Objective Response Detection Techniques Research Articles

Choosing multichannel objective response detectors for multichannel auditory steady-state responses

The assessment of evoked responses still largely relies on subjective assessment, though a number of objective response detection techniques have been proposed, which are usually based on the statistical analysis of electroencephalogram (EEG) signals. In the current work, we expand on this with an investigation of multichannel objective response detection (MORD) methods, by assessing the performance of six previously published MORD algorithms together with three new methods (named product of Local Spectral F-test, average and the product of Component Synchrony Measure). The MORD techniques were evaluated in both simulated data and in multifrequency Auditory Stead-State Responses (ASSRs) recorded from 11 normal-hearing volunteers. The performances of MORD techniques were evaluated based on detection rates and the number of false positive tests. The results demonstrate that inflated false positive rates can arise when correlation between EEG channels is not taken into account by some of the MORD methods, but the algorithms are fairly robust to low cross-channel correlations. Furthermore, two of the already established MORD techniques showed immunity to cross-channel correlation. The results showed that the sensitivity of response detection increased when more than one channel was used, and an increase of up to 16 % compared to the best single-channel method could be achieved by the newly proposed best MORD methods. MORD methods are thus a promising new tool for ASSR detection.

A bayesian approach to the spectral F-Test: Application to auditory steady-state responses

Background and ObjectiveAuditory steady-state responses (ASSRs) represent an objective method used in clinical practice to assess hearing thresholds. The steady-state nature of these signals allows response detection by means of statistical techniques in the frequency domain as spectral F-test. This objective response detection (ORD) compares the power of the response bin against the power of the neighboring frequency noise bins. Most ORD algorithms are based on the Neyman-Pearson approach to the hypothesis test provided that the likelihood ratio test is the most powerful test for a given significance level alpha (also called Type I error). On the other hand, the Bayesian approach allows the inclusion of prior information in the model and enables the updating of this information with posterior knowledge. This approach, however, has not been explored with respect to ORD techniques, thus enabling the exploration of new paradigms, which may contribute to this field of study, especially in terms of the time required for response detection. The aim of this study is to use the Bayesian approach in the implementation of the spectral F-test for application to ASSRs. MethodsMonte Carlo simulations were performed to evaluate Neyman-Pearson and Bayesian detectors’ performances with the spectral F-test as a function of the signal-to-noise ratio. Then, the two detectors were applied to ASSR recordings of nine normal-hearing individuals subjected to amplitude-modulated tones of various intensities. ResultsBoth simulation and ASSR data analyses showed that among the scenarios analyzed, the most promising case was that in which the lowest possible values for the a priori probability were selected for the null hypothesis (H0), allowing detection at low signal-to-noise ratios. The worst performance occurred when the a priori probabilities for both hypotheses were equal. The ASSR data also showed that higher stimulus intensity led to better performance and faster detection due to improvements in the signal-to-noise ratio. ConclusionsThe a priori probabilities can affect the Bayesian detector's performance, directly impacting the time needed to identify responses. The parallel behaviors observed between the performances of both approaches showed that the Bayesian detector can achieve its ideal performance at lower signal-to-noise ratios compared to the optimal performance of the Neyman-Pearson detector, reflecting the promising applicability of the Bayesian approach to evoked potentials.

Improving the detection of auditory steady-state responses near 80 Hz using multiple magnitude-squared coherence and multichannel electroencephalogram

Abstract The detection of auditory steady-state responses (ASSRs) is an important task in hearing sciences. Since the signal-to-noise ratio (SNR) of ASSR is low, only signal processing techniques can reveal the presence of such responses immersed in the background electroencephalogram (EEG). The Objective Response Detection (ORD) techniques are mathematical tools that perform an automatic hypothesis test in frequency domain and the Magnitude-Squared Coherence (MSC) is one of the most efficient univariate ORD technique. For a fixed SNR, the only way of improving the detection power of MSC is by using longer signals. However, recently the Multiple Magnitude-Squared Coherence (MMSC) was developed as a multivariable extension of the MSC technique. This multivariate approach may be used to shorten the data length used for detection by using more EEG channels. Thus, this work aims at investigating the performance of the MMSC in the detection of ASSRs and to compare the results with MSC. The ASSRs were elicited by amplitude modulation pure tones delivered binaurally at 70 dB SPL to 24 volunteers with normal hearing thresholds. The carrier frequencies were 500, 1000, 2000 and 4000 Hz and they were modulated with frequencies near 80 Hz. The maximum detection rate and the minimum average detection time obtained were 95.31% and 146.69 s, respectively, and this result was obtained by MMSC using a set of five electrodes (Fz, Pz, Oz, F4 and T4). This result was significantly better than the best MSC result and represented an overall improvement around 18%. Therefore, it is concluded that the multivariate method MMSC has advantage when applied to the detection of ASSRs evoked near 80 Hz.

