Topics

Normal and pathological human brain aging, Alzheimer's disease, mild cognitive impairment, dementia, large scale neuronal networks, white matter hyperintensities, in-vivo amyloid imaging.

Tools

Magnetic resonance imaging (MRI), resting-state fMRI, task-based fMRI, functional connectivity MRI, diffusion imaging, positron emission tomography (PET), longitudinal study design (i.e. multiple measures over time), linear mixed models for handling more than two measures over time and missing data.

Highlights

A review and empirical study regarding resting state functional connectivity (fcMRI). The paper offers practical recommendations regarding scan settings (e.g. TR and voxel size), resting condition (eyes-open with or without a fixation cross, eyes closed), feasibility of a break between two scans, and optimal scan-length.
Van Dijk KRA, Hedden T, Venkataraman A, Evans KC, Lazar SW, and Buckner RL (2010) Intrinsic Functional Connectivity As a Tool For Human Connectomics: Theory, Properties, and Optimization. JNeurophys. 103: 297-321. PDF

A confounding factor in magnetic resonance imaging is head motion: children move more than adults, older adults more than younger adults, and patients more than controls. Head motion during resting-state fMRI was estimated in 1000 healthy young adult subjects. While the majority of variation in functional brain network across subjects was not linked to motion, head motion had significant effects on fcMRI network measures. Not all networks were affected in the same way: some metrics showed decreases and others showed increases with more motion.
Van Dijk KRA, Sabuncu MR, and Buckner RL. (2012) The Influence of Head Motion on Intrinsic Functional Connectivity MRI. NeuroImage. 59(1):431-8:12686-12694. Abstract (e-mail kvandijk (at) nmr.mgh.harvard.edu for full text PDF)

Data from 872 healthy older adults who were tested 3 times over a period of 6 years showed that educational attainment had no significant effect on cognitive change over time. The majority of previous studies had found effects in subgroups but used only data from 2 assessment occasions. The results of the paper have now been replicated by other major longitudinal studies of cognitive aging (e.g. Wilson et al., 2009 Neurology, the Religious Orders Study at Rush University Medical Center, Chicago; and also by Zahodne et al., 2011, the Victoria Longitudinal Study, Victoria and Edmonton, Canada). Note: education may have protective effects in other contexts, for instance, regarding the onset of clinical symptoms of dementia (e.g. Evans et al., Arch Neurol, 1997; Wilson et al., Neurology, 2004) and effects of cerebro-vascular disease (e.g. Ott et al., 1995, MJ, 1995; Ojala-Oksala et al., Stroke, 2012).
Van Dijk KRA, Van Gerven PWM, Van Boxtel MPJ, Van der Elst W, Jolles J. (2008) No Protective Effects of Education during Normal Cognitive Aging: Results from the 6-year follow-up of the Maastricht Aging Study (MAAS), Psychology and Aging. 23(1):119-30. PDF

This editorial regarding Patrella et al., 2011, contains a very brief introduction to and history of the brain's default network and touches upon relevance of measuring this network in disease states such as Alzheimer’s disease.
Van Dijk KRA, and Sperling RA. (2011) Defaulting on the default network: Increased risk for dementia. Neurology. 76(6):498-500. PDF

A short paper written in Dutch introducing the default network.
Koene van Dijk. Activiteit in het brein als men gevraagd wordt ‘niets’ te doen – Het functionele basisnetwerk van de hersenen (Brain activity when people are asked to do ‘nothing’ - default mode network of the brain). Neuropraxis, 2008; 3: 86-91. PDF