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Hearing and the Auditory Brain in the Elderly
C H A P T E R
1 Hearing and the Auditory Brain in the Elderly 1.1 INTRODUCTION Age-related hearing impairment (ARHI), an invisible handicap, combines hearing loss (in the ear) and hearing problems, for example, in speech understanding (in the brain). ARHI is a condition with three underlying characteristics: (1) Reduced auditory sensation as a result of hearing loss, resulting in reduced input to the central auditory nervous system. (2) Degradation of auditory perception, resulting from frequency-dependent gain changes in the central auditory system synapses as well as a dysfunction in auditory temporal processing. This manifests itself in decreased speech understanding, especially in background noise. (3) Changes in nonauditory brain structures involved in attention, working memory, and executive functions. These cognitive changes affect auditory perception, especially in more demanding conditions, such as noisy or babble environments. Consequently, “hearing impairment tends to isolate people from friends and family because of a decreased ability to communicate; as such, untreated ARHI may have considerable negative social, psychological, cognitive, and health effects” (Li et al., 2014). We will discuss these three defining characteristics in detail in Chapters 2 4. High-frequency hearing loss is one of the hallmarks of sensory aging. Zwaardemaker (1891), a physiology professor in Utrecht, the Netherlands, was the first to describe and measure this, using Galton whistles tuned to various high frequencies. The Galton whistle, invented by Sir Frances Galton (1822 1911), was one of the earliest devices used in testing hearing. The Galton whistle can be adjusted to produce very high-frequency sounds between 5 and 42 kHz, and was used by its inventor to test the limits of hearing in the dogs he met on his walks in London’s Hyde Park. Later, Zwaardemaker (1897) coined
The Auditory Brain and Age-Related Hearing Impairment DOI: https://doi.org/10.1016/B978-0-12-815304-8.00001-3
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© 2019 Elsevier Inc. All rights reserved.
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1. HEARING AND THE AUDITORY BRAIN IN THE ELDERLY
the term presbycusis. Bunch (1929) was the first to use an audiometer to measure hearing loss associated with aging, thereby replacing the Galton whistle and other instruments such as the often-used monochord, a single-string tunable instrument (Mollison, 1917). One of the earlier studies (Otto and McCandless, 1982) into the potential loci of ARHI used a battery of auditory tests, including impedance measures, speech discrimination tests, synthetic sentence identification, compressed speech, two measures of tone decay, the short increment sensitivity index, a digit span test, and auditory brainstem response (ABR) audiometry (see Appendix). Decrease in synthetic sentence identification was the most consistent aging effect among the outcomes of central auditory function tests. The ABR revealed some prolonged interpeak latencies, potentially suggesting mild brainstem abnormalities. Otto and McCandless (1982) concluded that peripheral as well as central auditory disorders frequently accompany senescence. Using a comparable test battery, Arlinger (1991) also found that, in contrast to young adults with normal hearing and those with cochlear hearing loss, the elderly showed a mixture of characteristics typical of cochlear, retrocochlear, and central lesions. Later we will see that in more recent studies of healthy aging one rarely finds retrocochlear lesions and often only modest cochlear lesions, whereas the central “lesions” are typical of the cognitive variety, which do not show up in the ABR. The ABR is however useful in detecting temporal processing disorders (Chapter 5). In this chapter I will introduce the general effects of auditory aging by describing lifespan changes in hearing loss, changes in the perception of speech, and structural and functional changes in auditory cortex. I then introduce nonclassical auditory-responsive cortical areas, which will be relevant because of their changes in aging, and involvement in cognitive processes. Finally, I will address the diverging paths of hearing loss and tinnitus prevalent across the lifespan.
1.2 TRACKING AGE-RELATED HEARING IMPAIRMENT 1.2.1 Increasing Hearing Loss Let us start with a definition of presbycusis as used in the late 1960s (Spoor, 1967): “Presbycusis is the phenomenon that the threshold of hearing of people with otologically normal ears increases with age. It has to be realized, that this is not a pure physiological phenomenon, but that this is influenced to a certain degree by the [noisy] nature of Western civilization.” To quantify this progression of hearing loss across the lifespan, my colleague Spoor (1967) compiled information from
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1.2 TRACKING AGE-RELATED HEARING IMPAIRMENT
TABLE 1.1
Information Related to Fig. 1.1 Number
Author
Men
Women
Population Type
Value
Hinchcliffe (1959)
326
319
Rural
Median
Corso (1963)
493
754
Median
Jatho and Heck (1959)
399
361
Mean
Johansen (1943)
155
155
Mean
Beasly (1938)
2002
2660
Random
Mean
ASA Report (1954)
Mean
Glorig (1957)
2518
Glorig and Nixon (1962)
1724
Hearing level
25
35
1741
45
55
65
Professional
Median
Industrial
Median
75
85 year
dB 10 20 30 40 50 60 70
F = 4000 Hz Hinchcliffe Corso Jatho & Heck Johnsen Beasley ASA Gloring (1962) Gloring (WSF)
FIGURE 1.1 Data points (median values) derived from eight large studies showing hearing level in dB at 4000 Hz as a function of age with respect to the hearing level in the 20 25 year-old age group in the same investigations. For the characteristics of the populations used and indicated by name, see Table 1.1. Source: From Spoor, A., 1967. Presbycusis values in relation to noise induced hearing loss. Audiology 6, 48 57, reprinted by permission of the publisher (Taylor & Francis Ltd, http://www.tandfonline.com).
eight large published studies. Epidemiological information on these studies is presented in Table 1.1. In Fig. 1.1 the relative changes for 4 kHz with age are shown for males with reference to their hearing at age 20 25 years.
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Interestingly, the data indicated by the 3 3 symbols in Fig. 1.1 represent median values for men from a large industrial noise-exposed group (Glorig and Nixon, 1962), whereas the 1 1 data symbols represent median values from a large group of, likely less-exposed, professionals attending the 1954 Wisconsin State Fair (Glorig, 1957). These two particular studies illustrate an overall effect of occupational noise, on the amount of hearing loss, but they also showed the absence of an effect on the rate of hearing loss change with age. The other studies included in Fig. 1.1 likely are from populations with varying degrees of occupational hearing loss as they fall mostly in between the two extremes just presented. To introduce the differences in age-related hearing loss between males and females, we present data from a recent epidemiological study covering 15,606 participants up to 85 years of age, based on the Korea National Health and Nutrition Examination Survey 2010 12 (Park et al., 2016). Hearing thresholds of 3, 4, and 6 kHz showed a statistically significant difference between both genders for people older than 30 years of age, with the 4 kHz frequency showing the largest difference. The hearing thresholds for all the tested frequencies became worse with increasing age (Fig. 1.2), in close agreement with the Spoor’s (1967) data compilation. The data illustrate the very similar changes in hearing for men and women for the lower frequencies (Fig. 1.2A C), but also the potential effect of more noise exposure in men compared to women for higher frequencies starting at 3 kHz, but especially pronounced at 4 kHz (Fig. 1.2D F). Hoffman et al. (2012) had found that median thresholds for men across all frequencies except at 1 kHz are lower (better) in the 1999 2006 National Health and Nutrition Examination Survey compared with 1959 62. Results for women were similar. The prevalence of hearing impairment in older adults, age 70 years (65 74 years), was lower in 1999 2006 compared with 1959 62, consistent with earlier findings for younger adults. This potentially resulted from increased awareness of the effects of occupational noise with time. The above-cited studies did not cover people older than 85 years of age. What happens with the middle and inner ear beyond that age? Mao et al. (2013) measured middle-ear impedance, pure-tone behavioral thresholds, and distortion-product otoacoustic emissions (DPOAEs) from 74 centenarians living in the city of Shaoxing, China. DPOAEs originate from the active transduction process of cochlear outer hair cells (OHCs; Chapter 2). Their data showed that most .100-year-old participants had a reduced static compliance of the tympanic membrane, suggesting some conductive hearing loss. Pure-tone audiometry showed that more than 90% suffered from moderate to severe (41 80 dB) hearing loss below 2000 Hz, and profound ($81 dB) hearing loss at 4000 and 8000 Hz. This
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Female
30 50 70 Age (years)
90
0 20 40 60
Female
90
40
20
0
30 50 70 Age (years)
3 kHz Male Female
90
0
30 50 70 Age (years)
20
0 20 40 60
Male
10
10
(F)
4 kHz
Hearing threshold at 1 kHz (dB)
90
40
30 50 70 Age (years)
60
Female
60
Male
80
20 40
2 kHz
Hearing threshold at 3 Hz (dB)
10 (D)
Male
80
80
90
80
Hearing threshold at 4 Hz (dB)
30 50 70 Age (years)
0
10
10 (E)
Female
Hearing threshold at 6 Hz (dB)
Male
80
0 60
20 40
500 Hz
60
Hearing threshold at 2 Hz (dB)
(C)
(B)
80
(A)
Hearing threshold at 500 Hz (dB)
1.2 TRACKING AGE-RELATED HEARING IMPAIRMENT
10
6 kHz Male Female
70 30 50 Age (years)
90
FIGURE 1.2 Gender difference of the mean hearing threshold in proportion to age at 0.5 kHz (A), 1 kHz (B), 2 kHz (C), 3 kHz (D), 4 kHz (E), and 6 kHz (F) frequencies (highly screened population, n 5 33,011,778 ears). At 0.5, 1, and 2 kHz, no difference in the mean threshold level was found between males and females. However, at 3, 4, and 6 kHz, the mean threshold levels for males are worse than the levels for females. Among the three frequencies, the most significant difference of the mean threshold level between males and females with the same age occurs at 4 kHz. Source: From Park, Y.H., Shin, S.-H., Byun, S.W., Kim, J.Y., 2016. Age- and gender-related mean hearing threshold in a highly-screened population: The Korean National Health and Nutrition Examination Survey 2010 2012. PLoS ONE 11 (3), e0150783. doi:10.1371/journal.pone.0150783.
indicates a disproportional large threshold increase at frequencies below 2 kHz compared to the values for 85-year-olds in Fig. 1.2. DPOAEs were undetectable in the majority of centenarians, suggesting severe OHC loss. Liu et al. (2015) confirmed these findings in a study of 54 centenarians from North China, and noted that only a few centenarians had normal levels of speech detection scores.
