Symbolic time series analysis of fNIRS signals in brain development assessment

Zhenhu Liang, Yasuyo Minagawa, Ho Ching Yang, Hao Tian, Lei Cheng, Takeshi Arimitsu, Takao Takahashi, Yunjie Tong

Research output: Contribution to journalArticle

Abstract

OBJECTIVE: Assessing an infant's brain development remains a challenge for neuroscientists and pediatricians despite great technological advances. As a non-invasive neuroimaging tool, functional near-infrared spectroscopy (fNIRS) has great advantages in monitoring an infant's brain activity. To explore the dynamic features of hemodynamic changes in infants, in-pattern exponent (IPE), anti-pattern exponent (APE), as well as permutation cross-mutual information (PCMI) based on symbolic dynamics are proposed to measure the phase differences and coupling strength in oxyhemoglobin (HbO) and deoxyhemoglobin (Hb) signals from fNIRS. APPROACH: First, simulated sinusoidal oscillation signals and four coupled nonlinear systems were employed for performance assessments. Hilbert transform based measurements of hemoglobin phase oxygenation and deoxygenation (hPod) and phase-locking index of hPod (hPodL) were calculated for comparison. Then, the IPE, APE and PCMI indices from resting state fNIRS data of preterm, term infants and adults were calculated to estimate the phase difference and coupling of HbO and Hb. All indices' performance was assessed by the degree of monotonicity (DoM). The box plots and coefficients of variation (CV) were employed to assess the measurements and robustness in the results. MAIN RESULTS: In the simulation analysis, IPE and APE can distinguish the phase difference of two sinusoidal oscillation signals. Both hPodL and PCMI can track the strength of two coupled nonlinear systems. Compared to hPodL, the PCMI had higher DoM indices in measuring the coupling of two nonlinear systems. In the fNIRS data analysis, similar to hPod, the IPE and APE can distinguish preterm, term infants, and adults in 0.01-0.05 Hz, 0.05-0.1 Hz, and 0.01-0.1 Hz frequency bands, respectively. PCMI more effectively distinguished the term and preterm infants than hPodL in the 0.05-0.1 Hz frequency band. As symbolic time series measures, the IPE and APE were able to detect the brain developmental changes in subjects of different ages. PCMI can assess the resting-state HbO and Hb coupling changes across different developmental ages, which may reflect the metabolic and neurovascular development. SIGNIFICANCE: The symbolic-based methodologies are promising measures for fNIRS in estimating the brain development, especially in assessing newborns' brain developmental status.

Original languageEnglish
Number of pages1
JournalJournal of Neural Engineering
Volume15
Issue number6
DOIs
Publication statusPublished - 2018 Dec 1

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Near infrared spectroscopy
Time series analysis
Near-Infrared Spectroscopy
Brain
Oxygenation
Hemoglobin
Nonlinear systems
Premature Infants
Hemoglobins
Frequency bands
Neuroimaging
Hemodynamics
Oxyhemoglobins
Functional Neuroimaging
Time series
Child Development
Newborn Infant
Monitoring

ASJC Scopus subject areas

  • Biomedical Engineering
  • Cellular and Molecular Neuroscience

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Symbolic time series analysis of fNIRS signals in brain development assessment. / Liang, Zhenhu; Minagawa, Yasuyo; Yang, Ho Ching; Tian, Hao; Cheng, Lei; Arimitsu, Takeshi; Takahashi, Takao; Tong, Yunjie.

In: Journal of Neural Engineering, Vol. 15, No. 6, 01.12.2018.

