Summary neural networks- Parkinson Disease

Neural networks: parkinson’s disease

NEUROPLASTICITY AND NEUROREHABILITATION

 Why do we need to know about neural correlates and brain mechanisms as neurotherapists?
- 1. Behaviour alone can mask recovery as patients put in effort – true neural (lack of) recovery hidden?
 Als we kijken naar het gedrag van de P weten we niet wat er in de hersenen gebeurd
 Gedrag kan ervoor zorgen dat ze zich beter voordoen dan dat ze eigenlijk zijn (hersenen)
- 2. Knowledge of neural mechanisms  thinking more deeply about the goals of therapy
- 3. Provide inspiration for a different approach to therapy

 But knowledge to date is very incomplete and comes from different sources!
 Interpretation into one coherent picture is difficult.
- Really improved after practice, motor improvement -> yet, the connections in
the brain that are damaged are not altered

 Behaviour can hide things!

 Is it good to generate hyperactivity in the non-affected side of the stroke patient?
- It can be good but also bad… different patients with different patterns
- Reducing hyperactivity can be good in severely affected patients, bad in the early phase of recovery
- What is happening in the brain? Overstimulate unaffected side or opposite?

 Difficult part: this or that? One clear picture on what’s happening in the brain not possible at this moment
- Different sources and methodologies to know more (zie eerdere lessen)
- Coherent picture now not possible, try to make it as coherent as possible

1. METHODS non-invasive
 ← indicates methods prone to network analyses (most likely for network)

 The brain is an connection-organ  network analyses are increasing and combined methods (multimodal)
- Connection-organ -> specific lesion can have an effect on another region
- Network analyses! And combining methods to get an overall view
 Figuuur
- EEG= electrische activiteit
- MRI
 Perfusie
 Bold response= spatial spec
- White matter integrity
 Axonen
- Grey matter thickness
 Nuclei
- Functional near infrared spectroscopy
 Perfusie op cortical niveau


1.1. DIRECT MEASURES OF BRAIN ACTIVITY
 EEG 
- High density cap (really covered with 128 electrodes) to pick up brain activity
- Now already able to use EEG (high density) during active tasks
 More and more mobile method
 Transcranial Magnetic Stimulation
- Directly measuring activity of neurons -> localized measure
- Transcranial: brain facilitated or inhibited




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, Neural networks: parkinson’s disease

1.2. INDIRECT MEASURES OF BRAIN ACTIVITY
 Magnetic resonance imaging
- Functional 
 During a task -> task based functional imaging
- Resting state 
 Just look at how the brain is active in rest
 Learn about tendency of the brain, connect certain areas and others not
 Diffusion tensor and structural imaging
- Diffusion tensor: White matter integrity 
- Structural imaging: Gray matter thickness
 Functional Near-Infrared Spectroscopy (mobile)
- Looking at circulation of the brain during activity
- We do not need a scanner
 P can be active during the measurement
 For completion:
- Molecular imaging – indirect measures of brain activity PET using radio-tracers
 Glucose metabolic tracers
- Measures of neurotransmitter metabolism PET imaging using radiotracers (PD!)
 Dopamine transporters

2. Invasive methods
 Molecular imaging – indirect measures of brain activity PET using radio-tracers
- Glucose metabolic tracers (usually 18F-FDG)
 Gelijkaardig aan bold response
o Hoe actiever region, ↑ suiker, ↑activiteit PET
- PD= ↓ glucose metabolisme
 Measures of neurotransmitter metabolism PET imaging using radio-tracers
- Dopamine transporters (DAT)
 Regio’s dopamine vrijgeven zien
- Figuur
 Healthy
o Cirkel= putamen
 PD
o Frontale zijde licht op= post. Putamen 1st aangedaan
o L>R activiteit= unilateral onset PD
- Veel nigrastriataal dopamine geprojecteerd naar putamen
- Post. Putamen=auto bewegingen
- Ant. Putamen= goal directed bewegingen+ cognitie

 Jin et al. 2023 PaRD
- Careful first evidence to suggest that regular physical activity can slow down this process. Needs
verification in larger study (SPARX3)
- Actievere groep behouden dopamine activiteit beter als minder/ niet actieve groep
 Fysieke activiteit helpt afremmen progressie


INTERPRETATION OF NEURAL MARKERS OF COMPENSATION – RECOVERY
 Neurogenesis
- only possible in hippocampus/striatum in humans, sometimes generated from
neural stem cells and mediated by brain-derived neurotrophic factor (BDNF)
- generatie nieuwe neuronen
- BDNF
 Stim. Neuronale groei, olectric spine groei




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, Neural networks: parkinson’s disease

1. GREY MATTER
 Change of cortical thickness or shape of subcortical nuclei
- Exact neuronal cellular processes that underlie these changes are
unknown. Exercise- induced cortical thickness  appears to occur
rapidly in M1, through arborization of dendrites and dendritic spine
growth → synaptogenesis or metabolic changes?
- We denken geen neurogenesis in cortex
 Wat is corticale dikte ↑ dan?
 Hippocampus = KT-geheugen
 Striatum= rol in motor learning
 BDNF ≠ neuro imaging
- Van CSF/bloed
- Meer = ↑ learning & plasticiteit algemeen
- Depressie= dalen tot min. + flutueren

 Grey matter can be visualized with MRI (M1 = grey matter and CSF) measure the cortical
thickness in the brain. Possibly a marker of recovery.
 We can expect that after exercise there is in the connections of the neurons: dendritic spine
growth and become more prominent. Dendritic spine growth is possible but the exact
process is unknown

 What are the neural markers that indicate recovery? Is neurogenesis a marker?
- It is possible in the hippocampus and also in the striatum = learning centers
- It is likely that there are new neurons generated in these regions
- BDNF = molecule helps generation of neurones
 these levels in the blood can be seen as a marker of recovery
 very careful with this interpretation! Depression: BDNF = low, it can also fluctuate
 not really a reliable marke

2. WHITE MATTER
 Axonen + myelinisatie axonen
 Decreased WM integrity probably refers to poor neural efficiency but multimodal
studies are not providing consistent results
 White matter fibre structure changes are difficult to measure
 Increased WM integrity desirable outcome (usually slow) of rehabilitation. It can also
indicate adaptive or maybe maladaptive compensation. Therefore, comparison between
pathological groups and healthy controls is therefore very important!
- Second marker could be with matter changes, but if you combine studies (WM &
functional changes) -> lower activity
- Reversed story: after recovery/exercise we can see increase WM = slow process
- Difficulty of interpretation:
 Sometimes increase WM can also be an adaptive change, other areas are used more
(compensation) -> more WM light up
 Compensation can be a good thing but also maladaptive (overuse of unaffected side in stroke)
 Therefore: comparison of groups -> control with healthy people
 WMF changes = difficult to measure, not neatly going up or down, cross fibres.
 ↓WM in vb MS, mogelijks bij verouderen
- Of zegggen connecties verloren= minder WM integrity
 Soms zien ↓ WM tracts & bij meten met fMRI niet perse ↓ BOLD-respons
- ↓tracts ≠ ↓activiteit perse
 Efficiënter?
 Steeds interpreteren met andere info vb gedrag / ziekte ernstigheid/…
- ↑ziekte + ↑sympt= slecht
- ↓WM+ ↑performance (gerelateerd aan spontane/ neuroplast) = beter = efficiënter

 Echter WM / GM ∆ duren lang+ veel oefenen voor meetbare ∆
3. EXAMPLE OF BETWEEN GROUP WM CHANGES

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