Voxel-wise hemispheric Amyloid Asymmetry and its association with cerebral metabolism and grey matter density in cognitively normal older adults

Introduction

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by changes in beta amyloid (Aß) and tau as well as changes in cerebral glucose metabolism and gray matter volume. This has been categorized as three distinct stages of amyloid, tau, and neurodegeneration. Past studies have shown asymmetric Aβ accumulation and its association with asymmetric cerebral metabolism in preclinical AD. We analyzed data to replicate these findings and extend them to associations with gray matter volume and cognitive function.

Methods

We recruited 93 (mean age = 76.4±6.1 years) cognitively normal adults who underwent magnetic resonance imaging (MRI) and positron emission tomography (PET) with Pittsburgh compound B (PiB) and Fluorodeoxyglucose (FDG) tracers (to estimate Aβ and glucose metabolism, respectively). We conducted voxel-wise paired t-test on PiB (left vs. right hemispheres) to identify regions that differ in Aβ between the left and right cortex. We identified whether these regions showed asymmetry in FDG and gray matter volume using paired t-tests on each region. We then conducted correlations between asymmetry indices for each region that had significant asymmetry in PiB, FDG, and gray matter volume. We ran a group regression analysis on cognitive functions.

Results

We found 26 regions that had significant rightward asymmetry in PiB including prefrontal cortex, temporal cortex, insula, parahippocampus, caudate, and putamen. All these regions showed significant gray matter rightward asymmetry, and most of these regions showed significant FDG asymmetry except the caudate, orbital cortex, medial frontal gyrus, and superior temporal gyrus. Only in the superior frontal gyrus, we found that greater rightward asymmetry in PiB was associated with greater rightward asymmetry in FDG, r(82) =0.38, p<0.005 (FDR corrected) - no other regions showed significant Aß asymmetry correlation with either FDG or gray matter volume asymmetry. We found that greater rightward FDG asymmetry in the superior frontal gyrus was associated with greater visuospatial processing scores in our cognitive domain group regression analysis.

Discussion

AD has previously been modeled in three-stages: however, our results indicate that cerebral glucose metabolism may be dynamic throughout the disease progression and may serve as a compensatory pathway for maintaining cognitive functioning.

Continuous theta burst stimulation to dorsomedial prefrontal cortex in young adults with depression: Changes in resting frontostriatal functional connectivity relevant to positive mood

Depression is associated with diminished positive affect (PA), postulated to reflect frontostriatal reward circuitry disruptions. Depression has consistently been associated with higher dorsomedial prefrontal cortex (dmPFC) activation, a region that regulates PA through ventral striatum (VS) connections. Low PA in depression may reflect dmPFC's aberrant functional connectivity (FC) with the VS. To test this, we applied theta burst stimulation (TBS) to dmPFC in 29 adults with depression (79% female, Mage = 21.4, SD = 2.04). Using a randomized, counterbalanced design, we administered 3 types of TBS at different sessions: intermittent (iTBS; potentiating), continuous (cTBS; depotentiating), and sham TBS (control). We used neuronavigation to target personalized dmPFC targets based on VS-dmPFC FC. PA and negative affect (NA), and resting-state fMRI were collected pre- and post-TBS. We found no changes in PA or NA with time (pre/post), condition (iTBS, cTBS, sham), or their interaction. Functional connectivity (FC) between the nucleus accumbens and dmPFC showed a significant condition (cTBS, iTBS, and sham) by time (pre-vs. post-TBS) interaction, and post-hoc testing showed decreased pre-to post-TBS for cTBS but not iTBS or sham. For cTBS only, reduced FC pre/post stimulation was associated with increased PA (but not NA). Our findings lend support to the proposed mechanistic model of aberrant FC between the dmPFC and VS in depression and suggest a way forward for treating depression in young adults. Future studies need to evaluate multi-session TBS to test clinical effects.

Manual segmentation of the paraventricular nucleus of the hypothalamus and the dorsal and ventral bed nucleus of stria terminalis using multimodal 7 Tesla structural MRI: probabilistic atlases for a stress-control triad

The paraventricular nucleus of the hypothalamus (PVN) is uniquely capable of proximal control over autonomic and neuroendocrine stress responses, and the bed nucleus of the stria terminalis (BNST) directly modulates PVN function, as well as playing an important role in stress control itself. The dorsal BNST (dBNST) is predominantly preautonomic, while the ventral BNST (vBNST) is predominantly viscerosensory, receiving dense noradrenergic signaling. Distinguishing the dBNST and vBNST, along with the PVN, may facilitate our understanding of dynamic interactions among these regions. T1-weighted MPRAGE and high resolution gradient echo (GRE) modalities were acquired at 7T. GRE was coregistered to MPRAGE and segmentations were performed in MRIcroGL based on their Atlas of the Human Brain depictions. The dBNST, vBNST and PVN were manually segmented in 25 participants; 10 images were rated by 2 raters. These segmentations were normalized and probabilistic atlases for each region were generated in MNI space, now available as resources for future research. We found moderate-high inter-rater reliability [n = 10; Mean Dice (SD); PVN = 0.69 (0.04); dBNST = 0.77 (0.04); vBNST = 0.62 (0.04)]. Probabilistic atlases were reverse normalized into native space for six additional participants that were segmented but not included in the original 25. We also found moderate to moderate-high reliability between the probabilistic atlases and manual segmentations [n = 6; Mean Dice (SD); PVN = 0.55 (0.12); dBNST = 0.60 (0.10); vBNST = 0.47 (0.12 SD)]. By isolating these hypothalamic and BNST subregions using ultra-high field MRI modalities, more specific delineations of these regions can facilitate greater understanding of mechanisms underlying stress-related function and psychopathology.

Assessing depression recurrence, cognitive burden, and neurobiological homeostasis in late life: Design and rationale of the REMBRANDT Study

Background

Late-life depression is characterized by disability, cognitive impairment and decline, and a high risk of recurrence following remission. Aside from past psychiatric history, prognostic neurobiological and clinical factors influencing recurrence risk are unclear. Moreover, it is unclear if cognitive impairment predisposes to recurrence, or whether recurrent episodes may accelerate brain aging and cognitive decline. The purpose of the REMBRANDT study (Recurrence markers, cognitive burden, and neurobiological homeostasis in late-life depression) is to better elucidate these relationships and identify phenotypic, cognitive, environmental, and neurobiological factors contributing to and predictive of depression recurrence.

Methods

Across three sites, REMBRANDT will enroll 300 depressed elders who will receive antidepressant treatment. The goal is to enroll 210 remitted depressed participants and 75 participants with no mental health history into a two-year longitudinal phase focusing on depression recurrence. Participants are evaluated every 2 months with deeper assessments occurring every 8 months, including structural and functional neuroimaging, environmental stress assessments, deep symptom phenotyping, and two weeks of 'burst' ecological momentary assessments to elucidate variability in symptoms and cognitive performance. A broad neuropsychological test battery is completed at the beginning and end of the longitudinal study.

Significance

REMBRANDT will improve our understanding of how alterations in neural circuits and cognition that persist during remission contribute to depression recurrence vulnerability. It will also elucidate how these processes may contribute to cognitive impairment and decline. This project will obtain deep phenotypic data that will help identify vulnerability and resilience factors that can help stratify individual clinical risk.

White Noise-Is Anxiety in Late-Life Associated With White Matter Hyperintensity Burden?

OBJECTIVE

We investigated the relationship between anxiety phenotypes (global anxiety, worry, and rumination) and white matter hyperintensities (WMH), with special consideration for the roles of age and executive function (EF). Our hypotheses were 1) anxiety phenotypes would be associated with WMH and 2) EF would moderate this relationship.

DESIGN

Cross-sectional.

SETTING

Participants were recruited from the local community (Pittsburgh, PA).

PARTICIPANTS

We recruited 110 older adults (age ≥ 50) with varying worry severity and clinical comorbidity.

INTERVENTIONS

Not applicable.

MEASUREMENTS

Demographics (age, sex, race, education), clinical measures (cumulative illness burden, global anxiety, worry, and rumination), EF, and WMH quantified with magnetic resonance imaging.

RESULTS

Lower global anxiety and worry severity were significantly correlated with higher WMH volume, though the global anxiety relationship was not significant after controlling for age. Rumination as not associated with WMH burden. EF was not correlated with either global anxiety, worry, rumination, or WMH. However, in those with advanced age and/or greater WMH burden, there was an association between worry and EF as well as EF and WMH.

CONCLUSION

Longitudinal studies are needed in order to clarify the complex interactions between anxiety phenotypes, WMH, and EF.

