Complex span task is one of the commonly used cognitive tasks to evaluate an individual’s working memory capacity (WMC). It is a dual task consisting of a distractor subtask and a memory subtask. Though multiple studies have utilized complex span tasks, the electrophysiological correlates underlying the encoding and retrieval processes in working memory span task remain uninvestigated. One previous study that assessed electroencephalographic (EEG) measures utilizing complex span task found no significant difference between its working memory loads, a typical index observed in other working memory tasks (e.g., n-back task and digital span task). The following design constructs of the paradigm might have been the reason. (1) The fixed-time limit of the distractor subtask may have hindered the assessment of individual WMC precisely. (2) Employing a linear-system-favoring EEG data analysis method for a non-linear system such as the human brain. In the current study, the participants perform the Raven Advanced Progressive Matrices (RAMP) task on 1 day and the symmetry span (Sspan) task on the other. Prior to the formal Sspan task, the participants were instructed to judge 15 simple symmetry questions as quickly as possible. A participant-specific time-limit is chartered from these symmetry questions. The current study utilizes the Sspan task sequential to a distractor subtask. Instead of the fixed time-limit exercised in the previous study, the distractor subtask of the current study was equipped with the participant-specific time-limit obtained from the symmetry questions. This could provide a precise measure of individual WMC. This study investigates if the complex span task resonates EEG patterns similar to the other working memory tasks in terms of working memory-load by utilizing ensemble empirical mode decomposition (EEMD) of Hilbert-Huang transform (HHT). Prior expectations were to observe a decrement in the P300 component of event-related mode (ERM) and a decrement in the power of alpha and beta band frequency with increasing working memory-load. We observed a significantly higher P300 amplitude for the low-load condition compared to the high-load condition over the circumscribed brain network across F4 and C4 electrodes. Time–frequency analysis revealed a significant difference between the high- and low-load conditions at alpha and beta band over the frontal, central, and parietal channels. The results from our study demonstrate precise differences in EEG data pertaining to varied memory-load differences in the complex span task. Thus, assessing complex span tasks with the HHT-based analysis may aid in achieving a better signal to noise ratio and effect size for the results in working memory EEG studies.
Response inhibition has been widely explored using the stop signal paradigm in the laboratory setting. However, the mechanism that demarcates attentional capture from the motor inhibition process is still unclear. Error monitoring is also involved in the stop signal task. Error responses that do not complete, i.e., partial errors, may require different error monitoring mechanisms relative to an overt error. Thus, in this study, we included a “continue go” (Cont_Go) condition to the stop signal task to investigate the inhibitory control process. To establish the finer difference in error processing (partial vs. full unsuccessful stop (USST)), a grip-force device was used in tandem with electroencephalographic (EEG), and the time-frequency characteristics were computed with Hilbert–Huang transform (HHT). Relative to Cont_Go, HHT results reveal (1) an increased beta and low gamma power for successful stop trials, indicating an electrophysiological index of inhibitory control, (2) an enhanced theta and alpha power for full USST trials that may mirror error processing. Additionally, the higher theta and alpha power observed in partial over full USST trials around 100 ms before the response onset, indicating the early detection of error and the corresponding correction process. Together, this study extends our understanding of the finer motor inhibition control and its dynamic electrophysiological mechanisms.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.