Comparison of univariate and multivariate magnitude-squared coherences in the detection of human 40-Hz auditory steady-state evoked responses

Abstract Objective response detection (ORD) techniques for evaluating bioelectrical evoked responses in the electroencephalogram (EEG) are based on statistical criteria rather than on visual inspection. Hence, they do not depend on human evaluation, which is often a subjective approach. Furthermore, since such techniques do not involve heuristic approaches, they may be more easily implemented and used in automatic systems. The Magnitude-Squared Coherence (MSC), together with its recently developed multivariate extension (the multiple magnitude-squared coherence – MMSC), have been pointed out as one of the most efficient ORD techniques for detecting steady-state responses in the EEG. In this work, both MSC and MMSC were applied to EEG signals collected during auditory stimulation in order to allow comparison in the detection of auditory steady-state responses (ASSRs). The stimuli consisted of 40 Hz amplitude-modulated tones delivered binaurally in the intensity of 50 dB SPL (sound pressure level). The best result was obtained by using MMSC in the two-electrode set C4 and Fz. This configuration led to a 0.92-detection ratio, within 111.55 s in average to detect each response and kept the false alarm ratio under 0.05. The average improvement in performance was about 11% when compared to the MSC. These results allow concluding that the detection protocol of 40 Hz ASSRs can be improved by using MMSC in multichannel EEG analysis when compared to the traditional univariate MSC approach.

RICE DETECTOR: PROPOSAL OF A NOVEL OBJECTIVE RESPONSE DETECTION TECHNIQUE

INTRODUCTION: The detection of the somatosensory response (SR) is an important tool for the neurophysiological evaluation in the intra and post-operative period of some vascular and spine surgeries. Particularly, the SR identification with a maximum false positive ratio by means of Objective Response Detection (ORD) techniques could lead to a less subjective procedure. In this work a novel ORD, the Rice Detector (RD), is presented and its theoretical critical value is obtained. METHODS: The probability of detection (PD) of RD is assessed for different numbers of eletroencephalographic (EEG) signal epochs (M = 30, 60, 120, 240) and signal-to-noise ratios (-20 to 10 dB, in steps of 1 dB) by means of simulation. The simulated PD curves (PDc) are compared with the theoretical ones and with the PDc of the Magnitude-Squared Coherence (MSC), a well-known ORD technique. The performance of RD and MSC are also compared for real EEG data. The comparison is based on the DP for estimates calculated with M = 30, 60, 120 and 240 epochs. RESULTS: The results showed that the simulated PDc follow the theoretical ones and both the MSC and RD present similar performance, with slight advantage for this latter at low M-values. However, for real data, no statistical significant difference (proportion test with alpha=0.05) was found between MSC and RD. CONCLUSION: Both techniques presented mean detection rates varying from 70% to 90%, even for intermediate M-value (120 epochs), and can be useful for evoked response detection applications.

Tibial nerve somatosensory evoked response detection using uni and multivariate coherence

This work aims at comparing the capability of two Objective Response Detection techniques, the Magnitude-Squared Coherence (MSC or Ordinary Coherence) and its multivariate extension, the Multiple Coherence (MC), of detecting the somatosensory evoked response. Electroencephalographic (EEG) signals were collected during somatosensory stimulation from forty adult volunteers without history of neurological disease and with normal somatosensory evoked potential (SEP), using the 10-20 International System. All leads were referenced to the earlobe average. Current pulses with 200μs of duration were applied to the right posterior tibial nerve at the motor threshold intensity level (the lowest intensity able to produce hallux oscillations) at the rate of 5Hz. The MSC was applied to the derivations [Cz], [Fz], [C3] and [C4] – commonly used for tibial nerve SEP recordings with bipolar derivations – and the MC was applied to the pairs [Cz][Fz] and [C3][C4]. Both estimates (MC and MSC) were calculated with M=100 and 500 epochs and the response detection was based on rejecting the null hypothesis of response absence, which is achieved when the estimates exceed the critical value (detection threshold) calculated for a given significance level (α=0.05). The results showed that if two leads are available, the application of the MC is better than the MSC applied to each lead individually.