A network approach to the investigation of childhood irritability: probing frustration using social stimuli

BACKGROUND

Self-regulation in early childhood develops within a social context. Variations in such development can be attributed to inter-individual behavioral differences, which can be captured both as facets of temperament and across a normal:abnormal dimensional spectrum. With increasing emphasis on irritability as a robust early-life transdiagnostic indicator of broad psychopathological risk, linkage to neural mechanisms is imperative. Currently, there is inconsistency in the identification of neural circuits that underlie irritability in children, especially in social contexts. This study aimed to address this gap by utilizing a functional magnetic resonance imaging (fMRI) paradigm to investigate pediatric anger/frustration using social stimuli.

METHODS

Seventy-three children (M = 6 years, SD = 0.565) were recruited from a larger longitudinal study on irritability development. Caregivers completed questionnaires assessing irritable temperament and clinical symptoms of irritability. Children participated in a frustration task during fMRI scanning that was designed to induce frustration through loss of a desired prize to an animated character. Data were analyzed using both general linear modeling (GLM) and independent components analysis (ICA) and examined from the temperament and clinical perspectives.

RESULTS

ICA results uncovered an overarching network structure above and beyond what was revealed by traditional GLM analyses. Results showed that greater temperamental irritability was associated with significantly diminished spatial extent of activation and low-frequency power in a network comprised of the posterior superior temporal sulcus (pSTS) and the precuneus (p < .05, FDR-corrected). However, greater severity along the spectrum of clinical expression of irritability was associated with significantly increased extent and intensity of spatial activation as well as low- and high-frequency neural signal power in the right caudate (p < .05, FDR-corrected).

CONCLUSIONS

Our findings point to specific neural circuitry underlying pediatric irritability in the context of frustration using social stimuli. Results suggest that a deliberate focus on the construction of network-based neurodevelopmental profiles and social interaction along the normal:abnormal irritability spectrum is warranted to further identify comprehensive transdiagnostic substrates of the irritability.

Sex matters: acute functional connectivity changes as markers of remission in late-life depression differ by sex

The efficacy of antidepressant treatment in late-life is modest, a problem magnified by an aging population and increased prevalence of depression. Understanding the neurobiological mechanisms of treatment response in late-life depression (LLD) is imperative. Despite established sex differences in depression and neural circuits, sex differences associated with fMRI markers of antidepressant treatment response are underexplored. In this analysis, we assess the role of sex on the relationship of acute functional connectivity changes with treatment response in LLD. Resting state fMRI scans were collected at baseline and day one of SSRI/SNRI treatment for 80 LLD participants. One-day changes in functional connectivity (differential connectivity) were related to remission status after 12 weeks. Sex differences in differential connectivity profiles that distinguished remitters from non-remitters were assessed. A random forest classifier was used to predict the remission status with models containing various combinations of demographic, clinical, symptomatological, and connectivity measures. Model performance was assessed with area under the curve, and variable importance was assessed with permutation importance. The differential connectivity profile associated with remission status differed significantly by sex. We observed evidence for a difference in one-day connectivity changes between remitters and non-remitters in males but not females. Additionally, prediction of remission was significantly improved in male-only and female-only models over pooled models. Predictions of treatment outcome based on early changes in functional connectivity show marked differences between sexes and should be considered in future MR-based treatment decision-making algorithms.

Changes in cerebral connectivity and brain tissue pulsations with the antidepressant response to an equimolar mixture of oxygen and nitrous oxide: an MRI and ultrasound study

Nitrous oxide (N2O) has recently emerged as a potential fast-acting antidepressant but the cerebral mechanisms involved in this effect remain speculative. We hypothesized that the antidepressant response to an Equimolar Mixture of Oxygen and Nitrous Oxide (EMONO) would be associated with changes in cerebral connectivity and brain tissue pulsations (BTP). Thirty participants (20 with a major depressive episode resistant to at least one antidepressant and 10 healthy controls-HC, aged 25-50, only females) were exposed to a 1-h single session of EMONO and followed for 1 week. We defined response as a reduction of at least 50% in the MADRS score 1 week after exposure. Cerebral connectivity of the Anterior Cingulate Cortex (ACC), using ROI-based resting state fMRI, and BTP, using ultrasound Tissue Pulsatility Imaging, were compared before and rapidly after exposure (as well as during exposure for BTP) among HC, non-responders and responders. We conducted analyses to compare group × time, group, and time effects. Nine (45%) depressed participants were considered responders and eleven (55%) non-responders. In responders, we observed a significant reduction in the connectivity of the subgenual ACC with the precuneus. Connectivity of the supracallosal ACC with the mid-cingulate also significantly decreased after exposure in HC and in non-responders. BTP significantly increased in the three groups between baseline and gas exposure, but the increase in BTP within the first 10 min was only significant in responders. We found that a single session of EMONO can rapidly modify the functional connectivity in the subgenual ACC-precuneus, nodes within the default mode network, in depressed participants responders to EMONO. In addition, larger increases in BTP, associated with a significant rise in cerebral blood flow, appear to promote the antidepressant response, possibly by facilitating optimal drug delivery to the brain. Our study identified potential cerebral mechanisms related to the antidepressant response of N2O, as well as potential markers for treatment response with this fast-acting antidepressant.

"Brain age" predicts disability accumulation in multiple sclerosis

OBJECTIVE

Neurodegenerative conditions often manifest radiologically with the appearance of premature aging. Multiple sclerosis (MS) biomarkers related to lesion burden are well developed, but measures of neurodegeneration are less well-developed. The appearance of premature aging quantified by machine learning applied to structural MRI assesses neurodegenerative pathology. We assess the explanatory and predictive power of "brain age" analysis on disability in MS using a large, real-world dataset.

METHODS

Brain age analysis is predicated on the over-estimation of predicted brain age in patients with more advanced pathology. We compared the performance of three brain age algorithms in a large, longitudinal dataset (>13,000 imaging sessions from >6,000 individual MS patients). Effects of MS, MS disease course, disability, lesion burden, and DMT efficacy were assessed using linear mixed effects models.

RESULTS

MS was associated with advanced predicted brain age cross-sectionally and accelerated brain aging longitudinally in all techniques. While MS disease course (relapsing vs. progressive) did contribute to advanced brain age, disability was the primary correlate of advanced brain age. We found that advanced brain age at study enrollment predicted more disability accumulation longitudinally. Lastly, a more youthful appearing brain (predicted brain age less than actual age) was associated with decreased disability.

INTERPRETATION

Brain age is a technically tractable and clinically relevant biomarker of disease pathology that correlates with and predicts increasing disability in MS. Advanced brain age predicts future disability accumulation.

History of major depressive disorder is associated with differences in implicit learning of emotional faces

Major depressive disorder is often associated with worsened reward learning, with blunted reward response persisting after remission. In this study, we developed a probabilistic learning task with social rewards as a learning signal. We examined the impacts of depression on social rewards (facial affect displays) as an implicit learning signal. Fifty-seven participants without a history of depression and sixty-two participants with a history of depression (current or remitted) completed a structured clinical interview and an implicit learning task with social reward. Participants underwent an open-ended interview to evaluate whether they knew the rule consciously. Linear mixed effects models revealed that participants without a history of depression learned faster and showed a stronger preference towards the positive than the negative stimulus when compared to the participants with a history of depression. In contrast, those with a history depression learned slower on average and displayed greater variability in stimulus preference. We did not detect any differences in learning between those with current and remitted depression. The results indicate that on a probabilistic social reward task, people with a history of depression exhibit slower reward learning and greater variability in their learning behavior. Improving our understanding of alterations in social reward learning and their associations with depression and anhedonia may help to develop translatable psychotherapeutic approaches for modification of maladaptive emotion regulation.

Causal feature selection using a knowledge graph combining structured knowledge from the biomedical literature and ontologies: a use case studying depression as a risk factor for Alzheimer's disease

BACKGROUND

Causal feature selection is essential for estimating effects from observational data. Identifying confounders is a crucial step in this process. Traditionally, researchers employ content-matter expertise and literature review to identify confounders. Uncontrolled confounding from unidentified confounders threatens validity, conditioning on intermediate variables (mediators) weakens estimates, and conditioning on common effects (colliders) induces bias. Additionally, without special treatment, erroneous conditioning on variables combining roles introduces bias. However, the vast literature is growing exponentially, making it infeasible to assimilate this knowledge. To address these challenges, we introduce a novel knowledge graph (KG) application enabling causal feature selection by combining computable literature-derived knowledge with biomedical ontologies. We present a use case of our approach specifying a causal model for estimating the total causal effect of depression on the risk of developing Alzheimer's disease (AD) from observational data.

METHODS

We extracted computable knowledge from a literature corpus using three machine reading systems and inferred missing knowledge using logical closure operations. Using a KG framework, we mapped the output to target terminologies and combined it with ontology-grounded resources. We translated epidemiological definitions of confounder, collider, and mediator into queries for searching the KG and summarized the roles played by the identified variables. We compared the results with output from a complementary method and published observational studies and examined a selection of confounding and combined role variables in-depth.

