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 Aß 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 Aß and glucose metabolism, respectively). We conducted voxel-wise paired t-test on PiB (left vs. right hemispheres) to identify regions that differ in Aß 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.

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.

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.

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.

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.

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

BACKGROUND: Amyloid-ß (Aß) 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 Aß, 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, Aß, 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.

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.

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.

"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.

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.

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.

Independent replication of advanced brain age in mild cognitive impairment and dementia: detection of future cognitive dysfunction.

We previously developed a novel machine-learning-based brain age model that was sensitive to amyloid. We aimed to independently validate it and to demonstrate its utility using independent clinical data. We recruited 650 participants from South Korean memory clinics to undergo magnetic resonance imaging and clinical assessments. We employed a pretrained brain age model that used data from an independent set of largely Caucasian individuals (n = 757) who had no or relatively low levels of amyloid as confirmed by positron emission tomography (PET). We investigated the association between brain age residual and cognitive decline. We found that our pretrained brain age model was able to reliably estimate brain age (mean absolute error = 5.68 years, r(650) = 0.47, age range = 49-89 year) in the sample with 71 participants with subjective cognitive decline (SCD), 375 with mild cognitive impairment (MCI), and 204 with dementia. Greater brain age was associated with greater amyloid and worse cognitive function [Odds Ratio, (95% Confidence Interval {CI}): 1.28 (1.06-1.55), p = 0.030 for amyloid PET positivity; 2.52 (1.76-3.61), p < 0.001 for dementia]. Baseline brain age residual was predictive of future cognitive worsening even after adjusting for apolipoprotein E e4 and amyloid status [Hazard Ratio, (95% CI): 1.94 (1.33-2.81), p = 0.001 for total 336 follow-up sample; 2.31 (1.44-3.71), p = 0.001 for 284 subsample with baseline Clinical Dementia Rating ≤ 0.5; 2.40 (1.43-4.03), p = 0.001 for 240 subsample with baseline SCD or MCI]. In independent data set, these results replicate our previous findings using this model, which was able to delineate significant differences in brain age according to the diagnostic stages of dementia as well as amyloid deposition status. Brain age models may offer benefits in discriminating and tracking cognitive impairment in older adults.

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.

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.