Vishakha W. Rawool, PhD
Professor and Director of Graduate Study in Audiology
West Virginia University, Morgantown, West Virginia, USA
Email: VWRawool@mail.wvu.edu

 

 

The auditory system is capable of processing auditory stimuli without active attention as summarized in Rawool (2016a). This article is designed to review a few findings related to auditory processing without active attention and discuss how such processing can be capitalized to support the diagnoses of an auditory processing deficit in the presence of suspicion of other comorbid deficits such as autism spectrum disorders (ASD) or borderline cognitive deficits.

 

Auditory Processing during Sleep

 

Auditory brainstem responses, MMN and even P300 can be recorded during sleep.  In fact, it is easier to record the auditory brainstem response when the participant is asleep.  The auditory brainstem response of a child while the child was asleep is shown in Fig. 1.  In addition, it is well known that the auditory sensitivity of the participant can be determined through identification of wave V, in participants who are asleep.  The latencies and amplitudes of ABR waveforms change systematically with change in stimulus level showing that the loudness of the stimulus is coded within the auditory brainstem without the need for asking the participant to attend to the stimuli.

 

 

Figure 1.  Example of ipsilateral (upper trace) and contralateral (lower trace) auditory brainstem responses obtained during sleep from an 8 year old girl by stimulating the left (left panel) and right (right panel) ears.

 

 

Detection of Meaningful Auditory Events during Sleep

 

The thalamus, auditory cortex, and caudate activation is similar during non-rapid eye movement (NREM) sleep and wakefulness, when assessed through Functional Magenetic Resonance Imaging (fMRI). There are also differences in the response patterns to simple stimuli such as beeps and complex emotionally relevant stimuli such as the participant’s name during sleep (Portas et al., 2000). Enhancement of P300 responses is not apparent to any other names besides the participant’s name during sleep (Perrin, Garcia-Larrea, Mauguiere, and Bastuji, 1999). Angry voices evoke stronger evoked potentials compared to neutral voices during stage 2 sleep (Blume et al., 2016). Overall these findings show that processing of auditory stimuli and detection of meaningful events can occur during sleep (Portas, Krakow, Allen, et al. 2000) or without active attention. Such processing has functional significance and may allow protection from dangerous events. For example, young mothers usually are able to hear their own infants’ cries during deep sleep.

 

 

Discrimination of Auditory Stimuli during Sleep

 

Electroencephalographic recordings clearly show the presence of  a Mismatch Negativity (MMN) in response to tones, deviant in duration (75 ms), in the presence of standard tones of 30 ms, during the first three stages of sleep (Ruby, Caclin, Boulet, Delpuech, & Morlet, 2008). Full-term, 1-3 days old infants also show a response to tones deviant in frequency (500 Hz), in the presence of standard tones of 700 Hz (Háden, Németh, Török, & Winkler, 2016). This shows that the system is capable of distinguishing between auditory stimuli that differ in various dimensions including frequency or duration, without paying active attention. Clinical Implications:

 

Many children diagnosed with comorbid deficits can be diagnosed with auditory processing deficits using only behavioral procedures with proper controls. For example, children with attention deficits show good attention and vigilance in structured testing environments with appropriate breaks and reinforcements on behavioral tasks (Rawool, 2014). When there is a question about an auditory processing deficit in the presence of other potential deficits, it is possible to support the diagnoses of a processing deficit within the auditory pathways through objective procedures.

 

 

Case-Illustration

 

Key relevant case-history information: The patient is a 10-year-old boy with a history of ear infections from 12 to 24 months with sensitivity to loud sounds. He has been receiving speech-language therapy since the age of 2 years. Results of the Wechsler Intelligence Scale for Children – Fourth Edition (WISC-IV) yielded a Full Scale IQ of 75 (5th percentile rank), which falls within borderline range. However, there is a clinically significant disparity between his verbal (71 standard score with 3rd percentile rank) and perceptual reasoning scores (94 standard score with 34th percentile rank) with his perceptual score falling within the average range and his verbal score falling significantly below the average range. Such disparity limits the validity of his Full Scale IQ in predicting academic success. The patient was retained in grade 1 due to academic difficulties. At the time of referral for an auditory processing evaluation, the patient was in the 4th grade and his IEP included an FM device for classroom use, preferable sitting in the classroom, smaller classrooms for math and reading, recommendation for shorter assignments, proper use of visual reminders, repeat and restate directions and checks for understanding, and opportunities to type written work. Additional IEP goals included improving auditory memory, reading comprehension, and self-advocacy skills. The patient was aware of ongoing academic struggles and reported feeling sad about the issues.

