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Emmanuel A Stamatakis Centre for Speech, Language and the Brain,

Hemispheric connectivity in ageing. 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,

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Emmanuel A Stamatakis Centre for Speech, Language and the Brain,

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  1. Hemispheric connectivity in ageing 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

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

  3. 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

  4. Hemispheric connectivity in ageing • Need to examine age related changes in connectivity to determine whether related to impaired/preserved function

  5. Hemispheric connectivity in ageing • To address questions of age related changes in connectivity • and relationship to changes in cognitive function we combine: a) Cognitive performance • Behavioural data(studies based on cognitive models) b) Functional MRI • Use fMRI with subtractive designs e.g. condition A – Baseline • Establish 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

  6. 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?

  7. Example from Language: Processing word structure L>R R>L STG LIFG MTG 0 14 • 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

  8. Example from Language: Processing word structure ACC L>R R>L STG LIFG MTG 0 14 • 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

  9. Functional Connectivity: The method • Jumped vs. Slept: • How do regions within the network influence each other • in time? ? * LIFG

  10. Processing word structure: Functional Connectivity * * ACC L STS L MTG LIFG R STS LR • The pattern of connectivity between regions • differs for the two kinds of words (jumped vs. slept) Young: 20-40y n=14 * Predictor time series • The ACC modulates fronto-temporal connectivity (> jumped) • Interactions left lateralised Stamatakis et al., NeuroImage, 2005

  11. 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

  12. 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

  13. Anatomical Connectivity: DTI Directional FA Anterior-posterior, Left-right, Feet-head

  14. Anatomical Connectivity: DTI Directional FA SLF SLF ILF ILF Anterior-posterior, Left-right, Feet-head

  15. DTI: Hemispheric comparison • DTI: More coherence in white matter tracts in LH • This may explain functional connectivity between regions In preparation

  16. DTI, Contribution of white matter tracts 1 6 • White matter tracts connecting areas activated in fMRI study • (words which need to be decomposed - jumped • vs. those that do not - slept) * * ACC L MTG LIFG LR SLF * * LIFG LMTG L • Fronto-temporal connectivity supported by anatomical connectivity In progress

  17. 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?

  18. Ageing 19

  19. Ageing 30

  20. Ageing 50

  21. Ageing 68

  22. Ageing 80

  23. Ageing 90

  24. Ageing 90 19

  25. 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

  26. Ageing: Evidence of neural atrophy 4 t-scores 12 • Neural atrophy increases with age (Structural MRI evidence) • How does this affect cognition? Volunteers aged 20-75y old (n=28) L R Extent of age-related changes in grey matter for this group Stamatakis & Tyler, 2006

  27. Effect of neural atrophy on cognition with age? e.g. processing word structure 200 150 100 50 RT differences (ms) 0 older younger -50 -100 -150 • 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. Stamatakis & Tyler, 2006

  28. Effect of neural atrophy on cognition with age? e.g. processing word structure 200 150 100 50 RT differences (ms) 0 older younger -50 -100 -150 • Reaction time difference for words which need to be • decomposed compared to those that do not In spite of neural atrophy, no cognitive deficit. Is this evidence for plasticity? Stamatakis & Tyler, 2006

  29. Processing word structure (jumped vs. slept) Older volunteers (60-75y old) ACC L R LIFG R S/MTG L S/MTG • 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? Old-Young L R

  30. Processing word structure (jumped vs. slept) All volunteers (20-75y old) • Does functional connectivity change with age? * Predictor time series Younger (20-40) Older (60-75) * * * * ACC ACC LIFG LH seeds LIFG LR * * * * ACC ACC RH seeds RIFG RIFG LR Stamatakis & Tyler, 2006

  31. Processing word structure (jumped vs. slept) All volunteers (20-75y old) • Does functional connectivity change with age? * Predictor time series Younger (20-40) Older (60-75) * * * * ACC ACC LIFG LH seeds LIFG LR * * * * ACC ACC RH seeds RIFG RIFG LR Stamatakis & Tyler, 2006

  32. Processing word structure (jumped vs. slept) All volunteers (20-75y old) • Does functional connectivity change with age? * Predictor time series Younger (20-40) Older (60-75) * * * * ACC ACC LIFG LH seeds LIFG LR * * * * ACC ACC RH seeds RIFG RIFG LR Stamatakis & Tyler, 2006

  33. Processing word structure (jumped vs. slept) All volunteers (20-75y old) • Does functional connectivity change with age? * Predictor time series Younger (20-40) Older (60-75) * * * * ACC ACC LIFG LH seeds LIFG Left Lateralised Bi-Lateral * * * * ACC ACC RH seeds RIFG RIFG LR Stamatakis & Tyler, 2006

  34. 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

  35. Ageing: Evidence of neural atrophy 4 t-scores 12 • Neural atrophy increases with age (Structural MRI evidence) • How does this affect cognition? Volunteers aged 20-75y old (n=28) L R Extent of age-related changes in grey matter for this group Stamatakis & Tyler, 2006

  36. Ageing: Evidence of neural atrophy 4 t-scores 12 • Neural atrophy increases with age (Structural MRI evidence) • How does this affect cognition? Volunteers aged 20-75y old (n=28) L R Extent of age-related changes in grey matter for this group Stamatakis & Tyler, 2006

  37. Summary • Regions involved in this linguistic process show significant atrophy with age • Preserved cognitive function • Similar networks appear to be activated in young and old • BUT changes in fronto-temporal functional connectivity • -becomes more bilateral

  38. 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 ?

  39. Thank you • Lorraine K. Tyler • William Marslen-Wilson • Billi Randal • Meredith Shafto

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