TY - JOUR
T1 - Least-squares (LS) deconvolution of a series of overlapping cortical auditory evoked potentials
T2 - a simulation and experimental study
AU - Bardy, Fabrice
AU - Van Dun, Bram
AU - Dillon, Harvey
AU - Cowan, Robert
PY - 2014/8
Y1 - 2014/8
N2 - Objective. To evaluate the viability of disentangling a series of overlapping 'cortical auditory evoked potentials' (CAEPs) elicited by different stimuli using least-squares (LS) deconvolution, and to assess the adaptation of CAEPs for different stimulus onset-asynchronies (SOAs). Approach. Optimal aperiodic stimulus sequences were designed by controlling the condition number of matrices associated with the LS deconvolution technique. First, theoretical considerations of LS deconvolution were assessed in simulations in which multiple artificial overlapping responses were recovered. Second, biological CAEPs were recorded in response to continuously repeated stimulus trains containing six different tone-bursts with frequencies 8, 4, 2, 1, 0.5, 0.25 kHz separated by SOAs jittered around 150 (120-185), 250 (220-285) and 650 (620-685) ms. The control condition had a fixed SOA of 1175 ms. In a second condition, using the same SOAs, trains of six stimuli were separated by a silence gap of 1600 ms. Twenty-four adults with normal hearing (<20 dB HL) were assessed. Main results. Results showed disentangling of a series of overlapping responses using LS deconvolution on simulated waveforms as well as on real EEG data. The use of rapid presentation and LS deconvolution did not however, allow the recovered CAEPs to have a higher signal-to-noise ratio than for slowly presented stimuli. The LS deconvolution technique enables the analysis of a series of overlapping responses in EEG. Significance. LS deconvolution is a useful technique for the study of adaptation mechanisms of CAEPs for closely spaced stimuli whose characteristics change from stimulus to stimulus. High-rate presentation is necessary to develop an understanding of how the auditory system encodes natural speech or other intrinsically high-rate stimuli.
AB - Objective. To evaluate the viability of disentangling a series of overlapping 'cortical auditory evoked potentials' (CAEPs) elicited by different stimuli using least-squares (LS) deconvolution, and to assess the adaptation of CAEPs for different stimulus onset-asynchronies (SOAs). Approach. Optimal aperiodic stimulus sequences were designed by controlling the condition number of matrices associated with the LS deconvolution technique. First, theoretical considerations of LS deconvolution were assessed in simulations in which multiple artificial overlapping responses were recovered. Second, biological CAEPs were recorded in response to continuously repeated stimulus trains containing six different tone-bursts with frequencies 8, 4, 2, 1, 0.5, 0.25 kHz separated by SOAs jittered around 150 (120-185), 250 (220-285) and 650 (620-685) ms. The control condition had a fixed SOA of 1175 ms. In a second condition, using the same SOAs, trains of six stimuli were separated by a silence gap of 1600 ms. Twenty-four adults with normal hearing (<20 dB HL) were assessed. Main results. Results showed disentangling of a series of overlapping responses using LS deconvolution on simulated waveforms as well as on real EEG data. The use of rapid presentation and LS deconvolution did not however, allow the recovered CAEPs to have a higher signal-to-noise ratio than for slowly presented stimuli. The LS deconvolution technique enables the analysis of a series of overlapping responses in EEG. Significance. LS deconvolution is a useful technique for the study of adaptation mechanisms of CAEPs for closely spaced stimuli whose characteristics change from stimulus to stimulus. High-rate presentation is necessary to develop an understanding of how the auditory system encodes natural speech or other intrinsically high-rate stimuli.
KW - Cortical auditory evoked potentials
KW - Least-squares deconvolution
KW - Low-jittering
KW - Multiple overlapping responses
KW - SNR
UR - http://www.scopus.com/inward/record.url?scp=84903624851&partnerID=8YFLogxK
U2 - 10.1088/1741-2560/11/4/046016
DO - 10.1088/1741-2560/11/4/046016
M3 - Article
C2 - 24963952
AN - SCOPUS:84903624851
SN - 1741-2560
VL - 11
SP - 1
EP - 14
JO - Journal of Neural Engineering
JF - Journal of Neural Engineering
IS - 4
M1 - 046016
ER -