RESULTS

Our search identified 128 confounders, including 58 phenotypes, 47 drugs, 35 genes, 23 collider, and 16 mediator phenotypes. However, only 31 of the 58 confounder phenotypes were found to behave exclusively as confounders, while the remaining 27 phenotypes played other roles. Obstructive sleep apnea emerged as a potential novel confounder for depression and AD. Anemia exemplified a variable playing combined roles.

CONCLUSION

Our findings suggest combining machine reading and KG could augment human expertise for causal feature selection. However, the complexity of causal feature selection for depression with AD highlights the need for standardized field-specific databases of causal variables. Further work is needed to optimize KG search and transform the output for human consumption.

Utilization of machine learning to model the effect of blood product transfusion on short-term lung transplant outcomes

The objective of this study was to identify the relationship between blood product transfusion and short-term morbidity and mortality following lung transplantation utilizing machine learning. Preoperative recipient characterstics, procedural variables, perioperative blood product transfusions, and donor charactersitics were included in the model. The primary composite outcome was occurrence on any of the following six endpoints: mortality during index hospitalization; primary graft dysfunction at 72 h post-transplant or the need for postoperative circulatory support; neurological complications (seizure, stroke, or major encephalopathy); perioperative acute coronary syndrome or cardiac arrest; and renal dysfunction requiring renal replacement therapy. The cohort included 369 patients, with the composite outcome occurring in 125 cases (33.9%). Elastic net regression analysis identified 11 significant predictors of composite morbidity: higher packed red blood cell, platelet, cryoprecipitate and plasma volume from the critical period, preoperative functional dependence, any preoperative blood transfusion, VV ECMO bridge to transplant, and antifibrinolytic therapy were associated with higher risk of morbidity. Preoperative steroids, taller height, and primary chest closure were protective against composite morbidity.

Functional Asymmetry During Working Memory and Its Association with Markers of Alzheimer's Disease in Cognitively Normal Older Adults

BACKGROUND

Amyloid-β (Aβ) deposits asymmetrically early in Alzheimer's disease (AD). This process is variable and has been associated with asymmetric hypometabolism.

OBJECTIVE

We investigated whether neural asymmetry during working memory and executive function processing was associated with AD genetic risk and markers of AD as well as other brain neuropathology biomarkers, cognitive function, and cognitive reserve in cognitively normal older adults.

METHODS

We analyzed data from 77 cognitively healthy, older adults who completed functional magnetic resonance imaging, positron emission tomography, and cognitive testing. We identified regions of significant activation and asymmetry during the Digital Symbol Substitution Task (DSST). We examined associations between regions with significant hemispheric asymmetry (directional and absolute) and global cerebral Aβ, cerebral glucose metabolism, white matter hyperintensities, APOE ɛ4 allele status, DSST reaction time, age, sex, education, and cognitive function.

RESULTS

Asymmetry was not associated with several factors including cognitive function, Aβ, and white matter hyperintensities. The presence of at least one ɛ4 APOE allele in participants was associated with less asymmetric activation in the angular gyrus (right dominant activation). Greater education was associated with less asymmetric activation in mediodorsal thalamus (left dominant activation).

CONCLUSIONS

Genetic risk of AD was associated with lower asymmetry in angular gyrus activation, while greater education was associated with lower asymmetry in mediodorsal thalamus activation. Changes in asymmetry may reflect components of compensation or cognitive reserve. Asymmetric neural recruitment during working memory may be related to maintenance of cognitive function in cognitively normal older adults.

MRI predictors of pharmacotherapy response in major depressive disorder

Major depressive disorder is among the most prevalent psychiatric disorders, exacting a substantial personal, social, and economic toll. Antidepressant treatment typically involves an individualized trial and error approach with an inconsistent success rate. Despite a pressing need, no reliable biomarkers for predicting treatment outcome have yet been discovered. Brain MRI measures hold promise in this regard, though clinical translation remains elusive. In this review, we summarize structural MRI and functional MRI (fMRI) measures that have been investigated as predictors of treatment outcome. We broadly divide these into five categories including three structural measures: volumetric, white matter burden, and white matter integrity; and two functional measures: resting state fMRI and task fMRI. Currently, larger hippocampal volume is the most widely replicated predictor of successful treatment. Lower white matter hyperintensity burden has shown robustness in late life depression. However, both have modest discriminative power. Higher fractional anisotropy of the cingulum bundle and frontal white matter, amygdala hypoactivation and anterior cingulate cortex hyperactivation in response to negative emotional stimuli, and hyperconnectivity within the default mode network (DMN) and between the DMN and executive control network also show promise as predictors of successful treatment. Such network-focused measures may ultimately provide a higher-dimensional measure of treatment response with closer ties to the underlying neurobiology.

Changes in brain response to urgency before and after treatment of urgency urinary incontinence with onabotulinumtoxin A

INTRODUCTION

To better understand the role of the brain in urgency urinary incontinence (UUI), we used onabotulinumtoxin A (BoNTA) as a probe to evaluate changes in the brain's response to urgency in successful and unsuccessful treatment. Because BoNTA acts peripherally, brain changes observed should represent a reaction to changes in bladder function caused by BoNTA, or changes in the brain's compensatory mechanisms, rather than a direct effect of BoNTA on the brain.

METHODS

We recruited 20 women aged over 60 years with nonneurogenic UUI who were to undergo treatment with onabotulinum A toxin injected intravesically. We performed a baseline evaluation which included a 3-day bladder diary and functional magnetic resonance imaging with an urgency provocation task; we repeated this evaluation 6 weeks posttreatment. We performed an analysis of variance on a priori selected regions of interest and post hoc voxel-wise analysis on responders and nonresponders to treatment.

RESULTS

We found a significant interaction in the right insula [F(1,18) = 5.5, p = 0.031]; activity was different during urgency provocation in responders and non-responders to therapy, before and after therapy. The supramarginal gyrus (SMG) and inferior frontal gyrus (IFG) also displayed significant interactions (p < 0.005). Activity in the periaqueductal gray and prefrontal cortex was correlated with number of leakage episodes (p < 0.05).

CONCLUSION

The changes seen in the brain control mechanism after therapy likely reflect reduced bladder sensation caused by BoNTA's peripheral action. We ascribe the SMG and IFG changes to a coping mechanism for urgency which is reduced in those who respond well to treatment.

Are All Anxieties Created Equal? Stress-related Networks and Anxiety Phenotypes in Old Age

OBJECTIVE

The dysregulation of stress-related networks due to chronic symptoms such as severe worry and/or rumination is one of the putative pathways linking anxiety in late-life with cognitive decline and increased cardiovascular burden. Symptoms such as severe worry or rumination respond poorly to standard treatment and drive the morbidity associated with anxiety in older adults. We assessed if any of the neural networks anchored in the stress-related regions of interest (ROIs) are associated with distinct anxiety phenotypes (worry, rumination and global anxiety).

METHODS

We recruited older participants (over 50 years of age) with varying levels of worry (N = 91) to undergo resting state fMRI. We computed seed-based connectivity for each ROI: the bed nucleus of the stria terminalis, the paraventricular nucleus of the hypothalamus, habenula, and amygdala. We limited our connectivity analyses to extracted regions for each seeded ROI-based network based on their canonical networks in 1,000 participants (Neurosynth). Using connectivity and clinical factors, we fit cross-validated elastic net models to predict scores on Penn State Worry Questionnaire, Rumination Subscale Questionnaire, Hamilton Anxiety Rating Scale, and Perceived Stress Scale.

RESULTS

We identified several distinct connectivity patterns that predict anxiety phenotypes' severity. Greater worry was associated with greater paraventricular nucleus of the hypothalamus -subgenual anterior cingulate cortex, parahippocampal, and olfactory and amygdala-PHC connectivity. Greater global anxiety was associated with lower amygdala-superior temporal gyrus connectivity. Greater perceived stress was associated with lower amygdala-inferior temporal gyrus and amygdala-fusiform gyrus connectivity.

CONCLUSION

Our study suggests that various late-life anxiety phenotypes (worry, global anxiety, rumination) may be associated with varying functional connectivity related to stress and emotion regulation. This may aid in the development of future targeted interventions.

