revealed dissociable FC changes, shared FC in the dorsal attention network, and distinct FC in the salient network across SIVD and AD. Neuronal correlates for “Initiation” deficits that underlie apathy were explored through a regional-specific approach, which showed that the right inferior frontal gyrus, left middle frontal gyrus, and left anterior insula were the critical hubs. These findings broaden the disconnection theory by considering the effect of FC interactions across multiple RSNs on apathy formation.

Disrupted Causal Connectivity Anchored on the Right Anterior Insula in Drug-Naive First-Episode Patients With Depressive Disorder

OBJECT

Major depressive disorder (MDD) has been demonstrated to be associated with abnormalities in neural networks. However, few studies examined information flow in the salience network (SN). This study examined abnormalities in the causal connectivity between the SN and whole brain in drug-naive first-episode patients with MDD in the resting state.

METHODS

Based on the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) diagnostic criteria, 23 drug-naive first-episode MDD patients and 20 matched healthy individuals were recruited and underwent a resting-state magnetic resonance scan. The acquired functional image data were preprocessed using resting-state functional magnetic resonance imaging (rs-fMRI) data analysis toolkit plus (RESTplus). Then, using the data processing & analysis for brain imaging (DPABI) software and a coefficient-based general component analysis method with the right anterior insula (rAI) as the region of interest (ROI), the causal connectivity of the SN with the whole brain and its correlation with cognitive and mental performance were examined in the resting state.

RESULTS

(1) The MDD group showed a significantly higher Hamilton Depression Rating Scale total score and significantly higher scores for anxiety, cognitive disturbance, and block factors compared with normal controls. (2) Compared with control: from whole brain to the rAI, the MDD group showed a lower causal connectivity in the left inferior frontal gyrus; from the rAI to the whole brain, the MDD group showed a lower causal connectivity in the right cingulate gyrus, the right precuneus, and extending to paracentral lobule but higher causal connectivity in the left inferior and middle frontal gyrus. (3) In the MDD group, from rAI to the whole brain, the causal connectivity values for the right cingulate gyrus/precuneus were negatively correlated with the score of Stroop Color-Word Test A, B, and C as well as interference times.

CONCLUSION

Our results indicated disrupted causal connectivity among the default mode network (DMN), the central executive network (CEN), and SN in drug-naive first-episode MDD patients. Especially, our results suggest a unique role for rAI in the ordered or hierarchical information processing, presumed to include bottom-up and top-down reciprocal influences among the three networks in MDD.

Default-mode and fronto-parietal network connectivity during rest distinguishes asymptomatic patients with bipolar disorder and major depressive disorder

Bipolar disorder (BD) is commonly misdiagnosed as major depressive disorder (MDD). This is understandable, as depression often precedes mania and is otherwise indistinguishable in both. It is therefore imperative to identify neural mechanisms that can differentiate the two disorders. Interrogating resting brain neural activity may reveal core distinguishing abnormalities. We adopted an a priori approach, examining three key networks documented in previous mood disorder literature subserving executive function, salience and rumination that may differentiate euthymic BD and MDD patients. Thirty-eight patients with BD, 39 patients with MDD matched for depression severity, and 39 age-gender matched healthy controls, completed resting-state fMRI scans. Seed-based and data-driven Independent Component analyses (ICA) were implemented to examine group differences in resting-state connectivity (pFDR < 0.05). Seed analysis masks were target regions identified from the fronto-parietal (FPN), salience (SN) and default-mode (DMN) networks. Seed-based analyses identified significantly greater connectivity between the subgenual cingulate cortex (DMN) and right dorsolateral prefrontal cortex (FPN) in BD relative to MDD and controls. The ICA analyses also found greater connectivity between the DMN and inferior frontal gyrus, an FPN region in BD relative to MDD. There were also significant group differences across the three networks in both clinical groups relative to controls. Altered DMN-FPN functional connectivity is thought to underlie deficits in the processing, management and regulation of affective stimuli. Our results suggest that connectivity between these networks could potentially distinguish the two disorders and could be a possible trait mechanism in BD persisting even in the absence of symptoms.

