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INTRODUCTION: Compared to males, females have an accelerated trajectory of cognitive decline in Alzheimer's disease (AD). The neurobiological factors underlying the more rapid cognitive decline in AD in females remain unclear. This study explored how sex‐dependent alterations in hippocampal connectivity over 2 years are associated with cerebrovascular and amyloid pathologies in normal aging. METHODS: Thirty‐three females and 21 males 65 to 93 years of age with no cognitive impairment performed a face‐name associative memory functional magnetic resonance imaging (fMRI) task with a 2‐year follow‐up. We acquired baseline carbon 11‐labeled Pittsburgh compound B ([11C]PiB) positron emission tomography (PET) and T2‐weighted fluid‐attenuated inversion recovery (T2‐FLAIR) MRI to quantify amyloid β (Aβ) burden and white matter hyperintensity (WMH) volume, respectively. RESULTS: Males had increased hippocampal‐prefrontal connectivity over 2 years, associated with greater Aβ burden. Females had increased bilateral hippocampal functional connectivity, associated with greater WMH volume. DISCUSSION: These findings suggest sex‐dependent compensatory mechanisms in the memory network in the presence of cerebrovascular and AD pathologies and may explain the accelerated trajectory of cognitive decline in females. [ABSTRACT FROM AUTHOR]

Introduction: Carotid atherosclerosis may be associated with brain white matter hyperintensities (WMH). Few studies consider women at midlife, a critical time for women's cardiovascular and brain health. We tested the hypothesis that higher carotid intima media thickness (IMT) would be associated with greater WMH volume (WMHV) among midlife women. We explored interactions by apolipoprotein E (APOE) ε4 status. Methods: Two hundred thirty‐nine women aged 45 to 67 underwent carotid artery ultrasound, phlebotomy, and magnetic resonance imaging (MRI). One hundred seventy participants had undergone an ultrasound 5 years earlier. Results: Higher IMT was associated with greater whole brain (B[standard error (SE)] = 0.77 [.31], P = 0.01; multivariable) and periventricular (B[SE] = 0.80 [.30], P = 0.008; multivariable) WMHV. Associations were observed for IMT assessed contemporaneously with the MRI and 5 years prior to the MRI. Associations were strongest for APOE ε4–positive women. Discussion: Among midlife women, higher IMT was associated with greater WMHV. Vascular risk is critical to midlife brain health, particularly for APOE ε4–positive women. [ABSTRACT FROM AUTHOR]

Background: Emerging evidence indicates that COVID‐19 can negatively impact patient's brain health (Douaud et al., 2022) (Cecchetti et al., 2022). Common clinical symptoms include brain fog, headaches, difficulty concentrating, and loss of sense of smell or taste. Some studies suggest that SARS‐CoV‐2 infection can damage the blood brain barrier either directly or through immune‐inflammatory mechanisms (Zhang, et al. 2021). White matter hyperintensities (WMH) are imaging biomarkers of brain vascular or inflammatory injury. We investigated the association between severity of COVID‐19 infection and burden of white matter hyperintensity volumes within a diverse multi‐nation, multi‐racial cohort using 7 Tesla (7T) MRI that can detect more subtle injury than conventional 1.5 or 3T MRI. Method: Participants were recruited at 4 sites: Pittsburgh, San Antonio and Houston, USA, and Nottingham, UK. To date, we have scanned and included the following participants in our analysis (Table 1). Detailed cognitive, neurological, mood and functional assessments and high‐resolution MRI scans were collected. Subsequent WMH segmentation was performed using our in‐house built deep learning based model (Figure 1). All segmentations were visually inspected and manually corrected before statistical analysis. Normalized WMH is calculated as a ratio of the WMH volume and the intracranial volume (WMH/ICV). Imaging data for an additional 36 age‐matched controls were retrieved from the 7 Tesla Bioengineering Research Program (7TBRP) imaging bank at Pittsburgh. Result: Figure 1 shows the WMH segmentation outputs from our deep learning based model on images acquired at the 3 sites. Our Linear regression models along with our non‐parametric Kruskal‐Wallis test result suggests that compared to mild COVID cases and healthy control, COVID infected individuals that were ICU admitted show elevated WMH burden (Figure 2). Conclusion: Our results demonstrate that white matter hyperintensity volumes were higher among patients who had severe acute COVID infection that required ICU admission, compared to healthy age‐matched controls. In contrast, no difference in white matter burden was observed in patients with mild COVID infection compared to healthy controls. Additional data (both cross‐sectional and longitudinal), including more sensitive MRI measures is being collected to define the full spectrum of brain injury associated with sequelae of COVID infection. [ABSTRACT FROM AUTHOR]

