Aims and objectives
Our goal was to compare the predictive value of the motor speed,
fluid intelligence and crystallized intelligence in estimating the cortical thickness of healthy elderly.
Methods and materials
Forty-six older healthy subjects (37 women,
9 men) over 60 years of age were included in the study.
The participants were examined on two 3.0T MRI scanners (Philips Achieva TX and GE Discovery 750).
The protocol included standard anatomical sequences (to exclude brain pathology) as well as a high-resolution T1-weighted sequence used later for cortical thickness estimation (Philips: repetition time [TR]=8,1ms,
echo time [TE]=3,7ms,
voxel size 1x1x1mm,
flip angle: 8o; GE: TR=8,192ms,
voxel size 1x1x1mm,
The neuropsychological protocol included fluid...
Several interdependencies were discovered (presented in Table 2,
abberrevations: RPM-S: Raven Progressive Matrices Standard version,
WAIS-R: Wechsler Adult Intelligence Scale-Revised,
CTT: Colour Traits Test,
LH – left hemisphere,
RH – right hemisphere).
The fluid intelligence
proved being the best cognitive predictor of the cortical thickness with some paradoxical reversed associations found along the cingulate gyrus (where higher intelligence was associated with thinner grey matter).
The associations discovered demonstrate that the neural mechanisms underlying healthy ageing are complex and heterogenic across different cognitive domains and neuroanatomical regions.
None of the main brain ageing theories seems to provide a suitable interpretative framework
for all the results,
and thus maybe a novel,
more integrative approach should be reconsidered.
The work was founded by National Science Centre Grants PRELUDIUM (UMO-2013/09/HS6/N/02634) and MINIATURA (UMO-2017/01/X/NZ4/00779).
The Freesurfer’s calculations were carried out at the Academic Computer Centre in Gdańsk.
Detailed results can be found in: Naumczyk,
A (2018) Cognitive predictors of cortical thickness in healthy ageing.
Advances in Experimental and Medical Biology,