Sample entropy of electroencephalogram for children with autism based on virtual driving game

Lei Min; Meng Guang; Zhang Wen-Ming; Nilanjan Sarkar

doi:10.7498/aps.65.108701

Abstract

Autism spectrum disorder is a kind of mental disease which involves the disorders of the perception, emotion, memory, language, intelligence, thinking, action, etc. The aim of this paper is to investigate the brain activity characteristics of the children with autism during complex environments by analyzing electroencephalogram (EEG) signals from the neuroergonomics perspective. The virtual driving environment as a complex multi-task source is used to organically connect brain systems with human motion control. The 14-channel EEG signals are obtained including the EEG baseline signals on a resting state (about 3 min) and the EEG activity signals during driving (about 5 min). The method of the shift average sample entropy is proposed to deal with EEG signals in the resting and the virtual driving environments. Considering the highly complex hyper-dimensional characteristics of EEG signals, the different embedding dimensions (such as 2 and 6 dimensions) are analyzed in the sample entropy estimation. The results show that the average sample entropy values of autism spectrum disorder (ASD) subjects are lower than those of healthy subjects during resting and driving, respectively, especially in the prefrontal lobe, temporal lobe, parietal lobe and occipital lobe during resting and in temporal lobe and occipital lobe during driving. It indicates that ASD children lack the ability to adapt easily their behaviors. Meanwhile, like healthy subjects, the average sample entropy values of ASD subjects during driving are higher than those during resting as a whole. Moreover, the EEG activity signals of ASD are obviously higher than the EEG baseline signals in prefrontal lobe, frontal lobe, frontal central lobe and temporal lobe regions in 95% significant level. And for healthy subjects, the activity signals are significantly higher than the baseline signals only in parietal lobe region. Furthermore, the brain activities of ASD subjects during driving come closer to those of healthy subjects during resting. It suggests that the virtual driving environment may be helpful for the treatment of ASD individuals. In addition, the ASD and healthy subjects have a certain right hemisphere dominance in the whole region except in the parietal lobe region. In the parietal lobe region, they have some left hemisphere dominance, especially during driving. And for ASD subjects, there is the significant right hemisphere dominance in the temporal lobe in 95% confidence level no matter whether in the resting state or in the driving state. The results show that it is suitable for the shift average sample entropy analysis to study the brain activities of ASD individuals. This study will provide a new research method for the further research on the mechanism of autism and its diagnosis, evaluation and intervention.

Keywords:

Authors and contacts

1.
Institute of Vibration Shock and Noise, State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China;
2.
Robotics and Autonomous Systems Laboratory, Department of Mechanical Engineering, Vanderbilt University, USA

Corresponding author: Lei Min, leimin@sjtu.edu.cn

Funds: Project supported by the Science Fund for Creative Research Groups of the National Natural Science Foundation of China (Grant No. 51421092), the National Natural Science Foundation of China (Grant No. 10872125), the Natural Science Foundation of Shanghai, China (Grant No. 06ZR14042), the Research Fund of State Key Laboratory of Mechanical System and Vibration, China (Grant No. MSV-MS-2010-08), the Research Fund from Shanghai Jiao Tong University for Medical and Engineering Science, China (Grant No. YG2013MS74), the NSF Project of USA (Grant Nos. 0967170, 1264462), and the NIH Project of USA (Grant Nos. 1R01MH091102-01A1, 1R21MH103518-01).