Altered resting-state functional connectome in major depressive disorder: a mega-analysis from the PsyMRI consortium

Major depressive disorder (MDD) is associated with abnormal neural circuitry. It can be measured by assessing functional connectivity (FC) at resting-state functional MRI, that may help identifying neural markers of MDD and provide further efficient diagnosis and monitor treatment outcomes. The main aim of the present study is to investigate, in an unbiased way, functional alterations in patients with MDD using a large multi-center dataset from the PsyMRI consortium including 1546 participants from 19 centers ( www.psymri.com ). After applying strict exclusion criteria, the final sample consisted of 606 MDD patients (age: 35.8 ± 11.9 y.o.; females: 60.7%) and 476 healthy participants (age: 33.3 ± 11.0 y.o.; females: 56.7%). We found significant relative hypoconnectivity within somatosensory motor (SMN), salience (SN) networks and between SMN, SN, dorsal attention (DAN), and visual (VN) networks in MDD patients. No significant differences were detected within the default mode (DMN) and frontoparietal networks (FPN). In addition, alterations in network organization were observed in terms of significantly lower network segregation of SMN in MDD patients. Although medicated patients showed significantly lower FC within DMN, FPN, and SN than unmedicated patients, there were no differences between medicated and unmedicated groups in terms of network organization in SMN. We conclude that the network organization of cortical networks, involved in processing of sensory information, might be a more stable neuroimaging marker for MDD than previously assumed alterations in higher-order neural networks like DMN and FPN.

Anticipatory and Reactive Grip Force Control in Patients with Alzheimer's Disease: A Pilot Study

BACKGROUND

Alzheimer's disease (AD) affects several cognitive functions and causes altered motor function. Fine motor deficits during object manipulation are evident in other neurological conditions, but have not been assessed in dementia patients yet.

OBJECTIVE

Investigate reactive and anticipatory grip force control in response to unexpected and expected load force perturbation in AD.

METHODS

Reactive and anticipatory grip force was investigated using a grip-device with force sensors. In this pilot study, fifteen AD patients and fourteen healthy controls performed a catching task. They held the device with one hand while a sandbag was dropped into an attached receptacle either by the experimenter or by the participant.

RESULTS

In contrast to studies of other neurological conditions, the majority of AD patients exerted lower static grip force levels than controls. Interestingly, patients who were slow in the Luria's three-step test produced normal grip forces. The timing and magnitude of reactive grip force control were largely preserved in patients. In contrast, timing and extent of anticipatory grip forces were impaired in patients, although anticipatory control was generally preserved. These deficits were correlated with decreasing Mini-Mental State Examination scores. Apraxia scores, assessed by pantomime of tool-use, did not correlate with performance in the catching task.

CONCLUSION

We interpreted the decreased grip force in AD in the context of loss of strength and lethargy, typical for patients with AD. The lower static grip force during object manipulation may emerge as a potential biomarker for early stages of AD, but more studies with larger sample sizes are necessary.

Brain-based mechanisms of late-life depression: Implications for novel interventions

Late-life depression (LLD) is a particularly debilitating illness. Older adults suffering from depression commonly experience poor outcomes in response to antidepressant treatments, medical comorbidities, and declines in daily functioning. This review aims to further our understanding of the brain network dysfunctions underlying LLD that contribute to disrupted cognitive and affective processes and corresponding clinical manifestations. We provide an overview of a network model of LLD that integrates the salience network, the default mode network (DMN) and the executive control network (ECN). We discuss the brain-based structural and functional mechanisms of LLD with an emphasis on their link to clinical subtypes that often fail to respond to available treatments. Understanding the brain networks that underlie these disrupted processes can inform the development of targeted interventions for LLD. We propose behavioral, cognitive, or computational approaches to identifying novel, personalized interventions that may more effectively target the key cognitive and affective symptoms of LLD.

Mechanisms and Treatment of Late-Life Depression

(Appeared originally in Translational Psychiatry 2019; 9:188).

Resting-State Functional Connectivity Signatures of Apathy in Community-Living Older Adults

Apathy predicts poor outcomes in older adults, and its underlying neural mechanism needs further investigation. We examined the association between symptoms of apathy and functional connectivity (FC) in older adults without stroke or dementia. Participants included 48 individuals (mean age = 70.90) living independently in the community, who underwent resting-state fMRI and completed the Apathy Evaluation Scale (AES). Seed-to-voxel analysis (cluster-level p-FDR <0.05, voxel threshold p < 0.001) tested the association between AES scores and the whole-brain FC of brain regions involved in reward- and salience-related processing. We found that AES scores were negatively associated with FC of the right insula cortex and right anterior temporal regions (124 voxels, t = −5.10) and FC of the left orbitofrontal cortex and anterior cingulate regions (160 voxels, t = −5.45), and were positively associated with FC of the left orbitofrontal cortex and left lateral prefrontal (282 voxels, t = 4.99) and anterior prefrontal (123 voxels, t = 4.52) regions. These findings suggest that apathy in older adults may reflect disruptions in neural connectivity involved in reward- and salience-related processing.

