Geert Morren

Detection of fast neuronal signals in the motor cortex from functional near infrared spectroscopy measurements using independent component analysis

Fast changes, in the range of milliseconds, in the optical properties of cerebral tissue are associated with brain activity and can be detected using noninvasive near-infrared spectroscopy (NIRS). These changes are assumed to be caused by changes in the light scattering properties of the neuronal tissue. The aim of this study was to develop highly sensitive data analysi algorithms to detect this fast signal, which is small compared with other physiological signals. A frequency-domain tissue oximeter, whose laser diodes were intensity modulated at 110 MHz, was used. The amplitude, mean intensity and phase of the modulated optical signal were measured at a sample rate of 96 Hz. The probe, consisting of four crossed source detector pairs was placed above the motor cortex, contralateral to the hand performing a tapping exercise consisting of alternating rest and tapping periods of 20 s each. An adaptive filter was used to remove the arterial pulsatility from the optical signals. Independent component analysis allowed further separation of a signal component containing the fast signal. In nine out of 14 subjects, a significant fast neuronal signal related to the finger tapping was found in the intensity signals. In the phase signals, indications of the fast signal were found in only two subjects.

Cerebral tissue oxygenation index in very premature infants

Aim: To describe normal values of the cerebral tissue oxygenation index (TOI) in premature infants. Methods: TOI was measured by spatially resolved spectroscopy in preterm infants on the first 3 days of life. Infants with an abnormal cranial ultrasound were excluded. Other simultaneously measured variables were Pao2, Paco2, pH, mean arterial blood pressure, heart rate, haemoglobin, glycaemia, and peripheral oxygen saturation. Results: Fifteen patients with a median postmenstrual age of 28 weeks were measured. There was a significant increase in median TOI over the first 3 days of life: 57% on day 1, 66.1% on day 2, and 76.1% on day 3. Multiple regression analysis showed no correlation between TOI and postmenstrual age, peripheral oxygen saturation, mean arterial blood pressure, Pao2, Paco2, and haemoglobin concentration. Conclusion: Cerebral TOI increases significantly in the first 3 days of life in premature babies. This increase probably reflects the increase in cerebral blood flow at this time.

Measurement of tissue oxygenation index during the first three days in premature born infants.

No normal values of tissue oxygenation index (TOI) of the brain are known regarding premature born infants. We measured TOI, a measure for the cerebral hemoglobin oxygen saturation, on the head of 15 preterm infants with a median postmenstrual age of 28 weeks (interquartile range (IQR) between 26-29 weeks) with spatially resolved spectroscopy (NIRO 300, Hamamatsu) during the first three days of life. Infants with intra-ventricular hemorrhage or periventricular leucomalacia before the first measurement, as shown by ultrasound, were excluded. The first measurement was done within the first 6 hours of life, the second and third measurement at, respectively, 24 and 48 hours after this first measurement. The mean TOI was calculated if saturation did not change by more than 5% for at least 30 minutes. Other parameters measured were PaO2, PCO2, pH, mean arterial blood pressure, heart rate, hemoglobin, glycemia and peripheral oxygen saturation. There was a significant increase of TOI after 24 (p < 0.05) and 48 (p < 0.001) hours. The median TOI on the first day was 57% (95% CI: 54-65.7), 66.1% on the second day (95%CI: 61.9-82.3%) and 76.1% on the third day (95%CI 67.8-80.1%). No correlation was found between TOI and peripheral oxygen saturation, blood pressure, PaO2, PaCO2 and hemoglobin concentration after multiple regression analysis. TOI increases in the first three days in premature born babies. The increase of TOI is not due to an increase of oxygenation or mean arterial blood pressure. In our opinion, it reflects the increase in cerebral blood flow during the first three days.

Effects of non-nutritive sucking on heart rate, respiration and oxygenation: a model-based signal processing approach.

Several studies support the idea that the use of pacifiers can reduce the risk of Sudden Infant Death Syndrome. To investigate the effect of non-nutritive sucking (NNS), we measured heart rate, abdominal respiration, EMG and arterial oxygen saturation of 20 neonates. Also, in 10 of these neonates, changes in cerebral hemoglobin concentrations were acquired by means of near-infrared spectroscopy. Using a parametric technique to model the heart rate as a sum of exponentially damped sinusoids, two main frequency components were found in the heart rate during NNS: a frequency of approximately 0.08 Hz due to the alternation of sucking bursts and pauses, and a frequency of approximately 0.8 Hz that reflects the influence of the respiration. Our analysis shows that it is the alternation of bursts and pauses itself that causes the increased heart rate variability, and that this is not due to increased effort. This suggests that the neuronal mechanism regulating NNS also stimulates the heart rate. From our measurements, no effect of NNS on cerebral or peripheral oxygenation could be found. Furthermore, we show that our model-based signal processing technique is well suited for the analysis of non-stationary biomedical signals.