Background: Functional MRI (fMRI) studies have associated impaired memory networks with increase in AD pathology. Recently, cross‐sectional analyses found b‐amyloid (Aβ) deposition associated with different patterns of hippocampal connectivity in a memory task based on sex and white matter hyperintensity volume (WMHV). However, cross‐sectional studies don't provide insight into the driving mechanisms of network change. In this longitudinal study, we identify risk factors based on sex that are associated with memory network connectivity changes. Method: Our study included 54 cognitively normal older adults (N = 34 female, mean age 74.6 years) with MRI scans on average 2.43 (SD 0.82) years apart. T1w, T2‐FLAIR MRI, and PiB PET were collected to quantify cortical volume, WMHV and Aβ deposition, respectively. Task fMRI was collected while participants performed face‐name associative memory tasks. Left and right hippocampus seeds were used to estimate functional connectivity between hippocampus and voxels in the brain. Second‐level analyses were performed to determine regions of interest (ROI) with significant differences in sex by time interaction (p<0.001). The mean beta values were extracted from the significant ROIs for post‐hoc analysis where we performed multivariate linear regression analyses to find correlations with connectivity change (follow‐up minus baseline). Result: Three ROIs presented significant sex by time interactions: left‐right hippocampus, hippocampus‐anterior cingulate cortex (ACC), and hippocampus‐medial frontal gyrus. The change in left‐right hippocampus connectivity increased for women and decreased for men (Fig.1). For the other ROIs, connectivity increased for men and decreased for women (Fig.2). Left‐right hippocampal connectivity change had a significant sex‐WMHV interaction effect (p<0.01), where only women had a positive association between connectivity change and baseline WMHV. Hippocampus‐ACC connectivity change had a significant sex‐Aβ interaction (p<0.01), with greater baseline Aβ associated with increased connectivity change for men and decreased for women. Conclusion: We observed sex‐differences in risk architecture for altered hippocampal connectivity. In the presence of vascular pathology and Aβ, women appear to experience local hippocampal connectivity and decrease hippocampal‐frontal connectivity. Meanwhile, men experienced hippocampal‐frontal connectivity with increased Aβ burden. Characterizing these sex differences in memory network alterations can help guide the development of sex‐specific prevention and treatment strategies. [ABSTRACT FROM AUTHOR]

