基于fNIRS的大脑前额叶皮层在不同脑力负荷下的激活模式研究

桑林琼; 王莉; 乔梁; 张静娜; 李鹏岳; 尚光荣; 张晔; 王倩楠; 邱明国

doi:10.16016/j.2097-0927.202106243

您当前的位置：

首页 >

文章列表页 >

基于fNIRS的大脑前额叶皮层在不同脑力负荷下的激活模式研究

神经科学 | 更新时间：2026-01-09

- 基于fNIRS的大脑前额叶皮层在不同脑力负荷下的激活模式研究
- Load-dependent activation of bilateral prefrontal cortex: an fNIRS study
- 陆军军医大学学报 2022年44卷第3期页码：210-216
- 作者机构：
  
  1.400038重庆，陆军军医大学(第三军医大学)生物医学工程与影像医学系医学图像学教研室
  2.400038重庆，陆军军医大学(第三军医大学)高原军事医学系极端环境医学教育部重点试验室
- 作者简介：
  
  [ 邱明国，E-mail: qiumg_2002@sina.com QIU Mingguo, E-mail: qiumg_2002@sina.com
- 基金信息：
  
  第三军医大学青年培育项目(2018XQN04);军队卫勤保障能力创新与生成专项应用基础研究项目(21WQ004);教育部极端环境医学重点试验室开放课题(PR-KL2020GY001)
- DOI：10.16016/j.2097-0927.202106243
  中图分类号： R338.2;R338.64;R445.7
- 收稿：2021-06-30，
  
  修回：2021-08-27，
  
  纸质出版：2022-02-15
- 稿件说明：
移动端阅览
桑林琼, 王莉, 乔梁, 等. 基于fNIRS的大脑前额叶皮层在不同脑力负荷下的激活模式研究[J]. 陆军军医大学学报, 2022,44(3):210-216.

Linqiong SANG, Li WANG, Liang QIAO, et al. Load-dependent activation of bilateral prefrontal cortex: an fNIRS study[J]. Journal of Army Medical University, 2022, 44(3): 210-216.
桑林琼, 王莉, 乔梁, 等. 基于fNIRS的大脑前额叶皮层在不同脑力负荷下的激活模式研究[J]. 陆军军医大学学报, 2022,44(3):210-216. DOI： 10.16016/j.2097-0927.202106243.

Linqiong SANG, Li WANG, Liang QIAO, et al. Load-dependent activation of bilateral prefrontal cortex: an fNIRS study[J]. Journal of Army Medical University, 2022, 44(3): 210-216. DOI： 10.16016/j.2097-0927.202106243.

摘要

目的

利用功能性近红外光谱成像技术(functional near-infrared spectroscopy

fNIRS)探讨大脑双侧前额叶皮层(prefrontal cortex

PFC)在不同脑力负荷下的激活模式。

方法

选取本校在校学生34例(男性17例，女性17例)，分别进行3种负荷水平的n-back(

=1、2、3)认知记忆任务试验，采用fNIRS检测被试大脑双侧PFC的含氧血红蛋白(HbO

)的相对含量和时间特性。

结果

随着负荷水平的增加，被试任务的正确率显著下降，反应时逐步升高，在1-back时显著低于2-back和3-back，但2-back和3-back之间差异无统计学意义。大脑双侧PFC的激活强度随着负荷水平增加呈现非线性增强，相比于1-back，2-back时左、右侧PFC的激活均增强，特别是右侧PFC激活显著增强(

0.05)，然而3-back时双侧PFC的激活程度与2-back、1-back时差异均无统计学意义。检测fNIRS信号的时间特性发现，左侧PFC在3-back时的血流动力学响应较强。

结论

fNIRS可以检测到不同脑力负荷下大脑双侧PFC在激活强度和血氧响应模式上均存在差异，随着脑力负荷增加，右侧PFC的功能激活显得较为重要。

Abstract

Objective

To investigate the load-dependent activation in bilateral prefrontal cortex (PFC) during working memory tasks by functional near-infrared spectroscopy (fNIRS).

Methods

Thirty-four undergraduates (17 males and 17 females) completed a standard N-back task at 3 load levels (

3) while fNIRS data were collected from frontal cortex. Brain activation and relative content of oxygenated hemoglobin (HbO

) in left and right prefrontal cortex was calculated respectively.

Results

As the load level increased

the accuracy was linearly declined and the action time was significantly prolonged in 1-back than in 2-back and 3-back

but there was no significant difference between 2-back and 3-back. Moreover

the activation of bilateral prefrontal cortex showed non-linear growth with the increase of load level. The activation of bilateral prefrontal cortex in 2-back both presented stronger when compared to 1-back

particularly in the right PFC (

0.05). However

there was no obvious difference in the activation of bilateral prefrontal cortex in 3-back when compared to 2-back and 1-back. The time characters of fNIRS showed that the hemodynamic response of the left prefrontal cortex was stronger in 3-back.

Conclusion

fNIRS could detect the differences in the activation patterns and blood oxygen response mode of bilateral prefrontal cortex under different mental loads. Right prefrontal cortex plays more important role in higher mental load tasks.

关键词

Keywords

references

DURANTIN G, GAGNON J F, TREMBLAY S, et al . Using near infrared spectroscopy and heart rate variability to detect mental overload[J ] . Behav Brain Res, 2014, 259: 16-23. DOI: 10.1016/j.bbr.2013.10.042.

ARVIDSSON H, LARSSON G, LARSOLLE A, et al . Easily applicable methods for measuring the mental load on tractor operators[J ] . J Agric Saf Health, 2020, 26(1): 5-14. DOI: 10.13031/jash.13223.

