title: Recognition of stimulus-evoked neuronal optical response by identifying chaos levels of near-infrared spectroscopy time series.
abstract: Near-infrared spectroscopy (NIRS) can detect two different kinds of signals from the human brain: the hemodynamic response (slow) and the neuronal response (fast). This paper explores a nonlinear aspect in the tactile-stimulus-evoked neuronal optical response over a NIRS time series (light intensity variation). The existence of the fast optical responses (FORs) over the time series recorded in stimulus sessions is confirmed by event-related averaging. The chaos levels of the NIRS time series recorded both in stimulus and in rest sessions are then identified according to the estimated largest Lyapunov exponent. The obtained results ascertain that stimulus-evoked neuronal optical responses can be detected in the somatosensory cortex using continuous-wave NIRS equipment. Further, the results strongly suggest that the chaos level can be used to recognize the FORs in NIRS time series and, thereby, the state of the pertinent brain activity.
authors.affiliation: Department of Cogno-Mechatronics Engineering, Pusan National University, 30 Jangjeon-dong, Gumjeong-gu, Busan 609-735, Republic of Korea. Electronic address: x.hu@pusan.ac.kr.
authors.forename: Xiao-Su
authors.initials: XS
authors.lastname: Hu
authors.affiliation: Department of Cogno-Mechatronics Engineering, Pusan National University, 30 Jangjeon-dong, Gumjeong-gu, Busan 609-735, Republic of Korea; School of Mechanical Engineering, Pusan National University, 30 Jangjeon-dong, Gumjeong-gu, Busan 609-735, Republic of Korea. Electronic address: kshong@pusan.ac.kr.
authors.forename: Keum-Shik
authors.initials: KS
authors.lastname: Hong
authors.affiliation: Department of Cogno-Mechatronics Engineering, Pusan National University, 30 Jangjeon-dong, Gumjeong-gu, Busan 609-735, Republic of Korea; Department of Electrical & Computer Engineering, The National University of Singapore, Singapore 117576, Singapore; The Robotics Institute, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611813, China. Electronic address: samge@nus.edu.sg.
authors.forename: Shuzhi Sam
authors.initials: SS
authors.lastname: Ge
mesh_terms: D000328:Adult; D000465:Algorithms; D003627:Data Interpretation, Statistical; D005074:Evoked Potentials, Visual / Q000502:physiology*; D006339:Heart Rate / Q000502:physiology; D006801:Humans; D008297:Male; D009474:Neurons / Q000502:physiology*; D017711:Nonlinear Dynamics; D010775:Photic Stimulation; D010812:Physical Stimulation; D025341:Principal Component Analysis; D013003:Somatosensory Cortex / Q000502:physiology; D019265:Spectroscopy, Near-Infrared / Q000379:methods*; D013997:Time Factors; D055815:Young Adult