scholarly journals fMRI Investigation of Semantic Lexical Processing in Healthy Control and Alzheimer’s Disease Subjects Using Naming Task: A Preliminary Study

2021 ◽  
Vol 11 (6) ◽  
pp. 718
Author(s):  
Yen-Ting Chen ◽  
Chun-Ju Hou ◽  
Natan Derek ◽  
Min-Wei Huang
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Neural Activity ◽  
Lexical Processing ◽  
Inferior Frontal Gyrus ◽  
Naming Task ◽  
Compensatory Mechanism ◽  
Healthy Control ◽  
Preliminary Study ◽  
Ad Alzheimer’S Disease

For decades, scientists have been trying to solve the problem of dementia, with no cure currently available. Semantic–lexical impairment is well established as the early critical sign of dementia, although there are still gaps in knowledge that must be investigated. In this study, we used fMRI to observe the neural activity of 31 subjects, including 16 HC (Healthy Control) and 15 AD (Alzheimer’s Disease), who participated in the naming task. The neuropsychology profile of HC (Healthy Control) and AD (Alzheimer’s Disease) are discussed in this study. The involvement of FG (Fusiform Gyrus) and IFG (Inferior Frontal Gyrus) shows dominant activation in both of the groups. We observed a decrease in neural activity in the AD group, resulting in semantic deficit problems in this preliminary study. Furthermore, ROI analysis was performed and revealed both hyperactivation and hypoactivation in the AD group. The compensatory mechanism demonstrated during the task, due to the effort required to identify an animal’s name, represents the character profile of AD.

Structural Changes in Thalamic Nuclei Across Prodromal and Clinical Alzheimer’s Disease

2021 ◽  
pp. 1-11
Author(s):  
Adam S. Bernstein ◽  
Steven Z. Rapcsak ◽  
Michael Hornberger ◽  
Manojkumar Saranathan ◽  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Large Scale ◽  
Structural Changes ◽  
Thalamic Nuclei ◽  
Medial Temporal Lobes ◽  
Cognitive Changes ◽  
Temporal Lobes ◽  
Medial Geniculate ◽  
Healthy Control

Background: Increasing evidence suggests that thalamic nuclei may atrophy in Alzheimer’s disease (AD). We hypothesized that there will be significant atrophy of limbic thalamic nuclei associated with declining memory and cognition across the AD continuum. Objective: The objective of this work was to characterize volume differences in thalamic nuclei in subjects with early and late mild cognitive impairment (MCI) as well as AD when compared to healthy control (HC) subjects using a novel MRI-based thalamic segmentation technique (THOMAS). Methods: MPRAGE data from the ADNI database were used in this study (n = 540). Healthy control (n = 125), early MCI (n = 212), late MCI (n = 114), and AD subjects (n = 89) were selected, and their MRI data were parcellated to determine the volumes of 11 thalamic nuclei for each subject. Volumes across the different clinical subgroups were compared using ANCOVA. Results: There were significant differences in thalamic nuclei volumes between HC, late MCI, and AD subjects. The anteroventral, mediodorsal, pulvinar, medial geniculate, and centromedian nuclei were significantly smaller in subjects with late MCI and AD when compared to HC subjects. Furthermore, the mediodorsal, pulvinar, and medial geniculate nuclei were significantly smaller in early MCI when compared to HC subjects. Conclusion: This work highlights nucleus specific atrophy within the thalamus in subjects with early and late MCI and AD. This is consistent with the hypothesis that memory and cognitive changes in AD are mediated by damage to a large-scale integrated neural network that extends beyond the medial temporal lobes.

scholarly journals Joint Assessment of Structural, Perfusion, and Diffusion MRI in Alzheimer's Disease and Frontotemporal Dementia

2011 ◽  
Vol 2011 ◽  
pp. 1-11 ◽  
Author(s):  
Yu Zhang ◽  
Norbert Schuff ◽  
Christopher Ching ◽  
Duygu Tosun ◽  
Wang Zhan ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Frontotemporal Dementia ◽  
Diffusion Tensor ◽  
Healthy Control ◽  
Multimodal Mri ◽  
Imaging Markers ◽  
And Diffusion ◽  
Joint Assessment ◽  
Diffusion Tensor Imaging Dti