YÜCEL M A, SELB J J, HUPPERT T J, et al . Functional near infrared spectroscopy: enabling routine functional brain imaging[J ] . Curr Opin Biomed Eng, 2017, 4: 78-86. DOI: 10.1016/j.cobme.2017.09.011.

PINTI, TACHTSIDIS I, HAMILTON A, et al . The present and future use of functional near-infrared spectroscopy (fNIRS) for cognitive neuroscience[J ] . Ann N Y Acad Sci, 2020, 1464(1): 5-29. DOI: 10.1111/nyas.13948.

RAHMAN M A, SIDDIK A B, GHOSH T K, et al . A narrative review on clinical applications of fNIRS[J ] . J Digit Imaging, 2020, 33(5): 1167-1184. DOI: 10.1007/s10278-020-00387-1.

BUXTON R B. The physics of functional magnetic resonance imaging (fMRI)[J]. Rep Prog Phys, 2013, 76(9): 096601. DOI: 10.1088/0034-4885/76/9/096601.

PENG C, HOU X L. Applications of functional near-infrared spectroscopy (fNIRS) in neonates[J]. Neurosci Res, 2021, 170: 18-23. DOI: 10.1016/j.neures.2020.11.003.

姜劲, 焦学军, 潘津津, 等. 基于fNIRS的情绪对工作记忆负荷影响规律研究[J]. 航天医学与医学工程, 2017, 30(2): 115-122. DOI: 10.16289/j.cnki.1002-0837.2017.02.008.

JIANG J, JIAO X J, PAN J J, et al . Study on influence of emotional state on work memory response mechanism using functional near-infrared spectroscopy[J ] . Space Med Med Eng, 2017, 30(2): 115-122. DOI: 10.16289/j.cnki.1002-0837.2017.02.008.

潘津津, 焦学军, 姜劲, 等. 利用功能性近红外光谱成像方法评估脑力负荷[J]. 光学学报, 2014, 34(11): 344-349. DOI: 10.3788/aos201434.1130002.

PAN J J, JIAO X J, JIANG J, et al . Mental workload assessment based on functional near-infrared spectroscopy[J ] . Acta Opt Sin, 2014, 34(11): 344-349. DOI: 10.3788/aos201434.1130002.

FISHBURN F A, NORR M E, MEDVEDEV A V, et al . Sensitivity of fNIRS to cognitive state and load[J ] . Front Hum Neurosci, 2014, 8: 76. DOI: 10.3389/fnhum.2014.00076.

MEIDENBAUER K L, CHOE K W, CARDENAS-INIGUEZ C, et al . Load-dependent relationships between frontal fNIRS activity and performance: a data-driven PLS approach[J ] . Neuroimage, 2021, 230: 117795. DOI: 10.1016/j.neuroimage.2021.117795.

SCHOLKMANN F, KLEISER S, METZ A J, et al . A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology[J ] . Neuroimage, 2014, 85(Pt 1): 6-27. DOI: 10.1016/j.neuroimage.2013.05.004.

HUPPERT T J, DIAMOND S G, FRANCESCHINI M A, et al . HomER: a review of time-series analysis methods for near-infrared spectroscopy of the brain[J ] . Appl Opt, 2009, 48(10): D280-D29 8. DOI: 10.1364/ao.48.00d280.

COOPER R J, SELB J, GAGNON L, et al . A systematic comparison of motion artifact correction techniques for functional near-infrared spectroscopy[J ] . Front Neurosci, 2012, 6: 147. DOI: 10.3389/fnins.2012.00147.

AGHAJANI H, GARBEY M, OMURTAG A. Measuring mental workload with EEG+fNIRS[J]. Front Hum Neurosci, 2017, 11: 359. DOI: 10.3389/fnhum.2017.00359.

AYAZ H, SHEWOKIS P A, BUNCE S, et al . Optical brain monitoring for operator training and mental workload assessment[J ] . Neuroimage, 2012, 59(1): 36-47. DOI: 10.1016/j.neuroimage.2011.06.023.

MANDRICK K, PEYSAKHOVICH V, RÉMY F, et al . Neural and psychophysiological correlates of human performance under stress and high mental workload[J ] . Biol Psychol, 2016, 121(Pt A): 62-73. DOI: 10.1016/j.biopsycho.2016.10.002.

CAUSSE M, CHUA Z, PEYSAKHOVICH V, et al . Mental workload and neural efficiency quantified in the prefrontal cortex using fNIRS[J ] . Sci Rep, 2017, 7(1): 5222. DOI: 10.1038/s41598-017-05378-x.

MANDRICK K, DEROSIERE G, DRAY G, et al . Prefrontal cortex activity during motor tasks with additional mental load requiring attentional demand: a near-infrared spectroscopy study[J ] . Neurosci Res, 2013, 76(3): 156-162. DOI: 10.1016/j.neures.2013.04.006.

LUNDSTROM B N, INGVAR M, PETERSSON K M. The role of precuneus and left inferior frontal cortex during source memory episodic retrieval[J]. Neuroimage, 2005, 27(4): 824-834. DOI: 10.1016/j.neuroimage.2005.05.008.

SCHAEFFER J D, YENNU A S, GANDY K C, et al . An fNIRS investigation of associative recognition in the prefrontal cortex with a rapid event-related design[J ] . J Neurosci Methods, 2014, 235: 308-315. DOI: 10.1016/j.jneumeth.2014.07.011.

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

工作记忆任务的近红外脑功能成像研究

腺苷对小鼠前额叶皮质锥体细胞超极化激活阳离子电流的影响