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1.2.2 Decreasing Speech Understanding In the 1960s, it was not well known how background speech disrupted perception of the target speech in people with hearing impairment. Carhart and Tillman (1970) were pioneers in measuring the discrimination for monosyllables in a background of competing sentences in the same ear. There were two groups (n 5 6 each) with normal hearing and conductive hearing loss, respectively, and two groups (n 5 6 each) with similar sensorineural hearing loss but differing in speech discrimination in quiet (89.7% and 66.3%). They found that persons with conductive loss functioned as well as the normal-hearing subjects in the speech test. However, the people with sensorineural loss, regardless of their speech discrimination in quiet, found the competing-speech sentences disturbing. The disruption of their speech understanding was equivalent to having the masking efficiency of the competing sentences enhanced from 12 to 15 dB compared to that in the other two groups. Thus an additional handicap may be imposed by sensorineural pathology. Namely, such a pathology not only changes hearing thresholds and often impairs intelligibility in quiet but can also disturb the ability to overcome masking when in complex environments containing other sounds, particularly speech. This was further analyzed in depth by Plomp (1978) and will be presented in some detail in Chapter 3. Investigating speech discrimination in terms of the 50% discrimination score, also called the speech reception threshold (SRT), Mazelova´ et al. (2003) compared 30 elderly (mean age 5 75.7 years) and 30 young (mean age 5 23.1 years) people. They found that the SRT changed abruptly in the elderly when the pure-tone average (PTA) for 0.5 2 kHz increased above 10 dB and then increased linearly with hearing loss (cf. Fig. 5.3). Although in this study there were only a few young participants with PTA0.5 2 kHz . 10 dB hearing level (HL), the data suggested that hearing loss in the young had less of an effect on the SRT. They also found an average shift in the SRT of 24.6 dB between the young and the elderly that translated to 0.47 dB/year, and was significantly larger than the mean 17 dB drop in PTA (0.32 dB/year). Mazelova´ et al. (2003) suggested that presbycusis represents a combination of deteriorated function in both the auditory periphery and the central auditory system, reflecting closely the suggestions of Carhart and Tillman (1970). Gates et al. (2008) compared the age-dependent rates of change in measures of peripheral and central aspects of the auditory system of 241 participants aged 71 96 years. As a measure of cochlear function they used DPOAEs to assess OHC function, and PTAs both at 1, 2, and 3 kHz. As measures of central function they recorded ABRs, middle latency responses (MLRs), and cortical auditory evoked potentials
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(CAEPs), and a competing-speech test. The Appendix describes details about these electrophysiological responses, and Chapter 9 presents more extensive age-related electrophysiological findings. Gates et al. (2008) found that DPOAE thresholds increased by 0.34 dB/year, whereas the PTAs increased by 0.5 dB/year, which is quite a bit larger than in the Mazelova´ et al. (2003) study. This likely reflects differences in the particular cohorts studied, which is a general confound in crosssectional studies. The latency of the ABR wave V, and the amplitudes of the MLR (the Pa component) and CAEP (P2 component) did not vary with age. The mean synthetic sentence identification test scores with competing speech in the same ear dropped 1.7% per year. After adjustment for the decrease in hearing threshold level with age, the decline in synthetic sentence identification test was still significant. Gates et al. (2008) concluded that changes in central auditory functions are a prominent component of presbycusis. A more recent study parceled out effects of hearing loss from effects of aging on speech discrimination in noise (Billings et al., 2015). The effects of hearing impairment on SNR50 (i.e., the SRT in noise) were estimated to be about 12 dB; that is, the 50% speech understanding point on the psychometric function for the old hearing-impaired group is 12 dB to the right of the 50% point on the old normal-hearing psychometric function (Fig. 1.3). Pure age effects obtained by comparing SNR50 in the old normal-hearing group with the young normal-hearing one were only B2 dB. Note that this “minor” shift of the SRT curve induced by pure aging still represents B15% less speech understanding at this signal-to-noise ratio (SNR) compared to the young normal-hearing controls. Thus, the magnitude of hearing impairment effects at the 50% point of the psychometric functions (older normal hearing vs older hearing impaired) was about five to six times greater than the magnitude of age effects in young vs older normalhearing participants. In addition, the older hearing impaired never reached more than 80% discrimination at favorable SNRs, whereas the older normal hearing performed not significantly less at high SNRs. We are still missing here a comparison between young normal hearing and young people with hearing loss for a pure hearing impairment effect not confounded with aging, as it is likely that these effects do not add linearly. Fast spoken speech, the presence of background noise, and reverberation disrupt speech understanding more for older than younger listeners even when their hearing thresholds are clinically normal. A caution here is that “clinically normal” thresholds typically are defined as # 25 dB HL for frequencies of 125 Hz to 8 kHz. It is known that hearing loss for frequencies above 8 kHz has a well-defined effect on speech understanding, particularly in the presence of background noise (Eggermont, 2017; Chapter 3). We now look at some particular studies that cover this in some detail.
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100
IEEE mean (% correct)
80
60
40
20
OHI ONH YNH
0 –10
–5
0
5
15
25
35
FIGURE 1.3 Sentence-level psychometric functions at an 80 dB signal level. YNH group (solid black) shows the best performance followed by ONH group (dashed red) and then OHI group (blue dotted blue). IEEE, Institute of Electrical and Electronic Engineers; SNR, signal-to-noise ratio. ONH, older normal hearing; OHI, older hearing-impaired; YNH, young normal hearing. Source: From Billings, C.J., Penman, T.M., McMillan, G.P., Ellis, E.M., 2015. Electrophysiology and perception of speech in noise in older listeners: effects of hearing impairment and age. Ear Hear. 36 (6), 710 722. With permission from Wolters Kluwer Health.
Mild sensorineural hearing loss and age both have an effect on speech recognition in a babble background. Dubno et al. (1984) tested four groups of 18 subjects each: (1) normal-hearing listeners , 44 years of age (mean age 5 27.9 years), (2) participants , 44 years old (mean age 5 34.1 years) with mild sensorineural hearing loss and excellent speech recognition in quiet, (3) normal-hearing listeners . 65 years old (mean age 5 70.5 years), and (4) participants . 65 years old (mean age 5 73.4 years) with mild sensorineural hearing loss and excellent speech recognition in quiet. In this study, differences in the SRT in babble as a function of age were observed for both normal-hearing and hearing-impaired listeners despite equivalent performance in quiet. More specifically, overall differences in performance in noise as a function of age were observed at conversational speech levels ranging from 56 to 88 dB SPL. These age effects were independent of hearing loss.
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Age effects were not observed for SRTs measured in quiet, reflecting the selection criteria. Therefore, the decrement in performance in noise for the older subjects relative to the younger listeners likely represents the effects of age. What are the mechanisms that underlie the interaction between the effects of background noise and aging? Are they acting at the perceptual level, that is, temporal processing or at the cognitive level, for example, attention or memory? Pichora-Fuller et al. (1995) explored this in (1) a young normal-hearing group (n 5 8; mean age 5 23.9 years), (2) an elderly group with near-normal hearing (n 5 8; mean age 5 70.4 years), and (3) an elderly hearing-impaired group (n 5 8; mean age 5 75.8 years). The elderly participants recalled fewer of the sentence-final words they had earlier correctly identified when presented in isolation than did the young ones in all speech-in-noise conditions. The number of items recalled by both age groups was reduced in adverse speech-innoise conditions. Pichora-Fuller et al. (1995) attributed this compensation effect in the young to reallocation of central processing resources such as attention that are used to support auditory processing when listening becomes difficult. These resources are typically not sufficient to compensate for age-related degradation of speech in the auditory system. Frisina and Frisina (1997) determined speech recognition performance in noise in 50 young (n 5 10; mean age 5 25.5 years) and elderly listeners, with normal audiometric thresholds (n 5 10; mean age 5 65.5 years) or high-frequency hearing loss (n 5 10; mean age 5 70.1 years). They found that increased hearing loss resulted in elevated SRTs in quiet and reduced speech recognition in noise. Among participants with normal audibility and cognitive functioning, elderly listeners had reduced speech-in-noise understanding, which suggested to them a temporal processing dysfunction. Differences, of the order of 2 dB in SRT (compare Billings et al., 2015), in performance between young and elderly subjects with normal peripheral sensitivity were considered indicative of a central auditory dysfunction. Interrupted noise is typically a less effective masker than continuous noise, because it allows listening in the silent gaps. Stuart and Phillips (1996) examined this effect on the word recognition performance in young normal hearing (n 5 12; mean 5 24.9 years), older normal hearing (n 5 12; mean 5 61.0 years), and older hearing-impaired (n 5 12; mean 5 62.8 years) listeners. The young normal-hearing group performed best, followed by the older normal-hearing, and older hearingimpaired groups, respectively. Word recognition scores were higher in the interrupted broadband noise than in the continuous broadband noise, reflecting the release from masking in the former noise condition for all listeners. Further, within each noise condition, the older normalhearing recognition performance was better than that of the older
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hearing-impaired group in both noise conditions, despite that the PTA0.5 2 kHz (i.e., in the speech frequency range) of the older hearingimpaired group were ,25 dB HL. This again suggests a central processing deficit. These studies all strongly suggest that the reduced speech perception in background noise in the elderly with near-normal-hearing points to central auditory dysfunctions. We will now introduce some of the salient findings of changes in the brain with age—and hearing loss— that could underlie these deficits.
1.3 AUDITORY EVOKED POTENTIALS ACROSS THE LIFESPAN An extensive review on the effects of aging on auditory evoked potentials and magnetic fields is presented in Chapter 9. Here we introduce the topic with some general findings. Skoe et al. (2015) recorded ABRs to a click stimulus and a speech syllable /da/ in 586 normalhearing healthy individuals, aged 0.25 72.4 years. The ABR wave V latency showed a minimum around 5 8 years and then increased with age. The amplitude, both of the waveform and the frequency spectrum, of the envelope following response part of the response to the /da/ syllable was largest in the 5 8 year age group and then continued to decrease with age. Typically, peak latency is inversely related to peak amplitude in the ABR. At the other latency extreme, van Dinteren et al. (2014) assessed the development of the auditory P3 (latency B300 ms; see Appendix), often used as a marker of cognitive patency, across the lifespan. They conducted a systematic review and meta-analysis on the P3 in 75 studies (n 5 2811). These findings were validated in an independent, existing cross-sectional dataset including 1572 participants from ages 6 to 87 years. Curve-fitting procedures were applied to obtain a model of P3 development across the lifespan. The P3 amplitude followed a maturational path from childhood to adolescence, resulting in a period that marks a maximum at age 20 30 years, after which degenerative effects begin. Typically, the P3 latency showed a minimum in that age group (Fig. 1.4). Brickman et al. (2012) had found that white matter (WM) fiber tracts continued their development, as reflected in the fractional anisotropy (FA) a measure of nerve fiber myelination, until they reach a brief plateau, at about age 25, after which degeneration started (Fig. 1.4). The “inverted” resemblance of these FA data, which reflect myelination, with the P3 latency data of van Dinteren et al. (2014) suggests that myelination and P3 latency are closely related.
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FIGURE 1.4 P3 latency (Δ) trajectory across the lifespan as obtained from the metaanalysis. Trajectory of FA (K, FA 3 100) across the lifespan. FA, Fractional anisotropy. Source: Based on data from Brickman et al. (2012) and van Dinteren et al. (2014).