• What is the primary question addressed by this study? We investigated whether the presence of small vessel disease (SVD) (measured as significant WMH burden) altered the associations between brain amyloid-beta (Aβ) and hippocampal functional connectivity during associative encoding in cognitively normal older adults. • What is the main finding of this study? In older adults with significant WMH burden (WMH+), greater Aβ burden was associated with a more localized pattern of hippocampal-medial temporal lobe (MTL) hyperconnectivity, but not in individuals with minimum WMH burden (WMH-). This local hippocampal-MTL hyperconnectivity is associated with local MTL atrophy. • What is the meaning of the finding? These observations support a hippocampal excitotoxicity model linking SVD to neurodegeneration in pre-clinical AD. This may explain how SVD may accelerate the progression from Aβ positivity to neurodegeneration, and subsequent AD. Small Vessel Disease (SVD) is known to be associated with higher AD risk, but its relationship to amyloidosis in the progression of AD is unclear. In this cross-sectional study of cognitively normal older adults, we explored the interactive effects of SVD and amyloid-beta (Aβ) pathology on hippocampal functional connectivity during an associative encoding task and on hippocampal volume. This study included 61 cognitively normal older adults (age range: 65–93 years, age mean ± standard deviation: 75.8 ± 6.4, 41 [67.2%] female). PiB PET, T2-weighted FLAIR, T1-weighted and face-name fMRI images were acquired on each participant to evaluate brain Aβ, white matter hyperintensities (WMH+/- status), gray matter density, and hippocampal functional connectivity. We found that, in WMH (+) older adults greater Aβ burden was associated with greater hippocampal local connectivity (i.e., hippocampal-parahippocampal connectivity) and lower gray matter density in medial temporal lobe (MTL), whereas in WMH (-) older adults greater Aβ burden was associated with greater hippocampal distal connectivity (i.e., hippocampal-prefrontal connectivity) and no changes in MTL gray matter density. Moreover, greater hippocampal local connectivity was associated with MTL atrophy. These observations support a hippocampal excitotoxicity model linking SVD to neurodegeneration in preclinical AD. This may explain how SVD may accelerate the progression from Aβ positivity to neurodegeneration, and subsequent AD. [ABSTRACT FROM AUTHOR]

Background: APOE4 genotype is a stronger risk factor for Alzheimer's disease (AD) in women than men, and its influence on memory and AD biomarkers differs by disease stage. Among cognitively normal older APOE4 carriers, APOE4 status influences memory similarly in males and females but adversely influences hippocampal volume in males. The effect of APOE4 status on regional brain volumes earlier in life, and in relation to memory, are less well understood. We examined whether associations between verbal memory performance and regional brain volumes differed by APOE4 status in cognitively normal midlife women. We hypothesized that APOE4 carriers would show weaker associations between memory performance and brain volumes than non‐carriers, particularly in the temporal lobe. Method: Participants were enrolled in MsBrain, a cohort study of midlife women. Verbal memory was assessed with the California Verbal Learning Test (CVLT‐II). Cortical thickness was measured and segmented by FreeSurfer using individual T1w MPRAGE images. Multiple regressions were conducted to determine associations between memory (learning, free recall) and regional brain volumes by APOE4 status (carriers versus non‐carriers), controlling for age, education, and race. Result: In 148 cognitively normal postmenopausal women (mean age = 59.17 years, 84.4% white, n = 37 APOE4 carriers), APOE4 status had no main effect on CVLT‐II measures or brain volumes, except the volume of the left supramarginal gyrus. However, APOE4 status modified the magnitude of association between verbal memory and brain volumes, specifically the association between: a) verbal learning and volume in the left caudal middle frontal gyrus (CMFG), left isthmus cingulate gyrus, left parahippocampal gyrus, left insula, right precuneus, right lateral orbitofrontal gyrus (LOG), and right temporal pole (TP); and b) free recall and volume in the left CMFG, right LOG, right posterior cingulate gyrus, and right TP. The direction of the associations between verbal memory and brain volumes was positive in non‐carriers and negative in carriers. Conclusion: In cognitively normal midlife women, APOE4 carrier status may influence the extent to which the hippocampal, temporal, and frontal lobe structures support verbal memory performance. This subtle effect may emerge before the main effect of this genetic risk factor on brain volume and memory. [ABSTRACT FROM AUTHOR]

