目的 探讨发育迟缓儿童的功能性近红外光谱(fNIRS)特点,为发育迟缓儿童的脑功能分析提供参考依据。方法 2019年11日-2020年6月应用8通道功能性近红外光谱成像技术(fNIRS)检测13名发育迟缓儿童(发育迟缓组)和年龄、性别相匹配的19例健康儿童(正常组)的脑功能情况,采用独立样本t检验比较两组儿童各通道多尺度熵(MSE)及前额区MSE均值的差异。结果 发育迟缓组和正常组儿童前额区MSE均值分别为1.570±0.491、2.075±0.791,两组间差异具有统计学意义(t=2.228, P=0.034)。两组儿童的MSE均值在3通道和8通道差异统计学意义(t=2.513、2.868,P<0.01)。结论 发育迟缓儿童前额区自发脑信号的复杂性较正常健康儿童明显偏低,发育迟缓儿童存在前额叶双侧脑功能受损。
Abstract
Objective To study the characteristics of children with developmental delay (DD) by using functional near infrared spectroscopy (fNIRS), so as to provide reference for the individual diagnosis and treatment of DD. Methods A total of 13 children with DD(DD group) and 19 normal children (NC group) were selected in this study, whose brain function was tested by 8-channel fNIRS. Multiscale entropy (MSE) of each channel and the mean MSE of the frontal region between DD group and NC group were compared by t test. Results The mean MSE of DD group (1.570±0.491) was significantly lower than that of NC group (2.075±0.791) (t=2.228, P=0.034). The MSE values in channel 3 and 8 were significantly different between DD group and NC group(t=2.513, 2.868, P<0.01). Conclusions Compared with the normal control group, the complexity of frontal lobe spontaneous brain signals in children with DD is significantly lower, indicating that children with DD have bilateral prefrontal brain function impairment.
关键词
功能性近红外光谱 /
发育迟缓 /
儿童
Key words
functional near-infrared spectroscopy /
developmental delay /
children
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参考文献
[1] 刘宝根, 周兢, 李菲菲. 脑功能成像的新方法-功能性近红外光谱技术(fNIRS)[J].心理科学, 2011, 34(4): 943-949.
[2] 梁爱民.儿童发育迟缓研究进展[J].中国儿童保健杂志,2011,19(8): 726-728.
[3] 邹小兵,李咏梅.儿童发育迟缓及发育障碍的早期干预和管理[J].中国实用儿科杂志,2016,31(10):756-760.
[4] 阎俊,张红晓.儿童全面发育迟缓的早期诊断与干预措施[J].中医儿科杂志,2017,13(4):13-16.
[5] 张秀玲,李寄平,秦明镜,等. Gesell发展诊断量表3.5~6岁北京修订本的制定[J].中国临床心理学杂志,1994,2(3):148-150,191-192.
[6] Ahmed MU,Mandic DP. Multivariate multiscale entropy analysis[J].IEEE Signal Proc Let,2012, 19(2):91-94.
[7] Costa M, Goldberger AL,Peng CK. Multiscale entropy analysis of biological signals[J].Phys Rev E Stat Nonlin Soft Matter Phys, 2005, 71(2):021906.
[8] Cristine S, Placek MM, Czosnyka M, et al. Complexity of brain signals is associated with outcome in preterm infants[J].J Cereb Blood Flow Metab, 2017,37(10): 3368-3379.
[9] Angsuwatanakul T, O'Reilly J, Ounjai K. Multiscale entropy as a new feature for EEG and fNIRS analysis[J].Entropy (Basel), 2020, 22(2): 189.
[10] 邹雨晨,李燕芳,丁颖.早期高级认知发展与前额叶功能发育的fNIRS研究[J].心理发展与教育,2015,31(6):761-768.
[11] Smith EH,Horga G, Yates MJ, et al. Widespread temporal coding of cognitive control in the human prefrontal cortex[J].Nat Neurosci, 2019, 22(11):1883-1891.
[12] Patil AL, Deepak KK, Kochhar KP. Role of prefrontal cortex during Sudoku task: fNIRS study[J].Transl Neurosci, 2020, 11(1):419-427.
[13] Dunsmoor JE, Kroes MCW, Li J, et al. Role of human ventromedial prefrontal cortex in learning and recall of enhanced extinction[J].J Neurosci, 2019, 39(17):3264-3276.
[14] Widge AS, Heilbronner SR, Hayden BY. Prefrontal cortex and cognitive control: new insights from human electrophysiology[J].F1000 Research, 2019, 8:1696.
[15] 马玲. 婴幼儿发育迟缓的功能磁共振成像初步研究[D].广州:南方医科大学,2017.
[16] Mehnert J, Akhrif A, Telkemeyer S, et al. Developmental changes in brain activation and functional connectivity during response inhibition in the early childhood brain[J].Brain Dev, 2013, 35(10):894-904.
[17] Moriguchi Y, Lertladaluck K. Bilingual effects on cognitive shifting and prefrontal activations in young children[J].Int J Bilingual, 2019, 24(4):136700691988027.
[18] Chevalier N, Jackson J,Roux AR, et al. Differentiation in prefrontal cortex recruitment during childhood: Evidence from cognitive control demands and social contexts[J].Dev Cogn Neurosci, 2019, 36: 100629.
[19] Howard-Jones PA,Washbrook EV, Meadows S. The timing of educational investent: a neuroscientific perspective[J].Dev Cogn Neurosci,2012, 2(Suppl 1): 18-29.
基金
广西重点研发计划(桂科AB18126056);柳州重点研发计划(2018BJ10301);柳州市科技计划项目(2018DB20501)