The role of attention on stimulus-evoked brain activity across the lifespan was investigated by Aerts et al. (2013) by comparing attended and unattended auditory phoneme processing in 71 healthy subjects (aged 21 83 years) as reflected in the P3 and mismatch negativity (MMN) event-related potentials (ERPs, see Appendix). For phoneme processing the effect of aging was reflected in increased latencies and decreased amplitudes. However, there was a discrepancy between attended (P3) and unattended (MMN) processing, as well as between phonemic contrasts. During word recognition, aging only had an impact on ERPs elicited by real words, indicating that mainly semantic processes were altered, leaving lexical processes unaffected. Early sensory-perceptual processes, reflected by N1 and P1 (Appendix), did not show effects of aging.
1.4 AUDITORY BRAIN CHANGES WITH AGE 1.4.1 Cortical Atrophy One of the characteristics of nonuse of sensory cortical areas is that they either show atrophy or are co-opted for other sensory functions. Guo et al. (2008) examined potential brain atrophy in 111 70-year-old nondemented women. Their pure-tone thresholds were poorer in the
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left ear than in the right ear at frequencies 6 and 8 kHz with a significant difference of 2.2 2.7 dB, respectively. Among these women, 72 had cortical atrophy (34 in one lobe, 17 in two lobes, 13 in three lobes, and 8 in four lobes). Women with cortical atrophy at any lobe had poorer hearing in the left ear at the frequencies 6 kHz (mean value: 42.3 vs 50.1 dB HL) and 8 kHz (mean value: 49.0 vs 60.2 dB HL) than women without cortical atrophy. Women with atrophy of three or four lobes had poorer hearing of the left ear than those with atrophy of one or two lobes, and women without atrophy at frequencies 2, 4, 6, and 8 kHz. The findings for the right ear were not significant. Women with isolated temporal lobe atrophy (n 5 17) had similar hearing capacity as women with isolated atrophy of the other three lobes (n 5 17). Guo et al. (2008) concluded that there was “a relationship between general cortical atrophy and poorer hearing in the high-frequency range of the left ear in this population-based sample of 70-year-old women. The relation between pure-tone thresholds and brain atrophy was correlated to the extension of cortical atrophy, but not to specific location (temporal lobe).” Peelle et al. (2011) reported that in a group of elderly people (n 5 16; mean age 5 64.9 years) even a moderate decline (#25 dB HL) in peripheral auditory sensitivity (defined as PTA1,2,4 kHz), leads to a loss of gray matter volume in primary auditory cortex as measured by magnetic resonance imaging (MRI; Fig. 1.5). PTA1 4 kHzs in participants’ better ears ranged from 10 to 33.3 dB HL (mean 5 18.4 dB). One has to realize that these participants could have had extended hearing loss in the frequency range of 8 kHz and higher, as further exemplified below. In motor areas of the brain no signs of atrophy were found, suggesting the absence of a general age effect. In this study, it was found that gray matter density in primary auditory areas was predicted by hearing ability, and that this suggested a link between sensory stimulation and auditory cortical volume. Is it just hearing losses that cause auditory brain atrophy or does aging contribute as well? Eckert et al. (2012) showed that a decrease in gray matter was associated dominantly with high-frequency hearing loss (Fig. 1.6) but not with increasing age. These effects occurred most robustly in a primary auditory cortex region (Te1.0; see legend to Fig. 1.6) where there was also elevated cerebrospinal fluid volume in case of high-frequency hearing loss, suggesting that the dominant cause of auditory cortex atrophy is high-frequency hearing loss. The border between high- and low-frequency hearing loss according to their principal component analysis was B2 kHz. Note, however, that there is also a low-frequency effect on area Te1.2 (still primary auditory cortex). According to Eckert et al. (2012), “an intriguing explanation for the unique low- and high-frequency hearing effects observed in this study
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Right auditory
Gray matter volume
Left auditory r2 = 0.09, p = 0.088
r2 = 0.23, p = 0.012
0.4
0.35
0.3
0.25 10 20 30 40 Hearing acuity (dB HL)
20 30 40 10 Hearing acuity (dB HL) Left motor
Right motor
r2 = 0.01, p = 0.32
0.3
r2 = 0.02, p = 0.28
0.3
0.2
0.2 10
20
30
40
10
20
30
40
Hearing acuity (dB HL)
FIGURE 1.5 Relationship between regional gray matter volume and hearing ability. Average gray matter values were obtained from 25 participants for four cortical regions. Poorer hearing (PTA for 1, 2, and 4 kHz) was associated with reduced gray matter volume in right auditory cortex (red), and showed a similar nonsignificant trend in left auditory cortex (pink); neither of the changes in the motor cortex control regions (light and dark blue) approached significance. Larger markers in the scatterplots represent two participants with overlapping scores. Source: From Peelle, J.E., Troiani, V., Grossman, M., Wingfield, A., 2011. Hearing loss in older adults affects neural systems supporting speech comprehension. J. Neurosci. 31 (35), 12638 12643. Reproduced with permission of Society for Neuroscience.
is that they stem from different subtypes of presbycusis.” There are several causes for presbycusis, which have unique patterns of associated hearing loss, including metabolic and sensory presbycusis (Ohlemiller, 2004). Sensory presbycusis involves the loss of OHCs (Schuknecht, 1974) and spiral ganglion cells that are particularly affected in the basal turn of the cochlea (Makary et al., 2011; cf. Fig. 6.3) and is associated with relatively better low-frequency hearing and more steeply sloping high-frequency loss than metabolic presbycusis (Dubno et al., 2013). Metabolic presbycusis likely causes less or no auditory nerve fiber loss and thus preserves input to the central auditory system (Chapter 2). Melcher et al. (2013) reported that in patients with tinnitus (n 5 24; aged 33 62 years) mild hearing loss at 8 kHz (#30 dB HL) was also strongly correlated with changes in ventral posterior cingulate cortex, dorsomedial prefrontal cortex, and a subcallosal region that included ventromedial prefrontal cortex as well, likely resulting from spreading effects of the atrophy in auditory cortex for this high frequency.
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Left PAC Te1.2 Left PAC Te1.0 Left PAC Te1.1
16
3 2 1 0 –1 –2 –3 3 2 1 0 –1 –2 –3 3 2 1 0 –1 –2 –3
Male Female
r = –0.30, p < 0.05
r = –0.46, p < 0.001
r = –0.39, p < 0.01 0.5 1.5 2.5 –2.5 –1.5 –0.5 High-frequency hearing component
3 2 1 0 –1 –2 –3 3 2 1 0 –1 –2 –3 3 2 1 0 –1 –2 –3
r = –0.02, ns
r = –0.06, ns
r = –0.29, p < 0.05 –2.5 –1.5 –0.5 0.5 1.5 2.5 Low-frequency hearing component
FIGURE 1.6 Three areas, Te1.1, Te1.0, and Te1.2, with a well-developed layer IV, which represent the primary auditory cortex (Brodmann area 41), can be identified along the mediolateral axis of the Heschl gyrus. The cell density was significantly higher in Te1.1 compared to Te1.2 in the left but not in the right hemisphere. The cytoarchitectonically defined areal borders of the primary auditory cortex do not consistently match macroanatomic landmarks like gyral and sulcal borders (Morosan et al., 2001). Variation in auditory cortex gray matter (Te1.0 unsmoothed gray matter volume average, relative to total gray matter volume) was associated with the high-frequency hearing threshold component (left), but not the low-frequency hearing threshold component (right). The components were derived from factor analysis of the pure-tone threshold data from both ears for all 49 participants with the same variables for 852 older adults (mean age 5 69.9 years). While men (filled red circles) had more high-frequency hearing loss than women (open blue circles), an association between auditory cortex gray matter and high-frequency hearing threshold was present across the sample. Increasing age, represented by symbol size, did not substantially impact the left Te1.0 findings. Presented with each plot is an image of the associated PAC cytoarchitectonic mask (50% probability). PAC, Primary auditory cortex. Source: From Eckert, M.A., Cute, S.L., Vaden, K.I. Jr., Kuchinsky, S.E., Dubno, J.R., 2012. Auditory cortex signs of age-related hearing loss. J. Assoc. Res. Otolaryngol. 13 (5), 703 713. With permission from Springer Nature.
The question now arises whether hearing impairment interacts with aging to produce this effect. Lin et al. (2014), in a longitudinal study, analyzed brain volume measurements from MRI brain scans of individuals with clinically normal hearing and those with hearing impairment (speech-frequencies PTA # 25 and .25 dB HL, respectively, but not exceeding 45 dB HL) followed in the neuroimaging substudy of the Baltimore Longitudinal Study of Aging for on average 6.4 years after the baseline scan (n 5 126, age 56 86 years). They found that individuals with hearing impairment (n 5 51) compared to those with clinically normal hearing (n 5 75) had significantly accelerated volume decrease in the whole brain (as previously found by Guo et al., 2008)
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and regional volumes in the right temporal lobe (superior, middle, and inferior temporal gyri, parahippocampus). Lin et al. (2014) concluded, “These findings demonstrate that peripheral hearing impairment is independently associated with accelerated brain atrophy in whole brain and regional volumes concentrated in the right temporal lobe.” This corresponds with the asymmetry in atrophy reported by Peelle et al. (2011) for auditory cortex and shown in Fig. 1.5. Also, not specifically focusing on the auditory cortex, Rigters et al. (2017) studied the relation between nonconductive hearing loss and brain volume in a large elderly cohort of 2908 participants (mean age 65 years, 56% female). The group average low-frequency (PTA0.25 1 kHz) hearing loss was 14.1 dB, and the high-frequency (PTA2 8 kHz) loss was 32.4 dB. They quantified global and regional brain tissue volumes using MRI (total brain volume, gray matter volume, WM volume, and lobe-specific volumes). Higher puretone thresholds were significantly associated with a smaller total brain volume, and specifically smaller WM volume. Total brain volume and WM volume were more strongly associated with hearing loss in the lower frequencies. From a review of the literature, Cardin (2016) concluded that the occurrence of atrophy of auditory cortex depends both on hearing loss and older age and is likely underlying compromised auditory processing in these conditions. When there is a hearing loss, the sound quality will be degraded and therefore requires more cognitive efforts to achieve perception. Cardin (2016) argued, “this constant effortful listening and reduced cognitive spare capacity could be what accelerates cognitive decline in older adults with hearing loss.” I have the feeling that it is also the reduced social engagement that may result from degraded speech understanding that contributes to cognitive decline; Chapter 4 will present the available evidence.
1.4.2 Nonclassical Sound-Responsive Cortical Areas The putative effects of hearing loss on attention, memory, and other cognitive functions, are typically attributed to changes in prefrontal cortex. These changes may not be independent of changes in auditory cortex, especially when one realizes that many neurons in these brain areas also respond to sound. In a functional MRI (fMRI) study Langers and Melcher (2011) were the first to show multiple networks of acoustically responsive brain centers. One network comprised classical auditory centers, but four others included classically “nonauditory” areas, namely cingulo-insular cortex, mediotemporal limbic lobe, basal ganglia, and posterior orbitofrontal cortex. Functional connectivity analyses demonstrated coordinated activity between the involved brain structures.
