emmanuel a stamatakis centre for speech, language and the brain,

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


•Cognitive functions underpinned by an anatomically distributed neural system in which different neuronal regions are connected e.g.: Language


•Emphasis on understanding cognition and the ageing brain is in terms of regional changes i.e. which brain regions show age-related changes


• Need to examine age related changes in connectivity to determine whether related to impaired/preserved function


•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)


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)


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


All volunteers (20-75y old)

L R


ACC

LHseeds

Older (60-75)

RHseeds

Younger (20-40)

* *LIFG

ACC

* *

LIFG

ACC

**RIFG

ACC

**RIFG


L R

•Does functional connectivity change with age?




L R


ACC

LHseeds

Older (60-75)

RHseeds

Younger (20-40)

* *LIFG

ACC

* *

LIFG

ACC

**RIFG

ACC

**RIFG


L R




L R


ACC

LHseeds

Older (60-75)

RHseeds

Younger (20-40)

* *LIFG

ACC

* *

LIFG

ACC

**RIFG

ACC

**RIFG

LeftLateralised Bi-Lateral


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)


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

emmanuel a stamatakis centre for speech, language and the brain,

Documents