Altered hierarchical gradients of intrinsic neural timescales in mild cognitive impairment and Alzheimer's disease.

Alzheimer's disease (AD) is a devastating neurodegenerative disease that affects millions of seniors in the US. Resting-state functional magnetic resonance imaging (rs-fMRI) is widely used to study neurophysiology in AD and its prodromal condition, mild cognitive impairment (MCI). The intrinsic neural timescale (INT), which can be estimated through the magnitude of the autocorrelation of neural signals from rs-fMRI, is thought to quantify the duration that neural information is stored in a local circuit. Such heterogeneity of the timescales forms a basis of the brain functional hierarchy and captures an aspect of circuit dynamics relevant to excitation/inhibition balance, which is broadly relevant for cognitive functions. Given that, we applied rs-fMRI to test whether distinct changes of INT at different hierarchies are present in people with MCI, those progressing to AD (called Converter), and AD patients of both sexes. Linear mixed effect model was implemented to detect altered hierarchical gradients across populations followed by pairwise comparisons to identify regional differences. High similarities between AD and Converter were observed. Specifically, the inferior temporal, caudate, pallidum areas exhibit significant alterations in both AD and Converter. Distinct INT related pathological changes in MCI and AD were found. For AD/Converter, neural information is stored for a longer time in lower hierarchical areas, while higher levels of hierarchy seem to be preferentially impaired in MCI leading to a less pronounced hierarchical gradients. These results inform that the INT holds great potential as an additional measure for AD prediction, even a stable biomarker for clinical diagnosis.Significance Statement We observed high similarities of intrinsic neural timescales (INT) between patients with Alzheimer's Disease (AD) and people that will later progress to AD (called Converter), deviating from cognitively normal individuals. This indicates that pathological excitation/inhibition imbalance already started before the conversion to AD. We also revealed distinct pathophysiological changes in stable mild cognitive impairment (MCI) and AD/Converter. For the AD and Converter, neural information is stored for a longer time in lower brain hierarchical areas; while higher levels of the hierarchy seem to be preferentially impaired in stable MCI. These results suggest the potential for INT as an additional measure for AD prediction, even a stable biomarker for clinical diagnosis.

Brain reserve affects the expression of cognitive reserve networks.

Cognitive reserve (CR) explains differential susceptibility of cognitive performance to neuropathology. However, as brain pathologies progress, cognitive decline occurs even in individuals with initially high CR. The interplay between the structural brain health (= level of brain reserve) and CR-related brain networks therefore requires further research. Our sample included 142 individuals aged 60-70 years. National Adult Reading Test intelligence quotient (NART-IQ) was our CR proxy. On an in-scanner Letter Sternberg task, we used ordinal trend (OrT) analysis to extract a task-related brain activation pattern (OrT slope) for each participant that captures increased expression with task load (one, three, and six letters). We assessed whether OrT slope represents a neural mechanism underlying CR by associating it with task performance and NART-IQ. Additionally, we investigated how the following brain reserve measures affect the association between NART-IQ and OrT slope: mean cortical thickness, total gray matter volume, and brain volumes proximal to the areas contained in the OrT patterns. We found that higher OrT slope was associated with better task performance and higher NART-IQ. Further, the brain reserve measures were not directly associated with OrT slope, but they affected the relationship between NART-IQ and OrT slope: NART-IQ was associated with OrT slope only in individuals with high brain reserve. The degree of brain reserve has an impact on how (and perhaps whether) CR can be implemented in brain networks in older individuals.

Microglia measured by TSPO PET are associated with Alzheimer's disease pathology and mediate key steps in a disease progression model.

