Das Gehirn ist ein komplexes Netzwerk aus gekoppelten, dynamischen Systemen Neuronenpopulationen, welche neuronale Komplexität erzeugen. Die neuronale Komplexität ist ein Maß für die Menge an Informationen, in einem neuronalen System. Gehirnsignalkomplexität (brain signal complexity, BSC) kann anhand der mittels Multi-Skalen-Entropie (MSE) gemessen werden. In dieser Dissertation wird die Nützlichkeit der MSE zur Messung der BSC im Zusammenhang mit kognitiven Fähigkeiten untersucht. Die Ergebnisse zeigten, dass die MSE sensitiv zwischen verschiedenen Hirnzuständen unterscheiden kann und als verlässliches Merkmalsmaß für Personen genutzt werden kann. Weitere Ergebnisse zeigen, dass die BSC ein potentieller neuronaler Marker für verbale Kreativität ist. Insgesamt liefert die Dissertation wertvolle Erkenntnisse für zukünftige Studien, die MSE zur Beurteilung neuronaler Komplexität und ihrer Beziehung zu Kreativität, Intelligenz und Inhibition verwenden.
The brain is a network of dynamical system of interacting neuronal populations giving rise to neural complexity. Neural complexity provides a measure for the amount of information of a neural system. Neural complexity can be assessed by computing brain signal complexity (BSC) using Multi-Scale Entropy (MSE). This dissertation assessed the utility of MSE in the EEG signals with creativity from an individual differences perspective. Findings revealed that individual differences in MSE are reliable, indicating that MSE is a useful trait marker of BSC across individuals. Further findings indicated that BSC is a potential neural marker of creativity, intelligence, and inhibition. Taken together, the dissertation provides valuable insights for designing future studies using MSE to assess neural complexity and its relationship with certain cognitive abilities including creativity, intelligence, and inhibition.
Divergent thinking (DT) is an important constituent of creativity that captures aspects of fluency and originality. The literature lacks multivariate studies that report relationships between DT and its aspects with relevant covariates, such as cognitive abilities, personality traits (e.g. openness), and insight. In two multivariate studies (N = 152 and N = 298), we evaluate competing measurement models for a variety of DT tests and examine the relationship between DT and established cognitive abilities, personality traits, and insight. A nested factor model with a general DT and a nested originality factor described the data well. In Study 1, DT was moderately related with working memory, fluid intelligence, crystallized intelligence, and mental speed. In Study 2, we replicate these results and add insight, openness, extraversion, and honesty–humility as covariates. DT was associated with insight, extraversion, and honesty–humility, whereas crystallized intelligence mediated the relationship between openness and DT. In contrast, the nested originality factor (i.e. the specificity of originality tasks beyond other DT tasks) had low variance and was not meaningfully related with any other constructs in the nomological net. We highlight avenues for future research by discussing issues of measurement and scoring.
European journal of personality London : Sage Publications, 1987 2020 (2. Dez.), 22 Seiten Online-Ressource
