Impaired Memory Awareness and Loss Integration in Self-Referential Network Across the Progression of Alzheimer's Disease Spectrum

Deep Learning of Speech Data for Early Detection of Alzheimer's Disease in the Elderly

BACKGROUND

Alzheimer's disease (AD) is the most common form of dementia, which makes the lives of patients and their families difficult for various reasons. Therefore, early detection of AD is crucial to alleviating the symptoms through medication and treatment.

OBJECTIVE

Given that AD strongly induces language disorders, this study aims to detect AD rapidly by analyzing the language characteristics.

MATERIALS AND METHODS

The mini-mental state examination for dementia screening (MMSE-DS), which is most commonly used in South Korean public health centers, is used to obtain negative answers based on the questionnaire. Among the acquired voices, significant questionnaires and answers are selected and converted into mel-frequency cepstral coefficient (MFCC)-based spectrogram images. After accumulating the significant answers, validated data augmentation was achieved using the Densenet121 model. Five deep learning models, Inception v3, VGG19, Xception, Resnet50, and Densenet121, were used to train and confirm the results.

RESULTS

Considering the amount of data, the results of the five-fold cross-validation are more significant than those of the hold-out method. Densenet121 exhibits a sensitivity of 0.9550, a specificity of 0.8333, and an accuracy of 0.9000 in a five-fold cross-validation to separate AD patients from the control group.

CONCLUSIONS

The potential for remote health care can be increased by simplifying the AD screening process. Furthermore, by facilitating remote health care, the proposed method can enhance the accessibility of AD screening and increase the rate of early AD detection.

Altered structural and functional homotopic connectivity associated with the progression from mild cognitive impairment to Alzheimer's disease

The progressive mild cognitive impairment (pMCI) is associated with an increased risk of Alzheimer's disease (AD). Many studies have reported the disrupted brain alteration during the imminent conversion from pMCI to AD. However, the subtle difference of structural and functional of inter-hemispheric between pMCI and stable mild cognitive impairment (sMCI) remains unknown. In the present study, we scanned the multimodal magnetic resonance imaging of 38 sMCI, 26 pMCI, and 50 healthy controls (HC) and assessed the cognitive function. The voxel-mirrored homotopic connectivity (VMHC) and volume of corpus callosum were calculated. A structural equation modeling (SEM) was established to determine the relationships between the corpus callosum, the inter-hemispheric connectivity, and cognitive assessment. Compared to sMCI, pMCI exhibited decreased VMHC in insular and thalamus, and reduced volume of corpus callosum. SEM results showed that decreased inter-hemispheric connectivity was directly associated with cognitive impairment and corpus callosum atrophy, and corpus callosum atrophy indirectly caused cognitive impairment by mediating inter-hemispheric connectivity in pMCI. In conclusion, the destruction of homotopic connectivity is related to cognitive impairment, and the corpus callosum atrophy partially mediates the association between the homotopic connectivity and cognitive impairment in pMCI.

Differential Abnormality in Functional Connectivity Density in Preclinical and Early-Stage Alzheimer's Disease

Background

Both subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI) have a high risk of progression to Alzheimer's disease (AD). While most of the available evidence described changes in functional connectivity (FC) in SCD and aMCI, there was no confirmation of changes in functional connectivity density (FCD) that have not been confirmed. Therefore, the purpose of this study was to investigate the specific alterations in resting-state FCD in SCD and aMCI and further assess the extent to which these changes can distinguish the preclinical and early-stage AD.

Methods

A total of 57 patients with SCD, 59 patients with aMCI, and 78 healthy controls (HC) were included. The global FCD, local FCD, and long-range FCD were calculated for each voxel to identify brain regions with significant FCD alterations. The brain regions with abnormal FCD were then used as regions of interest for FC analysis. In addition, we calculated correlations between neuroimaging alterations and cognitive function and performed receiver-operating characteristic analyses to assess the diagnostic effect of the FCD and FC alterations on SCD and aMCI.

Results

FCD mapping revealed significantly increased global FCD in the left parahippocampal gyrus (PHG.L) and increased long-range FCD in the left hippocampus for patients with SCD when compared to HCs. However, when compared to SCD, patients with aMCI showed significantly decreased global FCD and long-range FCD in the PHG.L. The follow-up FC analysis further revealed significant variations between the PHG.L and the occipital lobe in patients with SCD and aMCI. In addition, patients with SCD also presented significant changes in FC between the left hippocampus, the left cerebellum anterior lobe, and the inferior temporal gyrus. Moreover, changes in abnormal indicators in the SCD and aMCI groups were significantly associated with cognitive function. Finally, combining FCD and FC abnormalities allowed for a more precise differentiation of the clinical stages.

Conclusion

To our knowledge, this study is the first to investigate specific alterations in FCD and FC for both patients with SCD and aMCI and confirms differential abnormalities that can serve as potential imaging markers for preclinical and early-stage Alzheimer's disease (AD). Also, it adds a new dimension of understanding to the diagnosis of SCD and aMCI as well as the evaluation of disease progression.

Hyperconnectivity Associated with Anosognosia Accelerating Clinical Progression in Amnestic Mild Cognitive Impairment

The incidence and prevalence of anosognosia are highly variable in amnestic mild cognitive impairment (aMCI) patients. The study aims to explore the neuropathological mechanism of anosognosia in aMCI patients using two different but complementary technologies, including ¹⁸F-flortaucipir positron emission tomography and resting state functional magnetic resonance imaging. The study found that anosognosia was related to higher tau accumulation in the left medial orbitofrontal cortex (OFC), left posterior cingulate cortex, and right precuneus in aMCI patients. Intrinsic functional connectivity analyses found significant correlations between anosognosia index and hypoconnectivity between the left medial OFC and left middle temporal gyrus (MTG), right precuneus and left lingual gyrus. Longitudinally, the connectivity of these brain regions as well as the right precuneus and right cuneus showed hyperconnectivity in aMCI patients with anosognosia. The anosognosia index was also correlated with AD pathological markers (i.e., Aβ, t-tau, and p-tau) and brain glucose metabolism in aMCI patients. In conclusion, anosognosia in aMCI patients is associated with the dysfunction of medial OFC-MTG circuit and the precuneus-visual cortex circuit and accelerates clinical progression to AD dementia.