Decimative subspace-based parameter estimation techniques

In this paper, the problem of estimating the frequencies, dampings, amplitudes and phases of closely spaced complex damped exponentials in the presence of noise is considered. In several papers, decimation is proposed as a way to increase the performance of subspace-based parameter estimation methods, in the case of oversampling (Signal Process. 63(3) (1997) 211; IEEE Signal Process. Lett. 4(2) (1997) 49; in: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Vol. V, Salt Lake City, UT, USA, May 7-11, 2001, pp. 3073-3076). In this paper, three decimative versions of the HTLS-method (J. Magn. Resonance A 110(2) (1994) 228), a subspace-based parameter estimation technique that operates directly on the data matrix, are derived and compared. Monte-Carlo simulation experiments show the influence of decimation on the statistical accuracy and the computational complexity of the algorithms.

Detection of autoregulation in the brain of premature infants using a novel subspace-based technique

A study by Tsuji et al. (2000) suggests that, under certain circumstances, concordant changes in cerebral intravascular oxygenation and mean arterial blood pressure reflect impaired cerebrovascular autoregulation. In this paper, we propose a new measure to quantify this concordance, derived from the common subspace of these signals. The method is compared to correlation and coherence analysis with respect to our application, but it is also suited to other biomedical signals. Furthermore, this model-based approach is not restricted to applications involving only two signals.

Continuous measurement of cerebral blood volume and oxygenation during rewarming of neonates.

Aim: To investigate the effect of rewarming in preterm infants presenting with hypothermia at admission. Methods: The tissue oxygenation index (TOI), changes in cerebral blood volume (ACBV) and changes in intravascular oxygenation (AHbD) were measured in eight preterm infants, presenting with a temperature less than 35°C at admission. Results: A significant increase in HbD and TOI was seen in four patients (group A), while a significant increase in CBV and a decrease in HbD was seen in four other patients (group B). Retrospective analysis showed that group A had important signs of peripartal asphyxia.

Quantitation of the Concordance Between Cerebral Intravascular Oxygenation and Mean Arterial Blood Pressure for the Detection of Impaired Autoregulation

Since some important forms of brain injury in premature infants are caused in considerable part by disturbances in cerebral blood flow (CBF), it is important to be able to detect whether the cerebrovascular autoregulation, the mechanism by which CBF is maintained constant despite alterations in mean arterial blood pressure (MAP), is working properly. A recent study suggested that concordant changes in MAP and cerebral intravascular oxygenation (HbD), measured non-invasively by near-infrared spectroscopy (NIRS) as the difference between the concentration changes of oxygenated hemoglobin (HbO2) and deoxygenated hemoglobin (Hb), reflect impaired cerebrovascular autoregulation. Consequently, premature infants with impaired cerebrovascular autoregulation could be identified by simultaneous, continuous measurements of HbD and MAP. From several premature babies, MAP, HbD and arterial oxygen saturation (SaO2) were measured simultaneously at the University Hospital Leuven, Belgium. The concordance between MAP and HbD was quantitated using three different measures, among which a newly developed measure that looks for similarity of the dynamics between signals. Some preliminary results obtained from the measured data are given.

Decimative subspace-based parameter estimation techniques applied to magnetic resonance spectroscopy signals

The problem of estimating the frequencies, dampings, amplitudes and phases of closely spaced complex damped exponentials in the presence of noise is considered. In several papers, decimation is proposed as a way to increase the performance of subspace-based parameter estimation methods, in the case of oversampling. In this paper, a novel extension of the HTLS-method (Hankel-Total Least Squares) that operates directly on the decimated data matrix is presented, and it is compared to other decimation methods. Experiments on simulated nuclear magnetic resonance (NMR) spectroscopy signals show the influence of decimation on the accuracy and computational complexity of the estimators.

Extraction of fast neuronal changes from multichannel functional near-infrared spectroscopy signals using independent component analysis

Fast changes in the range of milliseconds in the optical properties of cerebral tissue, which are associated with brain activity, can be detected using non-invasive near-infrared spectroscopy (NIRS). These changes in light scattering are due to an alteration in the refractive index at neuronal membranes. The aim of this study was to develop highly sensitive data analysis algorithms to detect this fast signal, which is small compared to other physiological signals. A frequency-domain tissue oximeter, whose laser diodes were modulated at 110MHz was used. The amplitude, mean intensity and phase of the modulated optical signal was measured at 96Hz sample rate. The probe consisting of 4 crossed source detector pairs was placed above the motor cortex, contralateral to the hand performing a tapping exercise consisting of alternating rest- and tapping periods of 20s each. The tapping frequency, which was set to 3.55Hz or 2.5 times the heart rate of the subject to avoid the influence of harmonics on the signal, could not be observed in any of the individual signals measured by the detectors. An adaptive filter was used to remove the arterial pulsatility from the optical signals. Independent Component Analysis allowed to separate signal components in which the tapping frequency was clearly visible.