Childhood Threat Is Associated With Lower Resting-State Connectivity Within a Central Visceral Network

Childhood adversity is associated with altered or dysregulated stress reactivity; these altered patterns of physiological functioning persist into adulthood. Evidence from both preclinical animal models and human neuroimaging studies indicates that early life experience differentially influences stressor-evoked activity within central visceral neural circuits proximally involved in the control of stress responses, including the subgenual anterior cingulate cortex (sgACC), paraventricular nucleus of the hypothalamus (PVN), bed nucleus of the stria terminalis (BNST) and amygdala. However, the relationship between childhood adversity and the resting-state connectivity of this central visceral network remains unclear. To this end, we examined relationships between childhood threat and childhood socioeconomic deprivation, the resting-state connectivity between our regions of interest (ROIs), and affective symptom severity and diagnoses. We recruited a transdiagnostic sample of young adult males and females (n = 100; mean age = 27.28, SD = 3.99; 59 females) with a full distribution of maltreatment history and symptom severity across multiple affective disorders. Resting-state data were acquired using a 7.2-min functional magnetic resonance imaging (fMRI) sequence; noted ROIs were applied as masks to determine ROI-to-ROI connectivity. Threat was determined by measures of childhood traumatic events and abuse. Socioeconomic deprivation (SED) was determined by a measure of childhood socioeconomic status (parental education level). Covarying for age, race and sex, greater childhood threat was significantly associated with lower BNST-PVN, amygdala-sgACC and PVN-sgACC connectivity. No significant relationships were found between SED and resting-state connectivity. BNST-PVN connectivity was associated with the number of lifetime affective diagnoses. Exposure to threat during early development may entrain altered patterns of resting-state connectivity between these stress-related ROIs in ways that contribute to dysregulated neural and physiological responses to stress and subsequent affective psychopathology.

Neuroimaging of situational urgency and incontinence provoked by personal urgency cues

INTRODUCTION

Situational triggers for urinary urgency and incontinence (UUI) such as "latchkey incontinence" and running water are often reported clinically, but no current clinical tools exist to directly address symptoms of UUI provoked by environmental stimuli. Previously we have shown that urgency and leakage can be reproduced during urodynamic studies with exposure to personal urgency-related images. Here we investigate the neural signatures associated with such situational triggers to inform potential therapies for reducing reactivity to these personal urgency-related cues among women with situational UUI.

METHOD

We recruited 23 women with situational UUI who took photographs of their personal "urgency trigger" and "safe" situations and were exposed to them in a magnetic resonance imaging (MRI) scanner. We identified brain areas that were more active during urgency versus safe image exposure.

RESULTS

We found that, during urgency image exposure, main components of the attention network and decision-related processes, the middle and medial frontal gyri, were more active (p < 0.01). In addition, areas well known to be involved in the continence mechanism, such as the cingulate and parahippocampal areas, were also more active during urgency image exposure.

CONCLUSION

Exposure to personal situational urgency images activated different areas of the brain compared with safe environments, highlighting the complex brain mechanisms that provoke real-world urgency. Using brain and behavioral-based therapies which target the attentional areas identified here and extinguish cue reactivity might reduce symptom burden in this subset of UUI sufferers.

Networks of worry-towards a connectivity-based signature of late-life worry using higher criticism

Severe worry is a complex transdiagnostic phenotype independently associated with increased morbidity, including cognitive impairment and cardiovascular diseases. We investigated the neurobiological basis of worry in older adults by analyzing resting state fMRI using a large-scale network-based approach. We collected resting fMRI on 77 participants (>50 years old) with varying worry severity. We computed region-wise connectivity across the default mode network (DMN), anterior salience network, and left executive control network. All 22,366 correlations were regressed on worry severity and adjusted for age, sex, race, education, disease burden, depression, anxiety, rumination, and neuroticism. We employed higher criticism, a second-level method of significance testing for rare and weak features, to reveal the functional connectivity patterns associated with worry. The analysis suggests that worry has a complex, yet distinct signature associated with resting state functional connectivity. Intra-connectivities and inter-connectivities of the DMN comprise the dominant contribution. The anterior cingulate, temporal lobe, and thalamus are heavily represented with overwhelmingly negative association with worry. The prefrontal regions are also strongly represented with a mix of positive and negative associations with worry. Identifying the most salient connections may be useful for targeted interventions for reducing morbidity associated with severe worry in older adults.

An Effect of Education on Memory-Encoding Activation in Subjective Cognitive Decline

BACKGROUND

Subjective cognitive decline (SCD) may be an early manifestation of pre-clinical Alzheimer's disease. Elevated amyloid-β (Aβ) is a correlate of SCD symptoms in some individuals. The underlying neural correlates of SCD symptoms and their association with Aβ is unknown. SCD is a heterogeneous condition, and cognitive reserve may explain individual differences in its neural correlates.

OBJECTIVE

We investigated the association between brain activation during memory encoding and SCD symptoms, as well as with Aβ, among older individuals. We also tested the moderating role of education (an index of cognitive reserve) on the associations.

METHODS

We measured brain activation during the "face-name" memory-encoding fMRI task and Aβ deposition with Pittsburgh Compound-B (PiB)-PET among cognitively normal older individuals (n = 63, mean age 73.1 ± 7.4 years). We tested associations between activation and SCD symptoms by self-report measures, Aβ, and interactions with education.

RESULTS

Activation was not directly associated with SCD symptoms or Aβ. However, education moderated the association between activation and SCD symptoms in the executive control network, salience network, and subcortical regions. Greater SCD symptoms were associated with greater activation in those with higher education, but with lower activation in those with lower education.

CONCLUSION

SCD symptoms were associated with different patterns of brain activation in the extended memory system depending on level of cognitive reserve. Greater SCD symptoms may represent a saturation of neural compensation in individuals with greater cognitive reserve, while it may reflect diminishing neural resources in individuals with lower cognitive reserve.

Effect of Experimental Manipulation of the Orbitofrontal Cortex on Short-Term Markers of Compulsive Behavior: A Theta Burst Stimulation Study

OBJECTIVE

Compulsive behaviors are a core feature of obsessive-compulsive spectrum disorders but appear across a broad spectrum of psychological conditions. It is thought that compulsions reflect a failure to override habitual behaviors "stamped in" through repeated practice and short-term distress reduction. Animal models suggest a possible causal role of the orbitofrontal cortex (OFC) in compulsive behaviors, but human studies have largely been limited by correlational designs. The goal of this study was to establish the first experimental evidence in humans for a mechanistic model in order to inform further experimental work and the eventual development of novel mechanistic treatments involving synergistic biological-behavioral pairings.

METHODS

After a baseline assessment, 69 individuals with compulsive behavior disorders were randomly assigned, in a double-blind, between-subjects design, to receive a single session of one of two active stimulation conditions targeting the left OFC: intermittent theta burst stimulation (iTBS), expected to increase OFC activity, or continuous TBS (cTBS), expected to decrease activity (both conditions, 600 pulses at 110% of target resting motor threshold). In both conditions, brain modulation was paired with a subsequent computer task providing practice in overriding a clinically relevant habit (an overlearned shock avoidance behavior), delivered during the expected window of OFC increase or decrease. Pre- and post-TBS functional MRI assessments were conducted of target engagement and compulsive behaviors performed in response to an idiographically designed stressful laboratory probe.

RESULTS

cTBS and iTBS modulated OFC activation in the expected directions. cTBS, relative to iTBS, exhibited a beneficial impact on acute laboratory assessments of compulsive behaviors 90 minutes after TBS. These acute behavioral effects persisted 1 week after cTBS.

CONCLUSIONS

Experimental modulation of the OFC, within the behavioral context of habit override training, affected short-term markers of compulsive behavior vulnerability. The findings help delineate a causal translational model, serving as an initial precursor to mechanistic intervention development.

Aging faster: worry and rumination in late life are associated with greater brain age

Older adults with anxiety have lower gray matter brain volume-a component of accelerated aging. We have previously validated a machine learning model to predict brain age, an estimate of an individual's age based on voxel-wise gray matter images. We investigated associations between brain age and anxiety, depression, stress, and emotion regulation. We recruited 78 participants (≥50 years) along a wide range of worry severity. We collected imaging data and computed voxel-wise gray matter images, which were input into an existing machine learning model to estimate brain age. We conducted a multivariable linear regression between brain age and age, sex, race, education, worry, anxiety, depression, rumination, neuroticism, stress, reappraisal, and suppression. We found that greater brain age was significantly associated with greater age, male sex, greater worry, greater rumination, and lower suppression. Male sex, worry, and rumination are associated with accelerated aging in late life and expressive suppression may have a protective effect. These results provide evidence for the transdiagnostic model of negative repetitive thoughts, which are associated with cognitive decline, amyloid, and tau.

Greater white matter hyperintensities and the association with executive function in suicide attempters with late-life depression

Late-life depression (LLD) is associated with greater risk of suicide and white matter hyperintensities (WMH), which are also found in suicide attempters regardless of age. Greater periventricular WMH are related to worse cognitive function. We investigated the spatial distribution of WMH in suicide attempters with LLD and its association with cognitive function. We recruited 114 participants with LLD (34 with history of suicide attempt and 80 without) and 47 older adult controls (individuals without LLD or history of suicide attempt). WMH were quantified by an automated segmentation algorithm and were classified into different regions. Suicide attempters with LLD had significantly higher global WMH (F3, 150 = 2.856, p = 0.039) and periventricular WMH (F3, 150 = 3.635, p = 0.014) compared to other groups. Suicide attempters with high WMH had significantly lower executive function, which could be an underlying mechanism for cognitive decline in older adults with suicidality.

