Relating structural and functional anomalous connectivity in the aging brain via neural mass modeling

• Published in: NeuroImage (Orlando, Fla.) Vol. 52; no. 3; pp. 848 - 861
• Main Authors: Pons, A.J., Cantero, Jose L., Atienza, Mercedes, Garcia-Ojalvo, Jordi
• Format: Journal Article Publication
• Language: English
• Published: United States Elsevier Inc 01.09.2010; Elsevier Limited
• Subjects: Aged; Aging - physiology; Alzheimer's disease; Alzheimer, Malaltia d; Brain; Brain - physiopathology; Brain connectivity; Brain Mapping - methods; Ciències de la salut; Cognition Disorders - physiopathology; EEG modeling; Electroencephalography; Female; Humans; Male; Medicina; Mild cognitive impairment; Models, Neurological; Neural mass models; Neural Pathways - physiopathology; Neurologia; Signal Processing, Computer-Assisted; Studies; Young Adult; Àrees temàtiques de la UPC; Neural mass models; Brain connectivity; Mild cognitive impairment; Alzheimer's disease; EEG modeling
• ISSN: 1053-8119; 1095-9572; 1095-9572
• DOI: 10.1016/j.neuroimage.2009.12.105

The structural changes that arise as the brain ages influence its functionality. In many cases, the anatomical degradation simply leads to normal aging. In others, the neurodegeneration is large enough to cause neurological disorders (e.g. Alzheimer's disease). Structure and function can be both currently measured using noninvasive techniques, such as magnetic resonance imaging (MRI) and electroencephalography (EEG) respectively. However, a full theoretical scheme linking structural and functional degradation is still lacking. Here we present a neural mass model that aims to bridge both levels of description and that reproduces experimentally observed multichannel EEG recordings of alpha rhythm in young subjects, healthy elderly subjects, and patients with mild cognitive impairment. We focus our attention in the dominant frequency of the signals at different electrodes and in the correlation between specific electrode pairs, measured via the phase-lag index. Our model allows us to study the influence of different structural connectivity pathways, independently of each other, on the normal and aberrantly aging brain. In particular, we study in detail the effect of the thalamic input on specific cortical regions, the long-range connectivity between cortical regions, and the short-range coupling within the same cortical area. Once the influence of each type of connectivity is determined, we characterize the regions of parameter space compatible with the EEG recordings of the populations under study. Our results show that the different types of connectivity must be fine-tuned to maintain the brain in a healthy functioning state independently of its age and brain condition.