INTRODUCTION: Evidence suggests microglial activation precedes regional tau and neurodegeneration in Alzheimer's disease (AD). We characterized microglia with translocator protein (TSPO) positron emission tomography (PET) within an AD progression model where global amyloid beta (Aß) precedes local tau and neurodegeneration, resulting in cognitive impairment. METHODS: Florbetaben, PBR28, and MK-6240 PET, T1 magnetic resonance imaging, and cognitive measures were performed in 19 cognitively unimpaired older adults and 22 patients with mild cognitive impairment or mild AD to examine associations among microglia activation, Aß, tau, and cognition, adjusting for neurodegeneration. Mediation analyses evaluated the possible role of microglial activation along the AD progression model. RESULTS: Higher PBR28 uptake was associated with higher Aß, higher tau, and lower MMSE score, independent of neurodegeneration. PBR28 mediated associations between tau in early and middle Braak stages, between tau and neurodegeneration, and between neurodegeneration and cognition. DISCUSSION: Microglia are associated with AD pathology and cognition and may mediate relationships between subsequent steps in AD progression.

Personality traits and cognitive reserve-High openness benefits cognition in the presence of age-related brain changes.

Cognitive reserve explains differential susceptibility of cognitive performance to neuropathology. We investigated whether certain personality traits underlie cognitive reserve and are accordingly associated with better cognition and less cognitive decline in the presence of age-related brain changes. We included healthy adults aged 19-80 years for cross-sectional (N=399) and longitudinal (N=273, mean follow-up time=5 years, SD=0.7 years) analyses. Assessment of the BIG5 personality traits openness, conscientiousness, extraversion, agreeableness, and neuroticism was questionnaire-based. Each cognitive domain (perceptual speed, memory, fluid reasoning, vocabulary) was measured with up to six tasks. Cognitive domain-specific brain status variables were obtained by combining 77 structural brain measures into single scores using elastic net regularization. These brain status variables explained up to 43.1% of the variance in cognitive performance. We found that higher openness was associated with higher fluid reasoning and better vocabulary after controlling for brain status, age, and sex. Further, lower brain status was associated with a greater decline in perceptual speed only in individuals with low openness. We conclude that high openness benefits cognitive reserve.

In vivo tau is associated with change in memory and processing speed, but not reasoning, in cognitively unimpaired older adults.

The relationship between tau deposition and cognitive decline in cognitively healthy older adults is still unclear. The tau PET tracer 18F-MK-6240 has shown favorable imaging characteristics to identify early tau deposition in aging. We evaluated the relationship between in vivo tau levels (18F-MK-6240) and retrospective cognitive change over 5 years in episodic memory, processing speed, and reasoning. For tau quantification, a set of regions of interest (ROIs) was selected a priori based on previous literature: (1) total-ROI comprising selected areas, (2) medial temporal lobe-ROI, and (3) lateral temporal lobe-ROI and cingulate/parietal lobe-ROI. Higher tau burden in most ROIs was associated with a steeper decline in memory and speed. There were no associations between tau and reasoning change. The novelty of this finding is that tau burden may affect not only episodic memory, a well-established finding but also processing speed. Our finding reinforces the notion that early tau deposition in areas related to Alzheimer's disease is associated with cognitive decline in cognitively unimpaired individuals, even in a sample with low amyloid-ß pathology.

Effects of APOE e4 and Neuropathological Diagnoses on Neuropsychiatric Symptoms: Mediation Analyses and Likely Causation in an Integrated NACC Database.

BACKGROUND: We sought to identify paths from APOE e4 to neurobehaviors itemized on a neuropsychiatric inventory that involved neuropathologies associated with e4 (amyloid, tau, cerebral amyloid angiopathy, and Lewy bodies) or cognition mediators (memory or global cognitive status), as well as direct paths from e4 to neurobehaviors. METHODS: A total of 1199 cases with available neurobehavioral, cognition and neuropathological data were included. We conducted a series of causal mediation analyses in R in which e4 always served as the independent variable and Neuropsychiatric Inventory (NPI) neurobehavioral items, when included in the mediation, the outcome. Neuropathologies or cognition served as mediators. RESULTS: Multiple significant indirect paths from e4 through neuropathologies to neurobehaviors were identified. More refined analyses indicated that neuritic plaques and Braak stage drove the findings. A significant direct effect of e4 to memory was also identified. Additionally, Lewy body disease, when treated as an exposure, had a direct effect on hallucinations consistent with features of the disease. CONCLUSIONS: We found strong evidence for partial mediation of NPI symptoms by cognition, suggesting that cognitive limitations may have promoted maladaptive behavior. In addition, neuritic amyloid plaque levels and Braak stage, but not diffuse amyloid plaque extent, were key in NPI mediated associations suggesting the possibility that synaptic failure play an important role in multiple neurobehavioral symptoms in dementia, including psychosis. Last, we found strong evidence that e4 may have direct effects on cognition when we used verbal episodic memory but not global cognitive status, as an outcome.

