Effects of Increasing Working Memory Load on EEG Signal Amplitude and Variability in the Prefrontal Cortex During an n-Back Task
DOI:
https://doi.org/10.58445/rars.4051Keywords:
EEG Signal Amplitude, Working memory (WM), Memory load, Electroencephalography (EEG)Abstract
Working memory is essential for cognitive processes such as reasoning, attention, and decision making, and can be assessed using tests such as the n-back task, a cognitive test that systematically increases memory load. The prefrontal cortex (PFC) plays a critical role in working memory because it is responsible for executive functions such as maintaining information, updating memories, regulating attention, and managing cognitive effort. Understanding how the PFC responds to increasing memory demands can provide insight into how the brain supports complex thinking and information processing. Previous research has shown that the prefrontal cortex becomes more active as the difficulty in the n-back task increases. In this study, electroencephalogram (EEG) data from an open access dataset were analyzed, focusing on activity recorded at the Fp1 (frontal) electrode across rest, 0-back, 2-back, and 3-back conditions. The n-back task was used to systematically vary working memory load, with higher levels requiring greater active remembering and continuous updating of information. EEG time-series plots, event-related potentials (ERPs), and frequency-based measures were examined to identify differences in signal amplitude and variability across the conditions. The results indicate that higher working memory load is associated with increased signal variability and larger amplitude fluctuations, suggesting greater neural engagement in the prefrontal cortex. These findings support previous research showing that neural activity increases as cognitive load rises, while also demonstrating how publicly available EEG datasets can be used to examine changes in working memory processing. Understanding these neural patterns may contribute to future research on attention, cognitive performance, and disorders that involve working memory impairments, including ADHD, age-related cognitive decline, and other neurological conditions.
References
Shin, J., von Lühmann, A., Kim, D. W., Mehnert, J., Hwang, H. J., & Müller, K. R. (2018). Simultaneous acquisition of EEG and NIRS during cognitive tasks for an open access dataset. Scientific data, 5, 180003. https://doi.org/10.1038/sdata.2018.3
Shalchy MA, Pergher V, Pahor A, Van Hulle MM, Seitz AR (2020).. N-Back Related ERPs Depend on Stimulus Type, Task Structure, Pre-processing, and Lab Factors. Front Hum Neurosci, 14, 549966. doi: 10.3389/fnhum.2020.549966.
Huang S, Chen C, Mo Y, Zhao Y, Zhu Y, Dong K, Xu T (2025).. Exploring the n-back task: insights, applications, and future directions. Front Hum Neurosci; 19, 1721330. doi: 10.3389/fnhum.2025.1721330.
Dong, S., Reder, L. M., Yao, Y., Liu, Y., & Chen, F. (2015). Individual differences in working memory capacity are reflected in different ERP and EEG patterns to task difficulty. Brain Research, 1616, 146–156. https://doi.org/10.1016/j.brainres.2015.05.003
Downloads
Posted
Categories
License
Copyright (c) 2026 Research Archive of Rising Scholars

This work is licensed under a Creative Commons Attribution 4.0 International License.