Spatial complexity method for tracking brain development and degeneration using functional near-infrared spectroscopy

Zhenhu Liang; Yuxi Wang; Hao Tian; Yue Gu; Takeshi Arimitsu; Takao Takahashi; Yasuyo Minagawa; Haijing Niu; Yunjie Tong

doi:10.1364/BOE.449341

Spatial complexity method for tracking brain development and degeneration using functional near-infrared spectroscopy

Biomed Opt Express. 2022 Feb 25;13(3):1718-1736. doi: 10.1364/BOE.449341. eCollection 2022 Mar 1.

Authors

Zhenhu Liang^{1

2}, Yuxi Wang^{1

2}, Hao Tian^{1

2}, Yue Gu³, Takeshi Arimitsu⁴, Takao Takahashi⁴, Yasuyo Minagawa^{5

6}, Haijing Niu^{7

8}, Yunjie Tong^{9

10}

Affiliations

¹ Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China.
² Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, Qinhuangdao 066004, China.
³ Key Laboratory of Computer Vision and System (Ministry of Education), School of Computer Science and Engineering, Tianjin University of Technology, Tianjin 300384, China.
⁴ Department of Pediatrics, Keio University School of Medicine, Tokyo, Japan.
⁵ Department of Psychology, Faculty of Letters, Keio University, Tokyo, Japan.
⁶ myasuyo@bea.hi-ho.ne.jp.
⁷ Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.
⁸ niuhjing@bnu.edu.cn.
⁹ Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, USA.
¹⁰ tong61@purdue.edu.

Abstract

Brain complexity analysis using functional near-infrared spectroscopy (fNIRS) has attracted attention as a biomarker for evaluating brain development and degeneration processes. However, most methods have focused on the temporal scale without capturing the spatial complexity. In this study, we propose a spatial time-delay entropy (STDE) method as the spatial complexity measure based on the time-delay measure between two oxy-hemoglobin (Δ[HbO]) or two deoxy-hemoglobin (Δ[Hb]) oscillations within the 0.01-0.1 Hz frequency band. To do this, we analyze fNIRS signals recorded from infants in their sleeping state, children, adults, and healthy seniors in their resting states. We also evaluate the effects of various noise to STDE calculations and STDE's performance in distinguishing various developmental age groups. Lastly, we compare the results with the normalized global spatial complexity (NGSC) and sample entropy (SampEn) measures. Among these measures, STDE_HbO (STDE based on Δ[HbO] oscillations) performs best. The STDE value increases with age throughout childhood (p < 0.001), and then decreases in adults and healthy seniors in the 0.01-0.1 Hz frequency band. This trajectory correlates with cerebrovascular development and degeneration. These findings demonstrate that STDE can be used as a new tool for tracking cerebrovascular development and degeneration across a lifespan based on the fNIRS resting-state measurements.