Background: Late‐life depression (LLD) has been consistently linked to an increased risk of dementia, with studies showing that older adults with depression have a two fold risk of developing dementia. Dementia has proven difficult to treat, yet depression has several viable treatment options, particularly antidepressants. However, the efficacy of antidepressants in LLD has proven modest as antidepressants typically achieve around a 50% remission rate and only after 4‐6 weeks of treatment. In this analysis, we investigate the effectiveness of combining fMRI data with deep learning for predicting antidepressant driven depression remission. Method: In two LLD studies using venlafaxine (n = 51) and escitalopram or levomilnacipran (n = 29), resting state fMRI scans were collected at baseline and at day one of antidepressants. Region‐to‐region functional connectivity (FC) was calculated for each scan using the Shen50 atlas, and differential connectivity (DC) was calculated to compare baseline and day 1 FC. Clinical factors including age, race, education and cumulative illness burden and DC were used as input to a semi‐supervised variational autoencoder (VAE) to predict remission status at treatment end (Fig.1). Remission was encoded as a binary variable, defined as a final MADRS score of 10 or less after 12 weeks of treatment and subject to blinded clinician assessment. Monte Carlo cross‐validation over 30 repetitions was used to evaluate the model performance with 10% of the data held out for testing. The VAE was compared to a random forest classifier with the same cross validation methods using the area under the curve (AUC). Result: The VAE achieved an average mean‐squared error of.005 and AUC of 0.87 on a held out test set during cross validation. The VAE outperformed the random forest classifier which achieved an average AUC of 0.68. Conclusion: The VAE using DC in fMRI scans between baseline and day one shows the potential in accurately identifying responders to antidepressants as early as in one day. Our results show that acute changes to functional networks triggered by a single dose of antidepressants are promising as a means to improve patient outcomes. These results can contribute to optimizing treatment for LLD in the future. [ABSTRACT FROM AUTHOR]

Background: During the menopause transition, levels of estradiol (E2) ecline. Although these changes are likely key determinants of cognition and brain structure during the menopause transition, how they are related to brain volume in women at elevated risk of Alzheimer's disease (AD) is not known. We predict associations of endogenous E1 and E2 levels to regional brain volumes will depend on APOE4 carrier status, such that the associations between lower levels of E1 and E2 and lower regional brain volumes will be more positive among APOE4 carriers. Methods: Participants were enrolled in MsBrain, a cohort study of postmenopausal women (n = 191, mean age 59.4 +/‐ 3.4 years, 45 APOE4 carriers, 84.3% white). Serum E1 and E2 were assessed using liquid chromatography‐tandem mass spectrometry. Cortical volume was measured and segmented by FreeSurfer software using individual T1w MPRAGE images. Cross‐sectional associations of interest were analyzed with APOE4 genotype (carrier versus noncarrier; excluding APOE2)ormone levels, and their interaction, as predictors and regional brain volumes (33 regions per hemisphere) as outcome measures using lme4 Package in R. Models controlled for, years of education, and body mass index. Results: Neither APOE4 carrier status nor hormone levels were associated with brain volumes. However, significant interactions were observed between APOE4 carrier status and E2 levels in relation to volume of the right (p<.05) and left isthmus cingulate (p<.01), right and left middle temporal lobe (p<.05), and the left posterior cingulate (p<.05), such that the positive association between E2 and regional brain volumes was more positive among APOE4 carriers (Figure 1). Further, there was a significant interaction between APOE4 carrier status and E1 levels in relation to volumes of the right and left inferior parietal lobe (p<.05), right (p<.05) and left isthmus cingulate (p<.05), left cuneus (p<.05), left precuneus (p<.05), and left lingual gyrus (p<.05)(Figure 2). Conclusion: Although some of these findings would be expected by chance, results suggest that lower levels of endogenous estrogens may be a risk factor for regional brain volume loss in female APOE4 carriers compared to non‐carriers. Supported by NIH RF1AG053504 and R01AG053504 (Thurston & Maki) [ABSTRACT FROM AUTHOR]

