The Cortical Automatic Threshold Estimation in Adults

This article brings together the work we have been doing at the National Acoustic Laboratories (NAL) to make cortical threshold testing easy, fast, and accurate. Our aim is to improve techniques for estimating hearing thresholds on people who, for whatever reason, are unable to give reliable behavioural responses to indicate that they have heard a sound. The particular techniques described have general applicability to cortical testing, and have been evaluated within a practical package that will become part of the HEARLab family of test modules. Cortical testing nicely complements auditory brainstem testing both because it is best carried out while the patient is awake rather than asleep, and it measures more of the auditory system compared with brainstem testing. Our eventual goal is to have a test that can be used for babies with auditory neuropathy spectrum disorder – in whom cortical thresholds can often be measured even though auditory brainstem responses are absent. We have not achieved that goal yet, but as the article shows, we developed a test that automatically produces reliable threshold estimates in older children and adults. The technique is highly automated – in principle, only one button press, and no human decision making or intervention, is needed to obtain an audiogram in both ears. Our philosophy is that if a computer is better able than humans to examine the consistency of the cortical responses to, say, 50 repeated stimulus presentations, and is able do this simultaneously for eight different stimuli, then it should be left to perform tests uninterrupted by humans! Clinicians should continue doing what they do best: deal with truly complex issues. These include understanding client beliefs and behaviors, and developing inferences from the results of diverse auditory tests. Harvey Dillon, PhDFigure 1: Screenshot of the CATE software while recording CAEPs from a normal-hearing adult with hearing thresholds in both ears at frequencies 500, 1000, 2000 and 4000 Hz. For each frequency, the cortical waveforms recorded at different intensities are displayed in each sub-windows. The estimated threshold is indicated in the audiogram on the right part of the screen. The bottom right window displays the continuous EEG.While use of cortical auditory evoked potentials (CAEPs) has been shown to be accurate and reliable for objective threshold estimation, the procedure is in general conducted manually (i.e., using only one stimulus frequency presented at one intensity level at a time). The consequence is a lengthy test duration and a significant number of manual operations for the audiologist, which renders it impractical in clinical applications. To address this issue, the National Acoustic Laboratories (NAL), through the HEARing Cooperative Research Centre, has come up with a combination of smarter technologies. SUBJECTIVE RESPONSESFigure: Fabrice BardyFigure: Bram Van DunStandard audiometric threshold assessment requires the client to subjectively respond when they hear a sound, either by pressing a button or giving a verbal indication. In the case of children, subjective responses are age-appropriate actions such as putting a toy into a jar or turning to a lighted puppet in response to the stimulus. For people with significant cognitive impairment, or for infants, obtaining reliable subjective responses may be difficult or impossible. In addition, the presence of other co-morbidities may further complicate the procedure.Figure: Harvey DillonFigure: Mark SeetoTo enable a reliable audiogram to be established in the so-called “difficult to test” client (i.e., those with severe dementia, those who experienced a stroke, malingerers looking for legal compensation, children with multiple disabilities, and children too young to respond behaviorally), there is a clear need for use of objective testing in addition to any reliance on voluntary responses. HEARING THRESHOLDSFigure: Humphry QinFigure: Teck LoiHearing thresholds can be estimated reliably in adults or children through electrophysiological assessment, without the need to rely on their behavioral feedback. This is achieved by using sensors attached to the scalp to record the brain's response to different sound frequencies presented at a range of intensities. An accurate estimate of a person's actual hearing threshold for any specific frequency can be determined based on the intensities that generate time-locked response to the stimulus.Figure: Robert CowanThere are two common ways to do this. One is through auditory brainstem response (ABR), done by recording the responses from the auditory brainstem (i.e., lower end of the auditory path). Another way is through the auditory cortex (i.e., higher end of the auditory path) or CAEP. For the ABR, responses are preferably recorded when the person is asleep; CAEP testing is best conducted when the client is awake. In cases of auditory neuropathy spectrum disorder (ANSD), however, brainstem