Comparison of Auditory Middle-Latency Responses From Two Deconvolution Methods at 40 Hz

Tan, Xiaodan; Peng, Xian; Zhan, Chang’an A.; Wang, Tao

doi:10.1109/tbme.2015.2485273

Cited by 4 publications

(8 citation statements)

References 56 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In combination with the regularization techniques (Hansen, 1998 ; Colton et al, 2000 ), stable solutions for transient response estimation can then be obtained. Therefore, the MSAD used a rate-jitter sequencing scheme, but still assumed identical responses to stimuli at different stimulation rates (Wang et al, 2013b ; Tan et al, 2016 ). Via comparing the CLAD and MSAD paradigms (Tan et al, 2016 ), it was intriguing to find that deconvolved transient responses at 40 Hz from them showed certain morphological differences.…”

Section: Introductionmentioning

confidence: 99%

Improved Transient Response Estimations in Predicting 40 Hz Auditory Steady-State Response Using Deconvolution Methods

Tan

Yuan

et al. 2017

Front. Neurosci.

Self Cite

View full text Add to dashboard Cite

The auditory steady-state response (ASSR) is one of the main approaches in clinic for health screening and frequency-specific hearing assessment. However, its generation mechanism is still of much controversy. In the present study, the linear superposition hypothesis for the generation of ASSRs was investigated by comparing the relationships between the classical 40 Hz ASSR and three synthetic ASSRs obtained from three different templates for transient auditory evoked potential (AEP). These three AEPs are the traditional AEP at 5 Hz and two 40 Hz AEPs derived from two deconvolution algorithms using stimulus sequences, i.e., continuous loop averaging deconvolution (CLAD) and multi-rate steady-state average deconvolution (MSAD). CLAD requires irregular inter-stimulus intervals (ISIs) in the sequence while MSAD uses the same ISIs but evenly-spaced stimulus sequences which mimics the classical 40 Hz ASSR. It has been reported that these reconstructed templates show similar patterns but significant difference in morphology and distinct frequency characteristics in synthetic ASSRs. The prediction accuracies of ASSR using these templates show significant differences (p < 0.05) in 45.95, 36.28, and 10.84% of total time points within four cycles of ASSR for the traditional, CLAD, and MSAD templates, respectively, as compared with the classical 40 Hz ASSR, and the ASSR synthesized from the MSAD transient AEP suggests the best similarity. And such a similarity is also demonstrated at individuals only in MSAD showing no statistically significant difference (Hotelling's T2 test, T2 = 6.96, F = 0.80, p = 0.592) as compared with the classical 40 Hz ASSR. The present results indicate that both stimulation rate and sequencing factor (ISI variation) affect transient AEP reconstructions from steady-state stimulation protocols. Furthermore, both auditory brainstem response (ABR) and middle latency response (MLR) are observed in contributing to the composition of ASSR but with variable weights in three templates. The significantly improved prediction accuracy of ASSR achieved by MSAD strongly supports the linear superposition mechanism of ASSR if an accurate template of transient AEPs can be reconstructed. The capacity in obtaining both ASSR and its underlying transient components accurately and simultaneously has the potential to contribute significantly to diagnosis of patients with neuropsychiatric disorders.

show abstract

Section: Introductionmentioning

confidence: 99%

Improved Transient Response Estimations in Predicting 40 Hz Auditory Steady-State Response Using Deconvolution Methods

Tan

Yuan

et al. 2017

Front. Neurosci.

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, SNR may be balanced by suppressed response due to the adaptation effect of nervous systems at rapid stimulation rates [22]. Since different AEP components may exhibit various adaptation effects, some components may even be enhanced if they are sensitive to the jitter in m-sequence [23, 24]. It is therefore not wise to investigate SNR under such conditions.…”

Section: Discussionmentioning

confidence: 99%

Noise Attenuation Estimation for Maximum Length Sequences in Deconvolution Process of Auditory Evoked Potentials