Differential Alterations in Resting State Functional Connectivity Associated with Depressive Symptoms and Early Life Adversity

Depression and early life adversity (ELA) are associated with aberrant resting state functional connectivity (FC) of the default mode (DMN), salience (SN), and central executive networks (CEN). However, the specific and differential associations of depression and ELA with FC of these networks remain unclear. Applying a dimensional approach, here we analyzed associations of FC between major nodes of the DMN, SN, and CEN with severity of depressive symptoms and ELA defined as childhood abuse and neglect in a sample of 83 healthy and depressed subjects. Depressive symptoms were linked to increased FC within the SN and decreased FC of the SN with the DMN and CEN. Childhood abuse was associated with increased FC within the SN, whereas childhood neglect was associated with decreased FC within the SN and increased FC between the SN and the DMN. Our study thus provides evidence for differential associations of depressive symptoms and ELA with resting state FC and contributes to a clarification of previously contradictory findings. Specific FC abnormalities may underlie specific cognitive and emotional impairments. Future research should link specific clinical symptoms resulting from ELA to FC patterns thereby characterizing depression subtypes with specific neurobiological signatures.

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.

Cortical Thickness of the Salience Network and Change in Apathy Following Antidepressant Treatment for Late-Life Depression

OBJECTIVE

Apathy is common in late-life depression and is associated with poor response to antidepressant drugs. In depressed older adults, apathy may be characterized by neuroanatomical abnormalities of the salience network. The current study examined whether cortical thickness of select salience network structures predicted change in apathy following a 12-week treatment with escitalopram.

METHODS

A sample of 46 older adults with major depressive disorder received 12 weeks of escitalopram treatment at a daily target dose of 20 mg. All participants underwent a structural brain MRI scan at baseline, and cortical thickness was estimated in key cortical nodes of the salience network: the caudal anterior cingulate cortex and the insula. We measured baseline and post-treatment symptoms using the Apathy Evaluation Scale and the Hamilton Depression Rating Scale.

RESULTS

A thicker insula at baseline predicted reduction in apathy symptoms following 12 weeks of treatment with escitalopram, even when controlling for age, baseline depression severity and change in depressive symptoms.

CONCLUSION

Reduced insular thickness predicted residual apathetic symptoms following escitalopram treatment. These results converge with our previous findings of abnormal functional connectivity of the insular cortex in older depressed individuals with apathy. Older depressed adults with apathy may benefit from alternative treatment approaches or augmentative interventions that target abnormalities of the salience network.

The efficacy of repetitive transcranial magnetic stimulation on emotional processing in apathetic patients with Parkinson's disease: A Placebo-controlled ERP study

BACKGROUND

Few studies have examined the effect of rTMS on impaired emotional processing in apathetic Parkinson's disease (PD) patients, which impelled us to use a combination of repetitive transcranial magnetic stimulation (rTMS) with event-related potentials (ERPs) to gain insight into the underlying mechanisms.

METHODS

Apathetic and non-apathetic patients diagnosed with PD performed a facial emotion categorization task, and ERP data were collected before and after HF-rTMS or sham stimulation over the right dorsolateral prefrontal cortex (DLPFC). We observed the behavioural results and early components of P100 and N170.

RESULTS

After rTMS, accuracy (ACC) was higher for negative expressions, and reaction times (RTs) were shorter for all expressions in both apathetic and non-apathetic patients. P100 amplitudes significantly increased except for negative expressions in the right hemisphere, and hemisphere lateralization was reversed in apathetic patients. P100 amplitudes increased for all expressions bilaterally in non-apathetic patients. N170 amplitudes in apathetic patients increased, and hemisphere lateralization was normalized. Neither the apathetic sham group nor the non-apathetic cohort of patients showed changes in P100 or N170 lateralization.

LIMITATIONS

The effects of rTMS on PD patients relative to normal subjects should be compared and observed over a long period of time.

CONCLUSIONS

HF-rTMS over the right DLPFC is beneficial for emotional processing in both apathetic and non-apathetic PD patients but shows different sensitivities. The effect of rTMS on emotional processing impairments in apathetic PD patients is profound. Treatment with rTMS may be an important, novel nonpharmaceutical approach for apathy in PD patients.

