# Decoding the human brain during intelligence testing

## TL;DR

This study explores how brain connectivity and signal complexity across different scales relate to performance on intelligence tests.

## Contribution

The study introduces a multiscale approach to analyzing intelligence by combining fMRI and EEG data.

## Key findings

- Stronger frontoparietal connectivity in fMRI data correlates with better intelligence test performance.
- Higher EEG signal complexity in long-range processes is associated with higher test scores.
- Multiscale analysis reveals new insights into the neural basis of human intelligence.

## 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 test 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. By considering processes across temporal and spatial scales, this study informs multiscale theories of human intelligence such as the Multilayer Processing Theory.

Variations in human brain frontoparietal functional connectivity and in signal complexity during intelligence tests relate to individual test performance. Results encourage exploring human intelligence across multiple spatial and temporal scales.