measurements are out of the question, and CAEPs are the only objective method with the potential to obtain reliable hearing thresholds. Traditional electrophysiological assessment has several potential drawbacks. Establishing thresholds using ABR and/or CAEP requires multiple test running at different frequencies and a sequence of intensities, producing traces that must then be subjectively evaluated by an experienced electrophysiologist or audiologist trained to identify the small peaks in the recorded waveforms that signify the presence of a response. This can be time-consuming, open to error (it's based on subjective judgement), and expensive, given the need for a skilled clinician. IMPROVEMENTS IN HEARING THRESHOLD ESTIMATION Recent innovations devised by NAL through the HEARing CRC and described in this article enable a full adult audiogram (i.e., hearing threshold estimation at four frequencies in both ears) to be acquired using objective CAEP testing in approximately 40 minutes for hearing impaired subjects. Figure 1 shows the test screen with CAEPs at different levels and derived CAEP thresholds for four audiometric frequencies in two ears. The method is designed to be fully push-of-the-button automatic; it requires only minimal training of the tester and focuses on maximizing the cortical response while minimizing the recording time. This is made possible by the use of: novel stimuli that increase the size of the CAEP; two EEG recording channels to weigh the response more toward the channel with the better signal-to-noise ratio; the presentation of interleaved frequencies, ears and levels (to keep the stimuli unpredictable enough such that the brain is kept interested); statistical evaluation of the recorded responses to make simpler the interpretation by the clinician; and an automatic decision algorithm that decides which stimulus and level to test and when to stop testing. NOVEL STIMULI The stimuli most commonly used to obtain frequency-specific hearing thresholds using CAEPs are short tone-bursts with a specific frequency (e.g., 1000 Hz) and a duration of around 50 ms. We recently have shown that by using multi-tone complexes, the size of the resulting CAEPs can be increased by 32 percent for normal-hearers and 29 percent for listeners with a hearing loss, corresponding to a potential recording time decrease of 40 percent for all audiometric frequencies except 500 Hz (Bardy. Ear Hear 2015;36[6]:677-87 http://www.ncbi.nlm.nih.gov/pubmed/26039014; Bardy. J Am Acad Audiol 2016;In press http://dspace.nal.gov.au/xmlui/handle/123456789/273). For example, the 1000 Hz pure tone is replaced by a set of tones contained within 2/3 of an octave and centered around 1000 Hz. We hypothesize that, despite the frequency specificity of these sounds, the larger cortical response is a result of increased processing in the auditory cortex of these complex sounds (possibly inhibitory processing associated with analyzing the multiple spectral peaks in the signal) as compared with processing of pure tones. The larger amplitude is not a result of the multi-tone stimulus having a bigger bandwidth than the pure tone, as the effect does not occur for bands of noise. In the cortical automatic threshold estimation (CATE) adult protocol, each stimulus is 50 ms long and presented a maximum number of 120 times, with an inter-stimulus interval varying between one and two seconds. TWO EEG RECORDING CHANNELS In most clinical applications involving CAEPs, three electrodes are placed on the scalp to record the responses of interest from the auditory cortex. The common (or ground) electrode is placed on the forehead, the active electrode on top of the head, and the reference electrode on one of the mastoids. This is generally referred to as a “one-channel setup,” which shows the voltage at the active electrode relative to that at the reference electrode. By using two reference electrodes instead of one, and placing them on the two mastoids (and hence using an additional channel), extra information can be simultaneously collected, which can then be exploited by choosing or weighting the channels considering their signal-to-noise ratio. In the extreme case—for example, when one mastoid electrode loses contact—the other channel can be chosen without the need to stop the current recording. On average, we found that using two reference electrodes results in an improved detection sensitivity of 5 percent as compared to a single channel montage. PRESENTATION OF INTERLEAVED FREQUENCIES, EARS AND LEVELS The brain habituates rapidly to similar stimuli. By randomizing the frequency of the stimulus, the ear of presentation and the stimulus intensity, the brain may be kept “more interested” in the stimuli being presented. Although the achieved benefit is usually rather small, studies have shown larger responses can be elicited (Bardy. Clin Neurophysiol 2014;125[4]:814-26 http://www.ncbi.nlm.nih.gov/pubmed/24269614). In particular, when stimuli are being presented at an intensity level below