Emmanuel A Stamatakis
Centre for Speech, Language and the Brain,
Department of Experimental Psychology,
University of Cambridge
School of Psychological Sciences &
Division of Imaging Science and Biomedical Engineering,
School of Medicine,
University of Manchester
Hemispheric connectivity in ageing
Hemispheric connectivity in ageing
•Cognitive functions underpinned by an anatomically distributed neural system in which different neuronal regions are connected e.g.: Language
Hemispheric connectivity in ageing
•Emphasis on understanding cognition and the ageing brain is in terms of regional changes i.e. which brain regions show age-related changes
Hemispheric connectivity in ageing
• Need to examine age related changes in connectivity to determine whether related to impaired/preserved function
Hemispheric connectivity in ageing
•To address questions of age related changes in connectivity and relationship to changes in cognitive function we combine:
a) Cognitive performanceBehavioural data (studies based on cognitive models)
b) Functional MRIUse fMRI with subtractive designs e.g. condition A – BaselineEstablish interactions (influences, modulations) between
regions with functional connectivity analysis
c) Structural MRI Establish region-specific grey/white matter atrophy
d) Diffusion Tensor MRI Establish white matter tract integrity & subcortical pathways
The language system
•Activity within this system modulated by different linguistic processes•Important that language is strongly left-lateralised; gives us an opportunity to look at RH contributions with age•How does language processing change with age?
Example from Language: Processing word structure
•Core aspect of language processing: To decompose complex words into stem + affix (jump+ed)
•This process engages a fronto-temporal system (when compared to words that do not require this kind of decomposition e.g. slept)
20-40y n=14
0 14
L>R R>L
LIFG MTG
STG
Example from Language: Processing word structure
•Core aspect of language processing: To decompose complex words into stem + affix (jump+ed)
•This process engages a fronto-temporal system (when compared to words that do not require this kind of decomposition e.g. slept)
20-40y n=14
0 14
L>R R>L
LIFG MTG
STG
ACC
Functional Connectivity: The method
•Jumped vs. Slept:How do regions within the network influence each other in time?
LIFG
?*
Processing word structure: Functional Connectivity
•The pattern of connectivity between regions differs for the two kinds of words (jumped vs. slept)
* Predictor time series
Stamatakis et al., NeuroImage, 2005
•The ACC modulates fronto-temporal connectivity (> jumped) Interactions left lateralised
L R
**ACC LIFG L STS
L MTG R STS
Young: 20-40y n=14
Functional Connectivity underpinned by Anatomical Connections?
Anatomical Connectivity: Diffusion Tensor Imaging
•Measure white matter integrity by Fractional Anisotropy (FA)
•FA measures directionality of tracts and integrity of WM tissue
•Higher FA values have been related to increases in WM organization/integrity
•DTI images used to calculate WM tracts
•Measure white matter integrity by Fractional Anisotropy (FA)
•FA measures directionality of tracts and integrity of WM tissue
•Higher FA values have been related to increases in WM organization/integrity
•DTI images used to calculate WM tracts
Functional Connectivity underpinned by Anatomical Connections?
Anatomical Connectivity: Diffusion Tensor Imaging
Anatomical Connectivity: DTI
Anterior-posterior, Left-right, Feet-head
Directional FA
Anterior-posterior, Left-right, Feet-head
SLFSLF
ILFILF
Anatomical Connectivity: DTI
Directional FA
DTI: Hemispheric comparison
•DTI: More coherence in white matter tracts in LH
•This may explain functional connectivity between regions
In preparation
DTI, Contribution of white matter tracts
•White matter tracts connecting areas activated in fMRI study (words which need to be decomposed - jumped
vs. those that do not - slept)
L
In progress
**
1 6
•Fronto-temporal connectivity supported by anatomical connectivity
SLF
LIFG LMTG
L R**
ACC
LIFG L MTG
Processing word structure in young
Summary
•Primarily L fronto-temporal system
-Modulated by different linguistic processes e.g. decomposition
-Anatomically distinct regions connected functionally
-Underpinned by white matter tracts - especially ILF and SLF
-What happens to this system as we age?