Background: In this study we evaluated age‐ and sex‐associated morphological changes of cerebral blood vessels using 7T Time‐of‐flight (TOF) magnetic resonance angiography (MRA). Method: Our study consisted of 25 cognitively normal older adults (20 female, mean age 68.2 years). Whole‐Brain TOF MRA images were collected on a 7T Siemens scanner at the University of Pittsburgh (slice number = 354, voxel size = 0.38*0.38*0.38 mm, 12 mins). An iterative vessel segmentation algorithm, VesselMapper, was used to segment blood vessels on TOF MRA images (Li et al., 2023). For each subject, vessels are further divided into large and small vessels by median split based on vessel diameters. Mean tortuosity of large vessels, small vessels and overall vessels was computed. Linear regression analyses were performed to evaluate the main effects of age and sex, and the age*sex interaction on vessel tortuosity and diameter. Result: As shown in Figure 1, we found age‐related increase in mean vessel tortuosity (greater age is associated with greater tortuosity, p<0.02). This age‐related difference is driven by small vessels (p = 0.002) rather than large vessels (p = 0.7). We also found that age is positively associated with mean voxel tortuosity (p<0.001, black line in Figure 2). Furthermore, women showed greater age‐related increase in mean arterial tortuosity, compared to men (age*sex interaction p = 0.04, Figure 2). Conclusion: Our findings validated that morphological markers of cerebral blood vessels are sensitive to aging. Small vessels in the brain are particularly vulnerable. Further, compared to men, older women are at a higher risk for cerebral small vessel disease, which may contribute to elevated SVD‐related AD risk in women. Limitation: The study has an unbalanced sample (more women than men) and a relatively modest sample size (N = 25). A cross‐sectional instead of longitudinal design was used in this analysis. Future study with a large balanced sample and a longitudinal design are required to confirm our findings. Reference: Li, Jiatai, et al. "VesselMapper ‐ A Robust Vessel Segmentation Algorithm for 3D Images." Annual Meeting of the Organization for Human Brain Mapping. 2023 [ABSTRACT FROM AUTHOR]

Background: In this study we evaluated age‐ and sex‐associated morphological changes of cerebral blood vessels using 7T Time‐of‐flight (TOF) magnetic resonance angiography (MRA). Method: Our study consisted of 25 cognitively normal older adults (20 female, mean age 68.2 years). Whole‐Brain TOF MRA images were collected on a 7T Siemens scanner at the University of Pittsburgh (slice number = 354, voxel size = 0.38*0.38*0.38 mm, 12 mins). An iterative vessel segmentation algorithm, VesselMapper, was used to segment blood vessels on TOF MRA images (Li et al., 2023). For each subject, vessels are further divided into large and small vessels by median split based on vessel diameters. Mean tortuosity of large vessels, small vessels and overall vessels was computed. Linear regression analyses were performed to evaluate the main effects of age and sex, and the age*sex interaction on vessel tortuosity and diameter. Result: As shown in Figure 1, we found age‐related increase in mean vessel tortuosity (greater age is associated with greater tortuosity, p<0.02). This age‐related difference is driven by small vessels (p = 0.002) rather than large vessels (p = 0.7). We also found that age is positively associated with mean voxel tortuosity (p<0.001, black line in Figure 2). Furthermore, women showed greater age‐related increase in mean arterial tortuosity, compared to men (age*sex interaction p = 0.04, Figure 2). Conclusion: Our findings validated that morphological markers of cerebral blood vessels are sensitive to aging. Small vessels in the brain are particularly vulnerable. Further, compared to men, older women are at a higher risk for cerebral small vessel disease, which may contribute to elevated SVD‐related AD risk in women. Limitation: The study has an unbalanced sample (more women than men) and a relatively modest sample size (N = 25). A cross‐sectional instead of longitudinal design was used in this analysis. Future study with a large balanced sample and a longitudinal design are required to confirm our findings. Reference: Li, Jiatai, et al. "VesselMapper ‐ A Robust Vessel Segmentation Algorithm for 3D Images." Annual Meeting of the Organization for Human Brain Mapping. 2023 [ABSTRACT FROM AUTHOR]