 

Relevant Auditory Processing Test Results:  A test-battery was administered. Behavioral auditory processing test results showed deficits in processing dichotic (simultaneous presentation of two different stimuli to the two ears) stimuli as shown by poor performance on the Competing Words- Directed Ear task, the dichotic digits test and the Competing Sentences test. The auditory processing deficit was supported by objective test results showing prolonged latencies and inter-peak latencies of the right ipsilateral ABR suggesting slower processing within the auditory brainstem. In addition, a significant decay was apparent during acoustic reflex decay testing (Fig. 2). A child with acoustic reflex decay can show poor vigilance on verbal tasks as his auditory system fails to maintain processing of incoming stimuli over a longer period.

 

 

 

Figure 2.  Reflex decay in a child referred for auditory processing evaluation. The upper traces show decay patterns for the left ear and the lower traces show the patterns for the right ear.  Responses obtained with the stimulus frequency of 500 Hz are shown in the left panel and those obtained with the frequency of 1000 Hz are shown in the right panel.

Figure 2.  Reflex decay in a child referred for auditory processing evaluation. The upper traces show decay patterns for the left ear and the lower traces show the patterns for the right ear.  Responses obtained with the stimulus frequency of 500 Hz are shown in the left panel and those obtained with the frequency of 1000 Hz are shown in the right panel.

 

 

The child’s ipsilateral click evoked acoustic reflex thresholds did not improve when the click rate was increased from 50 to 100/sec in both ears. In normal children, the click evoked acoustic reflex thresholds improve by at least 6 dB with an increase in the click rate from 50 to 100/sec (Fielding & Rawool, 2002). The lack of click rate induced facilitation of acoustic reflex thresholds can be due to either poor temporal integration (integration of acoustic energy across time) for faster stimuli and/or deficit in efficiently processing of faster stimuli which can cause the auditory system to miss the processing of some of the clicks presented at higher rates. This deficit will lead to difficulty in quickly processing incoming transient auditory stimuli such as those occur during speech and integrating such stimuli over time.

 

Case-Relevant Discussion: The patient has an auditory processing deficit including the possibility of retro-cochlear pathology within the auditory brainstem.  The deficit could have been diagnosed sooner with adequate attention to the discrepancy between verbal and perceptual reasoning scores and the use of objective procedures to support the diagnoses of auditory processing deficit.  The objective procedures used here could have been administered at an age earlier than that recommended for behavioral test procedures to make definitive diagnoses of an auditory processing deficit. Such use could have minimized the child’s struggles in academic settings, his self-esteem, and parental struggles in convincing the school district that he is intellectually capable of learning.

 

 

Conclusions

  1. The human auditory system is capable of processing auditory stimuli without active attention. Such processing includes differentiation of key stimulus dimensions such as intensity, duration and frequency.
  2. The ability of the human auditory system to process auditory stimuli without active attention can be capitalized to support the diagnoses of auditory processing deficits in the presence of suspected or actual comorbid deficits.
  3. Some audiology professionals are reluctant in undertaking auditory processing evaluations in the presence of comorbid issues due to the possibility of confounding factors such as cognition, attention, and other developmental disorders including ASD. In such cases it is possible to support the diagnoses of an auditory processing deficit through objective test procedures. Future technological trends are likely to lead to easier implementation of objective procedures (Rawool, 2015, 2016b)
  4. Some professionals believe that the diagnoses of an auditory processing deficit is irrelevant in the presence of other comorbid deficits such ASD. However, it should be noted that deficit-specific intervention can lead to substantial improvement in such cases. This is similar to detecting (Pillion, Rawool, & Naidu, 2000; Pillion, Rawool, Bibat, & Naidu, 2003) and providing intervention for a peripheral hearing loss in the presence of comorbid deficits to allow such children to reach their maximum potential (Rawool, 2010a, 2010b).  Objective procedures can also assist in documenting the effects of such intervention (Schochat, Musiek, Alonso, & Ogata, 2010).

