The science of ageing
Virtually all of the Cam-CAN analyses, both neuroimaging and
behavioural, are ultimately aimed at integration accoss domains
and modalities to fully understand the ageing process. See pages
analyses for further discussion of cross-modal analyses
using fMRI and MEG
A number of tools and methods are currently under development
for use in integrating across modalities in the Cam-CAN project:
Structural Equation Modeling (SEM) is a methodological framework
to test hypotheses about how a set of variables relate to each
other. In cognitive neuroscience, it can be used to test
hypotheses about brain-behaviour relationships. Since existing SEM
packages are not available within a MATLAB environment, we
developed a MATLAB-based SEM toolbox. This will make the analysis
seamless, since most other analyses for the project will also be
done in MATLAB.
The toolbox allows for model specification, model estimation and
model validation. It can be run through an easy-to-use GUI or in
MATLAB batch-mode. The figure on the right shows the GUI:
A useful feature of the SEM methodology is that it naturally
allows to test hypotheses about how variables of different types
and from different imaging modalities relate to each other.
Further work will include fitting models to data from different
cognitive tests. The range of neuro-imaging variables used will
also be expanded to include novel structural variables (eg. Mean
Diffusivity, Fractional Anisotropy) as well as functional
variables like BOLD activity, ERF amplitude, etc.
A method closely relatd to SEM is that of mediation and
moderation models. Age-related declines in many cognitive
functions are well established; for example older adults
demonstrate declines in episodic memory or language production.
These declines may be mediated by other age-related changes, such
as general-purpose cognitive processes or structural changes in
the brain (e.g. decrease in white matter (WM) integrity connecting
brain regions). Current analyses are examining the ways in which
age-related cognitive decline is mediated by general cognitive
measures, by neural changes, and by cardiovascular fitness (CVF).
For example, we are examining whether WM integrity and CVF could
be influencing cognitive decline independently (see figure below,
panel A). In order to address this question, we used mediation
analysis, which indicated that age-related declines in fluid
intelligence (see figure below, panel C) are mediated by white
matter quality in a number of prefrontal cortical (PFC) regions.
We first performed a whole-brain voxelwise analysis of diffusion
tensor imaging (DTI) data to identify regions of cortical WM that
mediate age-related declines in fluid intelligence (see figure
below, panel B). We then applied these values in our conceptual
mediation model, along with measures of CVF (systolic blood
pressure). This model (see figure below, panel D) demonstrated
that WM had a greater mediating influence than CVF, and
furthermore that the model overall attenuated the relationship
with cognitive decline predicted by age alone. The aim of this
approach is to demonstrate the relative contributions of white
matter health and cardiovascular fitness in predicting individual
differences in age-related cognitive decline.
Cam-CAN participants who have MR scans also watch an excerpt of a
movie to provide information on neural activity in a more
naturalistic setting. A good director makes movies that are highly
engaging, and as a result, activate a broad range of brain
regions. The pictures and sound stimulate the auditory and visual
system; watching people move or talk activates the motor system;
thinking about the intricacies of the plot activates regions in
the frontal and parietal lobe; and so on. This broad activation
provides us with a way to assess many brain regions within one
short scan. We can then look at what is common about the
activation patterns across people; and what changes through the
lifespan. We can examine what aspects of the brain's response
predict performance on another task (e.g., a test of memory).
Thus, a good Director also produces patterns of brain activity
that to the scientist are compelling viewing.
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