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Objective: Elevated entorhinal cortex (EC) tau in low beta‐amyloid individuals can predict accumulation of pathology and cognitive decline. We compared the accuracy of magnetic resonance imaging (MRI)‐derived locus coeruleus integrity, neocortical beta‐amyloid burden by positron emission tomography (PET), and hippocampal volume in identifying elevated entorhinal tau signal in asymptomatic individuals who are considered beta‐amyloid PET‐negative. Methods: We included 188 asymptomatic individuals (70.78 ± 11.51 years, 58% female) who underwent 3T‐MRI of the locus coeruleus, Pittsburgh compound‐B (PiB), and Flortaucipir (FTP) PET. Associations between elevated EC tau and neocortical PiB, hippocampal volume, or locus coeruleus integrity were evaluated and compared using logistic regression and receiver operating characteristic analyses in the PiB− sample with a clinical dementia rating (CDR) of 0. Associations with clinical progression (CDR‐sum‐of‐boxes) over a time span of 6 years were evaluated with Cox proportional hazard models. Results: We identified 26 (21%) individuals with high EC FTP in the CDR = 0/PiB− sample. Locus coeruleus integrity was a significantly more sensitive and specific predictor of elevated EC FTP (area under the curve [AUC] = 85%) compared with PiB (AUC = 77%) or hippocampal volume (AUC = 76%). Based on the Youden‐index, locus coeruleus integrity obtained a sensitivity of 77% and 85% specificity. Using the resulting locus coeruleus Youden cut‐off, lower locus coeruleus integrity was associated with a two‐fold increase in clinical progression, including mild cognitive impairment. Interpretation: Locus coeruleus integrity has promise as a low‐cost, non‐invasive screening instrument to detect early cortical tau deposition and associated clinical progression in asymptomatic, low beta‐amyloid individuals. ANN NEUROL 2024;96:650–661 [ABSTRACT FROM AUTHOR]

Introduction: Alterations in locus coeruleus' (LC) metabolic turnover are associated with Alzheimer's disease (AD)-pathology and cognitive impairment. However, the evolution of these changes across disease stages and their functional relevance remains unknown., Methods: We examined associations of [ 18 F]-fluorodeoxyglucose positron emission tomography (FDG-PET) -derived LC metabolism with clinical diagnostic status, cerebrospinal fluid (CSF) -based AD biomarkers of AD pathology, and cognitive decline in Alzheimer's Disease Neuroimaging Initiative (ADNI) participants (n = 604)., Results: FDG-PET-derived LC metabolism was elevated in the earliest preclinical stages and lower in later disease stages. Higher LC metabolism was associated with attenuated memory decline in preclinical stages, particularly in those with low CSF Aβ 42, but not in AD patients with cognitive impairment., Discussion: Higher locus coeruleus [ 18 F]-FDG-PET-derived signal in the early preclinical stages of AD can confer cognitive resilience and may reflect increased metabolic activity, whereas later stages are characterized by lower LC FDG-PET-derived signal, possibly due to neurodegeneration., Highlights: LC FDG-PET signal is lower in Alzheimer's disease (AD) patients. LC FDG-PET signal is higher in the preclinical stage of AD. We observed less memory decline in those with higher LC FDG-PET signal. Higher LC FDG-PET signal conferred cognitive resilience in preclinical AD., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

In this work, we employ simultaneous EEG-fMRI data acquired during a visually-guided attention task along with convolutional sparse coding (CSC) analysis to extract transient events from the EEG. Subsequently, we use these events in a standard voxel-wise fMRI analysis and compare the resultant activation maps with maps obtained using the subjects' response time (RT) in detection of visual target stimuli. We also employ FIR models to obtain HRF estimates using the detected CSC events. Our results show concordance between the resultant activation maps and consistent HRF shapes for most of the subjects, suggesting that CSC can be used as a tool for the detection of reliable events in the EEG.

In this work, we investigate the linear dynamic interactions between fluctuations in arterial CO2 that occur during normal breathing, and the BOLD fMRI signal. We cast this problem within a systems-theoretic framework, where we employ functional expansions for the estimation of the impulse responses in large regions of interest, as well as in individual voxels. We also implement classification schemes in order to identify different brain regions with similar cerebrovascular reactivity characteristics. Our results reveal that it is feasible to obtain reliable estimates of cerebrovascular reactivity curves from resting-state data and that these curves exhibit considerable variability across different brain regions that may be related to the underlying anatomy.