Understanding the Neurocomputational Mechanisms of Antidepressant Placebo Effects

Over the last two decades, neuroscientists have used antidepressant placebo probes to examine the biological mechanisms implicated in antidepressant placebo effects. However, findings from these studies have not yet elucidated a model-based theory that would explain the mechanism through which antidepressant expectancies evolve to induce persistent mood changes. Emerging evidence suggests that antidepressant placebo effects may be informed by models of reinforcement learning (RL). Such that an individual's expectation of improvement is updated with the arrival of new sensory evidence, by incorporating a reward prediction error (RPE), which signals the mismatch between the expected (expected value) and perceived improvement. Consistent with this framework, neuroimaging studies of antidepressant placebo effects have demonstrated placebo-induced μ-opioid activation and increased blood-oxygen-level dependent (BOLD) responses in regions tracking expected values (e.g., ventromedial prefrontal cortex (vmPFC)) and RPEs (e.g., ventral striatum (VS)). In this study, we will demonstrate the causal contribution of reward learning signals (expected values and RPEs) to antidepressant placebo effects by experimentally manipulating expected values using transcranial magnetic stimulation (TMS) targeting the vmPFC and μ-opioid striatal RPE signal using pharmacological approaches. We hypothesized that antidepressant placebo expectancies are represented in the vmPFC (expected value) and updated by means of μ-opioid-modulated striatal learning signal. In a 3 × 3 factorial double-blind design, we will randomize 120 antidepressant-free individuals with depressive symptoms to one of three between-subject opioid conditions: the μ-opioid agonist buprenorphine, the μ-opioid antagonist naltrexone, or an inert pill. Within each arm, individuals will be assigned to receive three within-subject counterbalanced forms of TMS targeting the vmPFC-intermittent Theta Burst Stimulation (TBS) expected to potentiate the vmPFC, continuous TBS expected to de-potentiate the vmPFC, or sham TBS. These experimental manipulations will be used to modulate trial-by-trial reward learning signals and related brain activity during the Antidepressant Placebo functional MRI (fMRI) Task to address the following aims: (1) investigate the relationship between reward learning signals within the vmPFC-VS circuit and antidepressant placebo effects; (2) examine the causal contribution of vmPFC expected value computations to antidepressant placebo effects; and (3) investigate the causal contribution of μ-opioid-modulated striatal RPEs to antidepressant placebo effects. The proposed study will be the first to investigate the causal contribution of μ-opioid-modulated vmPFC-VS learning signals to antidepressant placebo responses, paving the way for developing novel treatments modulating learning processes and objective means of quantifying and potentially reducing placebo effects during drug development.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT04276259.

Regional Gray Matter Density Associated With Fast-Paced Walking in Older Adults: A Voxel-Based Morphometry Study

BACKGROUND

Walking speed during fast-paced walking task has been associated with cognitive function. It is unclear what underlying brain structures are related to fast-paced walking. We investigated the association of gray matter (GM) density with fast-paced walking speed and usual-paced walking speed.

METHODS

We collected data from 284 older adults from a subset of the Health, Aging, and Body composition study (mean age = 83 [SD = 2.8], 58% women, 41% black). Voxel-wise analyses on magnetic resonance imaging data identified regions of the brain where GM density was associated with fast-paced walking speed. We then extracted GM density for all identified regions and modeled the association with fast-paced walking speed after adjusting for demographic factors, clinical factors, and cognitive function. Analyses were repeated for usual-paced walking. Regions with beta coefficients ≥0.3 m/s were considered to be meaningfully correlated.

RESULTS

GM density of clusters from cortical regions in the right middle and superior frontal gyrus, right postcentral gyrus, and left superior temporal gyrus were positively correlated with fast-paced walking speed in adjusted models. Adjustment for cognitive function had little impact on the findings. Caudate was correlated with usual paced walking speed at coefficient ≥0.3 m/s after adjustment of demographic factors and clinical factors, but not after further adjustment of cognitive function.

CONCLUSIONS

Fast-paced walking speed was correlated with GM density of right middle and superior frontal gyrus, right postcentral gyrus, and left superior temporal gyrus, and could potentially provide evidence about subclinical structural change of brain related to aging.

Accelerated brain aging in chronic low back pain

Chronic low back pain (CLBP) is a leading cause of disability and is associated with neurodegenerative changes in brain structure. These changes lead to impairments in cognitive function and are consistent with those seen in aging, suggesting an accelerated aging pattern. In this study we assessed this using machine-learning estimated brain age (BA) as a holistic metric of morphometric changes associated with aging. Structural imaging data from 31 non-depressed CLBP patients and 32 healthy controls from the Pain and Interoception Imaging Network were included. Using our previously developed algorithm, we estimated BA per individual based on grey matter density. We then conducted multivariable linear modeling for effects of group, chronological age, and their interaction on BA. We also performed two voxel-wise analyses comparing grey matter density between CLBP and control individuals and the association between gray matter density and BA. There was an interaction between CLBP and greater chronological age on BA such that the discrepancy in BA between healthy and CLBP individuals was greater for older individuals. In CLBP individuals, BA was not associated with sex, current level of pain, duration of CLBP, or mild to moderate depressive symptoms. CLBP individuals had lower cerebellar grey matter density compared to healthy individuals. Brain age was associated with lower gray matter density in numerous brain regions. CLBP was associated with greater BA, which was more profound in later life. BA as a holistic metric was sensitive to differences in gray matter density in numerous regions which eluded direct comparison between groups.

Testing a new, intensified infusion-withdrawal protocol for urinary urgency provocation in brain-bladder studies

INTRODUCTION

The brain's role in bladder control has become an important area of study in the last 15 years. Typically, the brain's role in urinary urgency has been studied by repeated infusion and withdrawal of fluid, per catheter, to provoke urgency sensation during a whole brain magnetic resonance imaging (MRI) scan. Since this technique generally requires a large group size, we tested a more intense infusion-withdrawal protocol in an attempt to improve signal to noise ratio and repeatability of the signal which would, in turn, allow us to further probe subtypes of urgency urinary incontinence.

METHODS

A total of 12 women over the age of 60 were recruited to test a new "intense" infusion withdrawal protocol. They underwent this new protocol during a functional brain MRI scan. The primary outcome was comparison of activity within the insula, medial pre-frontal cortex and dorsal anterior cingulate cortex/supplementary motor area (dACC/SMA). Immediate test-retest repeatability was measured using intraclass correlation. Secondary exploratory evaluation of differences in the whole brain between protocols was conducted.

RESULTS

There was no significant difference in signal in any of the a priori regions of interest between protocols. Test-retest repeatability in the new protocol was poor compared to the original protocol, and variability was higher. Three participants were not able to tolerate the "intense" protocol.

CONCLUSION

The small improvement in signal to noise ratio of the new protocol was not sufficient to overcome the poorly tolerated intense filling protocol.

Resting state connectivity within the basal ganglia and gait speed in older adults with cerebral small vessel disease and locomotor risk factors

BACKGROUND AND AIM

The basal ganglia are critical for planned locomotion, but their role in age-related gait slowing is not well known. Spontaneous regional co-activation of brain activity at rest, known as resting state connectivity, is emerging as a biomarker of functional neural specialization of varying human processes, including gait. We hypothesized that greater connectivity amongst regions of the basal ganglia would be associated with faster gait speed in the elderly. We further investigated whether this association was similar in strength to that of other risk factors for gait slowing, specifically white matter hyperintensities (WMH).

METHODS

A cohort of 269 adults (79-90 years, 146 females, 164 White) were assessed for gait speed (m/sec) via stopwatch; brain activation during resting state functional magnetic resonance imaging, WMH, and gray matter volume (GMV) normalized by intracranial volume via 3T neuroimaging; and risk factors of poorer locomotion via clinical exams (body mass index (BMI), muscle strength, vision, musculoskeletal pain, cardiometabolic conditions, depressive symptoms, and cognitive function). To understand whether basal ganglia connectivity shows distinct clusters of connectivity, we conducted a k-means clustering analysis of regional co-activation among the substantia nigra, nucleus accumbens, subthalamic nucleus, putamen, pallidum, and caudate. We conducted two multivariable linear regression models: (1) with gait speed as the dependent variable and connectivity, demographics, WMH, GMV, and locomotor risk factors as independent variables and (2) with basal ganglia connectivity as the dependent variable and demographics, WMH, GMV, and locomotor risk factors as independent variables.