Identifying risk factors for Alzheimer disease in women is important as women compose two-thirds of individuals with Alzheimer disease. Previous work links vasomotor symptoms, the cardinal menopausal symptom, with poor memory performance and alterations in brain structure, function, and connectivity. These associations are evident when vasomotor symptoms are monitored objectively with ambulatory skin conductance monitors. This study aimed to determine whether vasomotor symptoms are associated with Alzheimer disease biomarkers. Between 2017 and 2020, the MsBrain study enrolled 274 community-dwelling women aged 45 to 67 years who had a uterus and at least 1 ovary and were late perimenopausal or postmenopausal status. The key exclusion criteria included neurologic disorder, surgical menopause, and recent use of hormonal or nonhormonal vasomotor symptom treatment. Women underwent 24 hours of ambulatory skin conductance monitoring to assess vasomotor symptoms. Plasma concentrations of Alzheimer disease biomarkers, including amyloid β 42–to–amyloid β 40 ratio, phosphorylated tau (181 and 231), glial fibrillary acidic protein, and neurofilament light, were measured using a single-molecule array (Simoa) technology. Associations between vasomotor symptoms and Alzheimer disease biomarkers were assessed via linear regression models adjusted for age, race and ethnicity, education, body mass index, and apolipoprotein E4 status. Additional models adjusted for estradiol and sleep. A total of 248 (mean age, 59.06 years; 81% White; 99% postmenopausal status) of enrolled MsBrain participants contributed data. Objectively assessed vasomotor symptoms occurring during sleep were associated with significantly lower amyloid β 42/amyloid β 40, (beta, −.0010 [standard error,.0004]; P =.018; multivariable), suggestive of greater brain amyloid β pathology. The findings remained significant after additional adjustments for estradiol and sleep. Nighttime vasomotor symptoms may be a marker of women at risk of Alzheimer disease. It is yet unknown if these associations are causal. [ABSTRACT FROM AUTHOR]

Background: White matter hyperintensities (WMHs) are neuroimaging features associated with Alzheimer's disease (AD). Ex‐vivo studies may enable better characterization of WMHs pathological substrates. In this work, we present a novel method that leverages in‐vivo and ex‐vivo MRIs and histopathology to analyze the progression of WMHs in AD. Method: A single subject's in‐vivo MRI scans at four different time points were analyzed. Ex‐vivo scans of the brain left hemisphere were done using 16‐Tx and 32‐Rx TicTacToe coil3 and a 3‐D printed enclosure with integrated cutting guides1 (Fig. 1). The WMHs were segmented on the T2‐weighted FLAIR in‐vivo MRI 2, and registered onto the final time point via SPM's normalized mutual information‐based algorithm. All four WMH segmentations were warped to the ex‐vivo MRI's space by applying the deformation field from the ITK in‐vivo to ex‐vivo registration. Result: The 3D printed enclosure achieved an accurate alignment between gross pathology, ex‐vivo and in‐vivo MRI (Fig. 1). Then, we computed the WMHs' growth over time warped onto the ex‐vivo MRI (Fig. 2). This growth was quantified as the total number of voxels in each segmentation longitudinally with a quadratic fit with an R2 =0.99 (Fig. 2). Lastly, we found a significant change in the distribution of WMH segmentations over time as evident by their normalized histograms (Fig. 3). Conclusion: We present a novel method to track the progression of WMHs in‐vivo to ex‐vivo MRI and gross pathology. Future studies will perform a voxel‐wise analysis on the WMHs in MRI scans, both in‐vivo and ex‐vivo, along with its histological correlates to gain insight into the underlying cellular mechanisms during the biomarker's development. References: 1. Nadim Farhat et al. "Reusable 3D printed enclosure with integrated cutting guides for the alignment of high resolution ex‐vivo MRI with ex‐vivo gross brain photographs." 2021 ISMRM Meeting (Under revision). 2. Wu, M. et al (2006). "A fully automated method for quantifying and localizing white matter hyperintensities on MR images." Psychiatry Research: Neuroimaging, 148(2‐3), 133‐142. 3. T. Santini et al., "In‐vivo and numerical analysis of the eigenmodes produced by a multi‐level Tic‐Tac‐Toe head transmit array for 7 Tesla MRI," PLoS One, vol. 13, no. 11, p. e0206127, Nov. 2018. [ABSTRACT FROM AUTHOR]

