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.

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.

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.

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.

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.

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.

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.

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.

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.

Midazolam and Ketamine Produce Distinct Neural Changes in Memory, Pain, and Fear Networks during Pain.

BACKGROUND: Despite the well-known clinical effects of midazolam and ketamine, including sedation and memory impairment, the neural mechanisms of these distinct drugs in humans are incompletely understood. The authors hypothesized that both drugs would decrease recollection memory, task-related brain activity, and long-range connectivity between components of the brain systems for memory encoding, pain processing, and fear learning. METHODS: In this randomized within-subject crossover study of 26 healthy adults, the authors used behavioral measures and functional magnetic resonance imaging to study these two anesthetics, at sedative doses, in an experimental memory paradigm using periodic pain. The primary outcome, recollection memory performance, was quantified with d' (a difference of z scores between successful recognition versus false identifications). Secondary outcomes were familiarity memory performance, serial task response times, task-related brain responses, and underlying brain connectivity from 17 preselected anatomical seed regions. All measures were determined under saline and steady-state concentrations of the drugs. RESULTS: Recollection memory was reduced under midazolam (median [95% CI], d' = 0.73 [0.43 to 1.02]) compared with saline (d' = 1.78 [1.61 to 1.96]) and ketamine (d' = 1.55 [1.12 to 1.97]; P < 0.0001). Task-related brain activity was detected under saline in areas involved in memory, pain, and fear, particularly the hippocampus, insula, and amygdala. Compared with saline, midazolam increased functional connectivity to 20 brain areas and decreased to 8, from seed regions in the precuneus, posterior cingulate, and left insula. Compared with saline, ketamine decreased connectivity to 17 brain areas and increased to 2, from 8 seed regions including the hippocampus, parahippocampus, amygdala, and anterior and primary somatosensory cortex. CONCLUSIONS: Painful stimulation during light sedation with midazolam, but not ketamine, can be accompanied by increased coherence in brain connectivity, even though details are less likely to be recollected as explicit memories.

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.

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.

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 ±â€¯5.08 years) and thirty children (age = 7.75 ±â€¯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.

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 (Aß) 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 Aß 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 Aß 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 Aß. 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.

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 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.