| Abstract |
| This study compared and analyzed the characteristics of brain states by calculating brain network connectivity based on electroencephalogram data collected during resting (eyes closed/open) and cognitive processing states (abstract/verbal reasoning), and quantifying the results using graph-theoretical indices. Latent profile analysis (LPA) was conducted to structure the identified network features, revealing three distinct profiles within the resting states and two common profiles within the cognitive processing states. The psychological validity of these profiles was further verified through their associations with the six-factor personality model. Results showed that the eyes-open resting condition exhibited the highest network efficiency, suggesting that the brain manages cognitive resources more effectively during visual stimulation to minimize information processing costs. Significant differences were also observed between resting states based on the presence of visual input and increased modularity was specifically observed during abstract thinking. Through the classification of LPA profiles, the study found that even with different cognitive tasks, common patterns exist at the neural network level, and that distinct strategies (e.g., fast-and-efficient local processing versus slower-but-integrative distributed processing) can coexist. These findings indicate that functional brain network connectivity is directly linked to various mental activities. |
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| Key Words |
| QEEG, Resting state, Cognitive processing state, Graph theory, Latent Profile Analysis, HEXACO, 정량적뇌파, 안정상태, 인지처리상태, 그래프이론, 잠재프로파일분석, 성격6요인 |
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