Nearly 44 million people have Alzheimer’s or related dementia worldwide, according to the Alzheimer’s Disease International organization. That number is expected to double every 20 years. Unlike other books on the market, Alzheimer's Disease: Understanding Biomarkers, Big Data, and Therapy covers recent advancements in cognitive, clinical, neural, and therapeutic aspects of Alzheimer’s and other forms of dementia.
First, readers are introduced to cognitive and clinical studies, focusing on the different types of memory impairment, past and future thinking. This includes the prevalence of depression, its relationship to other symptoms, and the quality of life for those with Alzheimer’s disease. In addition, the book discusses recent studies on memory dysfunction in advanced-stage Alzheimer’s disease, in comparison to early-stage, including a chapter on the underlying factors in the transition from mild cognitive impairment to Alzheimer’s diagnosis. Following this section, the book presents recent studies on the role of different cortical and subcortical structures in the development of various symptoms in Alzheimer’s disease, as well as different neural biomarkers underlying the development and treatment of the disease. In the last section of the book, therapeutic aspects of Alzheimer’s disease, focusing on behavioral and pharmacological treatments of sleep disorders, memory problems, and depression, are reviewed. The book aids readers in understanding the advances in research and care, making it a prime tool for all clinicians, psychologists, researchers, neurologists, and caregivers of dementia patients.
Author(s): Ahmed A. Moustafa
Publisher: Academic Press
Year: 2021
Language: English
Pages: 254
City: London
Front Cover
Alzheimer’s Disease
Copyright Page
Dedication
Contents
List of contributors
Acknowledgments
I. Mental health in dementia
1 Measures of depression in Alzheimer’s disease
Introduction
Measures of depression in AD
Discussion and conclusion
References
2 The nature of depression in dementia: a narrative review
Introduction: the diagnosis, prevalence, and impact of depression in dementia
Methods
Depression as a risk factor for dementia
Subtypes of depression in dementia
Depression and insight
Depression in subtypes of dementia: relation to insight
Conclusions and future work
References
3 Stress and anxiety in dementia
Dementia background
Mental health in dementia
Anxiety and dementia
Anxiety as a risk factor for dementia
The prevalence of anxiety in different types of dementia
Anxiety in early versus late stages of dementia
Stress and dementia
Psychological stress, MCI, and dementia
Childhood stress, midlife stress, and dementia
Posttraumatic stress disorder in dementia
Conclusions
References
II. Advanced topics in dementia research
4 Alzheimer’s disease in the pupil: pupillometry as a biomarker of cognitive processing in Alzheimer’s disease
Introduction
Method
The case study
Procedures and materials
Results
Discussion
References
5 Cognitive and neural correlates of vitamin D deficiency: focus on healthy aging and Alzheimer’s disease
Introduction
Animal studies on cognitive function and vitamin D levels
Healthy aging, dementia, and Alzheimer’s disease
Conclusion
Future implications
Ethics approval and consent to participate
Consent for publication
Availability of data and material
Competing interests
Funding
Authors’ contributions
References
6 The effect of Alzheimer’s disease on the thalamus
Introduction
The effects of Alzheimer’s disease on the thalamus
Volume reduction
Nerve cell loss
Thalamus’s link to other parts of the brain
Hippocampus
Papez circuit
Retrosplenial cortex
Thalamocortical network
Prefrontal-striatal loops and the medial prefrontal cortex
Discussion
Future work
Conclusion
References
7 Using big data methods to understand Alzheimer’s disease
Introduction
What is Alzheimer’s disease?
What causes Alzheimer’s disease?
Are there treatments for Alzheimer’s disease?
How do researchers study Alzheimer’s disease?
Problems with standard Alzheimer’s disease research
Big data methods
What are databases?
The advantages of databases
Common difficulties with databases
Big data analysis
Statistical modeling
Computational modeling
The clinical applications of predictive models
Example: the Alzheimer’s Disease Neuroimaging Initiative
Data types
Mixed predictor models
Conclusion
References
8 Operational aspects of deep learning solutions for Alzheimer’s disease
Introduction
Traditional Alzheimer’s CAD method trends
Introduction
CAD methods in AD research
Data preprocessing
Feature extraction
Classification
External influences on the application of the model
Conclusion
Alzheimer’s in the deep learning context
Introduction
The transition
Deep learning model tasks
Segmentation
Feature extraction
Classification
Common model architectures
LeNet-5
UNET
Visual Geometry Group
ResNet
InceptionV4
Advantages of using deep learning
End-to-end learning
Increased accuracy
Transfer learning
Robustness
Scalability
Limitations of using deep learning
Conclusion
References
III. Treatment of dementia
9 Treatment of depression in Alzheimer’s disease
Introduction
Treatment
Pharmacological treatment
Behavioral treatment
Conclusions
References
10 Developing a Vulnerability to Negative Affect in Dementia Scale (VNADS) for music interventions
Introduction
Method
Item development
Pretesting the items
Piloting the VNADS (proxy) with people with dementia
Results
Pretest of version 1
Pilot of the VNADS (proxy)
Discussion
Funding
Conflict of interests
Acknowledgments
References
11 Using music to improve mental health in people with dementia
Introduction
Music therapy
Anxiety and agitation
Mood and depression
Nontherapist-led music interventions
Well-being, anxiety, mood
Negative versus positive impact of music interventions
Theories of how music therapies and interventions work
Conclusions and future studies
References
12 The efficacy of donepezil for the treatment of Alzheimer’s disease
Introduction
The effects of donepezil in Alzheimer’s disease
The effects of donepezil on the neuropsychological symptoms of AD
The adverse effects of donepezil
The potential effects of donepezil in AD
Combined treatments involving donepezil
Combined cognitive stimulation therapy and donepezil treatment
Combined donepezil and memantine treatment
Conclusion
References
Index
Back Cover