Effects of APOE e4 and Neuropathological Diagnoses on Neuropsychiatric Symptoms: Mediation Analyses and Likely Causation in an Integrated NACC Database.

Background: Our goal in this study was to identify paths from APOE e4 to neurobehaviors itemized on a neuropsychiatric inventory that involved neuropathologies associated with e4 (amyloid, tau, cerebral amyloid angiopathy, and Lewy bodies) or cognition mediators (memory or global cognitive status), as well as direct paths from e4 to cognition or neurobehaviors. Methods: A total of 1199 cases with available neurobehavioral, cognition and neuropathological data were included. We then conducted a series of causal mediation analyses in R in which e4 always served as the independent variable and Neuropsychiatric Inventory (NPI) neurobehavioral items, when included in the mediation, the outcome. Neuropathologies or cognition served as mediators. Results: Multiple significant indirect paths from e4 through neuropathologies to neurobehaviors were identified. More refined analyses indicated that neuritic plaques and Braak stage, but not extent of diffuse amyloid plaques, drove the findings. A significant direct effect of e4 to memory was also identified. Additionally, Lewy body disease, when treated as an exposure, had a direct effect on hallucinations in keeping with known features of the disease. Conclusions: We found strong evidence for partial mediation of NPI symptoms by cognition, suggesting that cognitive limitations that may have influenced understanding (or misunderstanding) the environment with impacts on maladaptive behavior. In addition, neuritic amyloid plaque levels and Braak stage, but not diffuse amyloid plaque extent, were key in NPI mediated associations suggesting the possibility that synaptic failure play an important role in multiple neurobehavioral symptoms in dementia, including psychosis. Last, we found strong evidence that e4 may have direct effects on cognition when we used verbal episodic memory as an outcome, suggesting that medial temporal regions that support memory may be sensitive to non-amyloidogenic and non-tau related pathophysiological processes.

Age of onset of obsessive-compulsive disorder differentially affects white matter microstructure.

Previous diffusion MRI studies have reported mixed findings on white matter microstructure alterations in obsessive-compulsive disorder (OCD), likely due to variation in demographic and clinical characteristics, scanning methods, and underpowered samples. The OCD global study was created across five international sites to overcome these challenges by harmonizing data collection to identify consistent brain signatures of OCD that are reproducible and generalizable. Single-shell diffusion measures (e.g., fractional anisotropy), multi-shell Neurite Orientation Dispersion and Density Imaging (NODDI) and fixel-based measures, were extracted from skeletonized white matter tracts in 260 medication-free adults with OCD and 252 healthy controls. We additionally performed structural connectome analysis. We compared cases with controls and cases with early (<18) versus late (18+) OCD onset using mixed-model and Bayesian multilevel analysis. Compared with healthy controls, adult OCD individuals showed higher fiber density in the sagittal stratum (B[SE] = 0.10[0.05], P = 0.04) and credible evidence for higher fiber density in several other tracts. When comparing early (n = 145) and late-onset (n = 114) cases, converging evidence showed lower integrity of the posterior thalamic radiation -particularly radial diffusivity (B[SE] = 0.28[0.12], P = 0.03)-and lower global efficiency of the structural connectome (B[SE] = 15.3[6.6], P = 0.03) in late-onset cases. Post-hoc analyses indicated divergent direction of effects of the two OCD groups compared to healthy controls. Age of OCD onset differentially affects the integrity of thalamo-parietal/occipital tracts and the efficiency of the structural brain network. These results lend further support for the role of the thalamus and its afferent fibers and visual attentional processes in the pathophysiology of OCD.