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Resting-state fMRI (Chapter 8) revealed largely similar networks. Subsequently, Michalka et al. (2015) used fMRI to show that two distinct auditory-biased attention regions, transverse gyrus intersecting precentral sulcus (tgPCS) and caudal inferior frontal sulcus (cIFS), were interleaved with visual-biased attention regions in lateral frontal cortex (Fig. 1.7; Tobyne et al., 2017).
1.4.3 Changed Cortical Responsiveness in Aging Does brain responsiveness correlate with speech discrimination? Wong et al. (2009) tested younger and older participants with clinically normal hearing up to 4 kHz (no data for higher frequencies) with fMRI when they identified single words in quiet and in two multitalkerbabble noise conditions (SNR 5 20 and 25 dB). Older and younger subjects did not show significant differences in discrimination in quiet and SNR 5 20 dB, but older adults performed less accurately in the more challenging SNR 5 25 dB condition. The between-group differences in fMRI results showed more increased activation in the auditory cortex in the young (cyan in Fig. 1.8) and more increased activity in working memory and attention-related cortical areas (prefrontal and precuneus regions, yellow in Fig. 1.8) in older participants, especially in the SNR 5 20 dB condition. Increased cortical activity in these cognitive regions in individuals was positively correlated with behavioral performance in older listeners, suggesting a compensatory strategy for the reduced activity in auditory cortex. However, for the challenging SNR 5 25 dB task the compensatory activity appears much reduced in the older population compared to the young, which correlates with the poorer performance. The decrease of activity difference in these cognitive areas for the SNR 5 25 dB in the older group may also be caused by the increased recruitment of these areas by the younger group. Peelle et al. (2011) had also monitored brain activity reflected in the fMRI of older adults (n 5 25; mean age 5 66.3 years) with age-normal hearing who listened to sentences that varied in their linguistic demands. There were several auditory regions, in which participants with poorer hearing showed reduced linguistic activation. They were largely bilateral and included superior temporal gyri, thalamus, and brainstem. There were no regions in which listeners with worse hearing showed increased activity related to linguistic complexity. Peelle et al. (2011) found that individual differences in hearing ability predicted the degree of language-driven neural activity during auditory sentence comprehension in primary auditory cortex, as well as in the auditory thalamus and brainstem. Thus, neural activity underlying perceptual cognitive interactions in speech processing provides a potential
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FIGURE 1.7 Visual- vs auditory-biased attention networks. (A) Task-based fMRI contrast of visual- vs. auditory-spatial attention from a representative individual (Michalka et al., 2015). Bilaterally, two visual-biased attention regions, sPCS and iPCS, were observed to be interleaved with two auditory-biased attention regions, tgPCS and cIFS. In posterior cortex, visual attention recruited IPS/TOS, while auditory attention recruited STG/S. (B) Summary of resting-state functional connectivity results from Michalka et al. (2015). sPCS, iPCS, and IPS/TOS selectively form a visual-biased network (blue), while tgPCS, cIFS, and STG/S selectively form an auditory-biased network (orange). sPCS, Superior precentral sulcus; iPCS, inferior precentral sulcus; tgPCS, transverse gyrus intersecting the precentral sulcus; cIFS, caudal inferior frontal sulcus; IPS/TOS, intraparietal sulcus/transverse occipital gyrus; STG/S, superior temporal gyrus/sulcus. Source: From Tobyne, S.M., Osher, D.E., Michalka, S.W., Somers, D.C., 2017. Sensory-biased attention networks in human lateral frontal cortex revealed by intrinsic functional connectivity. NeuroImage 162, 362 372. With permission from Elsevier.
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FIGURE 1.8 Between-group differences in quiet (left), SNR 20 (middle), and SNR 25 (right) conditions based on independent-sample t-tests (P , .05 corrected). A sagittal view is shown x 5 41 (right hemisphere). The spatial extent could include postcentral gyrus; and STR (medial to lateral, could include the insular cortex). Blue and red indicate stronger activation in younger and older groups, respectively. PP, Posterior parietal region including precuneus; PFC, prefrontal cortex; STR, superior temporal region. Source: From Wong, P.C., Jin, J.X., Gunasekera, G.M., Abel, R., Lee, E.R., Dhar, S., 2009. Aging and cortical mechanisms of speech perception in noise. Neuropsychologia 47 (3), 693 703. With permission from Elsevier.
explanation for age-related changes in spoken language comprehension. Also, in an fMRI study, stimulating with pink noise centered around 350, 700 Hz, 1.5, 3, or 8 kHz, Profant et al. (2015) demonstrated larger activation of the auditory cortex overall in both elderly groups, that is, with mild (n 5 15; mean age 5 67.9 years) and more advanced (n 5 15; mean age 5 70.7 years) presbycusis, in comparison with young normal-hearing controls (n 5 18; mean age 5 23.75 years). The active role of the participants in the Wong et al. (2009) and Peelle et al. (2011) studies showing decreased activity in auditory cortex in the elderly, contrasts with the finding of increased activity in the study by Profant et al. (2015), where the subjects were passive, and likely underlies the different results. Thus, as already foreseen a decade earlier (Reuter-Lorenz and Lustig, 2005): these “new discoveries challenge the long-held view that aging is characterized by progressive loss and decline. Evidence for functional reorganization, compensation and effective interventions holds promise for a more optimistic view of neurocognitive status in later life. Complexities associated with assigning function to age-specific activation patterns must be considered relative to performance and in light of pathological aging.”
1.5 PREVALENCE AND INCIDENCE OF TINNITUS ACROSS THE LIFESPAN Tinnitus often results from noise-induced hearing loss and has its highest prevalence in the elderly. Fosbroke (1831) perceptively stated (italics in
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25 22.5 (A) 20 17.5 15 12.5 10 7.5 5 2.5 0 20 30
UK (NHS) Sweden UK (NHIS) Norway Shargorodsky
40 50 60 70 Age (±5 years)
80
90
Incidence rate of significant tinnitus per 10,000 person-years 0 3 6 9 12 15
Prevalence (%)
the original), “Deafness varies from a diminution of hearing, to an almost extinction of the sense, A noise in the ears, resembling either the roar of the sea, the ebullition of boiling water, or the rustling of the wind among trees, accompanied sometimes with noise in the head, exists in almost every case of deafness, to whatever cause the deafness may be owing.” Tinnitus is considered the result of maladaptive brain plasticity induced by hearing loss. I previously extracted tinnitus prevalence in the general population from three reviews and the original publications contributing to those overviews and from more recent papers not included in those three reviews (Eggermont, 2012). Among the reviews that were covered, Hoffman and Reed (2004) provided an in-depth reanalysis of a few large epidemiology studies, Davis and El-Rafaie (2000) also covered some older epidemiology where different criteria for inclusion of tinnitus were used, and Sanchez (2004) presented a more general (but without a prevalence by age group) overview of a larger number of epidemiology studies. All in all they covered 14 studies that illustrate an upward trend of tinnitus prevalence with age that plateaux around age 70 and that is generally the same for all studies but where the absolute levels depend on the questions asked and the type of tinnitus included. The prevalence of significant tinnitus (lasting .5 minutes, excluding the transient form following noise exposure) by age group of some representative individual studies is shown in Fig. 1.9A (Eggermont, 2014). The overall prevalence of tinnitus in the sample groups was: United Kingdom 10.1%, Sweden 14.2%, United States 8.4%,
<10
(B)
10–19 20–29 30–39 40–49 50–59 60–69 70–79 80–84 Age (years) Male
Female
FIGURE 1.9 (A) Mean prevalence of significant tinnitus for adults. The UK (NHS) data are from Davis and El-Rafaie (2000), the US (NHIS) data are from Nondahl et al. (2002) and Shargorodsky et al. (2010), the Swedish data are from Axelsson and Ringdahl (1989), and the Norwegian study was by Tambs et al. (2003). (B) Gender- and age-specific incidence rates of clinically significant tinnitus. Source: (A) From Eggermont, 2014. Noise and the Brain. Experience Dependent Developmental and Adult Plasticity. Academic Press, London, UK. With permission from Elsevier. (B) From Martinez, C., Wallenhorst, C., McFerran, D., Hall, D.A., 2015. Incidence rates of clinically significant tinnitus: 10-year trend from a cohort study in England. Ear Hear. 36, e69 e75. With permission from Wolters Kluwer Health.
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70
Prevalence (%)
60
Mean tinnitus HL > 25 dB HL
50 40 30 20 10 0 20
30
40
50
60
70
80
Age (±5 years)
FIGURE 1.10 Prevalence of significant tinnitus (average of several studies, details in Eggermont, J.J., 2012. The Neuroscience of Tinnitus. Oxford University Press, Oxford) and of hearing loss .25 dB HL (data from Davis, A.C., 1989. The prevalence of hearing impairment and reported hearing disability among adults in Great Britain. Int. J. Epidemiol. 18, 911 917). Source: From Eggermont, J.J., 2014. Noise and the Brain. Experience Dependent Developmental and Adult Plasticity. Academic Press, London, UK. With permission from Elsevier.
and Norway 15.1%. The three studies with the lower prevalence used a more stringent criterion: the tinnitus should be bothersome. In a more recent large UK study, Dawes et al. (2014) found that the prevalence of tinnitus was 16.9% (95% CI 5 16.6% 17.1%). This was considerably higher than the earlier UK (NHS) study of Davis and El-Rafaie (2000), which averaged at about 12.5% for the age group from 45 to 75 years of age. Underlying the plateaux, Martinez et al. (2015) found that the incidence of tinnitus decreases sharply above 70 years of age (Fig. 1.9B). Note that prevalence is the proportion of a population that has a condition at a specific time. Incidence reflects the rate at which new cases of disease are being added to the population and become prevalent cases. Averaging the data from two Scandinavian countries, two US studies, and the United Kingdom gives the general trend as shown in Fig. 1.10. There is a tendency for the prevalence of tinnitus to level off in the seventh decade of life. In contrast, the prevalence for significant hearing loss (.25 dB HL, from 0.5 to 4 kHz) continues to increase (Davis, 1989).
1.6 SUMMARY The ARHI-associated changes occur in at least three levels, including the peripheral auditory system, central auditory system, and cognitive
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functions. In hearing-impaired elderly patients, the age-related declines of peripheral and central auditory processing interact with the diminished cognitive functions and support, leading to reduced auditory perception of speech (Li-Korotsky, 2012). An important aspect is that auditory stimuli, especially to voice, activate neurons in the prefrontal and other nonauditory areas. In studies of the connectome in aging (Chapter 8), these areas are often implicated as covariants with declining speech discrimination. It is thus clear that the auditory brain extends well beyond the classical auditory areas in the temporal lobe.
