Examination of neurocognitive processes during execution of sequential problem-solving tasks under varying demand.

Abstract

<i>Objective</i>. There exists a limited body of work that has jointly assessed behavioral performance and mental workload during the execution of sequential tasks. However, none of this work has jointly assessed performance and neurocognitive dynamics during the execution of problem-solving tasks having multiple solutions similar to real-world settings across different levels of cognitive demand. Additionally, only limited efforts have quantified an individual's performance using measures which constitute distinct aspects of cognitive-motor performance.<i>Approach</i>. Therefore, we extend a prior effort to assess performance through a computational approach to obtain the optimality stratified similarity degree metric (OSSD) through two different measures of performance (i.e. optimality and similarity). These performance measures along with brain dynamics captured through electroencephalography spectral power measures were combinedly assessed to determine their impact on neural efficiency. The recorded measures allowed the stratification of performance into distinct optimality tiers within which unique differences between sequences structured by individuals were captured by the similarity metric. In addition to a traditional population-based analysis, this approach led to the clustering of the best and worst performers, thus allowing one to evaluate cortical dynamics between groups of individuals.<i>Main results</i>. The main findings of the study were that enhanced levels of task demand caused a degraded performance (i.e. decreased optimality, similarity and OSSD) along with a greater recruitment of neurocognitive processes (i.e. whole scalp increase of theta and low/high-alpha power; frontal, central, and temporal low/high-beta and gamma power increase), ultimately leading to an attenuation of neural efficiency. The cluster-based analysis between the best versus worst performers revealed that temporal low/high beta and gamma power as well as central gamma power was greater for the former relative to the latter.<i>Significance</i>. This work has the potential to inform the neurocognitive processes underlying the performance of complex sequential problem-solving tasks in various industrial, occupational, military, and healthcare applications.