RESULTS

We identified two clusters of basal ganglia connectivity: high and low without a distinct spatial distribution allowing us to compute an average connectivity index of the entire basal ganglia regional connectivity (representing a continuous measure). Lower connectivity was associated with slower gait, independent of other locomotor risk factors, including WMH; the coefficient of this association was similar to those of other locomotor risk factors. Lower connectivity was significantly associated with lower BMI and greater WMH.

CONCLUSIONS

Lower resting state basal ganglia connectivity is associated with slower gait speed. Its contribution appears comparable to WMH and other locomotor risk factors. Future studies should assess whether promoting higher basal ganglia connectivity in older adults may reduce age-related gait slowing.

Resting-State Function Connectivity Associated With Being a "Morning-Type" Dementia Caregiver and Having Lower Depression Symptom Severity

OBJECTIVES

A lack of "morningness" predicts greater depression symptom severity over time, including in a vulnerable group of older adults: family dementia caregivers (dCGs). Evidence regarding the neurobiological basis of these correlations is needed to guide future research towards biomarker-informed detection and prevention approaches. We therefore primarily aimed to identify simple resting-state biomarkers that correlated with a lack of "morningness" in dCGs.

METHOD

We examined 54 dCGs (mean age = 70, range: 61-84; 70% female) of whom 40% were definite "morning types" according to Composite Scale of Morningness (CSM). Using a 7 Tesla resting-state sequence, we compared the functional connectivity of nodes in networks previously implicated in depression (fronto-parietal, default mode, limbic, and salience) between caregivers who were and were not "morning types."

RESULTS

Correcting for voxel-wise comparisons, "morning-type" dCGs had less amygdala-posterior cingulate connectivity (Cohen's d = -1.3), which statistically mediated ~32% of the association between the degree of "morningness" and lower depression severity. Post hoc analyses of CSM items found significant correlations, with both amygdala-posterior cingulate FC and depression severity, for 4/6 items pertaining to difficulty, 2/5 items pertaining to preference, and 0/2 items pertaining to typical patterns.

DISCUSSION

Prior research shows that amygdala-posterior cingulate connectivity increases when allocating attention to peripheral aspects of negative emotional stimuli. As such, difficulty with morning activation may relate to the ongoing direction of focus around distressing content; in contrast, morning activity participation may serve to limit focus on distress. Replication and experimental studies are required to confirm these associations and their modifiability.

Association between increased theta cordance and early response to ECT in late-life depression

OBJECTIVES

More than half of patients with major depression who do not respond to initial antidepressants become treatment resistant (TRD), and while electroconvulsive therapy (ECT) is effective, it involves anesthesia and other medical risks that are of concern in geriatric patients. Past studies have suggested that theta cordance (TC), a correlate of cerebral metabolism measured by electroencephalography, could guide treatment decisions related to patient selection and engagement of the therapeutic target.

METHODS/DESIGN

Eight patients with late-life treatment resistant depression (LL-TRD) underwent magnetoencephalography (MEG) at baseline and following seven sessions of ECT. We tested whether the mean and regional frontal cortex TC were able to differentiate early responders from nonresponders.

RESULTS

Five patients whose depression severity decreased by >30% after seven sessions were considered early responders. We found no baseline differences in mean frontal TC between early responders compared with nonresponders, but early responders exhibited a significant increase in TC following ECT. Further, we found that compared with nonresponders, early responders exhibited a greater change in TC specifically within the right prefrontal cortex.

CONCLUSIONS

These results support the hypothesis that increases in frontal TC are associated with antidepressant response. We expand on previous findings by showing that this change is specific to the right prefrontal cortex. Validation of this neural marker could contribute to improved ECT outcomes, by informing early clinical decisions about the acute efficacy of this treatment.

The effect of amyloid deposition on longitudinal resting-state functional connectivity in cognitively normal older adults

BACKGROUND

Pathological processes contributing to Alzheimer's disease begin decades prior to the onset of clinical symptoms. There is significant variation in cognitive changes in the presence of pathology, functional connectivity may be a marker of compensation to amyloid; however, this is not well understood.

METHODS

We recruited 64 cognitively normal older adults who underwent neuropsychological testing and biannual magnetic resonance imaging (MRI), amyloid imaging with Pittsburgh compound B (PiB)-PET, and glucose metabolism (FDG)-PET imaging for up to 6 years. Resting-state MRI was used to estimate connectivity of seven canonical neural networks using template-based rotation. Using voxel-wise paired t-tests, we identified neural networks that displayed significant changes in connectivity across time. We investigated associations among amyloid and longitudinal changes in connectivity and cognitive function by domains.

RESULTS

Left middle frontal gyrus connectivity within the memory encoding network increased over time, but the rate of change was lower with greater amyloid. This was no longer significant in an analysis where we limited the sample to only those with two time points. We found limited decline in cognitive domains overall. Greater functional connectivity was associated with better attention/processing speed and executive function (independent of time) in those with lower amyloid but was associated with worse function with greater amyloid.

CONCLUSIONS

Increased functional connectivity serves to preserve cognitive function in normal aging and may fail in the presence of pathology consistent with compensatory models.

An improved algorithm of white matter hyperintensity detection in elderly adults

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OASIS-AD is a method for automatic segmentation of white matter hyperintensities in older adults using structural brain MRIs.

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OASIS-AD is an approach evolved from OASIS, which was developed for automatic lesion segmentation in multiple sclerosis.

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OASIS-AD is a major refinement of OASIS that takes into account the specific challenges raised by white matter hyperintensities in Alzheimer’s disease.

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OASIS-AD combines three processing steps: 1) using an eroding procedure on the skull stripped mask; 2) adding a nearest neighbor feature construction approach; and 3) applying a Gaussian filter to refine segmentation results creating a novel process for WMH detection in aging population .

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OASIS-AD performs better than existing automatic white matter hyperintensity segmentation approaches.

Automated segmentation of the aging brain raises significant challenges because of the prevalence, extent, and heterogeneity of white matter hyperintensities. White matter hyperintensities can be frequently identified in magnetic resonance imaging (MRI) scans of older individuals and among those who have Alzheimer’s disease. We propose OASIS-AD, a method for automatic segmentation of white matter hyperintensities in older adults using structural brain MRIs. OASIS-AD is an approach evolved from OASIS, which was developed for automatic lesion segmentation in multiple sclerosis. OASIS-AD is a major refinement of OASIS that takes into account the specific challenges raised by white matter hyperintensities in Alzheimer’s disease. In particular, OASIS-AD combines three processing steps: 1) using an eroding procedure on the skull stripped mask; 2) adding a nearest neighbor feature construction approach; and 3) applying a Gaussian filter to refine segmentation results, creating a novel process for WMH detection in aging population. We show that OASIS-AD performs better than existing automatic white matter hyperintensity segmentation approaches.

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.

Relationships Between Executive Control Circuit Activity, Amyloid Burden, and Education in Cognitively Healthy Older Adults

INTRODUCTION

In cognitively healthy older adults, amyloid-beta (Aβ) burden is associated with greater activity on task-based functional magnetic resonance imaging. Higher levels of functional activation are associated with other factors along with amyloid and the authors investigated these relationships as well as how they relate to Aβ in cognitively healthy older adults.

METHODS

The authors recruited cognitive healthy older adults (N = 50) from the Pittsburgh community that underwent extensive cognitive batteries, activation during a working memory (digit symbol substitution task, DSST), positron emission tomography scan for Pittsburgh Compound B (PiB, measuring amyloid), and other demographic measures. The authors tested the association between DSST activation and global PiB, neurocognitive batteries, and education.

RESULTS

The authors found that the DSST robustly activated expected structures involved in working memory. The authors found that greater global Aβ deposition was associated with greater DSST activation in the right calcarine, precuneus, middle temporal as well as the left insula and inferior frontal gyrus. The authors also found that greater education was associated with lower DSST activation - however this was not significant after adjusting for Aβ.

DISCUSSION

Greater amyloid was associated with greater activation, which may represent compensatory activation. Greater education was associated with lower activation, which may represent more efficient activation (i.e., less activation for the same task). After adjusting for amyloid, education was not significantly associated with activation suggesting that during the preclinical stage amyloid is the primary determinant of activation. Further, activation was not associated with cognitive function. Compensatory activation in the preclinical stage may help maintain cognitive function.

Improving brain age prediction models: incorporation of amyloid status in Alzheimer's disease

Brain age prediction is a machine learning method that estimates an individual's chronological age from their neuroimaging scans. Brain age indicates whether an individual's brain appears "older" than age-matched healthy peers, suggesting that they may have experienced a higher cumulative exposure to brain insults or were more impacted by those pathological insults. However, contemporary brain age models include older participants with amyloid pathology in their training sets and thus may be confounded when studying Alzheimer's disease (AD). We showed that amyloid status is a critical feature for brain age prediction models. We trained a model on T1-weighted MRI images participants without amyloid pathology. MRI data were processed to estimate gray matter density voxel-wise, which were then used to predict chronological age. Our model performed accurately comparable to previous models. Notably, we demonstrated more significant differences between AD diagnostic groups than other models. In addition, our model was able to delineate significant differences in brain age relative to chronological age between cognitively normal individuals with and without amyloid. Incorporation of amyloid status in brain age prediction models ultimately improves the utility of brain age as a biomarker for AD.