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Melcher, J.R., Knudson, I.M., Levine, R.A., 2013. Subcallosal brain structure: correlation with hearing threshold at supra-clinical frequencies ( . 8 kHz), but not with tinnitus. Hear. Res. 295, 79 86. Michalka, S.W., Kong, L., Rosen, M.L., Shinn-Cunningham, B.G., Somers, D.C., 2015. Short-term memory for space and time flexibly recruit complementary sensory-biased frontal lobe attention networks. Neuron 87, 882 892. Mollison, W.M., 1917. A note on the monochord, with some Illustrative figures. Proc. R. Soc. Med. 10 (Otol Sect), 39 40. Morosan, P., Rademacher, J., Schleicher, A., Schormann, T., Zilles, K., 2001. Human primary auditory cortex: cytoarchitectonic subdivisions and mapping into a spatial reference system. NeuroImage 13, 684 701. Nondahl, D.M., Cruickshanks, K.J., Wiley, T.L., Klein, R., Klein, B.E., Tweed, T.S., 2002. Prevalence and 5-year incidence of tinnitus among older adults: the epidemiology of hearing loss study. J. Am. Acad. Audiol. 13 (6), 323 331. Ohlemiller, K.K., 2004. Age-related hearing loss: the status of Schuknecht’s typology. Curr. Opin. Otolaryngol. Head Neck Surg. 12, 439 443. Otto, W.C., McCandless, G.A., 1982. Aging and auditory site of lesion. Ear Hear. 3 (3), 110 117. Park, Y.H., Shin, S.-H., Byun, S.W., Kim, J.Y., 2016. Age- and gender-related mean hearing threshold in a highly-screened population: The Korean National Health and Nutrition Examination Survey 2010 2012. PLoS One 11 (3), e0150783. Available from: https:// doi.org/10.1371/journal.pone.0150783. Peelle, J.E., Troiani, V., Grossman, M., Wingfield, A., 2011. Hearing loss in older adults affects neural systems supporting speech comprehension. J. Neurosci. 31 (35), 12638 12643. Pichora-Fuller, M.K., Schneider, B.A., Daneman, M., 1995. How young and old adults listen to and remember speech in noise. J. Acoust. Soc. Am. 97 (1), 593 608. Plomp, R., 1978. Auditory handicap of hearing impairment and the limited benefit of hearing aids. J. Acoust. Soc. Am. 63, 533 549. Profant, O., Tintra, J., Balogova´, Z., Ibrahim, I., Jilek, M., Syka, J., 2015. Functional changes in the human auditory cortex in ageing. PLoS One 10 (3), e0116692. Available from: https://doi.org/10.1371/journal.pone.0116692. Reuter-Lorenz, P.A., Lustig, C., 2005. Brain aging: reorganizing discoveries about the aging mind. Curr. Opin. Neurobiol. 15, 245 251. Rigters, S.C., Bos, D., Metselaar, M., Roshchupkin, G.V., Baatenburg de Jong, R.J., Ikram, M.A., et al., 2017. Hearing impairment is associated with smaller brain volume in aging. Front. Aging Neurosci. 9, 2. Available from: https://doi.org/10.3389/ fnagi.2017.00002. Sanchez, L., 2004. The epidemiology of tinnitus. Audiol. Med. 2, 8 17. Schuknecht, H.F., 1974. Presbycusis. Harvard University Press, Cambridge, MA. Shargorodsky, J., Curhan, G.C., Wildon, R., Farwell, W.R., 2010. Prevalence and characteristics of tinnitus among US adults. Am. J. Med. 123, 711 718. Skoe, E., Krizman, J., Anderson, S., Kraus, N., 2015. Stability and plasticity of auditory brainstem function across the lifespan. Cereb. Cortex 25 (6), 1415 1426. Spoor, A., 1967. Presbycusis values in relation to noise induced hearing loss. Audiology 6, 48 57. Stuart, A., Phillips, D.P., 1996. Word recognition in continuous and interrupted broadband noise by young normal-hearing, older normal-hearing, and presbycusic listeners. Ear Hear. 17 (6), 478 489. Tambs, K., Hoffman, H.J., Borchgrevink, H.M., Holmen, J., Samuelsen, S.O., 2003. Hearing loss induced by noise, ear infections, and head injuries: results from the NordTrøndelag Hearing Loss Study. Int. J. Audiol. 42 (2), 89 105.
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Tobyne, S.M., Osher, D.E., Michalka, S.W., Somers, D.C., 2017. Sensory-biased attention networks in human lateral frontal cortex revealed by intrinsic functional connectivity. NeuroImage 162, 362 372. van Dinteren, R., Arns, M., Jongsma, M.L.A., Kessels, R.P.C., 2014. P300 development across the lifespan: a systematic review and meta-analysis. PLoS One 9 (2), e87347. Available from: https://doi.org/10.1371/journal.pone.0087347. Wong, P.C., Jin, J.X., Gunasekera, G.M., Abel, R., Lee, E.R., Dhar, S., 2009. Aging and cortical mechanisms of speech perception in noise. Neuropsychologia 47 (3), 693 703. Zwaardemaker, H., 1891. Der Verlust an hohen To¨nen mit zunehmendum Alter: Ein neues Gesetz. Arch. Ohr. Nas.-Kehlk.-Heilk. 32, 53 56. Zwaardemaker, H., 1897. The range of hearing: various stages. Z. Psychol. 7, 10 28.
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1 Hearing and the Auditory Brain in the Elderly 1.1 INTRODUCTION Age-related hearing impairment (ARHI), an invisible handicap, combines hearing loss (in the ear) and hearing problems, for example, in speech understanding (in the brain). ARHI is a condition with three underlying characteristics: (1) Reduced auditory sensation as a result of hearing loss, resulting in reduced input to the central auditory nervous system. (2) Degradation of auditory perception, resulting from frequency-dependent gain changes in the central auditory system synapses as well as a dysfunction in auditory temporal processing. This manifests itself in decreased speech understanding, especially in background noise. (3) Changes in nonauditory brain structures involved in attention, working memory, and executive functions. These cognitive changes affect auditory perception, especially in more demanding conditions, such as noisy or babble environments. Consequently, “hearing impairment tends to isolate people from friends and family because of a decreased ability to communicate; as such, untreated ARHI may have considerable negative social, psychological, cognitive, and health effects” (Li et al., 2014). We will discuss these three defining characteristics in detail in Chapters 2 4. High-frequency hearing loss is one of the hallmarks of sensory aging. Zwaardemaker (1891), a physiology professor in Utrecht, the Netherlands, was the first to describe and measure this, using Galton whistles tuned to various high frequencies. The Galton whistle, invented by Sir Frances Galton (1822 1911), was one of the earliest devices used in testing hearing. The Galton whistle can be adjusted to produce very high-frequency sounds between 5 and 42 kHz, and was used by its inventor to test the limits of hearing in the dogs he met on his walks in London’s Hyde Park. Later, Zwaardemaker (1897) coined
The Auditory Brain and Age-Related Hearing Impairment DOI: https://doi.org/10.1016/B978-0-12-815304-8.00001-3
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the term presbycusis. Bunch (1929) was the first to use an audiometer to measure hearing loss associated with aging, thereby replacing the Galton whistle and other instruments such as the often-used monochord, a single-string tunable instrument (Mollison, 1917). One of the earlier studies (Otto and McCandless, 1982) into the potential loci of ARHI used a battery of auditory tests, including impedance measures, speech discrimination tests, synthetic sentence identification, compressed speech, two measures of tone decay, the short increment sensitivity index, a digit span test, and auditory brainstem response (ABR) audiometry (see Appendix). Decrease in synthetic sentence identification was the most consistent aging effect among the outcomes of central auditory function tests. The ABR revealed some prolonged interpeak latencies, potentially suggesting mild brainstem abnormalities. Otto and McCandless (1982) concluded that peripheral as well as central auditory disorders frequently accompany senescence. Using a comparable test battery, Arlinger (1991) also found that, in contrast to young adults with normal hearing and those with cochlear hearing loss, the elderly showed a mixture of characteristics typical of cochlear, retrocochlear, and central lesions. Later we will see that in more recent studies of healthy aging one rarely finds retrocochlear lesions and often only modest cochlear lesions, whereas the central “lesions” are typical of the cognitive variety, which do not show up in the ABR. The ABR is however useful in detecting temporal processing disorders (Chapter 5). In this chapter I will introduce the general effects of auditory aging by describing lifespan changes in hearing loss, changes in the perception of speech, and structural and functional changes in auditory cortex. I then introduce nonclassical auditory-responsive cortical areas, which will be relevant because of their changes in aging, and involvement in cognitive processes. Finally, I will address the diverging paths of hearing loss and tinnitus prevalent across the lifespan.
1.2 TRACKING AGE-RELATED HEARING IMPAIRMENT 1.2.1 Increasing Hearing Loss Let us start with a definition of presbycusis as used in the late 1960s (Spoor, 1967): “Presbycusis is the phenomenon that the threshold of hearing of people with otologically normal ears increases with age. It has to be realized, that this is not a pure physiological phenomenon, but that this is influenced to a certain degree by the [noisy] nature of Western civilization.” To quantify this progression of hearing loss across the lifespan, my colleague Spoor (1967) compiled information from
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1.2 TRACKING AGE-RELATED HEARING IMPAIRMENT
TABLE 1.1
Information Related to Fig. 1.1 Number
Author
Men
Women
Population Type
Value
Hinchcliffe (1959)
326
319
Rural
Median
Corso (1963)
493
754
Median
Jatho and Heck (1959)
399
361
Mean
Johansen (1943)
155
155
Mean
Beasly (1938)
2002
2660
Random
Mean
ASA Report (1954)
Mean
Glorig (1957)
2518
Glorig and Nixon (1962)
1724
Hearing level
25
35
1741
45
55
65
Professional
Median
Industrial
Median
75
85 year
dB 10 20 30 40 50 60 70
F = 4000 Hz Hinchcliffe Corso Jatho & Heck Johnsen Beasley ASA Gloring (1962) Gloring (WSF)
FIGURE 1.1 Data points (median values) derived from eight large studies showing hearing level in dB at 4000 Hz as a function of age with respect to the hearing level in the 20 25 year-old age group in the same investigations. For the characteristics of the populations used and indicated by name, see Table 1.1. Source: From Spoor, A., 1967. Presbycusis values in relation to noise induced hearing loss. Audiology 6, 48 57, reprinted by permission of the publisher (Taylor & Francis Ltd, http://www.tandfonline.com).
eight large published studies. Epidemiological information on these studies is presented in Table 1.1. In Fig. 1.1 the relative changes for 4 kHz with age are shown for males with reference to their hearing at age 20 25 years.