Research output: Contribution to journalArticle

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abstract = "OBJECTIVE: Assessing an infant's brain development remains a challenge for neuroscientists and pediatricians despite great technological advances. As a non-invasive neuroimaging tool, functional near-infrared spectroscopy (fNIRS) has great advantages in monitoring an infant's brain activity. To explore the dynamic features of hemodynamic changes in infants, in-pattern exponent (IPE), anti-pattern exponent (APE), as well as permutation cross-mutual information (PCMI) based on symbolic dynamics are proposed to measure the phase differences and coupling strength in oxyhemoglobin (HbO) and deoxyhemoglobin (Hb) signals from fNIRS. APPROACH: First, simulated sinusoidal oscillation signals and four coupled nonlinear systems were employed for performance assessments. Hilbert transform based measurements of hemoglobin phase oxygenation and deoxygenation (hPod) and phase-locking index of hPod (hPodL) were calculated for comparison. Then, the IPE, APE and PCMI indices from resting state fNIRS data of preterm, term infants and adults were calculated to estimate the phase difference and coupling of HbO and Hb. All indices' performance was assessed by the degree of monotonicity (DoM). The box plots and coefficients of variation (CV) were employed to assess the measurements and robustness in the results. MAIN RESULTS: In the simulation analysis, IPE and APE can distinguish the phase difference of two sinusoidal oscillation signals. Both hPodL and PCMI can track the strength of two coupled nonlinear systems. Compared to hPodL, the PCMI had higher DoM indices in measuring the coupling of two nonlinear systems. In the fNIRS data analysis, similar to hPod, the IPE and APE can distinguish preterm, term infants, and adults in 0.01-0.05 Hz, 0.05-0.1 Hz, and 0.01-0.1 Hz frequency bands, respectively. PCMI more effectively distinguished the term and preterm infants than hPodL in the 0.05-0.1 Hz frequency band. As symbolic time series measures, the IPE and APE were able to detect the brain developmental changes in subjects of different ages. PCMI can assess the resting-state HbO and Hb coupling changes across different developmental ages, which may reflect the metabolic and neurovascular development. SIGNIFICANCE: The symbolic-based methodologies are promising measures for fNIRS in estimating the brain development, especially in assessing newborns' brain developmental status.",
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AU - Cheng, Lei

AU - Arimitsu, Takeshi

AU - Takahashi, Takao

AU - Tong, Yunjie

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N2 - OBJECTIVE: Assessing an infant's brain development remains a challenge for neuroscientists and pediatricians despite great technological advances. As a non-invasive neuroimaging tool, functional near-infrared spectroscopy (fNIRS) has great advantages in monitoring an infant's brain activity. To explore the dynamic features of hemodynamic changes in infants, in-pattern exponent (IPE), anti-pattern exponent (APE), as well as permutation cross-mutual information (PCMI) based on symbolic dynamics are proposed to measure the phase differences and coupling strength in oxyhemoglobin (HbO) and deoxyhemoglobin (Hb) signals from fNIRS. APPROACH: First, simulated sinusoidal oscillation signals and four coupled nonlinear systems were employed for performance assessments. Hilbert transform based measurements of hemoglobin phase oxygenation and deoxygenation (hPod) and phase-locking index of hPod (hPodL) were calculated for comparison. Then, the IPE, APE and PCMI indices from resting state fNIRS data of preterm, term infants and adults were calculated to estimate the phase difference and coupling of HbO and Hb. All indices' performance was assessed by the degree of monotonicity (DoM). The box plots and coefficients of variation (CV) were employed to assess the measurements and robustness in the results. MAIN RESULTS: In the simulation analysis, IPE and APE can distinguish the phase difference of two sinusoidal oscillation signals. Both hPodL and PCMI can track the strength of two coupled nonlinear systems. Compared to hPodL, the PCMI had higher DoM indices in measuring the coupling of two nonlinear systems. In the fNIRS data analysis, similar to hPod, the IPE and APE can distinguish preterm, term infants, and adults in 0.01-0.05 Hz, 0.05-0.1 Hz, and 0.01-0.1 Hz frequency bands, respectively. PCMI more effectively distinguished the term and preterm infants than hPodL in the 0.05-0.1 Hz frequency band. As symbolic time series measures, the IPE and APE were able to detect the brain developmental changes in subjects of different ages. PCMI can assess the resting-state HbO and Hb coupling changes across different developmental ages, which may reflect the metabolic and neurovascular development. SIGNIFICANCE: The symbolic-based methodologies are promising measures for fNIRS in estimating the brain development, especially in assessing newborns' brain developmental status.

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