Healthy and Pathological Neurocognitive Aging: Spectral and Functional Connectivity Analyses Using Magnetoencephalography
- Gianluca Susi, Gianluca SusiComplutense University of Madrid; Technical University of Madrid, Center for Biomedical Technology (CTB); University of Rome “Tor Vergata”
- Jaisalmer de Frutos-Lucas, Jaisalmer de Frutos-LucasUniversidad Autonoma de Madrid, Center for Biomedical Technology (CTB)
- Guiomar Niso, Guiomar NisoTechnical University of Madrid, Center for Biomedical Technology, Biomedical Research Networking Centre on Bioengineering, Biomaterials, and Nanomedicine (CIBER-BBN)
- Su Miao Ye-Chen, Su Miao Ye-ChenComplutense University of Madrid, Center for Biomedical Technology (CTB)
- Luis Antón Toro, Luis Antón ToroComplutense University of Madrid, Center for Biomedical Technology (CTB)
- Brenda Nadia Chino VilcaBrenda Nadia Chino VilcaUniversidad Nacional de San Agustin de Arequipa; Universidad Catolica San Pablo
- and Fernando MaestúFernando MaestúComplutense University of Madrid, Center for Biomedical Technology (CTB), Biomedical Research Networking Centre on Bioengineering, Biomaterials, and Nanomedicine (CIBER-BBN)
Oscillatory activity present in brain signals reflects the underlying time-varying electrical discharges within and between ensembles of neurons. Among the variety of non-invasive techniques available for measuring of the brain’s oscillatory activity, magnetoencephalography (MEG) presents a remarkable combination of spatial and temporal resolution, and can be used in resting-state or task-based studies, depending on the goals of the experiment.
Two important kinds of analysis can be carried out with the MEG signal: spectral a. and functional connectivity (FC) a. While the former provides information on the distribution of the frequency content within distinct brain areas, FC tells us about the dependence or interaction between the signals stemming from two (or among many) different brain areas.
The large frequency range combined with the good resolution offered by MEG makes MEG-based spectral and FC analyses able to highlight distinct patterns of neurophysiological alterations during the aging process in both healthy and pathological conditions. Since disruption in spectral content and functional interactions between brain areas could be accounted for by early neuropathological changes, MEG could represent a useful tool to unveil neurobiological mechanisms related to the cognitive decline observed during aging, particularly suitable for the detection of functional alterations, and then for the discovery of potential biomarkers in case of pathology.
The aging process is characterized by alterations in the spectral content across the brain. At the network level, FC studies reveal that older adults experience a series of changes that make them more vulnerable to cognitive interferences.
While special attention has been dedicated to the study of pathological conditions (in particular, mild cognitive impairment and Alzheimer’s disease), the lack of studies addressing the features of FC in healthy aging is noteworthy. This area of research calls for future attention because it is able to set the baseline from which to draw comparisons with different pathological conditions.