Background: Nearly all persons with Down Syndrome (DS) will show pathology of Alzheimer's Disease (AD) in their 40s. Our study of non‐demented DS individuals showed that episodic memory was the first cognitive domain to decline in this population (Hartley et al., 2014). We have shown that diffusion tensor imaging (DTI) measures of white matter (WM) microstructure are related to amyloid burden in DS (Patrick et al., 2019). The parietal (Berryhill et al., 2007), prefrontal (Fletcher et al., 1998), and medial‐temporal (Nyberg et al., 1996) lobes have been shown to be involved in episodic memory. In this work, we examined the relation between white matter microstructure, assessed using tract‐based spatial statistics (TBSS), and episodic memory. Method: DTI scans (b = 1000 s/mm2 and 48 encoding directions) of 43 adults (N = 43; mean age = 39.8+/‐7.0 years) with DS were acquired at 3T at two imaging sites in the Alzheimer's Biomarker Consortium‐Down Syndrome. A composite score of episodic memory was calculated based on summing the z‐scores of the 1)Free and Cued Recall test (Buschke et al., 1984), a measure of verbal episodic memory and the 2)Rivermead Behavioural Memory Test for Children‐Picture Recognition (Wilson et al., 1991), a measure of visual episodic memory. Voxelwise statistical analyses of fractional anisotropy (FA) and mean diffusivity (MD) were carried out using TBSS. The associations between episodic memory with FA and MD were analyzed using a general linear model in FSL, controlling for imaging site and baseline intelligence assessed using the Peabody Picture Vocabulary Test (Dunn et al., 2007). Result: Adjusting for site, baseline intelligence, and multiple comparisons, episodic memory and FA were significantly (p<.05) positively correlated in the right occipital, parietal, and temporal regions and bilateral prefrontal regions. MD and episodic memory were significantly negatively correlated in much of the association white matter in all lobes and survived additional correction for age. Conclusion: Our results show significant correlations of episodic memory with FA and MD in multiple areas. There is a strong correlation of both FA and MD with age, which makes disentangling age and AD‐related neurodegeneration difficult; however, these results suggest FA and MD as potential indicators of episodic memory decline in DS populations. [ABSTRACT FROM AUTHOR]

Objective: The aim of this exploratory study is to examine the default mode network (DMN) functional connectivity pattern in elderly depressed subjects with and without comorbid anxiety. Methods: Functional magnetic resonance imaging data were collected for 11 elderly depressed subjects with high comorbid anxiety and eight elderly depressed subjects with low anxiety. We analyzed the resting-connectivity patterns of the posterior cingulate cortex. We compared the DMN activity in the elderly depressed subjects with high versus low comorbid anxiety. Results: Depressed elderly with high comorbid anxiety had increased functional connectivity in the posterior regions of the DMN and decreased functional connectivity in the anterior regions of the DMN. Conclusions: Elderly depressed subjects with high anxiety display a dissociative pattern of connectivity in the DMN when compared with elderly depressed subjects with low anxiety. These results suggest a unique biologic signature of the anxiety symptoms in the context of late-life depression. (Am J Geriatr Psychiatry 2011; 19:980-983) [ABSTRACT FROM AUTHOR]

