Chris Niemczak , AuD, Ph.D.
Scientist at Dartmouth-Hitchcock Medical Center, Department of Medicine
Assistant Professor of Medicine at Geisel School of Medicine at Dartmouth
Accurate timing perception of auditory information, known as temporal processing, is essential for human communication and environmental awareness. It’s necessary for auditory psychoacoustic abilities, such as frequency discrimination, modulation detection, and perceiving speech in noise (Shetty 2016; Soli et al. 2008). Accurate assessment of temporal processing is fundamental to effective clinical care. This article will cover what gap detection is, how it is tested, and why it is so important.
The ability to order two auditory stimuli or separate them in time as distinct auditory events depends on auditory temporal processing (Fitzgibbons et al. 1987; Fitzgibbons et al. 1982; Moore et al. 1989). Detecting silent gaps in sound requires precise neural encoding between and within several levels of the auditory pathway. For example, distinguishing between the two phonemes /ba/ and /ga/ is largely based on voice onset time (VOT), or the length of the silent interval between the plosive burst (i.e. the /b/ or /g/) and the following vocalization of the vowel. At more peripheral levels of the auditory pathway, representation of VOT has been identified in the firing rate of auditory nerve fibers (Sinex et al. 1988) and cells in the inferior colliculus tuned to the dominant frequency in the vowel (Eggermont 2000b). Properties of these neurons within the auditory pathway include differential sensitivity to stimulus level, different width of the frequency-tuning curve, different first-spike latency, and different percentages of monotonic or nonmonotonic input-output functions (Schreiner 1995). This means that the entire auditory pathway is well tuned for detection of silent gaps in sounds, but degradations in the neural activity could lead to deficits in detecting those gaps.
Before discussing deficits in auditory neural pathway related to disordered temporal processing, behavioral gap detection requires a brief review of differential sensitivity. Differential sensitivity is the smallest perceptible difference between two sounds measured using a difference limen (DL) (Gelfand 2010). For example, the smallest intensity difference that can be distinguished between two sounds is the DL for intensity. This may be as small as 1 dB and is often called delta (Δ) intensity (I) or ΔI. With temporal discrimination we can replace ΔI with signal duration or the timing of the signal. Traditional gap detection paradigms consist of placing a silent gap in between two auditory stimuli and presenting these gaps (G) at progressively shorter durations. The DL for duration of the gap (ΔG) becomes smaller (shorter) as the overall duration of the gap (G) decreases until the subject can no longer hear the gap. The shortest detectable gap, or gap threshold, is then obtained. Here is where we could discuss how this violates Weber’s Law, but I will spare you the psychoacoustics review.
The stimulus used for gap detection testing is usually a pair of noises that are presented in rapid succession with a period of silence in the middle. In most gap detection paradigms, the gap is surrounded by spectrally identical noises (i.e. same frequency information on both sides of the gap). This requires a relative timing operation to be performed on activity between similar perceptual channels or frequency regions (Phillips et al. 1997). However, in the case of discriminating VOT as described above in the /ba/ and /ga/, the task is also to judge the relative timing of the high frequency plosive burst of the /ba/ compared to the predominantly low frequency /ga/. It has been shown that the mechanisms that mediate the perceptual responses of gap detection between spectrally similar and dissimilar noises are likely different (Phillips et al. 1997), but for the purposes of this discussion, let’s simply focus on length of the gap threshold.
A typical gap threshold is approximately 3-5 milliseconds (ms) in young normal hearing individuals completing the gap task for the first time (untrained). You may think that is incredibly quick, but considering we speak at 4-5 syllables per second (Miller et al. 1976), we need to be this fast to perceive sound accurately.
To measure a gap threshold precisely, several approaches exist. In the Random Gap Detection Test (RGDT; Keith 2000), the listener is presented with a series of noise bursts (or tone bursts) containing various gap durations and must indicate whether the gap was heard in each case. In contrast, the Adaptive Test of Temporal Resolution (ATTR; Lister et al. 2006) presents the listener with a choice of two noise bursts, and they must indicate which of them contains the gap. The test is adaptive because the duration of the silent gap is increased and decreased until the gap detection threshold had been found. In the Gaps-in-Noise (GIN) test (Musiek, Shinn, et al. 2005), listeners are presented with six-second blocks of broadband noise which may contain anywhere between zero and three gaps. Gap durations vary between 2 and 20 ms, and listeners are asked to press a button immediately following detection of a gap. The left and right ears are typically tested independently as previous work indicates that thresholds may vary between the ears, possibly due to the presence of damage in different neural locations (Efron et al. 1985). The GIN was specifically developed to serve as a rapid clinical measure of auditory temporal resolution (Musiek, Shinn, et al. 2005) and is typically used in various Central Auditory Processing batteries (Filippini et al. 2020).