Higher Glycemic Index and Glycemic Load Diet Is Associated with Slower Disease Progression in Amyotrophic Lateral Sclerosis.

OBJECTIVE: High-caloric diets may slow the progression of amyotrophic lateral sclerosis; however, key macronutrients have not been identified. We examined whether dietary macronutrients are associated with the rate of progression and length of survival among the prospective cohort study participants. METHODS: Participants with a confirmed diagnosis of sporadic amyotrophic lateral sclerosis enrolled in the Multicenter Cohort Study of Oxidative Stress were included (n = 304). We evaluated baseline macronutrient intake assessed by food frequency questionnaire in relation to change in revised amyotrophic lateral sclerosis functional rating scale total-score, and tracheostomy-free survival using linear regression and Cox proportional hazard models. Baseline age, sex, disease duration, diagnostic certainty, body mass index, bulbar onset, revised amyotrophic lateral sclerosis functional rating scale total-score, and forced vital capacity were included as covariates. RESULTS: Baseline higher glycemic index and load were associated with less decline of revised amyotrophic lateral sclerosis functional rating scale total score at 3-month follow-up (ß = -0.13, 95% CI -0.2, -0.01, p = 0.03) and (ß = -0.01, 95% CI -0.03, -0.0007, p = 0.04), respectively. Glycemic index second-quartile, third-quartile, and fourth-quartile groups were associated with less decline at 3 months by 1.9 (95% CI -3.3, -0.5, p = 0.008), 2.0 (95% CI -3.3, -0.6, p = 0.006), and 1.6 (95% CI -3.0, -0.2, p = 0.03) points compared with the first-quartile group; the glycemic load fourth-quartile group had 1.4 points less decline compared with the first-quartile group (95% CI -2.8, 0.1, p = 0.07). Higher glycemic index was associated with a trend toward longer tracheostomy-free survival (HR 0.97, 95% CI 0.93, 1.00, p = 0.07). INTERPRETATION: Higher dietary glycemic index and load are associated with slower disease progression in amyotrophic lateral sclerosis. ANN NEUROL 2024;95:217-229.

Maternal childhood trauma and observed maternal care behaviors with 4-month-old infants.

OBJECTIVE: To examine the relationship between maternal childhood trauma and early maternal caregiving behaviors (MCB). METHOD: Participants included 74 mother-infant dyads (maternal age 20-45 years; ethnicity 64.9% Latina) from a longitudinal pregnancy cohort study. Maternal childhood trauma was assessed during pregnancy with the childhood trauma questionnaire (CTQ). Observed mother-infant interactions at infant age 4 months were coded utilizing modified Ainsworth's MCB rating scales that assessed a range of behaviors (e.g., acceptance, soothing, and delight) which we analyze grouped together and will summarize using the term "maternal sensitivity." Linear regressions tested the associations between maternal childhood trauma and MCB. Primary analyses examined the relationships of MCB with (a) any maternal childhood trauma (moderate or greater exposure to physical abuse, sexual abuse, emotional abuse, physical neglect, and/or emotional neglect) and (b) cumulative childhood trauma. Secondary analyses examined the relationships between each type of childhood trauma and MCB. RESULTS: Exposure to childhood trauma was not associated with MCB (p = .88). Cumulative childhood trauma score was associated with lower scores on MCB (ß = -1.88, p < .05). Emotional abuse and emotional neglect were individually associated with lower scores on MCB (ß = -1.78, p = .04; ß = -1.55, p = .04, respectively). Physical abuse, sexual abuse, and physical neglect were not associated with MCB. CONCLUSIONS: Many mothers exposed to childhood trauma may be resilient to negative effects on parenting behaviors, while specific experiences of childhood trauma (emotional abuse, emotional neglect, and cumulative childhood trauma) may predict less sensitive early parenting behaviors. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Generalizability and Out-of-Sample Predictive Ability of Associations Between Neuromelanin-Sensitive Magnetic Resonance Imaging and Psychosis in Antipsychotic-Free Individuals.

