Using graph theoretical analysis of multi channel EEG to evaluate the neural efficiency hypothesis

• Published in: Neuroscience letters Vol. 402; no. 3; pp. 273 - 277
• Main Authors: Micheloyannis, Sifis, Pachou, Ellie, Stam, Cornelis J., Vourkas, Michael, Erimaki, Sophia, Tsirka, Vasso
• Format: Journal Article
• Language: English
• Published: Shannon Elsevier Ireland Ltd 24.07.2006; Elsevier
• Subjects: Adult; Biological and medical sciences; Educational Status; Electroencephalography; Female; Fundamental and applied biological sciences. Psychology; Graph theory; Humans; Male; Memory; Models, Neurological; Nerve Net - physiology; Neural efficiency; Neurons - physiology; Psychometrics; Small-world network; Synchronization likelihood; Vertebrates: nervous system and sense organs; Working memory; Neural efficiency; Small-world network; Synchronization likelihood; Graph theory; Working memory; Theory; Electrophysiology; Cognition; Electroencephalography; Synchronization
• DOI: 10.1016/j.neulet.2006.04.006
• ISSN: 0304-3940

Previous studies demonstrated that intelligence is significantly related to an impressive array of psychological, social, biological and genetic factors and that working memory (WM) can be considered as a general cognitive resource strongly related with a wide variety of higher order cognitive competencies and intelligence. Also, evaluating the WM of subjects might allow one to test the neural efficiency hypothesis (NEH). WM typically involves functional interactions between frontal and parietal cortices. We recorded EEG signals to study neuronal interactions during one WM test in individuals who had few years of formal education (LE) as compared to individuals with university degrees (UE). The two groups of individuals differed in the scores they obtained in psychological tests. To quantify the synchronization between EEG channels in several frequency bands, we evaluated the “synchronization likelihood” (SL), which takes into consideration nonlinear processes as well as linear ones. SL was then converted into graphs to estimate the distance from “small-world network” (SWN) organization, i.e., an optimally organized network that would give rise to the data. In comparison to LE subjects, those with university degrees exhibited less prominent SWN properties in most frequency bands during the WM task. This finding supports the NEH and suggests that the connections between brain areas of well-educated subjects engaged in WM tasks are not as well-organized in the sense of SWN.