Most MRI studies of Alzheimer's disease (AD) and frontotemporal dementia (FTD) have assessed structural, perfusion and diffusion abnormalities separately while ignoring the relationships across imaging modalities. This paper aimed to assess brain gray (GM) and white matter (WM) abnormalities jointly to elucidate differences in abnormal MRI patterns between the diseases. Twenty AD, 20 FTD patients, and 21 healthy control subjects were imaged using a 4 Tesla MRI. GM loss and GM hypoperfusion were measured using high-resolution T1 and arterial spin labeling MRI (ASL-MRI). WM degradation was measured with diffusion tensor imaging (DTI). Using a new analytical approach, the study found greater WM degenerations in FTD than AD at mild abnormality levels. Furthermore, the GM loss and WM degeneration exceeded the reduced perfusion in FTD whereas, in AD, structural and functional damages were similar. Joint assessments of multimodal MRI have potential value to provide new imaging markers for improved differential diagnoses between FTD and AD.

P3-138: Moral judgment in Alzheimer's disease: A preliminary study

2010 ◽  
Vol 6 ◽  
pp. S490-S490
Author(s):  
Eun-Jin Kim ◽  
Ju-Won Ha ◽  
Yeo-Jin Kang ◽  
Se-Won Lim ◽  
Kang-Seob Oh
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Moral Judgment ◽  
Preliminary Study

Lightweight deep residual network for alzheimer’s disease classification using sMRI slices

2021 ◽  
pp. 1-9
Author(s):  
Yanteng Zhang ◽  
Qizhi Teng ◽  
Linbo Qing ◽  
Yan Liu ◽  
Xiaohai He
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Deep Learning ◽  
Computational Cost ◽  
Disease Classification ◽  
Learning Networks ◽  
Feature Maps ◽  
Medical Field ◽  
Widespread Application ◽  
Healthy Control

Alzheimer’s disease (AD) is a degenerative brain disease and the most common cause of dementia. In recent years, with the widespread application of artificial intelligence in the medical field, various deep learning-based methods have been applied for AD detection using sMRI images. Many of these networks achieved AD vs HC (Healthy Control) classification accuracy of up to 90%but with a large number of computational parameters and floating point operations (FLOPs). In this paper, we adopt a novel ghost module, which uses a series of cheap operations of linear transformation to generate more feature maps, embedded into our designed ResNet architecture for task of AD vs HC classification. According to experiments on the OASIS dataset, our lightweight network achieves an optimistic accuracy of 97.92%and its total parameters are dozens of times smaller than state-of-the-art deep learning networks. Our proposed AD classification network achieves better performance while the computational cost is reduced significantly.

scholarly journals Linking the association between circRNAs and Alzheimer’s disease progression by multi-tissue circular RNA characterization

2020 ◽  
Author(s):  
IJu Lo ◽  
Jamie Hill ◽  
Bjarni J. Vilhjálmsson ◽  
Jørgen Kjems
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Inferior Frontal Gyrus ◽  
Circular Rna ◽  
Brain Regions ◽  
Parahippocampal Gyrus ◽  
Circular Rnas ◽  
Cognitive Disability ◽  
Anterior Prefrontal Cortex ◽  
Progressive Course

AbstractAlzheimer’s Disease (AD) has devastating consequences for patients during its slow, progressive course. It is important to understand the pathology of AD onset. Recently, circular RNAs (circRNAs) have been found to participate in many human diseases including cancers and neurodegenerative conditions. In this study, we mined the published dataset on the AMP-AD Knowledge Portal from the Mount Sinai Brain Bank (MSBB) to describe the circRNA profiles at different AD stage in brain samples from four AD patients brain regions, anterior prefrontal cortex, superior temporal lobe, parahippocampal gyrus, and inferior frontal gyrus. We found in total 147 circRNAs to be differentially expressed (DE) during AD progression in the four regions. We also characterized the mRNA-circRNA co-expression network and annotated the potential function of circRNAs based on the co-expressed modules. Based on our results, we propose that parahippocampal gyrus is the most circRNA-regulated region during the AD progression. The strongest negatively AD stage-correlated module in parahippocampal gyrus were enriched in cognitive disability and pathological-associated pathways such as synapse organization and regulation of membrane potential. Finally, the regression model based on the expression pattern of DE circRNAs in the module could help to distinguish the disease severity of patients, further supported the importance of circRNAs in AD pathology. In conclusion, our finding indicates that circRNAs in parahippocampal gyrus are possible regulators of AD progression and potentially be a therapeutic target or of AD.

Sign in / Sign up

Export Citation Format

Share Document