Verbal memory and hippocampal volume predict subsequent fornix microstructure in those at risk for Alzheimer's disease

Novel hippocampus-centered methodology for informative instance selection in Alzheimer's disease data

The quantity and quality of a dataset play a crucial role in the performance of prediction models. Increasing the amount of data increases the computational requirements and can introduce negligible variations, outliers, and noise. These significantly impact the model performance. Thus, instance selection techniques are crucial for building prediction models with informative data, reducing the dataset size, improving performance, and minimizing computational costs. This study proposed a novel methodology for identifying the most informative two-dimensional slices derived from magnetic resonance imaging (MRI) to study Alzheimer's disease. The efficacy of our methodology was attributable to a hippocampus-centered analysis using data from multiple atlases. The methodology was evaluated by constructing convolutional neural networks to identify Alzheimer's disease, using a consolidated dataset constructed from three standard datasets: Alzheimer's Disease Neuroimaging Initiative, Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing, and Open Access Series of Imaging Studies. The proposed methodology demonstrated a commendable subject-level classification accuracy of approximately ( 95.00 % ) when distinguishing between normal cognition and Alzheimer's.

Fixel-based and tensor-derived white matter abnormalities in relation to memory impairment and neurocognitive disorders

Aging-related neurocognitive disorders, including Alzheimer's disease (AD) and mild cognitive impairment (MCI), have been characterised by altered brain white matter (WM), relying widely on diffusion tensor imaging (DTI). DTI's limited accuracy in assessing crossing fibres prompted novel methods that distinguish fibres crossing through same voxel-spaces, such as fixel-based analysis (FBA), highlighting subtle macrostructural and microstructural alterations in AD and MCI. We examined the FBA and DTI's specificity in determining WM features relevant to memory in the neurocognitive aging spectrum. Diffusion-weighted images were analysed in 560 participants with various neurocognitive diagnoses from the Alzheimer's Disease Neuroimaging Initiative (F:297; mean age: 73.2 ± 8). Verbal memory was measured in 488 participants using the Rey Auditory Verbal Learning Test. FBA-derived measures of fibre density (FD), fibre-bundle cross-section (FC), and their combination (FDC), DTI fractional anisotropy (FA) and mean diffusivity (MD) were examined in relation to diagnoses and memory scores, controlling for age, sex, and intracranial volume. MCI and AD groups significantly differed from controls, with lower FD and FDC in the fornix and bilateral fibres extending to the medial temporal lobes (MTL). Memory was positively associated with FD and FDC in the fornix and MTL fibres, and FC in the anterior commissure (AC). Widespread FA reductions and MD increases were observed in AD and MCI and widely associated with memory. Fixel-wise measures highlight fibre tracts that are altered distinctly at the macroscopic and microscopic level in neurocognitive aging, and reveals structures associated with memory performance that are more specifically located than tensor-derived measures.

The hippocampus as a structural and functional network epicentre for distant cortical thinning in neurocognitive aging

Alterations in grey matter (GM) and white matter (WM) are associated with memory impairment across the neurocognitive aging spectrum and theorised to spread throughout brain networks. Functional and structural connectivity (FC,SC) may explain widespread atrophy. We tested the effect of SC and FC to the hippocampus on cortical thickness (CT) of connected areas. In 419 (223 F) participants (agemean=73 ± 8) from the Alzheimer's Disease Neuroimaging Initiative, cortical regions associated with memory (Rey Auditory Verbal Learning Test) were identified using Lasso regression. Two structural equation models (SEM), for SC and resting-state FC, were fitted including CT areas, and SC and FC to the left and right hippocampus (LHIP,RHIP). LHIP (β=-0.150,p=<.001) and RHIP (β=-0.139,p=<.001) SC predicted left temporopolar/rhinal CT; RHIP SC predicted right temporopolar/rhinal CT (β=-0.191,p=<.001). LHIP SC predicted right fusiform/parahippocampal (β=-0.104,p=.011) and intraparietal sulcus/superior parietal CT (β=0.101,p=.028). Increased RHIP FC predicted higher left inferior parietal CT (β=0.132,p=.042) while increased LHIP FC predicted lower right fusiform/parahippocampal CT (β=-0.97; p=.023). The hippocampi may be epicentres for cortical thinning through disrupted connectivity.