Using Objective Response Detection techniques for detecting the tibial somatosensory evoked response with different stimulation rates

This work investigates the influence of the stimulus frequency in the performance of two Objective Response Detection (ORD) techniques, the Magnitude-Squared Coherence (MSC) and the Component Synchrony Measure (CSM), as applied in somatosensory stimulation. Electroencephalographic signals were collected (10–20 International System) from forty adult volunteers without history of neurological pathologies. The stimuli were applied to the right posterior tibial nerve at the frequencies of 2, 5, 7 and 9Hz and motor threshold intensity level. The detection was based on the rejection of the null hypothesis of response absence (significance level α=0.05 and M=100 and 500epochs). The performances of the MSC at the four stimulation frequencies were compared, two-by-two, using the Proportion Test applied to the mean percentage rates in the total (2–100Hz) and optimal (20–60Hz) bands. The same was proceeded to the CSM. The evaluated derivations were Cz, C4, Pz and P4. No significant difference was found for any studied technique (MSC or CSM), any M-value, at any derivation. Thus, the highest stimulation frequency (9Hz) can be used in order to obtain a reduction in the time of response detection in an ORD approach for a fixed M-value.

Topographic distribution of the tibial somatosensory evoked potential using coherence

The objective of the present study was to determine the adequate cortical regions based on the signal-to-noise ratio (SNR) for somatosensory evoked potential (SEP) recording. This investigation was carried out using magnitude-squared coherence (MSC), a frequency domain objective response detection technique. Electroencephalographic signals were collected (International 10-20 System) from 38 volunteers, without history of neurological pathology, during somatosensory stimulation. Stimuli were applied to the right posterior tibial nerve at the rate of 5 Hz and intensity slightly above the motor threshold. Response detection was based on rejecting the null hypothesis of response absence (significance level alpha= 0.05 and M = 500 epochs). The best detection rates (maximum percentage of volunteers for whom the response was detected for the frequencies between 4.8 and 72 Hz) were obtained for the parietal and central leads mid-sagittal and ipsilateral to the stimulated leg: C4 (87%), P4 (82%), Cz (89%), and Pz (89%). The P37-N45 time-components of the SEP can also be observed in these leads. The other leads, including the central and parietal contralateral and the frontal and fronto-polar leads, presented low detection capacity. If only contralateral leads were considered, the centro-parietal region (C3 and P3) was among the best regions for response detection, presenting a correspondent well-defined N37; however, this was not observed in some volunteers. The results of the present study showed that the central and parietal regions, especially sagittal and ipsilateral to the stimuli, presented the best SNR in the gamma range. Furthermore, these findings suggest that the MSC can be a useful tool for monitoring purposes.

Objective response detection technique in frequency-domain for reflecting changes in MLAEP

The mid-latency auditory evoked potential (MLAEP) occurs within the interval 10–100 ms post-stimulus and exhibits morphological changes due to coma, general anaesthesia and neurological and psychiatric diseases. This work evaluates an objective response detection technique in the frequency domain, the magnitude squared coherence ( κ ˆ 2 ( f ) ) , in reflecting MLAEPs changes in amplitude and latencies. Both simulation and EEG data were used in this investigation. The EEG during auditory stimulation in 10 volunteers under propofol-induced anaesthesia was acquired. Based on the null hypothesis of non-existing response, critical values have been derived in order to detect the auditory response. The alternative hypothesis was used to infer about maximal-response frequencies as well as to derive confidence intervals for the estimated values of κ ˆ 2 ( f ) during anaesthesia. Changes in both simulated and real MLAEPs could be tracked by κ ˆ 2 ( f ) , even for low SNR. High degree of cortical activation occurred predominantly between 30 and 90 Hz. This finding could be related to the sensory-originated phase-locked oscillation in the gamma band (30–70 Hz). Hence, for applications where changes on MLAEPs should be assessed, the use of κ ˆ 2 ( f ) as an objective statistical response detection technique is worth to be applied.