NEUROLOGICAL ASPECTS:
NEURAL NETWORKS AND
REORGANIZATION
Academiejaar 2023-2024 – 2MARE
H1. CLINICAL RELEVANCE AND
INTERPRETATION ISSUES
H2. PARKINSONIAN DEFICITS AND
SPONTANEAOUS ADAPTATION
H3. NEURAL CORRELATES OF FREEZING OF
GAIT
H4. NEURAL ASPECTS OF ADAPTATION
PART PROF. MORAN GILAT
, PART MORAN GILAT
Neurological aspects: neural networks
and reorganization
CHAPTER 1: CLINICAL RELEVANCE AND INTERPRETATION ISSUES
Why do we need to know about neural correlates en brain mechanisms as neurotherapists?
1. Behaviour alone can mask recovery as patients put in effort – true neural recovery hidden?
2. Knowledge of neural mechanisms → thinking more deeply about therapy
3. Provide inspiration for a different approach to therapy
But knowledge to date is very incomplete and comes from different sources. Interpretation into single
coherent picture is difficult.
Link therapy improvement to changes in the brain → how did we as therapists make that
change happen?
Direct measures of brain activity Indirect measures of brain activity
• EEG (increasingly more mobile) • Magnetic resonance imaging
• Transcranial Magnetic Stimulation • Functional
• Resting state
The brain is a connection-organ: network analyses are • Diffusion tensor and structural imaging
increasing and combined methods (multimodal) • White matter integrity
Indicates methods prone to network analyses • Grey matter thickness
• Functional Near-Infrared Spectroscopy (mobile)
→ Multiple areas in the brain are talking together to achieve certain behaviours
➢ Past: studies only look at activity
➢ Now: brain is always connected to each other (more network analysis studies)
1.1 Neuroplasticity & neuroscientific methods
Molecular imaging: indirect measures of brain activity PET using radio-tracers
It typically binds to water, oxygen or glucose (glucose most common → the more active brain
region is, the more sugar it needs, more glucose attracted to those regions)
Measures of neurotransmitter metabolism PET imaging using radio-tracers
Dopamine transporters (DAT)
DAT-scan = we see areas where dopamine is mostly released (putamen is lighted up
in the left picture)
o PD in early stage: putamen only anteriorly (posterior part is diminished, goes down
first in PD)
▪ Anterior = involved with goal-directed movement and cognition
▪ Posterior = involved in automatic movements
o Left side more transporters compared to right side → unilateral-onset of the disease
(this is a left side onset patient, because the right side is diminished first
Physiotherapy/ PA can slow down this process
→ Careful first evidence to suggest that regular physical activity can slow down this process.
1
, PART MORAN GILAT
1.2 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)
o Hippocampus: short-term memory storage location
o Striatum: motor learning
o BDNF = stimulates neuronal growth
➢ Grey matter (change of cortical thickness or shape of subcortical nuclei)
o Exact neuronal cellular processes that underlie these changes are unknown.
o Exercise-induced higher cortical thickness appears to occur rapidly in M1, through
arborization of dendrites and dendritic spine growth
o Grey matter = neuronal bodies
➢ White matter (WM integrity)
o Decreased: probably refers to poor neural efficiency, but multimodal studies are not
providing consistent results
o White matter fibre structure changes are difficult to measure
o Increased: desirable outcome (slow) of rehabilitation. It can also indicate adaptive or
maybe maladaptive compensation. Therefore, comparison between pathological
groups and healthy controls is therefore very important!
▪ Decrease in myelinisation (loss of connection)
▪ Not necessarily less activity: the efficiency might increase (less ways needed
to get the same effect)
▪ There is a lot of crossing-fibres between axons
▪ Any structural change goes slow and the change has to be quite big to measure
it with neuro-imaging
1.2.1 Example of between group WM-changes
☞ Comparing WM tracts in 19 freezers,16 non-freezers and 18 controls, correlated to worse freezing
and behaviour on a balance task
• Visualization (3D) of WM streamlines between right mesencephalic locomotor region (MLR)
and left cerebellum from a randomly chosen non-freezer. The color of the streamline specifies
the direction (red: mediolateral; blue: inferior-superior; green: anteroposterior).
• There is a connection between a region in the brain stem (mesencephalon) and the cerebellum
INTERPRETATION:
- Freezers showed a lower biological connectivity in the WM tract between the right MLR
(mesencephalic locomotor region) and the right caudate than controls, associated with worse
severe freezing. (Right MLR-Putamen is not correlated with behaviour)
- Stronger biological integrity between cerebellar vermis en left pallidum, compensatory in
freezers (like controls)?