Both animal and human studies have shown gap detection to be both sensitive and specific to peripheral and central auditory system damage, as well as central nervous system deficits (i.e. requiring longer silent gaps than controls for accurate perception) (Bamiou et al. 2006). Auditory gap detection is essentially functional timing of a discontinuity in the neural activity pattern along its path from cochlea to cortex. This short discontinuity detection has been demonstrated in the activity of auditory nerve fibers (Zhang et al. 1990), in single cells of the inferior colliculus (Walton et al. 1997), and in cells in three divisions of auditory cortex (Bertoli et al. 2002; Eggermont 2000a, 2000b; Rupp et al. 2002). That is, while peripheral mechanisms in the cochlea encode temporal aspects of sound, the central auditory pathway including the auditory cortex also contributes to a temporal processing. Therefore, damage to either the peripheral or central auditory system could lead to problems with gap detection. The integration and diverse nature of temporal processing in the central auditory pathway is also the rationale for why gap detection is sensitive to central nervous system dysfunction.
Previous reports on gap detection tests have shown them to have considerable diagnostic consistency in populations with confirmed central auditory system lesions, insular strokes, and multiple sclerosis (Bamiou et al. 2006; Filippini et al. 2020; Musiek, Shinn, et al. 2005). The GIN specifically has proven highly sensitive to the presence of a wide range of brain pathologies in various clinical populations (Chowsilpa et al. 2021), including individuals blast-exposure and mTBI (Gallun et al. 2012; Saunders et al. 2015), adults with mild cognitive impairment (Iliadou et al. 2017), those who stutter (Prestes et al. 2017), and even in Parkinson’s disease (Guehl et al. 2008). Our work has shown people living with HIV experience hearing difficulties originating primarily in the central nervous system evidenced by temporal processing deficits (Buckey et al. 2019; Maro et al. 2014; Niemczak et al. 2021; Zhan et al. 2018).
As stated above, the range of pathologies associated with poor gap detection performance likely reflects the diverse auditory processing and brain networks required to perform this task. So, why isn’t this test included in a standard audiometric test battery? The reason is understandably complicated by clinical scheduling and reimbursement. But while gap detection performance clearly relies upon intact and high functioning temporal resolution within the auditory pathway, performance is also dependent on the listeners’ ability to attend to the auditory stimulus, their speed of information processing, and speed of motor response. The recruitment of non-auditory networks during auditory perceptual tasks is certainly not specific to the gap detection tasks. Indeed, all other perceptual and behavioral processes such as speech understanding in noise and dichotic listening similarly depend upon a range of sensory and cognitive functions, thus highlighting the non-modular nature of auditory processing in the brain (Musiek, Bellis, et al. 2005).
In part two, I will make the case that gap detection can not only provide an accurate measure of auditory temporal processing, but also a window in brain function utilizing metrics that are already accumulated while taking the test. I will also further highlight the sensitivity of gap detection measures in pathologic populations.
Accurate auditory temporal processing is essential for speech identification and recognition, highlighting the importance of this auditory perceptive ability in everyday conversations. Gap detection is by no means the only kind of time-released discrimination in hearing but provides an opportunity to better understand auditory temporal processing and potentially brain function. Poor gap detection (i.e. longer thresholds) has been identified in various clinical populations with central nervous system deficits highlighting the sensitivity of gap detection paradigms to provide a window into overall brain function.
Bamiou, D. E., Musiek, F. E., Stow, I., et al. (2006). Auditory temporal processing deficits in patients with insular stroke. Neurology, 67, 614-619.
Bertoli, S., Smurzynski, J., Probst, R. (2002). Temporal resolution in young and elderly subjects as measured by mismatch negativity and a psychoacoustic gap detection task. Clin Neurophysiol, 113, 396-406.
Buckey, J. C., Fellows, A. M., Magohe, A., et al. (2019). Hearing complaints in HIV infection originate in the brain not the ear. AIDS, 33, 1449-1454.
Chowsilpa, S., Bamiou, D. E., Koohi, N. (2021). Effectiveness of the Auditory Temporal Ordering and Resolution Tests to Detect Central Auditory Processing Disorder in Adults With Evidence of Brain Pathology: A Systematic Review and Meta-Analysis. Front Neurol, 12, 656117.
Efron, R., Yund, E. W., Nichols, D., et al. (1985). An ear asymmetry for gap detection following anterior temporal lobectomy. Neuropsychologia, 23, 43-50.
Eggermont, J. J. (2000a). Neural responses in primary auditory cortex mimic psychophysical, across-frequency-channel, gap-detection thresholds. J Neurophysiol, 84, 1453-1463.
Eggermont, J. J. (2000b). Sound-induced synchronization of neural activity between and within three auditory cortical areas. J Neurophysiol, 83, 2708-2722.