Importance: The link between psychosis and dopaminergic dysfunction is established, but no generalizable biomarkers with clear potential for clinical adoption exist. Objective: To replicate previous findings relating neuromelanin-sensitive magnetic resonance imaging (NM-MRI), a proxy measure of dopamine function, to psychosis severity in antipsychotic-free individuals in the psychosis spectrum and to evaluate the out-of-sample predictive ability of NM-MRI for psychosis severity. Design, Setting, and Participants: This cross-sectional study recruited participants from 2019 to 2023 in the New York City area (main samples) and Mexico City area (external validation sample). The main samples consisted of 42 antipsychotic-free patients with schizophrenia, 53 antipsychotic-free individuals at clinical high risk for psychosis (CHR), and 52 matched healthy controls. An external validation sample consisted of 16 antipsychotic-naive patients with schizophrenia. Main Outcomes and Measures: NM-MRI contrast within a subregion of the substantia nigra previously linked to psychosis severity (a priori psychosis region of interest [ROI]) and psychosis severity measured using the Positive and Negative Syndrome Scale (PANSS) in schizophrenia and the Structured Interview for Psychosis-Risk Syndromes (SIPS) in CHR. The cross-validated performance of linear support vector regression to predict psychosis severity across schizophrenia and CHR was assessed, and a final trained model was tested on the external validation sample. Results: Of the 163 included participants, 76 (46.6%) were female, and the mean (SD) age was 29.2 (10.4) years. In the schizophrenia sample, higher PANSS positive total scores correlated with higher mean NM-MRI contrast in the psychosis ROI (t37 = 2.24, P = .03; partial r = 0.35; 95% CI, 0.05 to 0.55). In the CHR sample, no significant association was found between higher SIPS positive total score and NM-MRI contrast in the psychosis ROI (t48 = -0.55, P = .68; partial r = -0.08; 95% CI, -0.36 to 0.23). The 10-fold cross-validated prediction accuracy of psychosis severity was above chance in held-out test data (mean r = 0.305, P = .01; mean root-mean-square error [RMSE] = 1.001, P = .005). External validation prediction accuracy was also above chance (r = 0.422, P = .046; RMSE = 0.882, P = .047). Conclusions and Relevance: This study provided a direct ROI-based replication of the in-sample association between NM-MRI contrast and psychosis severity in antipsychotic-free patients with schizophrenia. In turn, it failed to replicate such association in CHR individuals. Most critically, cross-validated machine-learning analyses provided a proof-of-concept demonstration that NM-MRI patterns can be used to predict psychosis severity in new data, suggesting potential for developing clinically useful tools.

Effects of age on the relationship between sleep quality and cognitive performance: Findings from the Human Connectome Project-Aging cohort.

BACKGROUND: The association between sleep quality and cognition is widely established, but the role of aging in this relationship is largely unknown. OBJECTIVE: To examine how age impacts the sleep-cognition relationship and determine whether there are sensitive ranges when the relationship between sleep and cognition is modified. This investigation could help identify individuals at risk for sleep-related cognitive impairment. SUBJECTS: Sample included 711 individuals (ages 36.00-89.8359.66 ± 14.9155.7 % female) from the Human Connectome Project-Aging (HCP-A). METHODS: The association between sleep quality (Pittsburgh Sleep Quality Index, PSQI) and cognition (Crystallized Cognition Composite and Fluid Cognition Composite from the NIH Toolbox, the Trail Making Test, TMT, and the Rey Auditory Verbal Learning Test, RAVLT) was measured using linear regression models, with sex, race, use of sleep medication, hypertension, and years of education as covariates. The interaction between sleep and age on cognition was tested using the moderation analysis, with age as both continuous linear and nonlinear (quadratic) terms. RESULTS: There was a significant interaction term between the PSQI and nonlinear age term (age2) on TMT-B (p = 0.02) and NIH Toolbox crystallized cognition (p = 0.02), indicating that poor sleep quality was associated with worse performance on these measures (sensitive age ranges 50-75 years for TMT-B and 66-70 years for crystallized cognition). CONCLUSIONS: The sleep-cognition relationship may be modified by age. Individuals in the middle age to early older adulthood age band may be most vulnerable to sleep-related cognitive impairment.

