The Neural Correlates of Cognitive Load in Learning: an Fmri Study on Graph Comprehension

Abstract

Background: Cognitive load theory suggests that excessive demands on the human cognitive system can lead to cognitive overload and impaired learning. However, whilst the neural correlates of cognitive load are unclear, neuroimaging techniques such as functional magnetic resonance imaging (fMRI) may help provide answers to these questions. Aims: Considering this potential, this study aims to investigate which brain structures are associated with cognitive load through conducting an fMRI study on graph comprehension. Sample: The study's sample consists of 15 undergraduate students. Methods: Based on a within-subjects design, participants answered comprehension questions using split (i.e., high cognitive load) and integrated (i.e., low cognitive load) graphs whilst undergoing a magnetic resonance imaging (MRI) scan. Results: Participants exhibited lower levels of accuracy and slower reaction times with split graphs compared to integrated graphs. The fMRI data showed that cognitive load was associated with the frontoparietal network. More specifically, the multiple demand network revealed greater activation in graphs with higher cognitive load than those of lower cognitive load. Conclusions: These findings may indicate that a domain-general attentional brain network is responsible for cognitive load.