Quantitative Modelling of Cognitive Decline

Teacher: dr. Goran Šimić, professor, MD
Semester: third
ECTS: 4
Elective course

Students should acquire capacity to understand:

  1. Cognitive decline in humans and experimental models.
  2. Statistical methods, neuroimaging methods, molecular methods and hidden goal task used in prediction of cognitive decline.

Following completion of the course students will be able to:

  1. explain cognitive decline in human and experimental models,
  2. explain the current understanding of the aging process in humans and experimental models, and from a neuropsyhological perspective,
  3. use statistical methods in analysis of cognitive decline.
  1. Molecular mechanisms of aging from cells to organisms: evolutionary theories of aging, theoretical models of aging, Gompertz-Makeham mortality curves, and progeroid syndromes.
  2. Genetic influence on lifespan and longevity: results from twin studies; neurodevelopmental origin of individual differences in cortical architecture in middle-aged adults: genetic dependence of cortical thickness.
  3. Molecular mechanisms of aging from cells to organisms: evolutionary theories of aging, theoretical models of aging, Gompertz-Makeham mortality curves, and progeroid syndromes.
  4. Genomic mosaicism of developing and adult brain (unlinked and linked to germline mutations); somatic APP gene recombination in Alzheimer’s disease.
  5. Experimental models of aging in Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster, and Mus musculus.
  6. Genome-wide association studies of cognitive capabilities and educational attainment: heritability and polygenic nature of human intelligence (with emphasis on differences between crystallized and fluid-type intelligence).
  7. Clinical variables and biomarkers in prediction of cognitive decline and slowing of perceptual processing speed in older adults using logistic, linear, and multivariate regression models.
  8. Subjective cognitive impairment, imaging cognitive decline by visualization of brain atrophy (MRI) and decreased functional connectivity and metabolic activity (fMRI, PET), differential diagnosis of minor neurocognitive disorder (mild cognitive impairment) and major neurocognitive disorder (dementia).
  9. Horvath’s and Hannum’s epigenetic aging clocks and their applications: positive and negative epigenetic drifts, risk factors and epigenetic rejuvenation (reversibility of epigenetic changes and reprogramming of aged cells), epigenetic prediction of time to death.
  10. Description of all steps in development of a new system to detect early mild cognitive impairment (MCI) based on a hidden goal task (HGT) test will be described; Upon explanation of calculation of positive and negative predictive values at different cohort prevalences for MCI, students will have to determine potential of the test for diagnostic and/or screening purposes based on a given data set.
  • Course objectives

    Students should acquire capacity to understand:

    1. Cognitive decline in humans and experimental models.
    2. Statistical methods, neuroimaging methods, molecular methods and hidden goal task used in prediction of cognitive decline.
  • Expected learning outcomes

    Following completion of the course students will be able to:

    1. explain cognitive decline in human and experimental models,
    2. explain the current understanding of the aging process in humans and experimental models, and from a neuropsyhological perspective,
    3. use statistical methods in analysis of cognitive decline.
  • Course content

    1. Molecular mechanisms of aging from cells to organisms: evolutionary theories of aging, theoretical models of aging, Gompertz-Makeham mortality curves, and progeroid syndromes.
    2. Genetic influence on lifespan and longevity: results from twin studies; neurodevelopmental origin of individual differences in cortical architecture in middle-aged adults: genetic dependence of cortical thickness.
    3. Molecular mechanisms of aging from cells to organisms: evolutionary theories of aging, theoretical models of aging, Gompertz-Makeham mortality curves, and progeroid syndromes.
    4. Genomic mosaicism of developing and adult brain (unlinked and linked to germline mutations); somatic APP gene recombination in Alzheimer’s disease.
    5. Experimental models of aging in Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster, and Mus musculus.
    6. Genome-wide association studies of cognitive capabilities and educational attainment: heritability and polygenic nature of human intelligence (with emphasis on differences between crystallized and fluid-type intelligence).
    7. Clinical variables and biomarkers in prediction of cognitive decline and slowing of perceptual processing speed in older adults using logistic, linear, and multivariate regression models.
    8. Subjective cognitive impairment, imaging cognitive decline by visualization of brain atrophy (MRI) and decreased functional connectivity and metabolic activity (fMRI, PET), differential diagnosis of minor neurocognitive disorder (mild cognitive impairment) and major neurocognitive disorder (dementia).
    9. Horvath’s and Hannum’s epigenetic aging clocks and their applications: positive and negative epigenetic drifts, risk factors and epigenetic rejuvenation (reversibility of epigenetic changes and reprogramming of aged cells), epigenetic prediction of time to death.
    10. Description of all steps in development of a new system to detect early mild cognitive impairment (MCI) based on a hidden goal task (HGT) test will be described; Upon explanation of calculation of positive and negative predictive values at different cohort prevalences for MCI, students will have to determine potential of the test for diagnostic and/or screening purposes based on a given data set.
PMF
EU fondovi
UNI-ZG