Prenatal sleep health and risk of offspring ADHD symptomatology and associated phenotypes: a prospective analysis of timing and sex differences in the ECHO cohort.

Background: Sleep difficulties are common in pregnancy, yet poor prenatal sleep may be related to negative long-term outcomes for the offspring, including risk for attention-deficit/hyperactivity disorder (ADHD). Existing studies are few and have not examined timing of exposure effects or offspring sex moderation. We thus aimed to test the hypotheses that poor sleep health in pregnancy is associated with increased risk for ADHD symptoms and offspring sleep problems at approximately 4 years of age. Methods: Participants were 794 mother-child dyads enrolled in the NIH Environmental Influences on Child Health Outcomes Study (ECHO). Participants self-reported on sleep duration, quality, and disturbances during pregnancy and on children's ADHD symptoms and sleep problems on the Child Behaviour Checklist. Findings: Pregnant participants were 32.30 ± 5.50 years and children were 46% female. 44 percent of pregnant participants identified as Hispanic or Latine; 49% identified as White. Second-trimester sleep duration was associated with offspring ADHD symptoms (b = -0.35 [95% CI = -0.57, -0.13], p = 0.026), such that shorter duration was associated with greater symptomatology. Poorer sleep quality in the second trimester was also associated with increased ADHD symptomatology (b = 0.66 [95% CI = 0.18, 1.14], p = 0.037). Greater sleep disturbances in the first trimester were associated with offspring ADHD (b = 1.03 [95% CI = 0.32, 1.03], p = 0.037) and in the second trimester with sleep problems (b = 1.53 [95% CI = 0.42, 2.92], p = 0.026). We did not document substantial offspring sex moderation. Interpretation: Poor prenatal sleep health, particularly quality and duration in the second trimester, may be associated with offspring risk of neurodevelopmental disorders and sleep problems in early childhood. Further research is needed to understand mechanisms, yet our study suggests that prenatal maternal sleep may be a modifiable target for interventions aimed at optimizing early neurodevelopment. Funding: NIH grants U2COD023375, U24OD023382, U24OD023319, UH3OD023320, UH3OD023305, UH3OD023349, UH3OD023313, UH3OD023272, UH3OD023328, UH3OD023290, K08MH117452 and NARSAD Young Investigator Award 28545.

Stress and DNA Methylation of Blood Leukocytes among Pregnant Latina Women.

Latinas experience physical and psychological stressors in pregnancy leading to increased morbidity and higher risk for adverse birth outcomes. Epigenetic changes, including DNA methylation (DNAm), have been proposed as markers to create more refined risk stratification, yet few of these studies have examined these changes in Latinas. We conducted a secondary analysis of stored blood leukocytes of Latina women (n = 58) enrolled in a larger National Institutes of Health funded R01 project (2011-2016). We examined DNAm on eight candidate stress genes to compare physically and psychologically stressed participants to healthy (low stress) participants. We found unique CpGs that were differentially methylated in stressed women early- and mid-pregnancy compared to the healthy group, though none remained significant after FDR correction. Both physical and psychological stress were associated with hypomethylation at two consecutive CpG sites on NR3C1 in early pregnancy and one CpG site on NR3C1 in mid-pregnancy before adjustment. Stress was also associated with hypomethylation at two CpG sites on FKBP5 in early and mid-pregnancy but were no longer significant after FDR adjustment. Though we did not find statistically significant differences in DNAm during pregnancy between stressed and healthy women in this sample, signals were consistent with previous findings. Future work in larger samples should further examine the associations between stress and DNAm in pregnancy as this mechanism may explain underlying perinatal health inequities.

Comparison of relative change with effect size metrics in Alzheimer's disease clinical trials.