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Interestingly, the data indicated by the 3 3 symbols in Fig. 1.1 represent median values for men from a large industrial noise-exposed group (Glorig and Nixon, 1962), whereas the 1 1 data symbols represent median values from a large group of, likely less-exposed, professionals attending the 1954 Wisconsin State Fair (Glorig, 1957). These two particular studies illustrate an overall effect of occupational noise, on the amount of hearing loss, but they also showed the absence of an effect on the rate of hearing loss change with age. The other studies included in Fig. 1.1 likely are from populations with varying degrees of occupational hearing loss as they fall mostly in between the two extremes just presented. To introduce the differences in age-related hearing loss between males and females, we present data from a recent epidemiological study covering 15,606 participants up to 85 years of age, based on the Korea National Health and Nutrition Examination Survey 2010 12 (Park et al., 2016). Hearing thresholds of 3, 4, and 6 kHz showed a statistically significant difference between both genders for people older than 30 years of age, with the 4 kHz frequency showing the largest difference. The hearing thresholds for all the tested frequencies became worse with increasing age (Fig. 1.2), in close agreement with the Spoor’s (1967) data compilation. The data illustrate the very similar changes in hearing for men and women for the lower frequencies (Fig. 1.2A C), but also the potential effect of more noise exposure in men compared to women for higher frequencies starting at 3 kHz, but especially pronounced at 4 kHz (Fig. 1.2D F). Hoffman et al. (2012) had found that median thresholds for men across all frequencies except at 1 kHz are lower (better) in the 1999 2006 National Health and Nutrition Examination Survey compared with 1959 62. Results for women were similar. The prevalence of hearing impairment in older adults, age 70 years (65 74 years), was lower in 1999 2006 compared with 1959 62, consistent with earlier findings for younger adults. This potentially resulted from increased awareness of the effects of occupational noise with time. The above-cited studies did not cover people older than 85 years of age. What happens with the middle and inner ear beyond that age? Mao et al. (2013) measured middle-ear impedance, pure-tone behavioral thresholds, and distortion-product otoacoustic emissions (DPOAEs) from 74 centenarians living in the city of Shaoxing, China. DPOAEs originate from the active transduction process of cochlear outer hair cells (OHCs; Chapter 2). Their data showed that most .100-year-old participants had a reduced static compliance of the tympanic membrane, suggesting some conductive hearing loss. Pure-tone audiometry showed that more than 90% suffered from moderate to severe (41 80 dB) hearing loss below 2000 Hz, and profound ($81 dB) hearing loss at 4000 and 8000 Hz. This
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Female
30 50 70 Age (years)
90
0 20 40 60
Female
90
40
20
0
30 50 70 Age (years)
3 kHz Male Female
90
0
30 50 70 Age (years)
20
0 20 40 60
Male
10
10
(F)
4 kHz
Hearing threshold at 1 kHz (dB)
90
40
30 50 70 Age (years)
60
Female
60
Male
80
20 40
2 kHz
Hearing threshold at 3 Hz (dB)
10 (D)
Male
80
80
90
80
Hearing threshold at 4 Hz (dB)
30 50 70 Age (years)
0
10
10 (E)
Female
Hearing threshold at 6 Hz (dB)
Male
80
0 60
20 40
500 Hz
60
Hearing threshold at 2 Hz (dB)
(C)
(B)
80
(A)
Hearing threshold at 500 Hz (dB)
1.2 TRACKING AGE-RELATED HEARING IMPAIRMENT
10
6 kHz Male Female
70 30 50 Age (years)
90
FIGURE 1.2 Gender difference of the mean hearing threshold in proportion to age at 0.5 kHz (A), 1 kHz (B), 2 kHz (C), 3 kHz (D), 4 kHz (E), and 6 kHz (F) frequencies (highly screened population, n 5 33,011,778 ears). At 0.5, 1, and 2 kHz, no difference in the mean threshold level was found between males and females. However, at 3, 4, and 6 kHz, the mean threshold levels for males are worse than the levels for females. Among the three frequencies, the most significant difference of the mean threshold level between males and females with the same age occurs at 4 kHz. Source: From Park, Y.H., Shin, S.-H., Byun, S.W., Kim, J.Y., 2016. Age- and gender-related mean hearing threshold in a highly-screened population: The Korean National Health and Nutrition Examination Survey 2010 2012. PLoS ONE 11 (3), e0150783. doi:10.1371/journal.pone.0150783.
indicates a disproportional large threshold increase at frequencies below 2 kHz compared to the values for 85-year-olds in Fig. 1.2. DPOAEs were undetectable in the majority of centenarians, suggesting severe OHC loss. Liu et al. (2015) confirmed these findings in a study of 54 centenarians from North China, and noted that only a few centenarians had normal levels of speech detection scores.
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1.2.2 Decreasing Speech Understanding In the 1960s, it was not well known how background speech disrupted perception of the target speech in people with hearing impairment. Carhart and Tillman (1970) were pioneers in measuring the discrimination for monosyllables in a background of competing sentences in the same ear. There were two groups (n 5 6 each) with normal hearing and conductive hearing loss, respectively, and two groups (n 5 6 each) with similar sensorineural hearing loss but differing in speech discrimination in quiet (89.7% and 66.3%). They found that persons with conductive loss functioned as well as the normal-hearing subjects in the speech test. However, the people with sensorineural loss, regardless of their speech discrimination in quiet, found the competing-speech sentences disturbing. The disruption of their speech understanding was equivalent to having the masking efficiency of the competing sentences enhanced from 12 to 15 dB compared to that in the other two groups. Thus an additional handicap may be imposed by sensorineural pathology. Namely, such a pathology not only changes hearing thresholds and often impairs intelligibility in quiet but can also disturb the ability to overcome masking when in complex environments containing other sounds, particularly speech. This was further analyzed in depth by Plomp (1978) and will be presented in some detail in Chapter 3. Investigating speech discrimination in terms of the 50% discrimination score, also called the speech reception threshold (SRT), Mazelova´ et al. (2003) compared 30 elderly (mean age 5 75.7 years) and 30 young (mean age 5 23.1 years) people. They found that the SRT changed abruptly in the elderly when the pure-tone average (PTA) for 0.5 2 kHz increased above 10 dB and then increased linearly with hearing loss (cf. Fig. 5.3). Although in this study there were only a few young participants with PTA0.5 2 kHz . 10 dB hearing level (HL), the data suggested that hearing loss in the young had less of an effect on the SRT. They also found an average shift in the SRT of 24.6 dB between the young and the elderly that translated to 0.47 dB/year, and was significantly larger than the mean 17 dB drop in PTA (0.32 dB/year). Mazelova´ et al. (2003) suggested that presbycusis represents a combination of deteriorated function in both the auditory periphery and the central auditory system, reflecting closely the suggestions of Carhart and Tillman (1970). Gates et al. (2008) compared the age-dependent rates of change in measures of peripheral and central aspects of the auditory system of 241 participants aged 71 96 years. As a measure of cochlear function they used DPOAEs to assess OHC function, and PTAs both at 1, 2, and 3 kHz. As measures of central function they recorded ABRs, middle latency responses (MLRs), and cortical auditory evoked potentials
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9
(CAEPs), and a competing-speech test. The Appendix describes details about these electrophysiological responses, and Chapter 9 presents more extensive age-related electrophysiological findings. Gates et al. (2008) found that DPOAE thresholds increased by 0.34 dB/year, whereas the PTAs increased by 0.5 dB/year, which is quite a bit larger than in the Mazelova´ et al. (2003) study. This likely reflects differences in the particular cohorts studied, which is a general confound in crosssectional studies. The latency of the ABR wave V, and the amplitudes of the MLR (the Pa component) and CAEP (P2 component) did not vary with age. The mean synthetic sentence identification test scores with competing speech in the same ear dropped 1.7% per year. After adjustment for the decrease in hearing threshold level with age, the decline in synthetic sentence identification test was still significant. Gates et al. (2008) concluded that changes in central auditory functions are a prominent component of presbycusis. A more recent study parceled out effects of hearing loss from effects of aging on speech discrimination in noise (Billings et al., 2015). The effects of hearing impairment on SNR50 (i.e., the SRT in noise) were estimated to be about 12 dB; that is, the 50% speech understanding point on the psychometric function for the old hearing-impaired group is 12 dB to the right of the 50% point on the old normal-hearing psychometric function (Fig. 1.3). Pure age effects obtained by comparing SNR50 in the old normal-hearing group with the young normal-hearing one were only B2 dB. Note that this “minor” shift of the SRT curve induced by pure aging still represents B15% less speech understanding at this signal-to-noise ratio (SNR) compared to the young normal-hearing controls. Thus, the magnitude of hearing impairment effects at the 50% point of the psychometric functions (older normal hearing vs older hearing impaired) was about five to six times greater than the magnitude of age effects in young vs older normalhearing participants. In addition, the older hearing impaired never reached more than 80% discrimination at favorable SNRs, whereas the older normal hearing performed not significantly less at high SNRs. We are still missing here a comparison between young normal hearing and young people with hearing loss for a pure hearing impairment effect not confounded with aging, as it is likely that these effects do not add linearly. Fast spoken speech, the presence of background noise, and reverberation disrupt speech understanding more for older than younger listeners even when their hearing thresholds are clinically normal. A caution here is that “clinically normal” thresholds typically are defined as # 25 dB HL for frequencies of 125 Hz to 8 kHz. It is known that hearing loss for frequencies above 8 kHz has a well-defined effect on speech understanding, particularly in the presence of background noise (Eggermont, 2017; Chapter 3). We now look at some particular studies that cover this in some detail.
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100
IEEE mean (% correct)
80
60
40
20
OHI ONH YNH
0 –10
–5
0
5
15
25
35
FIGURE 1.3 Sentence-level psychometric functions at an 80 dB signal level. YNH group (solid black) shows the best performance followed by ONH group (dashed red) and then OHI group (blue dotted blue). IEEE, Institute of Electrical and Electronic Engineers; SNR, signal-to-noise ratio. ONH, older normal hearing; OHI, older hearing-impaired; YNH, young normal hearing. Source: From Billings, C.J., Penman, T.M., McMillan, G.P., Ellis, E.M., 2015. Electrophysiology and perception of speech in noise in older listeners: effects of hearing impairment and age. Ear Hear. 36 (6), 710 722. With permission from Wolters Kluwer Health.
Mild sensorineural hearing loss and age both have an effect on speech recognition in a babble background. Dubno et al. (1984) tested four groups of 18 subjects each: (1) normal-hearing listeners , 44 years of age (mean age 5 27.9 years), (2) participants , 44 years old (mean age 5 34.1 years) with mild sensorineural hearing loss and excellent speech recognition in quiet, (3) normal-hearing listeners . 65 years old (mean age 5 70.5 years), and (4) participants . 65 years old (mean age 5 73.4 years) with mild sensorineural hearing loss and excellent speech recognition in quiet. In this study, differences in the SRT in babble as a function of age were observed for both normal-hearing and hearing-impaired listeners despite equivalent performance in quiet. More specifically, overall differences in performance in noise as a function of age were observed at conversational speech levels ranging from 56 to 88 dB SPL. These age effects were independent of hearing loss.