 

 

 

 

 

Vishakha W. Rawool is a professor and director of the Doctor of Audiology program at West Virginia University, Morgantown, WV.  Dr. Rawool’s research spans across prevention, screening, diagnosis, and intervention of hearing difficulties among all populations including infants to older adults. The research is conducted using a variety of subjective and objective procedures. Currently the focus of her research is on three interconnected areas of research including auditory processing deficits, age-related hearing loss and speech perception deficits, and hearing conservation. Her recent achievements include a new text-book on auditory processing deficits and the Dr. SRC Travel Fellow Award from the Banglore Speech and Hearing Trust to speak at the Dr. S. R. Chandrashekhar Institute of Speech and Hearing College, Banglore, India.

 

 

 

 

References

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Pillion, J. P., Rawool, V. W., & Naidu, S. (2000).  Auditory brainstem responses in Rett syndrome: effects of hyperventilation, seizures, and tympanometric variables. Audiology, 39(2), 80-87. http://search.proquest.com/openview/8a4b6496dafee6a95f9eb3973de0c5bb/1?pq-origsite=gscholar

Portas, C. M., Krakow, K., Allen, P., Josephs, O., Armony, J. L., & Frith, C. D. (2000). Auditory processing across the sleep-wake cycle: simultaneous EEG and fMRI monitoring in humans. Neuron, 28(3), 991-999. Auditory processing across the sleep± wake cycle: simultaneous EEG and fMRI monitoring in humans. Neuron 2000; 28:991±999. http://www.sciencedirect.com/science/article/pii/S0896627300001690

Rawool, V. W. (2010a). Invisible hearing loss among multiple disabilities, Part 1: Ensuring auditory care. Hearing Review 17(1), P. 18, 19-21, 50. http://www.hearingreview.com/2010/01/invisible-hearing-loss-among-obvious-multiple-disabilities-part-1-ensuring-auditory-care/

Rawool, V. W. (2010b). Invisible hearing loss among multiple disabilities, Part 2: The case of the missing hearing aids. Hearing Review 17(2), P. 32, 33-37. http://www.hearingreview.com/2010/02/invisible-hearing-loss-among-obvious-multiple-disabilities-part-2-the-case-of-the-missing-hearing-aids/

Rawool, V. W. (2014, Nov 5). Comparison of Staggered Spondaic Words and Competing Words Test results in ADHD: A case study.  Hearing Health Matters.  Retrieved from http://hearinghealthmatters.org/pathways/2014/comparison-staggered-spondaic-words-competing-words-test-results-adhd-case-study/

Rawool, V. W. (2015, July/August). Future Trends in Objective Evaluation of Auditory Processing of Speech Stimuli. Audiology Today, 27(4), 22-29. http://online.qmags.com/AT0715?pg=1&mode=2#pg25&mode2

Rawool, V. W. (2016a). Introduction. In Rawool (ed.) Auditory Processing Deficits: Assessment and Intervention (pp. 1-24). New York: Thieme. http://www.thieme.com/books-main/audiology/product/1949-auditory-processing-deficits

Rawool, V. W. (2016b). Emerging technologies with potential for objectively evaluating speech recognition skills. International journal of audiology,55(sup1), S41-S50. http://www.tandfonline.com/doi/abs/10.3109/14992027.2015.1128570?journalCode=iija20

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Schochat, E., Musiek, F. E., Alonso, R., & Ogata, J. (2010). Effect of auditory training on the middle latency response in children with (central) auditory processing disorder. Brazilian Journal of Medical and Biological Research, 43(8), 777-785. http://www.scielo.br/scielo.php?pid=S0100-879X2010000800011&script=sci_arttext&tlng=pt

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