Research Repository

The Effect of Longitudinal Training on Working Memory Capacities: An Exploratory EEG Study

Zian, Pei and Tao, Xu and Anastasios, Bezerianos and Li, Junhua and Yu, Sun and Hongtao, Wang (2020) The Effect of Longitudinal Training on Working Memory Capacities: An Exploratory EEG Study. In: The 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, 2020-07-20 - 2020-07-24, Montreal, Canada. (In Press)

[img]
Preview
Text
EMBC_PEI20200427-final.pdf - Accepted Version

Download (217kB) | Preview

Abstract

The study of working memory (WM) is a hot topic in recent years and accumulating literatures underlying the achievement and neural mechanism of WM. However, the effect of WM training on cognitive functions were rarely studied. In this study, nineteen healthy young subjects participated in a longitudinal design with one week N-back training (N=1,2,3,4). Experimental results demonstrated that training procedure could help the subjects master more complex psychological tasks when comparing the pre-training performance with those post-training. More specifically, the behavior accuracy increased from 68.14±9.34%, 45.09±14.90%, 39.12±12.71%, and 32.11±10.98% for 1-back, 2-back, 3-back and 4-back respectively to 73.52±4.01%, 69.14±5.28%, 69.09±6.41% and 64.41±5.12% after training. Furthermore, we applied elec-troencephalogram (EEG) power and functional connectivity to reveal the neural mechanisms of this beneficial effect and found that the EEG power of δ, θ and α band located in the left temporal and occipital lobe increased significantly. Meanwhile, the functional connectivity strength also increased obviously in δ and θ band. In sum, we showed positive effect of WM training on psychological performance and explored the neural mechanisms. Our findings may have the implications for enhancing the performance of participants who are prone to cognitive.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: _not provided_
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 20 May 2020 08:37
Last Modified: 25 Jul 2020 01:00
URI: http://repository.essex.ac.uk/id/eprint/27576

Actions (login required)

View Item View Item