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Age effects were not observed for SRTs measured in quiet, reflecting the selection criteria. Therefore, the decrement in performance in noise for the older subjects relative to the younger listeners likely represents the effects of age. What are the mechanisms that underlie the interaction between the effects of background noise and aging? Are they acting at the perceptual level, that is, temporal processing or at the cognitive level, for example, attention or memory? Pichora-Fuller et al. (1995) explored this in (1) a young normal-hearing group (n 5 8; mean age 5 23.9 years), (2) an elderly group with near-normal hearing (n 5 8; mean age 5 70.4 years), and (3) an elderly hearing-impaired group (n 5 8; mean age 5 75.8 years). The elderly participants recalled fewer of the sentence-final words they had earlier correctly identified when presented in isolation than did the young ones in all speech-in-noise conditions. The number of items recalled by both age groups was reduced in adverse speech-innoise conditions. Pichora-Fuller et al. (1995) attributed this compensation effect in the young to reallocation of central processing resources such as attention that are used to support auditory processing when listening becomes difficult. These resources are typically not sufficient to compensate for age-related degradation of speech in the auditory system. Frisina and Frisina (1997) determined speech recognition performance in noise in 50 young (n 5 10; mean age 5 25.5 years) and elderly listeners, with normal audiometric thresholds (n 5 10; mean age 5 65.5 years) or high-frequency hearing loss (n 5 10; mean age 5 70.1 years). They found that increased hearing loss resulted in elevated SRTs in quiet and reduced speech recognition in noise. Among participants with normal audibility and cognitive functioning, elderly listeners had reduced speech-in-noise understanding, which suggested to them a temporal processing dysfunction. Differences, of the order of 2 dB in SRT (compare Billings et al., 2015), in performance between young and elderly subjects with normal peripheral sensitivity were considered indicative of a central auditory dysfunction. Interrupted noise is typically a less effective masker than continuous noise, because it allows listening in the silent gaps. Stuart and Phillips (1996) examined this effect on the word recognition performance in young normal hearing (n 5 12; mean 5 24.9 years), older normal hearing (n 5 12; mean 5 61.0 years), and older hearing-impaired (n 5 12; mean 5 62.8 years) listeners. The young normal-hearing group performed best, followed by the older normal-hearing, and older hearingimpaired groups, respectively. Word recognition scores were higher in the interrupted broadband noise than in the continuous broadband noise, reflecting the release from masking in the former noise condition for all listeners. Further, within each noise condition, the older normalhearing recognition performance was better than that of the older
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hearing-impaired group in both noise conditions, despite that the PTA0.5 2 kHz (i.e., in the speech frequency range) of the older hearingimpaired group were ,25 dB HL. This again suggests a central processing deficit. These studies all strongly suggest that the reduced speech perception in background noise in the elderly with near-normal-hearing points to central auditory dysfunctions. We will now introduce some of the salient findings of changes in the brain with age—and hearing loss— that could underlie these deficits.
1.3 AUDITORY EVOKED POTENTIALS ACROSS THE LIFESPAN An extensive review on the effects of aging on auditory evoked potentials and magnetic fields is presented in Chapter 9. Here we introduce the topic with some general findings. Skoe et al. (2015) recorded ABRs to a click stimulus and a speech syllable /da/ in 586 normalhearing healthy individuals, aged 0.25 72.4 years. The ABR wave V latency showed a minimum around 5 8 years and then increased with age. The amplitude, both of the waveform and the frequency spectrum, of the envelope following response part of the response to the /da/ syllable was largest in the 5 8 year age group and then continued to decrease with age. Typically, peak latency is inversely related to peak amplitude in the ABR. At the other latency extreme, van Dinteren et al. (2014) assessed the development of the auditory P3 (latency B300 ms; see Appendix), often used as a marker of cognitive patency, across the lifespan. They conducted a systematic review and meta-analysis on the P3 in 75 studies (n 5 2811). These findings were validated in an independent, existing cross-sectional dataset including 1572 participants from ages 6 to 87 years. Curve-fitting procedures were applied to obtain a model of P3 development across the lifespan. The P3 amplitude followed a maturational path from childhood to adolescence, resulting in a period that marks a maximum at age 20 30 years, after which degenerative effects begin. Typically, the P3 latency showed a minimum in that age group (Fig. 1.4). Brickman et al. (2012) had found that white matter (WM) fiber tracts continued their development, as reflected in the fractional anisotropy (FA) a measure of nerve fiber myelination, until they reach a brief plateau, at about age 25, after which degeneration started (Fig. 1.4). The “inverted” resemblance of these FA data, which reflect myelination, with the P3 latency data of van Dinteren et al. (2014) suggests that myelination and P3 latency are closely related.
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FIGURE 1.4 P3 latency (Δ) trajectory across the lifespan as obtained from the metaanalysis. Trajectory of FA (K, FA 3 100) across the lifespan. FA, Fractional anisotropy. Source: Based on data from Brickman et al. (2012) and van Dinteren et al. (2014).
The role of attention on stimulus-evoked brain activity across the lifespan was investigated by Aerts et al. (2013) by comparing attended and unattended auditory phoneme processing in 71 healthy subjects (aged 21 83 years) as reflected in the P3 and mismatch negativity (MMN) event-related potentials (ERPs, see Appendix). For phoneme processing the effect of aging was reflected in increased latencies and decreased amplitudes. However, there was a discrepancy between attended (P3) and unattended (MMN) processing, as well as between phonemic contrasts. During word recognition, aging only had an impact on ERPs elicited by real words, indicating that mainly semantic processes were altered, leaving lexical processes unaffected. Early sensory-perceptual processes, reflected by N1 and P1 (Appendix), did not show effects of aging.
1.4 AUDITORY BRAIN CHANGES WITH AGE 1.4.1 Cortical Atrophy One of the characteristics of nonuse of sensory cortical areas is that they either show atrophy or are co-opted for other sensory functions. Guo et al. (2008) examined potential brain atrophy in 111 70-year-old nondemented women. Their pure-tone thresholds were poorer in the
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left ear than in the right ear at frequencies 6 and 8 kHz with a significant difference of 2.2 2.7 dB, respectively. Among these women, 72 had cortical atrophy (34 in one lobe, 17 in two lobes, 13 in three lobes, and 8 in four lobes). Women with cortical atrophy at any lobe had poorer hearing in the left ear at the frequencies 6 kHz (mean value: 42.3 vs 50.1 dB HL) and 8 kHz (mean value: 49.0 vs 60.2 dB HL) than women without cortical atrophy. Women with atrophy of three or four lobes had poorer hearing of the left ear than those with atrophy of one or two lobes, and women without atrophy at frequencies 2, 4, 6, and 8 kHz. The findings for the right ear were not significant. Women with isolated temporal lobe atrophy (n 5 17) had similar hearing capacity as women with isolated atrophy of the other three lobes (n 5 17). Guo et al. (2008) concluded that there was “a relationship between general cortical atrophy and poorer hearing in the high-frequency range of the left ear in this population-based sample of 70-year-old women. The relation between pure-tone thresholds and brain atrophy was correlated to the extension of cortical atrophy, but not to specific location (temporal lobe).” Peelle et al. (2011) reported that in a group of elderly people (n 5 16; mean age 5 64.9 years) even a moderate decline (#25 dB HL) in peripheral auditory sensitivity (defined as PTA1,2,4 kHz), leads to a loss of gray matter volume in primary auditory cortex as measured by magnetic resonance imaging (MRI; Fig. 1.5). PTA1 4 kHzs in participants’ better ears ranged from 10 to 33.3 dB HL (mean 5 18.4 dB). One has to realize that these participants could have had extended hearing loss in the frequency range of 8 kHz and higher, as further exemplified below. In motor areas of the brain no signs of atrophy were found, suggesting the absence of a general age effect. In this study, it was found that gray matter density in primary auditory areas was predicted by hearing ability, and that this suggested a link between sensory stimulation and auditory cortical volume. Is it just hearing losses that cause auditory brain atrophy or does aging contribute as well? Eckert et al. (2012) showed that a decrease in gray matter was associated dominantly with high-frequency hearing loss (Fig. 1.6) but not with increasing age. These effects occurred most robustly in a primary auditory cortex region (Te1.0; see legend to Fig. 1.6) where there was also elevated cerebrospinal fluid volume in case of high-frequency hearing loss, suggesting that the dominant cause of auditory cortex atrophy is high-frequency hearing loss. The border between high- and low-frequency hearing loss according to their principal component analysis was B2 kHz. Note, however, that there is also a low-frequency effect on area Te1.2 (still primary auditory cortex). According to Eckert et al. (2012), “an intriguing explanation for the unique low- and high-frequency hearing effects observed in this study
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1.4 AUDITORY BRAIN CHANGES WITH AGE
Right auditory
Gray matter volume
Left auditory r2 = 0.09, p = 0.088
r2 = 0.23, p = 0.012
0.4
0.35
0.3
0.25 10 20 30 40 Hearing acuity (dB HL)
20 30 40 10 Hearing acuity (dB HL) Left motor
Right motor
r2 = 0.01, p = 0.32
0.3
r2 = 0.02, p = 0.28
0.3
0.2
0.2 10
20
30
40
10
20
30
40
Hearing acuity (dB HL)
FIGURE 1.5 Relationship between regional gray matter volume and hearing ability. Average gray matter values were obtained from 25 participants for four cortical regions. Poorer hearing (PTA for 1, 2, and 4 kHz) was associated with reduced gray matter volume in right auditory cortex (red), and showed a similar nonsignificant trend in left auditory cortex (pink); neither of the changes in the motor cortex control regions (light and dark blue) approached significance. Larger markers in the scatterplots represent two participants with overlapping scores. Source: From Peelle, J.E., Troiani, V., Grossman, M., Wingfield, A., 2011. Hearing loss in older adults affects neural systems supporting speech comprehension. J. Neurosci. 31 (35), 12638 12643. Reproduced with permission of Society for Neuroscience.
is that they stem from different subtypes of presbycusis.” There are several causes for presbycusis, which have unique patterns of associated hearing loss, including metabolic and sensory presbycusis (Ohlemiller, 2004). Sensory presbycusis involves the loss of OHCs (Schuknecht, 1974) and spiral ganglion cells that are particularly affected in the basal turn of the cochlea (Makary et al., 2011; cf. Fig. 6.3) and is associated with relatively better low-frequency hearing and more steeply sloping high-frequency loss than metabolic presbycusis (Dubno et al., 2013). Metabolic presbycusis likely causes less or no auditory nerve fiber loss and thus preserves input to the central auditory system (Chapter 2). Melcher et al. (2013) reported that in patients with tinnitus (n 5 24; aged 33 62 years) mild hearing loss at 8 kHz (#30 dB HL) was also strongly correlated with changes in ventral posterior cingulate cortex, dorsomedial prefrontal cortex, and a subcallosal region that included ventromedial prefrontal cortex as well, likely resulting from spreading effects of the atrophy in auditory cortex for this high frequency.
