eprintid: 13385
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/33/85
datestamp: 2023-11-10 03:27:56
lastmod: 2023-11-10 03:27:56
status_changed: 2023-11-10 01:51:02
type: conference_item
metadata_visibility: show
creators_name: Ung, W.C.
creators_name: Yahya, N.
creators_name: Tang, T.B.
title: Detection of Mathematical Fluency Effects on Working Memory using near Infrared Spectroscopy
ispublished: pub
keywords: Calculations; Chemical activation; Near infrared spectroscopy, Area under the curves; Brain activation; Functional near infrared spectroscopy; Mental arithmetic; Oxygenated hemoglobin; Prefrontal cortex; Task performance; Working memory, Infrared devices
note: cited By 0; Conference of 15th IEEE Sensors Applications Symposium, SAS 2020 ; Conference Date: 9 March 2020 Through 11 March 2020; Conference Code:164022
abstract: The prefrontal cortex (PFC) not only plays a less mathematics-specific role in number processing and calculation but it is also responsible for working memory demands coping. Through functional near-infrared spectroscopy imaging, this study explored how differently the PFC of 31 subjects with contrasting mathematical fluency would respond to increasing working memory demands of mental arithmetic task. Area under the curve analyses of the oxygenated hemoglobin signals, hereinafter representing brain activation, were compared across levels and groups. Depending on task performance, the subjects were allocated to either normal performers (NP) or high performers (HP) group. Both groups showed sensitivity with regards to task performance (i.e., the number of problems attempted and accuracy) towards increasing working memory demands (level 1 to 3). With increasing task level, NP's PFC activation increased while HP's remained unchanged. NP also showed consistent greater PFC activation than HP in all three levels. These findings implied that the PFC plays a more auxiliary role to cope with working memory demands imposed by mental arithmetic on individuals who are less fluent in mathematics. This can potentially serve as a framework to monitor workload hemodynamics continuously and unobtrusively. © 2020 IEEE.
date: 2020
publisher: Institute of Electrical and Electronics Engineers Inc.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85095577257&doi=10.1109%2fSAS48726.2020.9220070&partnerID=40&md5=ab7eedcf5f6b8d1e8a9bc03a4d36ed74
id_number: 10.1109/SAS48726.2020.9220070
full_text_status: none
publication: 2020 IEEE Sensors Applications Symposium, SAS 2020 - Proceedings
refereed: TRUE
isbn: 9781728148427
citation:   Ung, W.C. and Yahya, N. and Tang, T.B.  (2020) Detection of Mathematical Fluency Effects on Working Memory using near Infrared Spectroscopy.  In: UNSPECIFIED.