threshold at one frequency, it appears to the brain that the stimuli immediately before and after it (at other frequencies and intensities) have a particularly long inter-stimulus interval. The brain “rewards” this long gap with a larger than usual cortical response. STATISTICAL EVALUATION OF THE RECORDED RESPONSES The use of automatic interpretation of the response waveform obviates the need for subjective visual interpretation by the clinician. The software provides for an automatic interpretation of the response waveform by cutting the waveform into predefined time slices. It subsequently measures whether any combination of the average values within all of these slices is significantly different from zero by taking into account the repeatability over epochs within each slice. This can be achieved using the Hotelling's T2 statistic, which returns a p-value expressing the level of confidence in response presence. That is, it can be used to decide whether a response is present or not (e.g., using a cut-off point of p = 0.01 to correct for multiple testing) (Golding. Int J Audiol 2009;48[12]:833-42 http://www.ncbi.nlm.nih.gov/pubmed/20017680). For this statistical approach, no template is required, which is beneficial as CAEP shapes are quite variable across ages or even across different states of attention (Sharma. J Am Acad Audiol 2005;16[8]:564-73 http://www.ncbi.nlm.nih.gov/pubmed/16295243). The Hotelling's T2 generally is at least as good as an expert human interpreter (Golding; Carter. J Am Acad Audiol 2010;21[5]:347-56 http://www.ncbi.nlm.nih.gov/pubmed/20569668). In addition, statistical tests are calculated at specific residual noise values instead of a fixed interval, which is the common approach. This allows optimization of the (variable) time intervals and the number of statistical tests during one recording (the fewer the better). Moreover, the test can be stopped as soon as a significant response is detected whilst keeping the specificity (false positive rate) at an acceptable level. AUTOMATIC DECISION ALGORITHM FOR THE NEXT LEVEL Starting from an initial intensity level of 60 dB HL and using a set of rules, the algorithm automatically searches for the CAEP threshold using an adaptive step size. When the statistical detection algorithm decides that a response is present, the presentation level is lowered (in steps of 10 or 20 dB, depending on the stage of testing). When the response is absent, presentation level is increased (in steps of 20 dB). In both cases, it is also possible that the software decides to stop testing the ear-specific stimulus altogether. For example, a response detected at 20 dB HL is considered enough evidence that the subject is normal-hearing at that frequency. Similarly, if a response has been detected at a specific level within the tested range, but no response at a level one step lower, the cortical threshold is placed at the lowest level with a significant response. HEARING THRESHOLD ESTIMATIONTable 1: Corrections and standard deviations (SDs) obtained from 20 normal-hearers and 27 listeners with a hearing loss. These corrections can be subtracted from the thresholds found from a fully automated CAEP audiometer to estimate behavioral thresholdsFigure 2: Child tested with the new CATE approach. Although the threshold searching approach has been verified in adults only, there is ongoing research in infants and young children.Table 1 shows the corrections and standard deviations obtained from 20 normal-hearing adults and 27 adult listeners with known hearing loss, using CATE to derive auditory thresholds. The corrections are determined as the difference between CAEP thresholds, obtained via CATE, and behavioral thresholds obtained through an automatic computerized audiometry with feedback from the listener using a push button. These corrections and their standard deviations are similar to those achieved with ABR (Stapells. J Speech Lang Pathol Audiol 2000;24:74–83 http://www.courses.audiospeech.ubc.ca/haplab/stapellsJSLPA.pdf). A more sophisticated correction strategy can be used by applying a non-linear regression to the observed CAEP thresholds, with the regressions based on the same data that gave rise to Table 1. The CATE approach can be used to determine hearing thresholds in a time-efficient and reliable way in adults. After the algorithm estimates the client's CAEP thresholds, simple corrections or a regression function can be applied to estimate the client's actual audiogram. Applications include the testing of adults who cannot provide reliable feedback. Child evaluation has so far tested children aged 8 to 9 years, but there is no reason why it shouldn't be possible to apply the technique down to the age of 6. In fact, our current research is investigating the feasibility of hearing threshold estimation using CAEPs in children younger than 6 years of age (Figure 2). Such a solution would be especially valuable for infants with ANSD, for whom hearing thresholds cannot be reliably obtained at present.