References

[1]	Kanner L 1943 Nervous Child. 2 217
[2]	Ghanbari Y, Bloy L, Edgar J C, Blaskey L, Verma Ragini, Roberts T 2015 J. Autism Dev. Disord. 45 444
[3]	Li N, Chen G, Song X, Du W, Zheng X 2011 Epilepsy Behav. 22 786
[4]	Duan Y F, Wu X L, Jin F 2015 Scientia Sinica Vitae 45 820 (in Chinese) [段云峰, 吴晓丽, 金锋 2015 中国科学: 生命科学 45 820]
[5]	Wang J, Barstein J, Ethridge L E, Mosconi M W, Takarae Y, Sweeney J A 2013 J. Neurodev. Disord. 5 24
[6]	Li J, Lin Z M, Zhu L Q 2012 Prog. Biochem. Biophys. 39 952 (in Chinese) [李晶, 林珠梅, 朱莉琪 2012 生物化学与生物物理进展 39 952]
[7]	Hua R, Wei M P, Zhang C 2015 Sci. China: Life Sci. 58 933
[8]	Li Z X, Zhu L Q 2015 Prog. Biochem. Biophys. 42 1103 (in Chinese) [李占星, 朱莉琪 2015 生物化学与生物物理进展 42 1103]
[9]	Chen S, Zhong X, Jiang L, Zheng X, Xiong Y, Ma S, Qiu M, Huo S, Ge J, Chen Q 2016 Behav. Brain Res. 296 61
[10]	Stigler K A, McDonald B C, Anand A, Saykin A J, McDougle C J 2011 Brain Res. 1381 146
[11]	Strzelecka J 2014 Res. Autism Spectr. Disord. 8 317
[12]	Courchesne, E, Pierce K, Schumann C M, Redcay E, Buckwalter J A, Kennedy D P, Morgan J 2007 Neuron 56 399
[13]	Weinsten M, Ben-Sira L, Levy Y, Zachor D A, Itzhak E B, Artzi M, Tarrasch R, Eksteine P M, Hendler T, Bashat D B 2011 Hum. Brain Mapp. 32 534
[14]	Ambrosino S, Bos D J, van Raalten T R, Kobussen N A, van Belle J, Oranje B, Durston S 2014 J. Neural Transm. 121 1145
[15]	Chen H, Duan X, Liu F, Lu F, Ma X, Zhang Y Uddin L Q, Chen H 2016 Prog. Neuro-Psychopharmacol. Biol. Psychiatry 64 1
[16]	Hahamy A, Behrmann, Malach 2015 Nat. Neurosci. 18 302
[17]	Zhu H, Li J, Fan Y, Li X, Huang D, He S 2015 Biomed. Opt. Express 6 690
[18]	Billeci L, Sicca F, Maharatna K, Apicella F, Narzisi A, Campatelli G, Calderoni S, Pioggia G, Muratori F 2014 Res. Autism Spectr. Disord. 8 317
[19]	Chan A S, Sze S L, Cheung M C 2007 Neuropsychologia 21 74
[20]	Cantor D S, Thatcher R W, Hrybyk M, Kaye H 1986 J. Autism Dev. Disord. 16 169
[21]	Mathewson K J, Jetha M K, Drmic I E, Bryson S E, Goldberg J O, Schmidt L A 2012 Clin. Neurophysiol. 123 1798
[22]	Coben R, Clarke A R, Hudspeth W, Barry R J 2008 Clin. Neurophysiol. 119 1002
[23]	Orekhova E V, Stroganova T A, Nygren G, Tsetlin M M, Posikera I N, Gillberg C, Elam M 2007 Biol. Psychiat. 62 1022
[24]	Van Diessen E, Senders J, Jansen F E, Boersma M, Bruining H 2015 Eur. Arch. Psy. Clin. N. 265 537
[25]	Sheikhani A, Behnam H, Noroozian M, Mohammadi M R, Mohammadi M 2009 Res. Autism Spectr. Disord. 3 538
[26]	Sheikhani A, Behnam H, Mohammadi MR, Noroozian M, Mohammadi M 2012 J. Med. Syst. 36 957
[27]	Maxwell C R, Villalobos M E, Schultz R T, Dahlmann B H, Konrad K, Kohls G 2015 J. Autism Dev. Disord. 45 292
[28]	Tierney A L, Gabard-Durnam L, Vogel-Farley V, Tager-Flusberg H, Nelson C A 2012 PloS One 7 e39127
[29]	Wang X Y, Chen W X, Zhang F Q, Yang S Y, Liang C F 2013 J. Epileptol Electroneurophysiol. 22 226 (in Chinese) [王秀英, 陈文雄, 张凤琼, 杨思渊, 梁翠芳 2013 癫痫与神经电生理学杂志 22 226]
[30]	Chan A, Han Y, Sze S, Lau E 2015 Front. Psychol. 6 1893
[31]	Hashemian M, Pourghassem H 2014 Neurophysiology 46 183
[32]	Sheikhani A, Behnam H, Mohammadi M R, Noroozian M, Golabi P 2007 Proc of the 4th IEEE-EMBS International Summer School and Symposium on Medical Devices and Biosensors Cambridge, UK, August 19-22, 2007 p111
[33]	Bosl W, Tierney A, Tager-Flusberg H, Nelson C 2011 BMC Med. 9 18
[34]	Catarino A, Churches O, Baron-Cohen S, Andrade A, Ring H 2011 Clin. Neurophysiol. 122 2375
[35]	Ahmadlou M, Adeli H, Adeli A 2010 J. Clin. Neurophysiol. 27 328
[36]	Ahmadlou M, Adeli H, Adeli A 2012 Physica A 391 4720
[37]	Keh L, Chupungco A, Esguerra J 2012 Int. J. Bifurcat. Chaos 22 1250044
[38]	Lei M, Meng G, Sarkar N 2015 The Chinese Congress of Theoretical and Applied Mechanics 2015 Shanghai, P.R. China, August 15-18, 2015 pMS5437 (in Chinese) [雷敏, 孟光, Sarkar N 2015 中国力学大会CCTAM2015 上海, 中国, 2015年8月15-18日 pMS5437]
[39]	Lei M, Meng G, Fan J, Wade J, Bian D, Sarkar N 2014 24th Annual International Conference of Society for Chaos Theory in Psychology Life Sciences, Milwaukee, Wisconsin, USA, July 31-August 2 2014 p10
[40]	Ni L, Cao J, Wang R 2013 Comput. Math. Method Med. 2013 618743
[41]	Huang X L, Huo C Y, Si J F, Liu H X 2014 Acta Phys. Sin. 63 100503 (in Chinese) [黄晓林, 霍铖宇, 司峻峰, 刘红星 2014 物理学报 63 100503]
[42]	Richman J, Moorman J 2000 Am. J. Physiol. Heart Circ. Physiol. 278 H2039
[43]	Zhu L, Deng J, Wu J H, Zhou N R 2015 Acta Phys. Sin. 64 184302 (in Chinese) [朱莉, 邓娟, 吴建华, 周南润 2015 物理学报 64 184302]
[44]	Singer W 2013 Trends in Cognitive Sci. 17 616
[45]	Shen Z, Fang F, Yang J J 2010 Introduction to Cognitive Neuroscience (Beijing: Peking University Press) pp224-226 (in Chinese) [沈政, 方方, 杨炯炯 2010 认知神经科学导论 (北京: 北京大学出版社) 第224-226页]
[46]	Zhu X Q, Song Y W, Bi H Y 2014 Prog. Biochem. Biophys. 41 749 (in Chinese) [朱晓倩, 宋耀武, 毕鸿燕 2014 生物化学与生物物理进展 41 749]