When worry may be good for you: Worry severity and limbic-prefrontal functional connectivity in late-life generalized anxiety disorder

BACKGROUND

Late-life generalized anxiety disorder (GAD) is one of the most common anxiety disorders in older adults. However, its neural markers have received relatively little attention. In this study, we explored the association between worry severity and limbic-prefrontal connectivity during emotional reactivity in late-life GAD.

METHODS

We recruited 16 anxious (GAD) and 20 non-anxious (HC) older adults to perform the faces/shapes emotional reactivity task during functional magnetic resonance imaging (fMRI). We investigated the functional connectivity of both the amygdala and the bed nucleus of stria terminalis (BNST) with the prefrontal cortex (PFC) using generalized psychophysiological interaction (gPPI) analysis. We tested for (1) group differences in connectivity, (2) association between worry severity and connectivity, and (3) interaction between group and worry severity and its association with connectivity.

RESULTS

Amygdala-PFC and BNST-PFC functional connectivity were associated with worry severity in an inverse U-shape, and was independent of depression severity, global anxiety, neuroticism, and general cognitive function.

LIMITATIONS

Our limitations include slightly skewed PSWQ distributions, lack of non-anxious individuals with high worry, small sample size, and low depression comorbidity in a sample of late-life GAD that may not generalize to GAD in younger populations.

CONCLUSIONS

This suggests that moderate worry is associated with maximum engagement of the limbic-PFC connectivity, while severe worry is associated with failure of the limbic-PFC emotional regulation circuit. This may explain the aberrant and exaggerated responses to negative stimuli observed in participants with pathological worry.

Amyloid deposition is associated with different patterns of hippocampal connectivity in men versus women

Compared to men, women are disproportionally affected by Alzheimer's disease (AD) and have an accelerated trajectory of cognitive decline and disease progression. Neurobiological factors underlying gender differences in AD remain unclear. This study investigated brain beta-amyloid (Aβ)-related neural system differences in cognitively normal older men and women (N = 61; 41 females, 65-93 years old). We found that men and women showed different associations between Aβ load and hippocampal functional connectivity. During associative memory encoding, in men greater Aβ burden was accompanied by greater hippocampus-prefrontal connectivity (i.e., more synchronized activities), whereas in women hippocampal connectivity did not vary by Aβ burden. For resting-state data, the interaction of gender × Aβ on hippocampal connectivity did not survive multiple comparison in the whole-brain analyses. In the region of interest-based analyses, resting-state hippocampal-prefrontal connectivity was positively correlated with Aβ load in men and was negatively correlated with Aβ load in women. The observed Aβ-related neural differences may explain the accelerated trajectory of cognitive decline and AD progression in women.

Neural architecture supporting active emotion processing in children: A multivariate approach

BACKGROUND

Adaptive emotion processing is critical for nearly all aspects of social and emotional functioning. There are distinct developmental trajectories associated with improved emotion processing, with a protracted developmental course for negative or complex emotions. The specific changes in neural circuitry that underlie this development, however are still scarcely understood. We employed a multivariate approach in order to elucidate distinctions in complex, naturalistic emotion processing between childhood and adulthood.

METHOD

Twenty-one adults (M±SD age = 26.57 ± 5.08 years) and thirty children (age = 7.75 ± 1.80 years) completed a free-viewing movie task during BOLD fMRI scanning. This task was designed to assess naturalistic processing of movie clips portraying positive, negative, and neutral emotions. Multivariate support vector machines (SVM) were trained to classify age groups based on neural activation during the task.

RESULTS

SVMs were able to successfully classify condition (positive, negative, and neutral) across all participants with high accuracy (61.44%). SVMs could successfully distinguish adults and children within each condition (ps < 0.05). Regions that informed the age group SVMs were associated with sensory and socio-emotional processing (inferior parietal lobule), emotion regulation (inferior frontal gyrus), and sensory regions of the temporal and occipital lobes.

CONCLUSIONS

These results point to distributed differences in activation between childhood and adulthood unique to each emotional condition. In the negative condition specifically, there is evidence for a shift in engagement from regions of sensory and socio-emotional integration to emotion regulation regions between children and adults. These results provide insight into circuitry contributing to maturation of emotional processing across development.

Low-dose augmentation with buprenorphine increases emotional reactivity but not reward activity in treatment resistant mid- and late-life depression

Buprenorphine is currently being studied for treatment-resistant depression because of its rapid effect, relative safety, and unique pharmacodynamics. To understand the neural impact of buprenorphine in depression, we examined acute limbic and reward circuit changes during an intervention with low-dose buprenorphine augmentation pharmacotherapy. Mid and late-life adults with major depression (N = 31) who did not completely respond to an adequate trial of venlafaxine were randomized to augmentation with low-dose buprenorphine or matching placebo. We investigated early neural changes using functional magnetic resonance imaging (fMRI) from pre-randomization to 3 weeks using both an emotional reactivity task and a gambling task. We tested if: 1) there were significant neural changes acutely per intervention group, and 2) if acute neural changes were associated with depressive symptom change over 8 weeks using both the total score and the dysphoria subscale of the Montgomery Asberg Depression Rating Scale. Participants in both the buprenorphine and placebo groups showed similar changes in depressive symptoms. Neither the emotional reactivity nor gambling task resulted in significant neural activation changes from pre-randomization to 3-weeks. In both groups, increases in rostral anterior cingulate (rACC) and ventromedial prefrontal cortex (vmPFC) activation during the emotional reactivity task were associated with overall symptom improvement. In the buprenorphine but not the placebo group, increased activation in left anterior insula (aINS) and bilateral middle frontal gyrus (MFG) was associated with improvement on the dysphoria subscale. Activation changes in the reward task were not associated with buprenorphine. This is the first study to show an association between acute neural changes during emotion reactivity and changes in depression severity with buprenorphine treatment.

Impact of acute sleep restriction on cerebral glucose metabolism during recovery non-rapid eye movement sleep among individuals with primary insomnia and good sleeper controls

BACKGROUND

Restricting time in bed improves insomnia symptoms, but the neural mechanisms for this effect are unknown. Total and partial acute sleep restriction may be useful paradigms for elucidating these effects. We examined the impact of acute sleep restriction on cerebral glucose metabolism during non-rapid eye movement (NREM) sleep in individuals with primary insomnia (n = 17) and good sleep (n = 19).

METHODS

Participants underwent [¹⁸F]fluorodeoxyglucose positron emission tomography scans during baseline and recovery NREM sleep following one night of partial or total sleep restriction. We compared group differences in baseline-recovery changes, as well as main effects of group and condition (baseline vs. recovery NREM sleep), for relative regional cerebral metabolic rate for glucose (rCMR_glc), whole-brain glucose metabolism, and sleep quality.

RESULTS

Relative rCMR_glc was significantly lower during recovery NREM sleep compared to baseline in the left frontoparietal cortex, medial frontal cortex, posterior cingulate cortex, and thalamus, with no significant group differences. Good sleepers, but not insomnia patients, had lower whole-brain glucose metabolism during recovery NREM sleep compared to baseline. Acute sleep restriction improved sleep quality in individual with insomnia. Subgroup analyses including only participants who underwent partial sleep restriction yielded the same pattern of findings.

CONCLUSION

Individuals with insomnia and good sleepers showed similar relative rCMR_glc responses to acute sleep restriction. Brain regions showing the greatest baseline-recovery changes in both groups included regions previously shown to have smaller sleep-wake differences in patients with primary insomnia. Acute sleep restriction, and by extension sleep restriction therapy, may impact regional metabolic alterations that characterize insomnia.

Trajectories in Cerebral Blood Flow Following Antidepressant Treatment in Late-Life Depression: Support for the Vascular Depression Hypothesis

OBJECTIVE

Studies have identified longitudinally that there exists an association between depression, cerebral blood flow (CBF), and white matter hyperintensities that are thought to be due to vascular pathologies in the brain. However, the changes in CBF, a measure that reflects cerebrovascular integrity, following pharmacotherapy are not well understood. In this study, we investigated the dynamic CBF changes over the course of antidepressant treatment and the association of these changes with depressive symptoms.