Background: In a recent systematic review, the Alzheimer's Association concluded that it is yet unclear whether sleep disturbance may be a modifiable risk factor for cognitive decline and dementia. This conclusion underscored the gap in understanding of which specific aspects of sleep (e.g., amount or quality) are associated with that risk and whether the sleep problems are a cause or precursor of dementia. To address that gap, we examined objective (actigraphy) measures of sleep in relation to hippocampal functional connectivity during a memory task. We focused on community‐dwelling postmenopausal women, a population with frequent poor sleep and a heightened lifetime risk of Alzheimer's disease. We hypothesized that lower sleep efficiency but not sleep quantity would be associated with alterations in connectivity between the hippocampus and prefrontal cortex. Method: A total of 109 women (mean age=59.11 years; mean MOCA= 26.36; 78.0% white) from the MsBrain study completed 72‐hour sleep actigraphy assessments (Phillips Actiwatch‐A2) and blood‐oxygen‐level‐dependent (BOLD) fMRI assessments of verbal encoding and recognition. A generalized psychophysiological interaction (gPPI) analysis estimated task‐based hippocampal functional connectivity using SPM12 and Conn. The design matrix included principal time series of the seed region (left or right hippocampus), task conditions (novel words, familiar words), interaction variables (seed times series × task condition), and motion parameters. Sleep efficiency (% of time in bed spent sleeping) and total sleep time (hours slept) were regressed on patterns of brain connectivity in a region of interest confined to the hippocampus and prefrontal cortex, controlling for age, education and body mass index. Result: Sleep inefficiency but not sleep quantity was associated with lower hippocampal‐prefrontal connectivity during encoding (corrected p <.05). During encoding, sleep inefficiency was associated with lower connectivity between the /right hippocampus and left/right middle frontal gyrus and dorsal anterior cingulate cortex (ACC). No effects were evident for recognition. Conclusion: The well‐established association between poor sleep and memory dysfunction in aging may be driven by poor sleep efficiency, which in turn may influence memory performance through decreased hippocampal‐prefrontal connectivity during encoding. Findings indicate a need for sleep interventions that help older adults to sleep better rather than longer. [ABSTRACT FROM AUTHOR]

Background: Declining levels of estrogen have been implicated as a key mechanism contributing to declines in verbal memory that occur with menopause and as a potential factor contributing to risk of AD in women. We examined the association of two estrogens in postmenopausal women ‐ estradiol (E2), secreted by the ovary, and estrone (E1), secreted by peripheral tissues and the dominant estrogen in postmenopause – with functional connectivity during performance of verbal encoding and recognition tasks. We hypothesized that higher estrogen would be associated with greater functional connectivity between the hippocampus and prefrontal cortex (PFC) and between the left and right hippocampus. Method: Participants were enrolled in MsBrain, a cross sectional investigation of postmenopausal women (n=98, mean age 59.2 +/‐ 4.2 years, 78.6% White). Serum E1 and E2 were assessed using liquid chromatography‐tandem mass spectrometry. Verbal memory was assessed using the California Verbal Learning Test (CVLT) and a functional MRI verbal memory task using a block design with two phases: encoding and recognition. A generalized psychophysiological interaction (gPPI) analysis estimated task‐based hippocampal‐whole brain functional connectivity using SPM12. Principal time series of the seed region (left or right hippocampus), task conditions (novel words, familiar words), interaction variables (seed times series × task condition), and motion parameters were included in the design matrix. Result: E1 was positively associated with connectivity between the hippocampus and rostral anterior cingulate cortex (ACC), mid cingulate, dorsal ACC, and left insula during verbal encoding. E2 was positively associated with connectivity with rostral ACC/medial PFC and left orbital inferior frontal cortex during encoding and connectivity with rostral ACC, bilateral orbital PFC, bilateral middle temporal cortex, precuneus and posterior cingulate cortex during retrieval. All results survived multiple comparison at corrected p < 0.05. No associations were found between estrogen levels and verbal memory performance. Conclusion: Estrogen levels in postmenopause may play a significant role in functional connections between the hippocampus and key nodes of the salience network via E1 and cognitive control network via E2. Results suggest that estrogens enhance the ability to attend to stimuli and engage neural resources required for encoding and recognizing verbal information. [ABSTRACT FROM AUTHOR]