→ Right MLR – right caudate:
➢ Green: highest WM-integrity
➢ Connection: the lower, the worse the freezing → decreased WM-integrity = worse FIG
2
NEURAL NETWORKS AND
REORGANIZATION
Academiejaar 2023-2024 – 2MARE
H1. CLINICAL RELEVANCE AND
INTERPRETATION ISSUES
H2. PARKINSONIAN DEFICITS AND
SPONTANEAOUS ADAPTATION
H3. NEURAL CORRELATES OF FREEZING OF
GAIT
H4. NEURAL ASPECTS OF ADAPTATION
PART PROF. MORAN GILAT
, PART MORAN GILAT
Neurological aspects: neural networks
and reorganization
CHAPTER 1: CLINICAL RELEVANCE AND INTERPRETATION ISSUES
Why do we need to know about neural correlates en brain mechanisms as neurotherapists?
1. Behaviour alone can mask recovery as patients put in effort – true neural recovery hidden?
2. Knowledge of neural mechanisms → thinking more deeply about therapy
3. Provide inspiration for a different approach to therapy
But knowledge to date is very incomplete and comes from different sources. Interpretation into single
coherent picture is difficult.
Link therapy improvement to changes in the brain → how did we as therapists make that
change happen?
Direct measures of brain activity Indirect measures of brain activity
• EEG (increasingly more mobile) • Magnetic resonance imaging
• Transcranial Magnetic Stimulation • Functional
• Resting state
The brain is a connection-organ: network analyses are • Diffusion tensor and structural imaging
increasing and combined methods (multimodal) • White matter integrity
Indicates methods prone to network analyses • Grey matter thickness
• Functional Near-Infrared Spectroscopy (mobile)
→ Multiple areas in the brain are talking together to achieve certain behaviours
➢ Past: studies only look at activity
➢ Now: brain is always connected to each other (more network analysis studies)
1.1 Neuroplasticity & neuroscientific methods
Molecular imaging: indirect measures of brain activity PET using radio-tracers
It typically binds to water, oxygen or glucose (glucose most common → the more active brain
region is, the more sugar it needs, more glucose attracted to those regions)
Measures of neurotransmitter metabolism PET imaging using radio-tracers
Dopamine transporters (DAT)
DAT-scan = we see areas where dopamine is mostly released (putamen is lighted up
in the left picture)
o PD in early stage: putamen only anteriorly (posterior part is diminished, goes down
first in PD)
▪ Anterior = involved with goal-directed movement and cognition
▪ Posterior = involved in automatic movements
o Left side more transporters compared to right side → unilateral-onset of the disease
(this is a left side onset patient, because the right side is diminished first
Physiotherapy/ PA can slow down this process
→ Careful first evidence to suggest that regular physical activity can slow down this process.
1
, PART MORAN GILAT
1.2 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)
o Hippocampus: short-term memory storage location
o Striatum: motor learning
o BDNF = stimulates neuronal growth
➢ Grey matter (change of cortical thickness or shape of subcortical nuclei)
o Exact neuronal cellular processes that underlie these changes are unknown.
o Exercise-induced higher cortical thickness appears to occur rapidly in M1, through
arborization of dendrites and dendritic spine growth
o Grey matter = neuronal bodies
➢ White matter (WM integrity)
o Decreased: probably refers to poor neural efficiency, but multimodal studies are not
providing consistent results
o White matter fibre structure changes are difficult to measure
o Increased: desirable outcome (slow) of rehabilitation. It can also indicate adaptive or
maybe maladaptive compensation. Therefore, comparison between pathological
groups and healthy controls is therefore very important!
▪ Decrease in myelinisation (loss of connection)
▪ Not necessarily less activity: the efficiency might increase (less ways needed
to get the same effect)
▪ There is a lot of crossing-fibres between axons
▪ Any structural change goes slow and the change has to be quite big to measure
it with neuro-imaging
1.2.1 Example of between group WM-changes
☞ Comparing WM tracts in 19 freezers,16 non-freezers and 18 controls, correlated to worse freezing
and behaviour on a balance task
• Visualization (3D) of WM streamlines between right mesencephalic locomotor region (MLR)
and left cerebellum from a randomly chosen non-freezer. The color of the streamline specifies
the direction (red: mediolateral; blue: inferior-superior; green: anteroposterior).
• There is a connection between a region in the brain stem (mesencephalon) and the cerebellum
INTERPRETATION:
- Freezers showed a lower biological connectivity in the WM tract between the right MLR
(mesencephalic locomotor region) and the right caudate than controls, associated with worse
severe freezing. (Right MLR-Putamen is not correlated with behaviour)
- Stronger biological integrity between cerebellar vermis en left pallidum, compensatory in
freezers (like controls)?
→ Right MLR – right caudate:
➢ Green: highest WM-integrity
➢ Connection: the lower, the worse the freezing → decreased WM-integrity = worse FIG
2