Cited By

[1]	Kanner L 1943 Nervous Child. 2 217
[2]	Ghanbari Y, Bloy L, Edgar J C, Blaskey L, Verma Ragini, Roberts T 2015 J. Autism Dev. Disord. 45 444
[3]	Li N, Chen G, Song X, Du W, Zheng X 2011 Epilepsy Behav. 22 786
[4]	Duan Y F, Wu X L, Jin F 2015 Scientia Sinica Vitae 45 820 (in Chinese) [段云峰, 吴晓丽, 金锋 2015 中国科学: 生命科学 45 820]
[5]	Wang J, Barstein J, Ethridge L E, Mosconi M W, Takarae Y, Sweeney J A 2013 J. Neurodev. Disord. 5 24
[6]	Li J, Lin Z M, Zhu L Q 2012 Prog. Biochem. Biophys. 39 952 (in Chinese) [李晶, 林珠梅, 朱莉琪 2012 生物化学与生物物理进展 39 952]
[7]	Hua R, Wei M P, Zhang C 2015 Sci. China: Life Sci. 58 933
[8]	Li Z X, Zhu L Q 2015 Prog. Biochem. Biophys. 42 1103 (in Chinese) [李占星, 朱莉琪 2015 生物化学与生物物理进展 42 1103]
[9]	Chen S, Zhong X, Jiang L, Zheng X, Xiong Y, Ma S, Qiu M, Huo S, Ge J, Chen Q 2016 Behav. Brain Res. 296 61
[10]	Stigler K A, McDonald B C, Anand A, Saykin A J, McDougle C J 2011 Brain Res. 1381 146
[11]	Strzelecka J 2014 Res. Autism Spectr. Disord. 8 317
[12]	Courchesne, E, Pierce K, Schumann C M, Redcay E, Buckwalter J A, Kennedy D P, Morgan J 2007 Neuron 56 399
[13]	Weinsten M, Ben-Sira L, Levy Y, Zachor D A, Itzhak E B, Artzi M, Tarrasch R, Eksteine P M, Hendler T, Bashat D B 2011 Hum. Brain Mapp. 32 534
[14]	Ambrosino S, Bos D J, van Raalten T R, Kobussen N A, van Belle J, Oranje B, Durston S 2014 J. Neural Transm. 121 1145
[15]	Chen H, Duan X, Liu F, Lu F, Ma X, Zhang Y Uddin L Q, Chen H 2016 Prog. Neuro-Psychopharmacol. Biol. Psychiatry 64 1
[16]	Hahamy A, Behrmann, Malach 2015 Nat. Neurosci. 18 302
[17]	Zhu H, Li J, Fan Y, Li X, Huang D, He S 2015 Biomed. Opt. Express 6 690
[18]	Billeci L, Sicca F, Maharatna K, Apicella F, Narzisi A, Campatelli G, Calderoni S, Pioggia G, Muratori F 2014 Res. Autism Spectr. Disord. 8 317
[19]	Chan A S, Sze S L, Cheung M C 2007 Neuropsychologia 21 74
[20]	Cantor D S, Thatcher R W, Hrybyk M, Kaye H 1986 J. Autism Dev. Disord. 16 169
[21]	Mathewson K J, Jetha M K, Drmic I E, Bryson S E, Goldberg J O, Schmidt L A 2012 Clin. Neurophysiol. 123 1798
[22]	Coben R, Clarke A R, Hudspeth W, Barry R J 2008 Clin. Neurophysiol. 119 1002
[23]	Orekhova E V, Stroganova T A, Nygren G, Tsetlin M M, Posikera I N, Gillberg C, Elam M 2007 Biol. Psychiat. 62 1022
[24]	Van Diessen E, Senders J, Jansen F E, Boersma M, Bruining H 2015 Eur. Arch. Psy. Clin. N. 265 537
[25]	Sheikhani A, Behnam H, Noroozian M, Mohammadi M R, Mohammadi M 2009 Res. Autism Spectr. Disord. 3 538