BACKGROUND: Per cent slowing of decline is frequently used as a metric of outcome in Alzheimer's disease (AD) clinical trials, but it may be misleading. Our objective was to determine whether per cent slowing of decline or Cohen's d is the more valid and informative measure of efficacy. METHODS: Outcome measures of interest were per cent slowing of decline; Cohen's d effect size and number-needed-to-treat (NNT). Data from a graphic were used to model the inter-relationships among Cohen's d, placebo decline in raw score units and per cent slowing of decline with active treatment. NNTs were computed based on different magnitudes of d. Last, we tabulated recent AD anti-amyloid clinical trials that reported per cent slowing and for which we computed their respective d's and NNTs. RESULTS: We demonstrated that d and per cent slowing were potentially independent. While per cent slowing of decline was dependent on placebo decline and did not include variance in its computation, d was dependent on both group mean difference and pooled SD. We next showed that d was a critical determinant of NNT, such that NNT was uniformly smaller when d was larger. In recent AD associated trials including those focused on anti-amyloid biologics, d's were below 0.23 and thus considered small, while per cent slowing was in the 22-29% range and NNTs ranged from 14 to 18. CONCLUSIONS: Standardised effect size is a more meaningful outcome than per cent slowing of decline because it determines group overlap, which can directly influence NNT computations, and yield information on the likelihood of minimum clinically important differences. In AD, greater use of effect sizes, NNTs, rather than relative per cent slowing, will improve the ability to interpret clinical trial results and evaluate the clinical meaningfulness of statistically significant results.

Altered hierarchical gradients of intrinsic neural timescales in mild cognitive impairment and Alzheimer's disease.

Alzheimer's disease (AD) is a devastating neurodegenerative disease that affects millions of older adults in the US and worldwide. Resting-state functional magnetic resonance imaging (rs-fMRI) has become a widely used neuroimaging tool to study neurophysiology in AD and its prodromal condition, mild cognitive impairment (MCI). The intrinsic neural timescale (INT), which can be estimated through the magnitude of the autocorrelation of intrinsic neural signals using rs-fMRI, is thought to quantify the duration that neural information is stored in a local cortical circuit. The heterogeneity of the timescales is considered to be a basis of the functional hierarchy in the brain. In addition, INT captures an aspect of circuit dynamics relevant to excitation/inhibition (E/I) balance, which is thought to be broadly relevant for cognitive functions. Here we examined its relevance to AD. We used rs-fMRI data of 904 individuals from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The subjects were divided into 4 groups based on their baseline and end-visit clinical status, which were cognitively normal (CN), stable MCI, Converter, and AD groups. Linear mixed effect model and pairwise comparison were implemented to investigate the large-scale hierarchical organization and local differences. We observed high similarities between AD and Converter groups. Specifically, among the eight identified ROIs with distinct INT alterations in AD, three ROIs (inferior temporal, caudate, pallidum areas) exhibit stable and significant alteration in AD converter. In addition, distinct INT related pathological changes in stable MCI and AD/Converter were found. For AD and Converter groups, neural information is stored for a longer time in lower hierarchical order areas, while higher levels of hierarchy seem to be preferentially impaired in stable MCI leading to a less pronounced hierarchical gradient effect. These results inform that the INT holds great potential as an additional measure for AD prediction, a stable biomarker for clinical diagnosis and an important therapeutic target in AD.

Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium.

BACKGROUND: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. METHODS: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. RESULTS: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. CONCLUSION: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.

Association of Cognitive Polygenic Index and Cognitive Performance with Age in Cognitively Healthy Adults.

