Time-frequency analysis of the electrocortical activity during maturation using wavelet transform

Abstract

In this study, we introduce the wavelet transform (WT) as a method for characterizing the maturational changes in electrocortical activity in 24 fetal lambs ranging from 110–144 days gestation (term 145 days). The WT, based on multiresolution signal decomposition, is free of assumptions regarding the characteristics of the signal. The approximation of the electrocortical activity at resolutions varying from 2^j+1 to 2^j can be extracted by decomposing the signal on a wavelet orthonormal basis of L ²(R). We performed multiresolution decomposition for four sets of parameters D _2j , where -1 < j < -4. The four series WT represent the detail signal bandwidths: (1) 16–32 Hz, (2) 8–16 Hz, (3) 4–8 Hz, (4) 2–4 Hz. The data were divided into three groups according to gestational age: 110–122 days (early), 123–135 days (middle), and 136–144 days (late). In the early group, the power was highest in the fourth signal bandwidth, with relatively low power in the other bands. Increase in gestational age was characterized by increased power in all four bandwidths. Comparison of the cumulative distribution function of the power in the four wavelet bands confirmed the presence of two statistically different patterns in all three age groups. These two patterns correspond to the visually identified patterns of HVSA (high-voltage slow activity) and LVFA (low-voltage fast activity). The earliest development change occurred in HVSA, with progressive increase in power in the 2–8 Hz band. Later changes occurred in LVFA, with a significant increase in power in the 16–32 Hz band. The same database was also analyzed by the short-term Fourier transform (STFT) method, the most common time-frequency analysis method. Comparison of the results clearly show that the WT provided much better time-frequency resolution than the STFT method and was superior in demonstrating maturational changes in electrocortical activity.