Using graph theoretical analysis of multi channel EEG to evaluate the neural efficiency hypothesis
Abstract
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.
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During task performance, a more prominent small-world architecture was found in those without higher education than in those with a university education.
“During the performance of a task, a more prominent small-world architecture was found in those without higher education than in those with a university education”
From Graph theory analysis of complex brain networks: new concepts in brain mapping applied to neurosurgery (2016) · cites this paper as [69]
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References 32 · Cited by 277
- Authors
- Micheloyannis, S., Pachou, E., Stam, C. J., Vourkas, M., Erimaki, S., & Tsirka, V.
- Affiliations
- University of Crete (GR)
- Amsterdam UMC Location Vrije Universiteit Amsterdam (NL)
- Corresponding author
- Micheloyannis, Sifis
- Venue
- Neuroscience Letters
- Publisher
- Elsevier BV
- Published
- 2006-07
- Volume
- 402
- Issue
- 3
- Pages
- 273-277
- ISSN
- 0304-3940 (ISSN-L)
- OpenAlex
- W2041684398
- Cited by
- 277
- References
- 32
- Citations by year
- 2026: 6 · 2025: 6 · 2024: 9 · 2023: 13 · 2022: 2 · 2021: 8 · 2020: 9 · 2019: 14 · 2018: 10 · 2017: 17 · 2016: 26 · 2015: 7 · 2014: 18 · 2013: 15 · 2012: 22
- FWCI
- 7.66
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Neuroscience Letters (publishedVersion)
- PubMed (publishedVersion)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion)
- Pure Amsterdam UMC (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Keywords
- neural efficiency hypothesis, working memory, small-world networks, graph theory, educational attainment, intelligence, nonlinear coupling, frequency bands
- MeSH terms
- Adult, Educational Status, Electroencephalography, Female, Humans, Male, Memory, Models, Neurological, Nerve Net, Neurons, Psychometrics
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