Genome-wide association studies have discovered common genetic variants associated with cognitive performance. Polygenic scores that summarize these discoveries explain up to 10% of the variance in cognitive test performance in samples of adults. However, the role these genetics play in cognitive aging is not well understood. We analyzed data from 168 cognitively healthy participants aged 23-77 years old, with data on genetics, neuropsychological assessment, and brain-imaging measurements from two large ongoing studies, the Reference Abilities Neural Networks, and the Cognitive Reserve study. We tested whether a polygenic index previously related to cognition (Cog PGI) would moderate the relationship between age and measurements of the cognitive domains extracted from a neuropsychological evaluation: fluid reasoning, memory, vocabulary, and speed of processing. We further explored the relationship of Cog PGI and age on cognition using Johnson-Neyman intervals for two-way interactions. Sex, education, and brain measures of cortical thickness, total gray matter volume, and white matter hyperintensity were considered covariates. The analysis controlled for population structure-ancestry. There was a significant interaction effect of Cog PGI on the association between age and the domains of memory (Standardized coefficient = -0.158, p-value = 0.022), fluid reasoning (Standardized coefficient = -0.146, p-value = 0.020), and vocabulary (Standardized coefficient = -0.191, p-value = 0.001). Higher PGI strengthened the negative relationship between age and the domains of memory and fluid reasoning while PGI weakened the positive relationship between age and vocabulary. Based on the Johnson-Neyman intervals, Cog PGI was significantly associated with domains of memory, reasoning, and vocabulary for younger adults. There is a significant moderation effect of genetic predisposition for cognition for the association between age and cognitive performance. Genetics discovered in genome-wide association studies of cognitive performance show a stronger association in young and midlife older adults.

Explaining Deep Learning-Based Representations of Resting State Functional Connectivity Data: Focusing on Interpreting Nonlinear Patterns in Autism Spectrum Disorder.

Background: Resting state Functional Magnetic Resonance Imaging fMRI (rs-fMRI) has been used to study brain function in psychiatric disorders, yielding insight into brain organization. However, the high dimensionality of the rs-fMRI data presents challenges, and requires dimensionality reduction before applying machine learning techniques. Neural networks, specifically variational autoencoders (VAEs), have been instrumental in extracting low-dimensional latent representations of resting state functional connectivity patterns, addressing the complex nonlinear structure of rs-fMRI. However, interpreting those latent representations remains a challenge. This paper aims to address this gap by creating explainable VAE models and testing their utility using rs-fMRI data in autism spectrum disorder (ASD). Methods: One-thousand one hundred and fifty participants (601 HC and 549 patients with ASD) were included in the analysis. We extracted functional connectivity correlation matrices from the preprocessed rs-fMRI data using Power atlas with 264 ROIs. Then VAEs were trained in an unsupervised fashion. Lastly, we introduce our latent contribution scores to explain the relationship between estimated representations and the original rs-fMRI brain measures. Results: We quantified the latent contribution scores for the ASD and control groups at the network level. We found that both ASD and control groups share the top network connectivity that contribute to all estimated latent components. For example, latent 0 was driven by resting state functional connectivity patterns (rsFC) within ventral attention network in both the ASD and control. However, significant differences in the latent contribution scores between the ASD and control groups were discovered within the ventral attention network in latent 0 and the sensory/somatomotor network in latent 2. Conclusion: This study introduced latent contribution scores to interpret nonlinear patterns identified by VAEs. These scores effectively capture changes in each observed rsFC features as estimated latent representation changes, enabling an explainable deep learning model to better understand the underlying neural mechanism of ASD.

Effects of lithium on serum Brain-Derived Neurotrophic Factor in Alzheimer's patients with agitation.

BACKGROUND: There is ample evidence in animal models that lithium increases Brain-Derived Neurotrophic Factor (BDNF) with supporting evidence in human studies. Little is known, however, about the effects of lithium on BDNF in Alzheimer's Dementia (AD). In one study of patients with Mild Cognitive Impairment, serum BDNF increased after treatment with lithium. These patients also showed mild improvement in cognitive function. OBJECTIVES: To evaluate low-dose lithium treatment of agitation in Alzheimer's disease (AD). METHOD: We measured levels of BDNF in patients treated with lithium prior to and after a 12-week randomized placebo-controlled trial. RESULTS: BDNF levels did not change significantly and were not associated with improvement in overall neuropsychiatric symptoms or in cognitive function. CONCLUSIONS: More research is needed to understand the potential effects of lithium on BDNF in AD including whether its use might be dependent on the stage of cognitive decline and dementia.