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The precuneus is a site of early amyloid-beta (Aß) accumulation. Previous cross-sectional studies reported increased precuneus fMRI activity in older adults with mild cognitive deficits or elevated Aß. However, longitudinal studies in early Alzheimer's disease (AD) are lacking and the relationship to the Apolipoprotein-E (APOE) genotype is unclear. Investigating the PREVENT-AD dataset, we assessed how baseline and longitudinal precuneus activity during successful memory retrieval relates to future Aß and tau burden and change in memory performance. We further studied the moderation by APOE4 genotype. We included 165 older adults (age, 62.8 ± 4.4 years; 113 female; 66 APOE4 carriers) who were cognitively normal at baseline with a family history of AD. All participants performed task-fMRI at baseline and underwent 18F-flortaucipir-PET and 18F-NAV4694-Aß-PET on average 5 years later. We found that higher baseline activity and greater longitudinal increase in precuneus activity were associated with higher Aß burden in APOE4 carriers but not noncarriers. We observed no effects of precuneus activity on tau burden. Finally, APOE4 noncarriers with low baseline precuneus activity exhibited better longitudinal performance in an independent memory test compared with (1) noncarriers with higher baseline activity and (2) APOE4 carriers. Our findings suggest that higher task-related precuneus activity duringmemory retrieval at baseline and over time are associated with greater Aß burden in cognitively normal APOE4 carriers. Our results further indicate that the absence of "hyperactivation" and the absence of the APOE4 allele is related with better future cognitive outcomes in cognitively normal older adults at risk for AD. [ABSTRACT FROM AUTHOR]

Glutathione (GSH) is a crucial antioxidant in the human brain. Although proton magnetic resonance spectroscopy using the Mescher-Garwood point-resolved spectroscopy sequence is highly recommended, limited literature has measured cortical GSH using this method in major psychiatric disorders. By combining magnetic resonance spectroscopy and resting-state functional magnetic resonance imaging, we quantified brain GSH and glutamate in the medial prefrontal cortex and precuneus and explored relationships between GSH levels and intrinsic neuronal activity as well as clinical symptoms among healthy control (HC) participants (n = 30), people with major depressive disorder (MDD) (n = 28), and people with obsessive-compulsive disorder (OCD) (n = 28). GSH concentrations were lower in the medial prefrontal cortex and precuneus in both the MDD and OCD groups than in the HC group. In the HC group, positive correlations were noted between GSH and glutamate levels and between GSH and fractional amplitude of low-frequency fluctuations in both regions. However, while these correlations were absent in both patient groups, there was a weak positive correlation between glutamate and fractional amplitude of low-frequency fluctuations. Moreover, GSH levels were negatively correlated with depressive and compulsive symptoms in MDD and OCD, respectively. These findings suggest that reduced GSH levels and an imbalance between GSH and glutamate could increase oxidative stress and alter neurotransmitter signaling, thereby leading to disruptions in GSH-related neurochemical-neuronal coupling and psychopathologies across MDD and OCD. Understanding these mechanisms could provide valuable insights into the processes that underlie these disorders and potentially become a springboard for future directions and advancing our knowledge of their neurobiological foundations. [ABSTRACT FROM AUTHOR]

Understanding the complex activation patterns of brain regions during motor tasks is crucial. Integrated functional magnetic resonance imaging (fMRI) and functional near-infrared spectroscopy (fNIRS) offers advanced insights into how brain activity fluctuates with motor activities. This study explores neuronal activation patterns in the cerebral cortex during active, passive, and imagined wrist movements using these functional imaging techniques. Data were collected from 10 right-handed volunteers performing a motor task using fMRI and fNIRS. fMRI utilized a 3T scanner and a 20-channel head coil, while fNIRS recorded data with a 48-channel device at 765 nm and 855 nm. Analysis focused on key motor and sensory cortices using NIRS-SPM and SPM12, applying a significance threshold of p < 0.05 and a minimum cluster size of 10 voxels for group analysis. Super-threshold voxels were identified with FWE thresholding in SPM12. For activation map extraction we focused on the primary motor cortex, primary somatosensory cortex, somatosensory association cortex, premotor cortex, and supplementary motor cortex. Both fMRI and fNIRS detected activation in the primary motor cortex (M1). The primary somatosensory cortex was found to influence movement direction coding, with smaller activation sizes for upward movements. Combining fNIRS with fMRI provided clearer differentiation of brain activation patterns for wrist movements in various directions and conditions (p < 0.05). This study highlights variations in left motor cortex activity across different movement states. fNIRS proved effective in detecting brain function and showed strong correlation with fMRI results, suggesting it as a viable alternative for those unable to undergo fMRI. [ABSTRACT FROM AUTHOR]

Introduction: Alzheimer’s disease (AD), the most prevalent age-related dementia, leads to significant cognitive decline. While genetic risk factors and neuroimaging biomarkers have been extensively studied, establishing a neuroimaging-based metric to assess AD risk has received less attention. This study introduces the Brain-wide Risk Score (BRS), a novel approach using multimodal neuroimaging data to assess the risk of mild cognitive impairment (MCI), a precursor to AD. Methods: Participants from the OASIS-3 cohort (N = 1,389) were categorized into control (CN) and MCI groups. Structural MRI (sMRI) data provided gray matter (GM) segmentation maps, while resting-state functional MRI (fMRI) data yielded functional network connectivity (FNC) matrices via spatially constrained independent component analysis. Similar imaging features were computed from the UK Biobank (N = 37,780). The BRS was calculated by comparing each participant’s neuroimaging features to the difference between average features of CN and MCI groups. Both GM and FNC features were used. The BRS effectively differentiated CN from MCI individuals within OASIS-3 and in an independent dataset from the ADNI cohort (N = 729), demonstrating its ability to identify MCI risk. Results: Unimodal analysis revealed that sMRI provided greater differentiation than fMRI, consistent with prior research. Using the multimodal BRS, we identified two distinct groups: one with high MCI risk (negative GM and FNC BRS) and another with low MCI risk (positive GM and FNC BRS). Additionally, 46 UK Biobank participants diagnosed with AD showed FNC and GM patterns similar to the high-risk groups. Conclusion: Validation using the ADNI dataset confirmed our results, highlighting the potential of FNC and sMRI-based BRS in early Alzheimer’s detection.