Peng

Chen

Wang

et al. 2017

Computational and Mathematical Methods in Medicine

Self Cite

View full text Add to dashboard Cite

The use of maximum length sequence (m-sequence) has been found beneficial for recovering both linear and nonlinear components at rapid stimulation. Since m-sequence is fully characterized by a primitive polynomial of different orders, the selection of polynomial order can be problematic in practice. Usually, the m-sequence is repetitively delivered in a looped fashion. Ensemble averaging is carried out as the first step and followed by the cross-correlation analysis to deconvolve linear/nonlinear responses. According to the classical noise reduction property based on additive noise model, theoretical equations have been derived in measuring noise attenuation ratios (NARs) after the averaging and correlation processes in the present study. A computer simulation experiment was conducted to test the derived equations, and a nonlinear deconvolution experiment was also conducted using order 7 and 9 m-sequences to address this issue with real data. Both theoretical and experimental results show that the NAR is essentially independent of the m-sequence order and is decided by the total length of valid data, as well as stimulation rate. The present study offers a guideline for m-sequence selections, which can be used to estimate required recording time and signal-to-noise ratio in designing m-sequence experiments.

show abstract

“…Some applicable sequences were presented for the convenience of similar uses in the study of MLR components [16,18, 26,31]. These sequences have been evaluated in terms of C dec values or by visual inspection on their spectra.…”

Section: Discussionmentioning

confidence: 99%

“…Because the existence of AEP and its major components elicited at this rate have been well established[13,14,18], the purpose of this experiment is to demonstrate possible distortions on AEP caused by different sequences. The rarefaction clicks of duration of 0.1 ms were delivered monaurally to the right ear at 82 dB SPL via an insert earphone (ER-3A Etymotic Research, Elk Grove Village, IL).…”

Section: Methodsmentioning

confidence: 99%

“…To date, multiple related techniques have been introduced, leading to several new deconvolution algorithms, such as the randomized stimulation and averaging method proposed by Valderrama et al [13], least-squares deconvolution method by Bardy et al [14], and multi-rate steady-state averaging deconvolution method by Wang et al [15]. These methods have been found valuable for studies of transient AEPs and their roles in the generation of SSRs [16–18]. They have also been used in investigating basic neuroscience problems, e.g., neuronal adaptation phenomena observed from high-rate ABRs [19] and ABRs simultaneously with electrocochleography [20], and in assisting clinical procedures, e.g., anesthesia monitoring [21,22].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

New metric for optimizing Continuous Loop Averaging Deconvolution (CLAD) sequences under the 1/f noise model

et al. 2017

Self Cite

View full text Add to dashboard Cite

Continuous loop averaging deconvolution (CLAD) is one of the proven methods for recovering transient auditory evoked potentials (AEPs) in rapid stimulation paradigms, which requires an elaborated stimulus sequence design to attenuate impacts from noise in data. The present study aimed to develop a new metric in gauging a CLAD sequence in terms of noise gain factor (NGF), which has been proposed previously but with less effectiveness in the presence of pink (1/f) noise. We derived the new metric by explicitly introducing the 1/f model into the proposed time-continuous sequence. We selected several representative CLAD sequences to test their noise property on typical EEG recordings, as well as on five real CLAD electroencephalogram (EEG) recordings to retrieve the middle latency responses. We also demonstrated the merit of the new metric in generating and quantifying optimized sequences using a classic genetic algorithm. The new metric shows evident improvements in measuring actual noise gains at different frequencies, and better performance than the original NGF in various aspects. The new metric is a generalized NGF measurement that can better quantify the performance of a CLAD sequence, and provide a more efficient mean of generating CLAD sequences via the incorporation with optimization algorithms. The present study can facilitate the specific application of CLAD paradigm with desired sequences in the clinic.

show abstract

Comparison of Auditory Middle-Latency Responses From Two Deconvolution Methods at 40 Hz

Abstract: These findings have critical implications in our current understanding of the rate effects on MLR characteristics which may inspire further studies to explore the characteristics of evoked responses at high rates and deconvolution paradigms.

Cited by 4 publications

References 56 publications

Improved Transient Response Estimations in Predicting 40 Hz Auditory Steady-State Response Using Deconvolution Methods

Improved Transient Response Estimations in Predicting 40 Hz Auditory Steady-State Response Using Deconvolution Methods

Noise Attenuation Estimation for Maximum Length Sequences in Deconvolution Process of Auditory Evoked Potentials

New metric for optimizing Continuous Loop Averaging Deconvolution (CLAD) sequences under the 1/f noise model

Contact Info

Product

Resources

About