Neurovascular coupling analysis of working memory based on electroencephalography and functional near-infrared spectroscopy.
10.7507/1001-5515.202108048
- Author:
Wenzheng LIU
1
;
Hao ZHANG
2
;
Liu YANG
1
;
Yue GU
1
Author Information
1. School of Computer Science and Engineering, Tianjin University of Technology, Tianjin 300384, P. R. China.
2. State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, P. R. China.
- Publication Type:Journal Article
- Keywords:
Canonical correlation analysis;
Electroencephalography;
Functional near-infrared spectroscopy;
Neurovascular coupling;
Working memory
- MeSH:
Electroencephalography/methods*;
Memory, Short-Term;
Neurovascular Coupling/physiology*;
Prefrontal Cortex;
Spectroscopy, Near-Infrared/methods*
- From:
Journal of Biomedical Engineering
2022;39(2):228-236
- CountryChina
- Language:Chinese
-
Abstract:
Working memory is an important foundation for advanced cognitive function. The paper combines the spatiotemporal advantages of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) to explore the neurovascular coupling mechanism of working memory. In the data analysis, the convolution matrix of time series of different trials in EEG data and hemodynamic response function (HRF) and the blood oxygen change matrix of fNIRS are extracted as the coupling characteristics. Then, canonical correlation analysis (CCA) is used to calculate the cross correlation between the two modal features. The results show that CCA algorithm can extract the similar change trend of related components between trials, and fNIRS activation of frontal pole region and dorsolateral prefrontal lobe are correlated with the delta, theta, and alpha rhythms of EEG data. This study reveals the mechanism of neurovascular coupling of working memory, and provides a new method for fusion of EEG data and fNIRS data.