Ageing
19
Ageing
30
Ageing
50
Ageing
68
Ageing
80
Ageing
90
Ageing
9019
Ageing, statistical assessment of grey matter atrophy
A voxel by voxel statistical analysis is used to detect regional differences in the amount of grey matter between populations
Ageing: Evidence of neural atrophy
•Neural atrophy increases with age (Structural MRI evidence) •How does this affect cognition?
L R
4 t-scores 12
Volunteers aged 20-75y old (n=28)
Stamatakis & Tyler, 2006
Extent of age-related changes in grey matter for this group
Effect of neural atrophy on cognition with age? e.g. processing word structure
•Reaction time difference for words which need to be decomposed compared to those that do not
•Takes longer to recognise a word that needs to be decomposed (jump+ed), and this is the same across age.
-150
-100
-50
0
50
100
150
200
older younger
RT
dif
fere
nc
es
(m
s)
Stamatakis & Tyler, 2006
Effect of neural atrophy on cognition with age? e.g. processing word structure
•Reaction time difference for words which need to be decomposed compared to those that do not
-150
-100
-50
0
50
100
150
200
older younger
RT
dif
fere
nc
es
(m
s)
Stamatakis & Tyler, 2006
In spite of neural atrophy, no cognitive deficit. Is this evidence for plasticity?
Processing word structure (jumped vs. slept)
Older volunteers (60-75y old)
•Decomposing complex words into stem + affix (jump+ed) activates fronto-temporal system in older group
•No differences between old and young in regions involved 60-75y n=14
•Is cognitive preservation associated with changes in functional connectivity?
L RL S/MTG
R S/MTG
ACC
LIFG
Old-Young
L R
Processing word structure (jumped vs. slept)
All volunteers (20-75y old)
L R
Stamatakis & Tyler, 2006
ACC
LHseeds
Older (60-75)
RHseeds
Younger (20-40)
* *LIFG
ACC
* *
LIFG
ACC
**RIFG
ACC
**RIFG
* Predictor time series
L R
•Does functional connectivity change with age?
Processing word structure (jumped vs. slept)
All volunteers (20-75y old)
•Does functional connectivity change with age?
L R
Stamatakis & Tyler, 2006
ACC
LHseeds
Older (60-75)
RHseeds
Younger (20-40)
* *LIFG
ACC
* *
LIFG
ACC
**RIFG
ACC
**RIFG
* Predictor time series
L R
Processing word structure (jumped vs. slept)
All volunteers (20-75y old)
L R
Stamatakis & Tyler, 2006
ACC
LHseeds
Older (60-75)
RHseeds
Younger (20-40)
* *LIFG
ACC
* *
LIFG
ACC
**RIFG
ACC
**RIFG
* Predictor time series
L R
•Does functional connectivity change with age?
Processing word structure (jumped vs. slept)
All volunteers (20-75y old)
* Predictor time series
L R
Stamatakis & Tyler, 2006
ACC
LHseeds
Older (60-75)
RHseeds
Younger (20-40)
* *LIFG
ACC
* *
LIFG
ACC
**RIFG
ACC
**RIFG
LeftLateralised Bi-Lateral
•Does functional connectivity change with age?
White matter changes with age
All volunteers n=28 (20-75y old)
• DTI - decreased integrity with increasing age
•Does this affect functional connectivity?In preparation
Ageing: Evidence of neural atrophy
•Neural atrophy increases with age (Structural MRI evidence) •How does this affect cognition?
L R
4 t-scores 12
Volunteers aged 20-75y old (n=28)
Stamatakis & Tyler, 2006
Extent of age-related changes in grey matter for this group
Ageing: Evidence of neural atrophy
•Neural atrophy increases with age (Structural MRI evidence) •How does this affect cognition?
L R
4 t-scores 12
Volunteers aged 20-75y old (n=28)
Stamatakis & Tyler, 2006
Extent of age-related changes in grey matter for this group
Summary
1. Regions involved in this linguistic process show significant atrophy with age
2. Preserved cognitive function
3. Similar networks appear to be activated in young and old
BUT changes in fronto-temporal functional connectivity-becomes more bilateral
Summary
• Changes in connectivity with increasing age:
Due to grey and/or white matter deterioration
• In spite of neural deterioration, cognitive performance on this task is preserved across the life-span
Due to recruitment of RH ?
Thank you
•Lorraine K. Tyler
•William Marslen-Wilson
•Billi Randal
•Meredith Shafto