METHODS

We used pseudocontinuous arterial spin labeling to investigate CBF changes in a sample of older patients (≥ 50 years of age; N = 46; 29 female) with a DSM-IV diagnosis of major depressive disorder. Participants had 5 magnetic resonance imaging scans (at baseline, the day after receiving a placebo, the day after receiving a first dose of venlafaxine, a week after starting venlafaxine treatment, and at the end of trial [12 weeks]). Montgomery-Asberg Depression Rating Scale (MADRS) was used to evaluate depression severity and treatment outcome. We investigated the association between changes in depression severity with changes in voxel-wise CBF while adjusting for potential confounding factors.

RESULTS

Increased CBF in the middle and posterior cingulate between baseline and end of treatment was significantly associated with percent decrease in MADRS score, independent of sex and Mini-Mental State Examination score (5,000 permutations, cluster forming threshold P < .005, family-wise error P < .05). No significant effects were detected between baseline and other scans (ie, placebo, acute [single dose], or subacute [after a week]).

CONCLUSIONS

Regional CBF increases were associated with decreases in depressive symptoms. This observation is consistent with the vascular depression hypothesis in late-life depression.

TRIAL REGISTRATION

ClinicalTrials.gov identifiers: NCT00892047 and NCT01124188.

Functional connectivity of the brain in older women with urgency urinary incontinence

BACKGROUND

The brain's role in continence is critical but poorly understood. Although regions activated during bladder stimulation have been identified, little is known about the interaction between regions. In this secondary analysis we evaluate resting state and effective connectivity in older women treated for urgency urinary incontinence (UUI).

METHOD

54 women ≥60 years old with UUI and 10 continent women underwent fMRI scanning during provocation of urinary urgency, both before and after therapy. Response was defined by >50% reduction in leaks on bladder diary. Regions of interest (RoIs) were selected a priori: right insula, medial prefrontal cortex, and dorsal anterior cingulate cortex. Generalized psycho-physiological interaction (gPPI) was used to calculate "effective connectivity" between RoIs during urgency. We performed a one-way ANOVA pre-treatment between groups (continent/responders/non-responders), as well as a two-way mixed ANOVA between group and time (responders/non-responders; pre-/post-therapy) using false discovery rate (FDR) correction. Principal component analysis was used to assess the variance within RoIs. Exploratory voxel-wise connectivity analyses were conducted between each RoI and the rest of the brain.

RESULTS

RoI-RoI connectivity analysis showed connectivity differences between controls, responders, and non-responders, although statistical significance was lost after extensive correction. Principal component analysis confirmed appropriate RoI selection. Voxel-wise analyses showed that connectivity in responders became more like that of controls after therapy (cluster-wise correction P < 0.05). In non-responders, no consistent changes were seen.

CONCLUSION

These data support the postulate that responders and non-responders to therapy may represent different subsets of UUI, one with more of a central etiology, and one without.

Acute trajectories of neural activation predict remission to pharmacotherapy in late-life depression

Pharmacological treatment of major depressive disorder (MDD) typically involves a lengthy trial and error process to identify an effective intervention. This lengthy period prolongs suffering and worsens all-cause mortality, including from suicide, and is typically longer in late-life depression (LLD). Our group has recently demonstrated that during an open-label venlafaxine (serotonin-norepinephrine reuptake inhibitor) trial, significant changes in functional resting state connectivity occurred following a single dose of treatment, which persisted until the end of the trial. In this work, we propose an analysis framework to translate these perturbations in functional networks into predictors of clinical remission. Participants with LLD (N = 49) completed 12-weeks of treatment with venlafaxine and underwent functional magnetic resonance imaging (fMRI) at baseline and a day following a single dose of venlafaxine. Data was collected at rest as well as during an emotion reactivity task and an emotion regulation task. Remission was defined as a Montgomery-Asberg Depression Rating Scale (MADRS) ≤10 for two weeks. We computed eigenvector centrality (whole brain connectivity) and activation during the emotion regulation and emotion reactivity tasks. We employed principal components analysis, Tikhonov-regularized logistic classification, and least angle regression feature selection to predict remission by the end of the 12-week trial. We utilized ten-fold cross-validation and Receiver Operator Curves (ROC) curve analysis. To determine task-region pairs that significantly contributed to the algorithm's ability to predict remission, we used permutation testing. Using the fMRI data at both baseline and after the first dose of treatment yielded a sensitivity of 72% and a specificity of 68% (AUC = 0.77), a 15% increase in accuracy over baseline MADRS. In general, the accuracy at baseline was further improved by using the change in activation following a single dose. Activation of the frontal cortex, hippocampus, parahippocampus, caudate, thalamus, medial temporal cortex, middle cingulate, and visual cortex predicted treatment remission. Acute, dynamic trajectories of functional imaging metrics in response to a pharmacological intervention are a valuable tool for predicting treatment response in late-life depression and elucidating the mechanism of pharmacological therapies in the context of the brain's functional architecture.

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Neural activation changes after a single dose of antidepressants have been observed.

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Patients with late-life depression were treated with an antidepressant for 12 weeks.

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Neuroimaging data was recorded pre-treatment and after a single dose.

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Pre-treatment neuroimaging predicted remission at the end of the trial.

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Neuroimaging after a single dose improved prediction and may guide treatment.

Association of Hippocampal Substructure Resting-State Functional Connectivity with Memory Performance in Older Adults

OBJECTIVES

Hippocampal hyperactivation marks preclinical dementia pathophysiology, potentially due to differences in the connectivity of specific medial temporal lobe structures. Our aims were to characterize the resting-state functional connectivity of medial temporal lobe sub-structures in older adults, and evaluate whether specific substructural (rather than global) functional connectivity relates to memory function.

METHODS

In 15 adults (mean age: 69 years), we evaluated the resting state functional connectivity of medial temporal lobe substructures: dentate/Cornu Ammonis (CA) 4, CA1, CA2/3, subiculum, the molecular layer, entorhinal cortex, and parahippocampus. We used 7-Tesla susceptibility weighted imaging and magnetization-prepared rapid gradient echo sequences to segment substructures of the hippocampus, which were used as structural seeds for examining functional connectivity in a resting BOLD sequence. We then assessed correlations between functional connectivity with memory performance (short and long delay free recall on the California Verbal Learning Test [CVLT]).

RESULTS

All the seed regions had significant connectivity within the temporal lobe (including the fusiform, temporal, and lingual gyri). The left CA1 was the only seed with significant functional connectivity to the amygdala. The left entorhinal cortex was the only seed to have significant functional connectivity with frontal cortex (anterior cingulate and superior frontal gyrus). Only higher left dentate-left lingual connectivity was associated with poorer CVLT performance (Spearman r = -0.81, p = 0.0003, Benjamini-Hochberg false discovery rate: 0.01) after multiple comparison correction.

CONCLUSIONS

Rather than global hyper-connectivity of the medial temporal lobe, left dentate-lingual connectivity may provide a specific assay of medial temporal lobe hyper-connectivity relevant to memory in aging.

Insulin sensitivity predicts brain network connectivity following a meal

There is converging evidence that insulin plays a role in food-reward signaling in the brain and has effects on enhancing cognition. Little is known about how these effects are altered in individuals with insulin resistance. The present study was designed to identify the relationships between insulin resistance and functional brain connectivity following a meal. Eighteen healthy adults (7 male, 11 female, age: 41-57 years-old) completed a frequently-sampled intravenous glucose tolerance test to quantify insulin resistance. On separate days at least one week apart, a resting state functional magnetic resonance imaging scan was performed: once after a mixed-meal and once after a 12-h fast. Seed-based resting state connectivity of the caudate nucleus and eigenvector centrality were used to identify relationships between insulin resistance and functional brain connectivity. Individuals with greater insulin resistance displayed stronger connectivity within reward networks following a meal suggesting insulin was less able to suppress reward. Insulin resistance was negatively associated with eigenvector centrality in the dorsal anterior cingulate cortex following a meal. These data suggest that individuals with less sensitivity to insulin may fail to shift brain networks away from reward and toward cognitive control following a meal. This altered feedback loop could promote overeating and obesity.

Association between change in brain gray matter volume, cognition, and depression severity: Pre- and post- antidepressant pharmacotherapy for late-life depression

Late-life depression (LLD) is associated with cognitive impairments and reduced gray matter volume (GMV); however the mechanisms underlying this association are not well understood. The goal of this study was to characterize changes in depression severity, cognitive function, and brain structure associated with pharmacologic antidepressant treatment for LLD. We administered a detailed neurocognitive battery and conducted structural magnetic resonance imaging (MRI) on 26 individuals with LLD, pre-/post-a 12-week treatment trial with venlafaxine. After calculating changes in cognitive performance, GMV, and depression severity, we calculated Pearson's correlations, performed permutation testing, and false discovery rate correction. We found that loss of GMV over 12 weeks in the superior orbital frontal gyrus was associated with less improvement in depression severity and that increased GMV in the same was associated with greater improvement in depression severity. We detected no associations between changes in cognitive performance and improvements in either depressive symptoms or changes in GMV.