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Computational Models and Advanced Digital Techniques in Alzheimer’s Disease

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Handbook of Computational Neurodegeneration

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Abstract

Alzheimer’s disease (AD) is an irreversible and progressive neurodegenerative disease and the most common form of dementia. AD is characterized by two main pathological hallmarks, the plaque deposits of the β-amyloid peptide (Aβ) and the neurofibrillary tangles of the microtubule binding protein tau. The two most well-established AD biomarkers are the biomarker for brain amyloid Aβ protein and CSF/brain tau deposition. The cerebrospinal fluid (CSF) Aβ42 levels are inversely associated with AD risk, meaning that low CSF Aβ42 levels are indicative of an increased AD risk. On the other hand, elevated CSF/brain tau shows a potential AD diagnosis. This biomarker can be validated by imaging techniques seeing as reduced tau uptake on positron emission tomography (PET) in the temporoparietal lobes and atrophy of medial temporal (MTL) on a magnetic resonance imaging (MRI) scan may also reveal an AD diagnosis. Appropriately validated and optimized mathematical models can be used to mechanistically explain the structure of the brain and neural networks. Such models in combination with methods of nonlinear dynamical systems and statistics may help identify and predict brain diseases and disorders. The capabilities of computational models include an understanding of brain function and dysfunction. These models can provide, in unprecedented detail, an understanding of the neurobiological and mental basis of brain disorders such as AD, and this knowledge can offer key insights in disease progression, diagnosis, and treatment. In computational neuroscience, such models are created that can imitate behaviors by conducting simulation experiments on neural simulators.

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Author information

Authors and Affiliations

  1. Tilburg University, Tilburg, Netherlands

    Eleni Stella

  2. HAU, Hellenic American Union, Athens, Greece

    Athanasia Maria Tsiampa

  3. National and Kapodistrian University of Athens, Athens, Greece

    Antonia Stella

Authors
  1. Eleni Stella
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  2. Athanasia Maria Tsiampa
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  3. Antonia Stella
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Corresponding author

Correspondence to Eleni Stella .

Editor information

Editors and Affiliations

  1. Department of Informatics, Ionian University Department of Informatics, Corfu, Greece

    Panayiotis Vlamos

  2. Dept of Physics and Computer Science, Wilfrid Laurier University, Waterloo, ON, Canada

    Ilias S. Kotsireas

  3. ResearchGate, ETH Zurich ResearchGate, Zurich, Zürich, Switzerland

    Ioannis Tarnanas

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Stella, E., Tsiampa, A.M., Stella, A. (2023). Computational Models and Advanced Digital Techniques in Alzheimer’s Disease. In: Vlamos, P., Kotsireas, I.S., Tarnanas, I. (eds) Handbook of Computational Neurodegeneration. Springer, Cham. https://doi.org/10.1007/978-3-319-75479-6_47-1

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  • DOI: https://doi.org/10.1007/978-3-319-75479-6_47-1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-75479-6

  • Online ISBN: 978-3-319-75479-6

  • eBook Packages: Springer Reference Biomedicine and Life SciencesReference Module Biomedical and Life Sciences

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