Filippini, R., Wong, B., Schochat, E., et al. (2020). GIN Test: A Meta-Analysis on Its Neurodiagnostic Value. J Am Acad Audiol, 31, 147-157.
Fitzgibbons, P. J., Gordon-Salant, S. (1987). Minimum stimulus levels for temporal gap resolution in listeners with sensorineural hearing loss. J Acoust Soc Am, 81, 1542-1545.
Fitzgibbons, P. J., Wightman, F. L. (1982). Gap detection in normal and hearing-impaired listeners. J Acoust Soc Am, 72, 761-765.
Gallun, F. J., Diedesch, A. C., Kubli, L. R., et al. (2012). Performance on tests of central auditory processing by individuals exposed to high-intensity blasts. J Rehabil Res Dev, 49, 1005-1025.
Gelfand, S. (2010). Essentials of Audiology. In.
Guehl, D., Burbaud, P., Lorenzi, C., et al. (2008). Auditory temporal processing in Parkinson’s disease. Neuropsychologia, 46, 2326-2335.
Iliadou, V. V., Bamiou, D. E., Sidiras, C., et al. (2017). The Use of the Gaps-In-Noise Test as an Index of the Enhanced Left Temporal Cortical Thinning Associated with the Transition between Mild Cognitive Impairment and Alzheimer’s Disease. J Am Acad Audiol, 28, 463-471.
Keith, R. W. (2000). Random gap detection test. St. Louis, MO: Auditec, 13.
Lister, J. J., Roberts, R. A., Shackelford, J., et al. (2006). An adaptive clinical test of temporal resolution. Am J Audiol, 15, 133-140.
Maro, II, Moshi, N., Clavier, O. H., et al. (2014). Auditory impairments in HIV-infected individuals in Tanzania. Ear Hear, 35, 306-317.
Miller, N., Maruyama, G., Beaber, R. J., et al. (1976). Speed of Speech and Persuasion. Journal of Personality and Social Psychology, 34, 615-624.
Moore, B. C., Glasberg, B. R., Donaldson, E., et al. (1989). Detection of temporal gaps in sinusoids by normally hearing and hearing-impaired subjects. J Acoust Soc Am, 85, 1266-1275.
Musiek, F. E., Bellis, T. J., Chermak, G. D. (2005). Nonmodularity of the central auditory nervous system: implications for (central) auditory processing disorder. Am J Audiol, 14, 128-138; discussion 143-150.
Musiek, F. E., Shinn, J. B., Jirsa, R., et al. (2005). GIN (Gaps-In-Noise) test performance in subjects with confirmed central auditory nervous system involvement. Ear Hear, 26, 608-618.
Niemczak, C. E., Lichtenstein, J. D., Magohe, A., et al. (2021). The Relationship Between Central Auditory Tests and Neurocognitive Domains in Adults Living With HIV. Front Neurosci, 15, 696513.
Phillips, D. P., Taylor, T. L., Hall, S. E., et al. (1997). Detection of silent intervals between noises activating different perceptual channels: some properties of “central” auditory gap detection. J Acoust Soc Am, 101, 3694-3705.
Prestes, R., de Andrade, A. N., Santos, R. B., et al. (2017). Temporal processing and long-latency auditory evoked potential in stutterers. Braz J Otorhinolaryngol, 83, 142-146.
Rupp, A., Gutschalk, A., Hack, S., et al. (2002). Temporal resolution of the human primary auditory cortex in gap detection. Neuroreport, 13, 2203-2207.
Saunders, G. H., Frederick, M. T., Arnold, M., et al. (2015). Auditory difficulties in blast-exposed Veterans with clinically normal hearing. J Rehabil Res Dev, 52, 343-360.
Schreiner, C. E. (1995). Order and disorder in auditory cortical maps. Curr Opin Neurobiol, 5, 489-496.
Shetty, H. N. (2016). Temporal cues and the effect of their enhancement on speech perception in older adults – A scoping review. J Otol, 11, 95-101.
Sinex, D. G., McDonald, L. P. (1988). Average discharge rate representation of voice onset time in the chinchilla auditory nerve. J Acoust Soc Am, 83, 1817-1827.
Soli, S. D., Wong, L. L. (2008). Assessment of speech intelligibility in noise with the Hearing in Noise Test. Int J Audiol, 47, 356-361.
Walton, J. P., Frisina, R. D., Ison, J. R., et al. (1997). Neural correlates of behavioral gap detection in the inferior colliculus of the young CBA mouse. J Comp Physiol A, 181, 161-176.
Zhan, Y., Fellows, A. M., Qi, T., et al. (2018). Speech in Noise Perception as a Marker of Cognitive Impairment in HIV Infection. Ear Hear, 39, 548-554.
Zhang, W., Salvi, R. J., Saunders, S. S. (1990). Neural correlates of gap detection in auditory nerve fibers of the chinchilla. Hear Res, 46, 181-200.