Decoding the Human Brain during Intelligence Testing

Abstract

Understanding the brain mechanisms underlying complex human cognition is a major objective in neuroscience. Previous studies have identified neural correlates of intelligence at different temporal and spatial scales using functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) separately. This study treats intelligence as a multilayer phenomenon across temporal and spatial scales and examines how the connectedness of brain regions as well as the complexity of multilayer brain dynamics relates to performance in an established intelligence test. Graph-theoretical analyses of fMRI-derived functional connectivity (N=67) revealed that the connectedness of frontal and parietal regions was associated with individual performance. Further, multiscale entropy analyses of EEG signals (N=131) disclosed that higher test scores were linked to more complex long-range processes and, at a trend level, to less complex short-range processes. These findings support the Multilayer Processing Theory, proposing the interplay between flexible long-range and modular short-range processes as the neural bases of intelligence.