[26]	Sheikhani A, Behnam H, Mohammadi MR, Noroozian M, Mohammadi M 2012 J. Med. Syst. 36 957
[27]	Maxwell C R, Villalobos M E, Schultz R T, Dahlmann B H, Konrad K, Kohls G 2015 J. Autism Dev. Disord. 45 292
[28]	Tierney A L, Gabard-Durnam L, Vogel-Farley V, Tager-Flusberg H, Nelson C A 2012 PloS One 7 e39127
[29]	Wang X Y, Chen W X, Zhang F Q, Yang S Y, Liang C F 2013 J. Epileptol Electroneurophysiol. 22 226 (in Chinese) [王秀英, 陈文雄, 张凤琼, 杨思渊, 梁翠芳 2013 癫痫与神经电生理学杂志 22 226]
[30]	Chan A, Han Y, Sze S, Lau E 2015 Front. Psychol. 6 1893
[31]	Hashemian M, Pourghassem H 2014 Neurophysiology 46 183
[32]	Sheikhani A, Behnam H, Mohammadi M R, Noroozian M, Golabi P 2007 Proc of the 4th IEEE-EMBS International Summer School and Symposium on Medical Devices and Biosensors Cambridge, UK, August 19-22, 2007 p111
[33]	Bosl W, Tierney A, Tager-Flusberg H, Nelson C 2011 BMC Med. 9 18
[34]	Catarino A, Churches O, Baron-Cohen S, Andrade A, Ring H 2011 Clin. Neurophysiol. 122 2375
[35]	Ahmadlou M, Adeli H, Adeli A 2010 J. Clin. Neurophysiol. 27 328
[36]	Ahmadlou M, Adeli H, Adeli A 2012 Physica A 391 4720
[37]	Keh L, Chupungco A, Esguerra J 2012 Int. J. Bifurcat. Chaos 22 1250044
[38]	Lei M, Meng G, Sarkar N 2015 The Chinese Congress of Theoretical and Applied Mechanics 2015 Shanghai, P.R. China, August 15-18, 2015 pMS5437 (in Chinese) [雷敏, 孟光, Sarkar N 2015 中国力学大会CCTAM2015 上海, 中国, 2015年8月15-18日 pMS5437]
[39]	Lei M, Meng G, Fan J, Wade J, Bian D, Sarkar N 2014 24th Annual International Conference of Society for Chaos Theory in Psychology Life Sciences, Milwaukee, Wisconsin, USA, July 31-August 2 2014 p10
[40]	Ni L, Cao J, Wang R 2013 Comput. Math. Method Med. 2013 618743
[41]	Huang X L, Huo C Y, Si J F, Liu H X 2014 Acta Phys. Sin. 63 100503 (in Chinese) [黄晓林, 霍铖宇, 司峻峰, 刘红星 2014 物理学报 63 100503]
[42]	Richman J, Moorman J 2000 Am. J. Physiol. Heart Circ. Physiol. 278 H2039
[43]	Zhu L, Deng J, Wu J H, Zhou N R 2015 Acta Phys. Sin. 64 184302 (in Chinese) [朱莉, 邓娟, 吴建华, 周南润 2015 物理学报 64 184302]
[44]	Singer W 2013 Trends in Cognitive Sci. 17 616
[45]	Shen Z, Fang F, Yang J J 2010 Introduction to Cognitive Neuroscience (Beijing: Peking University Press) pp224-226 (in Chinese) [沈政, 方方, 杨炯炯 2010 认知神经科学导论 (北京: 北京大学出版社) 第224-226页]
[46]	Zhu X Q, Song Y W, Bi H Y 2014 Prog. Biochem. Biophys. 41 749 (in Chinese) [朱晓倩, 宋耀武, 毕鸿燕 2014 生物化学与生物物理进展 41 749]

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