An objective assessment of fetal and neonatal auditory evoked responses

Abstract

Objective-We propose to use cross-correlation function to determine significant fetal and neonatal evoked responses (ERs).Methods-We quantify ERs by cross-correlation between the stimulus time series and the recorded brain signals. The statistical significance of the correlation is calculated by surrogate analysis. For validation of our approach we investigated a model which mimics the generation of ERs. The model assumes a fixed latency of the ER and contains two parameters, ε and λ. Whether or not the system responds to a given stimulus is controlled by ε. The amount to which the system is excited from the base line (background activity) is governed by λ. We demonstrate the technique by applying it to auditory evoked potentials from four fetuses (21 records) between 27-39 weeks of gestational age and four neonates (eight records).Results-The method correctly identified the ER and the latency incorporated in the model. A combined analysis of fetuses and neonates data resulted in a significant negative correlation between age and latency.Conclusions-The analysis of ER, especially for fetal and newborn recordings, should be based on advanced data analysis including the assessment of the significance of responses. The negative correlation between age and latency indicates the neurological maturation.Significance-The proposed method can be used to objectively assess the ER in fetuses and neonates.

Fetal MEG evoked response latency from beamformer with random field theory

“…The problem is to select statistically significant latency by some objective and automated means for investigation of neurophysiological markers. This has been addressed recently in the application of cross correlation analysis (Govindan et al, 2008) and beamformer model search (McCubbin et al, 2007, Robinson and Vrba, 2004) to fetal MEG evoked response detection. In Govindan et al (2008), the cross correlation computed between the stimulus signal and each MEG channel was subjected to a bootstrap confidence level estimate.…”

“…This has been addressed recently in the application of cross correlation analysis (Govindan et al, 2008) and beamformer model search (McCubbin et al, 2007, Robinson and Vrba, 2004) to fetal MEG evoked response detection. In Govindan et al (2008), the cross correlation computed between the stimulus signal and each MEG channel was subjected to a bootstrap confidence level estimate. The peaks in the correlation time course which exceeded the confidence level were then selected as latency for each MEG channel.…”

“…Fetal MEG analysis suffers from the same problem as exemplified in Govindan et al (2008) where p-values over about 150 MEG channels are compared, and in McCubbin et al (2007) with thousands of p-values in the search grid for comparison. We have selected an approach which seems particularly well suited to beamformer SPM analysis (Barnes and Hillebrand, 2003) and is based on PET and fMRI applications (Friston et al, 1996; Worsley et al, 1999).…”

Characterizing the Propagation of Uterine Electrophysiological Signals Recorded with a Multi-Sensor Abdominal Array in Term Pregnancies

“…For a given 30-second period, we calculated delay between the CoG from two active windows using time shifted cross-correlation analysis as described in Furdea et al [ 24 ]. The delays were tabulated and tested for significance using a bootstrap approach [ 27 ]. Finally, the propagation speed was calculated as the ratio of the distance between the average CoGs of the two quadrants to time delay.…”

Habituation of visual evoked responses in neonates and fetuses: A MEG study

“…If the peaks on the subsequent flashes appeared more than 150 ms earlier or later than the peaked response to the first flash, these were considered different components of the evoked response and therefore disregarded. In the second step, we conducted a bootstrap test (Govindan et al, 2008). ERs were identified by visual inspection and then confirmed or rejected by bootstrap.…”