Abstract
We investigated the development of the brain's functional connectivity throughout the life span (ages 5 through 71 years) by measuring EEG activity in a large population-based sample. Connectivity was established with Synchronization Likelihood. Relative randomness of the connectivity patterns was established with Watts and Strogatz' (1998) graph parameters C (local clustering) and L (global path length) for alpha (∼10 Hz), beta (∼20 Hz), and theta (∼4 Hz) oscillation networks. From childhood to adolescence large increases in connectivity in alpha, theta and beta frequency bands were found that continued at a slower pace into adulthood (peaking at ∼50 yrs). Connectivity changes were accompanied by increases in L and C reflecting decreases in network randomness or increased order (peak levels reached at ∼18 yrs). Older age (55+) was associated with weakened connectivity. Semi-automatically segmented T1 weighted MRI images of 104 young adults revealed that connectivity was significantly correlated to cerebral white matter volume (alpha oscillations: r = 33, p<01; theta: r = 22, p<05), while path length was related to both white matter (alpha: max. r = 38, p<001) and gray matter (alpha: max. r = 36, p<001; theta: max. r = 36, p<001) volumes. In conclusion, EEG connectivity and graph theoretical network analysis may be used to trace structural and functional development of the brain.
Highlights
The brain is a complex network of highly connected brain areas that exchange information via long-range axonal projections
As a final aim we investigated whether brain anatomy was correlated with the observed differences in functional connectivity–and the graph parameters derived from these networks–by correlating these with cerebral white matter volume (WMV) and gray matter volume (GMV) established from magnetic resonance imaging (MRI) scans available in a young adult subset of the subjects
We estimated connectivity based on synchronization likelihood (SL) between EEG signals from distant electrodes for a large sample aged 5 to 71 years
Summary
The brain is a complex network of highly connected brain areas that exchange information via long-range axonal projections. Watts and Strogat [12] showed that highly ordered networks (high C) with only a few random links could achieve optimal connectivity (short L) close to the random state These small-world networks have favorable properties with efficient information transfer and resilience to (simulated) attack [10,15,16,17]. The graph parameters C and L make statements about network quality along the dimension of random – small world – ordered, they may not reveal these qualitative topological differences and their development over time [26]: All of the above networks, in different degrees, show small-world properties of a relatively high C and short L. Restricted to one age group, a correlation between functional connectivity, network randomness, and underlying anatomical variables may prove helpful in understanding how the observed large changes in brain anatomy–including both young developmen [30,34,35] and agin [33,36,37]– shapes brain activity and, brain function
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