Characterization of diffusion magnetic resonance imaging revealing relationships between white matter disconnection and behavioral disturbances in mild cognitive impairment: a systematic review

White matter disconnection is the primary cause of cognition and affection abnormality in mild cognitive impairment (MCI). Adequate understanding of behavioral disturbances, such as cognition and affection abnormality in MCI, can help to intervene and slow down the progression of Alzheimer's disease (AD) promptly. Diffusion MRI is a non-invasive and effective technique for studying white matter microstructure. This review searched the relevant papers published from 2010 to 2022. Sixty-nine studies using diffusion MRI for white matter disconnections associated with behavioral disturbances in MCI were screened. Fibers connected to the hippocampus and temporal lobe were associated with cognition decline in MCI. Fibers connected to the thalamus were associated with both cognition and affection abnormality. This review summarized the correspondence between white matter disconnections and behavioral disturbances such as cognition and affection, which provides a theoretical basis for the future diagnosis and treatment of AD.

Relations of hippocampal subfields atrophy patterns with memory and biochemical changes in end stage renal disease

End-stage renal disease (ESRD) results in hippocampal volume reduction, but the hippocampal subfields atrophy patterns cannot be identified. We explored the volumes and asymmetry of the hippocampal subfields and their relationships with memory function and biochemical changes. Hippocampal global and subfields volumes were derived from 33 ESRD patients and 46 healthy controls (HCs) from structural MRI. We compared the volume and asymmetric index of each subfield, with receiver operating characteristic curve analysis to evaluate the differentiation between ESRD and HCs. The relations of hippocampal subfield volumes with memory performance and biochemical data were investigated in ESRD group. ESRD patients had smaller hippocampal subfield volumes, mainly in the left CA1 body, left fimbria, right molecular layer head, right molecular layer body and right HATA. The right molecular layer body exhibited the highest accuracy for differentiating ESRD from HCs, with a sensitivity of 80.43% and specificity of 72.73%. Worse learning process (r = 0.414, p = 0.032), immediate recall (r = 0.396, p = 0.041) and delayed recall (r = 0.482, p = 0.011) was associated with left fimbria atrophy. The left fimbria volume was positively correlated with Hb (r = 0.388, p = 0.05); the left CA1 body volume was negatively correlated with Urea (r = - 0.469, p = 0.016). ESRD patients showed global and hippocampal subfields atrophy. Left fimbria atrophy was related to memory function. Anemia and Urea level may be associated with the atrophy of left fimbria and CA1 body, respectively.

Dissecting the Fornix in Basic Memory Processes and Neuropsychiatric Disease: A Review

Background: The fornix is the primary axonal tract of the hippocampus, connecting it to modulatory subcortical structures. This review reveals that fornix damage causes cognitive deficits that closely mirror those resulting from hippocampal lesions. Methods: We reviewed the literature on the fornix, spanning non-human animal lesion research, clinical case studies of human patients with fornix damage, as well as diffusion-weighted imaging (DWI) work that evaluates fornix microstructure in vivo. Results: The fornix is essential for memory formation because it serves as the conduit for theta rhythms and acetylcholine, as well as providing mnemonic representations to deep brain structures that guide motivated behavior, such as when and where to eat. In rodents and non-human primates, fornix lesions lead to deficits in conditioning, reversal learning, and navigation. In humans, damage to the fornix manifests as anterograde amnesia. DWI research reveals that the fornix plays a key role in mild cognitive impairment and Alzheimer's Disease, and can potentially predict conversion from the former to the latter. Emerging DWI findings link perturbations in this structure to schizophrenia, mood disorders, and eating disorders. Cutting-edge research has investigated how deep brain stimulation of the fornix can potentially attenuate memory loss, control epileptic seizures, and even improve mood. Conclusions: The fornix is essential to a fully functioning memory system and is implicated in nearly all neurological functions that rely on the hippocampus. Future research needs to use optimized DWI methods to study the fornix in vivo, which we discuss, given the difficult nature of fornix reconstruction. Impact Statement The fornix is a white matter tract that connects the hippocampus to several subcortical brain regions and is pivotal for episodic memory functioning. Functionally, the fornix transmits essential neurotransmitters, as well as theta rhythms, to the hippocampus. In addition, it is the conduit by which memories guide decisions. The fornix is biomedically important because lesions to this tract result in irreversible anterograde amnesia. Research using in vivo imaging methods has linked fornix pathology to cognitive aging, mild cognitive impairment, psychosis, epilepsy, and, importantly, Alzheimer's Disease.