The Contribution of Thalamic Nuclei in Salience Processing

The brain continuously receives diverse information about the external environment and changes in the homeostatic state. The attribution of salience determines which stimuli capture attention and, therefore, plays an essential role in regulating emotions and guiding behaviors. Although the thalamus is included in the salience network, the neural mechanism of how the thalamus contributes to salience processing remains elusive. In this mini-review, we will focus on recent advances in understanding the specific roles of distinct thalamic nuclei in salience processing. We will summarize the functional connections between thalamus nuclei and other key nodes in the salience network. We will highlight the convergence of neural circuits involved in reward and pain processing, arousal, and attention control in thalamic structures. We will discuss how thalamic activities represent salience information in associative learning and how thalamic neurons modulate adaptive behaviors. Lastly, we will review recent studies which investigate the contribution of thalamic dysfunction to aberrant salience processing in neuropsychiatric disorders, such as drug addiction, posttraumatic stress disorder (PTSD), and schizophrenia. Based on emerging evidence from both human and rodent research, we propose that the thalamus, different from previous studies that as an information relay, has a broader role in coordinating the cognitive process and regulating emotions.

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.

Coexistence of perseveration and apathy in the TDP-43Q331K knock-in mouse model of ALS-FTD

Perseveration and apathy are two of the most common behavioural and psychological symptoms of dementia (BPSDs) in amyotrophic lateral sclerosis-frontotemporal dementia (ALS-FTD). Availability of a validated and behaviourally characterised animal model is crucial for translational research into BPSD in the FTD context. We behaviourally evaluated the male TDP-43^Q331K mouse, an ALS-FTD model with a human-equivalent mutation (TDP-43^Q331K) knocked into the endogenous Tardbp gene. We utilised a panel of behavioural tasks delivered using the rodent touchscreen apparatus, including progressive ratio (PR), extinction and visual discrimination/reversal learning (VDR) assays to examine motivation, response inhibition and cognitive flexibility, respectively. Relative to WT littermates, TDP-43^Q331K mice exhibited increased responding under a PR schedule. While elevated PR responding is typically an indication of increased motivation for reward, a trial-by-trial response rate analysis revealed that TDP-43^Q331K mice exhibited decreased maximal response rate and slower response decay rate, suggestive of reduced motivation and a perseverative behavioural phenotype, respectively. In the extinction assay, TDP-43^Q331K mice displayed increased omissions during the early phase of each session, consistent with a deficit in activational motivation. Finally, the VDR task revealed cognitive inflexibility, manifesting as stimulus-bound perseveration. Together, our data indicate that male TDP-43^Q331K mice exhibit a perseverative phenotype with some evidence of apathy-like behaviour, similar to BPSDs observed in human ALS-FTD patients. The TDP-43^Q331K knock-in mouse therefore has features that recommend it as a useful platform to facilitate translational research into behavioural symptoms in the context of ALS-FTD.

Neuroanatomical Abnormalities in Older Depressed Adults With Apathy: A Systematic Review

OBJECTIVE

Apathy is a common phenomenon in late-life depression and is associated with poor outcomes. Apathy is often unrecognized in older depressed adults, and efficacious treatment options are lacking. This review provides a systematic review of the neuroanatomical abnormalities associated with apathy in late-life depression. In addition, the review summarizes the neuroimaging findings from studies of neurodegenerative and focal brain injury conditions that frequently present with apathy. The goal is to elucidate cerebral network abnormalities that give rise to apathy in older adults with mood disturbances and to inform future treatment targets.

METHOD

Systematic literature review.

RESULTS

The few studies that have directly examined the neuroanatomical abnormalities of apathy in late-life depression suggest disturbances in the anterior cingulate cortex, insula, orbital and dorsal prefrontal cortex, striatum, and limbic structures (ie, amygdala, thalamus, and hippocampus). Studies examining the neuroanatomical correlates of apathy in other aging populations are consistent with the pattern observed in late-life depression.

CONCLUSIONS

Apathy in late-life depression appears to be accompanied by neuroanatomical abnormalities in the salience and reward networks. These network findings are consistent with that observed in individuals presenting with apathy in other aging-related conditions. These findings may inform future treatments that target apathy.

Dimensions of Poststroke Depression and Neuropsychological Deficits in Older Adults

OBJECTIVE

Poststroke depression (PSD) has a heterogeneous presentation and is often accompanied by cognitive impairment. This study aimed to identify distinct dimensions of depressive symptoms in older adults with PSD and to evaluate their relationship to cognitive functioning.

DESIGN

Cross-sectional factor and correlational analyses of patients with poststroke depression.

SETTING

Patients were recruited from the community and from acute inpatient stroke rehabilitation hospitals.

PARTICIPANTS

Participants had suffered a stroke and met DSM-IV criteria for major depression (≥18 Montgomery Åsberg Depression Scale; MADRS).

INTERVENTION

None.

MEASUREMENTS

MADRS was used to quantify depression severity at study entry. Neuropsychological assessment at the time of study entry consisted of measures of Global Cognition, Attention, Executive Function, Processing Speed, Immediate Memory, Delayed Memory, and Language.

