Summary neural networks- neuroplasticity and aging

Neural networks: neuroplasticity & aging
AGEING – A BIOLOGICAL PERSPECTIVE
 Nine metabolic "hallmarks" of ageing
- 1. genomic instability (mutations in nuclear DNA)
- 2. telomere shortening
- 3. epigenetic alterations (e.g. DNA methylation patterns)
- 4. loss of proteostasis (protein folding and proteolysis)
- 5. deregulated nutrient sensing
- 6. mitochondrial dysfunction
- 7. cellular senescence (accumulation of no longer dividing cells)
- 8. stem cell exhaustion
- 9. altered intercellular communication

 Mutations
- In nuclear DNA/ mitochondria (important for energy production)
 Accumulation of ‘junk’
- Inside cells/ outside cells
- Problems with ‘cleaning’ the cells
 Cells
- Cellular loss – too few new cells
- Cellular senescence – too many old cells (cells fail to die)
 Extracellular cross-links
- Loss of elasticity in tissues

 The processes that characterize neurodegenerative diseases (e.g. Alzheimer’s) take place in most old
brains !
- Bij normal agingook vorm hiervan
 However! some people might have compensatory mechanisms that enable them to cope better with these
processes and to maintain normal cognition
- Compensating mech: bij normale aging meer aanwezig
=> Tempting to view neurodegeneration as accelerated ageing…
- we see the same in an old brain but with less abnormalities as in a neurodegenerating brain
 normal aging= good strategies to cope with/regenerate/restore

AGEING AT THE BRAIN SYSTEM LEVEL
ANATOMICAL CHANGES

 The brain shrinks with age => volume loss
- in both gray matter and white matter
 Gray matter loss may start earlier, but progress more gradually
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 White matter loss may start later, but progress more rapidly

1. GRAY MATTER AND WHITE MATTER VOLUME LOSS
 Most pronounced in frontal lobe, followed by temporal lobe
 Primary sensory areas and occipital lobes seem relatively spared by the shrinking process relevant to
normal aging




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, Neural networks: neuroplasticity & aging

2. DIFFUSION TENSOR IMAGING – DTI
 Fractional anisotrpy – FA
- Structural/ anatomical connectivity

 FA
- ↑warden= ↑ structurele integrity




 Greater age-related reductions in FA in frontal regions, compared to posterior regions
- ~ anterior-posterior gradient of age-related FA reductions
 FA is a sensitive marker of aging that may precede atrophy in many regions of the brain
- ∆in ana.integrity might proceed the volume loss veradering

 Example study – FA of corpus callosum
- Higher FA => better
- mostly in prefrontal lobes, posterior regions are similar in older and younger people
- FA meeste fedaald bij oudere
 Vnl. Super regeions frontal corpus calosum tov post
 Post= vrij intact

3. CONCLUSION ANATOMICAL CHANGES (snelle samenvatti ng )
 GM & WM volumes loss
- GM= grey matter
- WM= white matter
 Loss of white matter integrity (FA)
- Mostly in frontal lobes!

INTRINSIC FUNCTIONAL CHANGES

1. RESTING-STATE FMRI
 Measurement of intrinsic functional connectivity
- Overall, connectivity and network integrity appear to decrease in healthy aging
- Decrease is accelerated in Alzheimer’s disease
- specific systems hit hardest, such as the default mode network (DMN)

2. DEFAULT MODE NETWORK
 One of the most robustly identified and extensively investigated resting state networks
 Includes regions in the
- Posterior cingulate/precuneus
- medial prefrontal cortex
- lateral parietal cortex
 In general, DMN activity increases during rest, but decreases during attention demanding tasks
 Linked to ‘mind-wandering’
- Self-referential thoughts
- Thinking about other
- Remembering the past and thinking about the future




3. EXAMPLE STUDY

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