RESULTS

There were 135 (age ≥50) older adult participants with PSD and varying degrees of cognitive impairment (MMSE Total ≥20). Factor analysis of the MADRS identified three factors, that is sadness, distress, and apathy. Items comprising each factor were totaled and correlated with neuropsychological domain z-score averages. Symptoms of the apathy factor (lassitude, inability to feel) were significantly associated with greater impairment in executive function, memory, and global cognition. Symptoms of the sadness and distress factors had no relationship to cognitive impairment.

CONCLUSION

PSD consists of three correlated dimensions of depressive symptoms. Apathy symptoms are associated with cognitive impairment across several neuropsychological domains. PSD patients with prominent apathy may benefit from careful attention to cognitive functions and by interventions that address both psychopathology and behavioral deficits resulting from cognitive impairment.

Reduced spatiotemporal brain dynamics are associated with increased depressive symptoms after a relationship breakup

Depressive symptoms following a stressful life event, such as a relationship breakup, are common, and constitute a potent risk factor for the onset of a major depressive episode. Resting-state neuroimaging studies have increasingly identified abnormal whole-brain communication in patients with depression, but it is currently unclear whether depressive symptoms in individuals without a clinical diagnosis have reliable neural underpinnings. We investigated to what extent the severity of depressive symptoms in a non-clinical sample was associated with imbalances in the complex dynamics of the brain during rest. To this end, a novel intrinsic ignition approach was applied to resting-state neuroimaging data from sixty-nine participants with varying degrees of depressive symptoms following a relationship breakup. Ignition-based measures of integration, hierarchy, and metastability were calculated for each participant, revealing a negative correlation between these measures and depressive ratings. We found that the severity of depressive symptoms was associated with deficits in the brain's capacity to globally integrate and process information over time. Furthermore, we found that increased depressive symptoms were associated with reduced spatial diversity (i.e., hierarchy) and reduced temporal variability (i.e., metastability) in the functional organization of the brain. These findings suggest the merit of investigating constrained dynamical complexity as it is sensitive to the level of depressive symptoms even in a non-clinical sample.

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.

Disruption of resting-state functional connectivity of right posterior insula in adolescents and young adults with major depressive disorder

BACKGROUND

The neural basis of Major Depressive Disorder (MDD) which is a clinical syndrome characterized by emotional and cognitive impairments is poorly understood. Accumulating evidence has suggested that the insula is an important substrate underlying the mechanism of MDD. This study aimed to examine the disrupted resting-state brain regional function in insula and to further investigate the associated resting-state functional connectivity (rs-FC) of insula underlie the MDD in adolescents and young adults.

METHODS

We employed 3.0T resting-state functional magnetic resonance imaging (rs-fMRI) to acquire data from 76 adolescents and young adults with MDD and 44 age and sex matched healthy control subjects. We employed a regional Amplitude of Low-Frequency Fluctuation (ALFF) analysis to explore local intrinsic neural oscillation alterations in insula and an ALFF-based functional connectivity (FC) approach to detect the potential changes in remote connectivity with insula in adolescents and young adults with MDD.

RESULTS

By applying ALFF analysis, significantly decreased activities were detected in bilateral insula, and in particular in right anterior insular gyrus (MNI; ROI1: 42, 24, -3), right posterior insular gyrus (Montreal Neurological Institute, MNI; ROI2: 36, -9, 15) and left anterior insular gyrus (MNI; ROI3: -36, 12, 9) in patients with MDD compared to the healthy controls (p < 0.05, 1000 permutations, TFCE corrected). With ROI2 as the seed in the subsequent ALFF-based rs-FC analysis, patients with MDD were observed to have significantly reduced FC with bilateral middle occipital gyrus, lingual gyrus, calcarine, postcentral gyrus, precentral gyrus, supramarginal area, superior temporal gyrus and middle cingulate gyrus as compared to the healthy controls (p < 0.05, 1000 permutations, TFCE corrected). No significant differences of FC were detected between the patients and healthy controls when using ROI1 and ROI3 as the seeds. We found no correlations between ALFF or rs-FC values and the severity of depression as estimated by Hamilton Depression Rating Scale (HAM-D).

LIMITATIONS

Clinical information were limited and no significant correlations were found between imaging variables and HAM-D scores, which reduces the power to interpret the present findings. A cross-sectional design was employed in this study so that it is not possible to know whether the abnormal ALFF or altered brain FC of insula reflects a state or trait effect in young people with MDD.

CONCLUSIONS

This study highlights the regional/network interaction abnormalities of insula in adolescents and young adults with MDD, and could provide further insight into understanding the neural pathomechanism of MDD in young patients.