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Left PAC Te1.2 Left PAC Te1.0 Left PAC Te1.1
16
3 2 1 0 –1 –2 –3 3 2 1 0 –1 –2 –3 3 2 1 0 –1 –2 –3
Male Female
r = –0.30, p < 0.05
r = –0.46, p < 0.001
r = –0.39, p < 0.01 0.5 1.5 2.5 –2.5 –1.5 –0.5 High-frequency hearing component
3 2 1 0 –1 –2 –3 3 2 1 0 –1 –2 –3 3 2 1 0 –1 –2 –3
r = –0.02, ns
r = –0.06, ns
r = –0.29, p < 0.05 –2.5 –1.5 –0.5 0.5 1.5 2.5 Low-frequency hearing component
FIGURE 1.6 Three areas, Te1.1, Te1.0, and Te1.2, with a well-developed layer IV, which represent the primary auditory cortex (Brodmann area 41), can be identified along the mediolateral axis of the Heschl gyrus. The cell density was significantly higher in Te1.1 compared to Te1.2 in the left but not in the right hemisphere. The cytoarchitectonically defined areal borders of the primary auditory cortex do not consistently match macroanatomic landmarks like gyral and sulcal borders (Morosan et al., 2001). Variation in auditory cortex gray matter (Te1.0 unsmoothed gray matter volume average, relative to total gray matter volume) was associated with the high-frequency hearing threshold component (left), but not the low-frequency hearing threshold component (right). The components were derived from factor analysis of the pure-tone threshold data from both ears for all 49 participants with the same variables for 852 older adults (mean age 5 69.9 years). While men (filled red circles) had more high-frequency hearing loss than women (open blue circles), an association between auditory cortex gray matter and high-frequency hearing threshold was present across the sample. Increasing age, represented by symbol size, did not substantially impact the left Te1.0 findings. Presented with each plot is an image of the associated PAC cytoarchitectonic mask (50% probability). PAC, Primary auditory cortex. Source: From Eckert, M.A., Cute, S.L., Vaden, K.I. Jr., Kuchinsky, S.E., Dubno, J.R., 2012. Auditory cortex signs of age-related hearing loss. J. Assoc. Res. Otolaryngol. 13 (5), 703 713. With permission from Springer Nature.
The question now arises whether hearing impairment interacts with aging to produce this effect. Lin et al. (2014), in a longitudinal study, analyzed brain volume measurements from MRI brain scans of individuals with clinically normal hearing and those with hearing impairment (speech-frequencies PTA # 25 and .25 dB HL, respectively, but not exceeding 45 dB HL) followed in the neuroimaging substudy of the Baltimore Longitudinal Study of Aging for on average 6.4 years after the baseline scan (n 5 126, age 56 86 years). They found that individuals with hearing impairment (n 5 51) compared to those with clinically normal hearing (n 5 75) had significantly accelerated volume decrease in the whole brain (as previously found by Guo et al., 2008)
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and regional volumes in the right temporal lobe (superior, middle, and inferior temporal gyri, parahippocampus). Lin et al. (2014) concluded, “These findings demonstrate that peripheral hearing impairment is independently associated with accelerated brain atrophy in whole brain and regional volumes concentrated in the right temporal lobe.” This corresponds with the asymmetry in atrophy reported by Peelle et al. (2011) for auditory cortex and shown in Fig. 1.5. Also, not specifically focusing on the auditory cortex, Rigters et al. (2017) studied the relation between nonconductive hearing loss and brain volume in a large elderly cohort of 2908 participants (mean age 65 years, 56% female). The group average low-frequency (PTA0.25 1 kHz) hearing loss was 14.1 dB, and the high-frequency (PTA2 8 kHz) loss was 32.4 dB. They quantified global and regional brain tissue volumes using MRI (total brain volume, gray matter volume, WM volume, and lobe-specific volumes). Higher puretone thresholds were significantly associated with a smaller total brain volume, and specifically smaller WM volume. Total brain volume and WM volume were more strongly associated with hearing loss in the lower frequencies. From a review of the literature, Cardin (2016) concluded that the occurrence of atrophy of auditory cortex depends both on hearing loss and older age and is likely underlying compromised auditory processing in these conditions. When there is a hearing loss, the sound quality will be degraded and therefore requires more cognitive efforts to achieve perception. Cardin (2016) argued, “this constant effortful listening and reduced cognitive spare capacity could be what accelerates cognitive decline in older adults with hearing loss.” I have the feeling that it is also the reduced social engagement that may result from degraded speech understanding that contributes to cognitive decline; Chapter 4 will present the available evidence.
1.4.2 Nonclassical Sound-Responsive Cortical Areas The putative effects of hearing loss on attention, memory, and other cognitive functions, are typically attributed to changes in prefrontal cortex. These changes may not be independent of changes in auditory cortex, especially when one realizes that many neurons in these brain areas also respond to sound. In a functional MRI (fMRI) study Langers and Melcher (2011) were the first to show multiple networks of acoustically responsive brain centers. One network comprised classical auditory centers, but four others included classically “nonauditory” areas, namely cingulo-insular cortex, mediotemporal limbic lobe, basal ganglia, and posterior orbitofrontal cortex. Functional connectivity analyses demonstrated coordinated activity between the involved brain structures.
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Resting-state fMRI (Chapter 8) revealed largely similar networks. Subsequently, Michalka et al. (2015) used fMRI to show that two distinct auditory-biased attention regions, transverse gyrus intersecting precentral sulcus (tgPCS) and caudal inferior frontal sulcus (cIFS), were interleaved with visual-biased attention regions in lateral frontal cortex (Fig. 1.7; Tobyne et al., 2017).
1.4.3 Changed Cortical Responsiveness in Aging Does brain responsiveness correlate with speech discrimination? Wong et al. (2009) tested younger and older participants with clinically normal hearing up to 4 kHz (no data for higher frequencies) with fMRI when they identified single words in quiet and in two multitalkerbabble noise conditions (SNR 5 20 and 25 dB). Older and younger subjects did not show significant differences in discrimination in quiet and SNR 5 20 dB, but older adults performed less accurately in the more challenging SNR 5 25 dB condition. The between-group differences in fMRI results showed more increased activation in the auditory cortex in the young (cyan in Fig. 1.8) and more increased activity in working memory and attention-related cortical areas (prefrontal and precuneus regions, yellow in Fig. 1.8) in older participants, especially in the SNR 5 20 dB condition. Increased cortical activity in these cognitive regions in individuals was positively correlated with behavioral performance in older listeners, suggesting a compensatory strategy for the reduced activity in auditory cortex. However, for the challenging SNR 5 25 dB task the compensatory activity appears much reduced in the older population compared to the young, which correlates with the poorer performance. The decrease of activity difference in these cognitive areas for the SNR 5 25 dB in the older group may also be caused by the increased recruitment of these areas by the younger group. Peelle et al. (2011) had also monitored brain activity reflected in the fMRI of older adults (n 5 25; mean age 5 66.3 years) with age-normal hearing who listened to sentences that varied in their linguistic demands. There were several auditory regions, in which participants with poorer hearing showed reduced linguistic activation. They were largely bilateral and included superior temporal gyri, thalamus, and brainstem. There were no regions in which listeners with worse hearing showed increased activity related to linguistic complexity. Peelle et al. (2011) found that individual differences in hearing ability predicted the degree of language-driven neural activity during auditory sentence comprehension in primary auditory cortex, as well as in the auditory thalamus and brainstem. Thus, neural activity underlying perceptual cognitive interactions in speech processing provides a potential
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FIGURE 1.7 Visual- vs auditory-biased attention networks. (A) Task-based fMRI contrast of visual- vs. auditory-spatial attention from a representative individual (Michalka et al., 2015). Bilaterally, two visual-biased attention regions, sPCS and iPCS, were observed to be interleaved with two auditory-biased attention regions, tgPCS and cIFS. In posterior cortex, visual attention recruited IPS/TOS, while auditory attention recruited STG/S. (B) Summary of resting-state functional connectivity results from Michalka et al. (2015). sPCS, iPCS, and IPS/TOS selectively form a visual-biased network (blue), while tgPCS, cIFS, and STG/S selectively form an auditory-biased network (orange). sPCS, Superior precentral sulcus; iPCS, inferior precentral sulcus; tgPCS, transverse gyrus intersecting the precentral sulcus; cIFS, caudal inferior frontal sulcus; IPS/TOS, intraparietal sulcus/transverse occipital gyrus; STG/S, superior temporal gyrus/sulcus. Source: From Tobyne, S.M., Osher, D.E., Michalka, S.W., Somers, D.C., 2017. Sensory-biased attention networks in human lateral frontal cortex revealed by intrinsic functional connectivity. NeuroImage 162, 362 372. With permission from Elsevier.
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FIGURE 1.8 Between-group differences in quiet (left), SNR 20 (middle), and SNR 25 (right) conditions based on independent-sample t-tests (P , .05 corrected). A sagittal view is shown x 5 41 (right hemisphere). The spatial extent could include postcentral gyrus; and STR (medial to lateral, could include the insular cortex). Blue and red indicate stronger activation in younger and older groups, respectively. PP, Posterior parietal region including precuneus; PFC, prefrontal cortex; STR, superior temporal region. Source: From Wong, P.C., Jin, J.X., Gunasekera, G.M., Abel, R., Lee, E.R., Dhar, S., 2009. Aging and cortical mechanisms of speech perception in noise. Neuropsychologia 47 (3), 693 703. With permission from Elsevier.
explanation for age-related changes in spoken language comprehension. Also, in an fMRI study, stimulating with pink noise centered around 350, 700 Hz, 1.5, 3, or 8 kHz, Profant et al. (2015) demonstrated larger activation of the auditory cortex overall in both elderly groups, that is, with mild (n 5 15; mean age 5 67.9 years) and more advanced (n 5 15; mean age 5 70.7 years) presbycusis, in comparison with young normal-hearing controls (n 5 18; mean age 5 23.75 years). The active role of the participants in the Wong et al. (2009) and Peelle et al. (2011) studies showing decreased activity in auditory cortex in the elderly, contrasts with the finding of increased activity in the study by Profant et al. (2015), where the subjects were passive, and likely underlies the different results. Thus, as already foreseen a decade earlier (Reuter-Lorenz and Lustig, 2005): these “new discoveries challenge the long-held view that aging is characterized by progressive loss and decline. Evidence for functional reorganization, compensation and effective interventions holds promise for a more optimistic view of neurocognitive status in later life. Complexities associated with assigning function to age-specific activation patterns must be considered relative to performance and in light of pathological aging.”
1.5 PREVALENCE AND INCIDENCE OF TINNITUS ACROSS THE LIFESPAN Tinnitus often results from noise-induced hearing loss and has its highest prevalence in the elderly. Fosbroke (1831) perceptively stated (italics in
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25 22.5 (A) 20 17.5 15 12.5 10 7.5 5 2.5 0 20 30
UK (NHS) Sweden UK (NHIS) Norway Shargorodsky
40 50 60 70 Age (±5 years)
80
90
Incidence rate of significant tinnitus per 10,000 person-years 0 3 6 9 12 15
Prevalence (%)
the original), “Deafness varies from a diminution of hearing, to an almost extinction of the sense, A noise in the ears, resembling either the roar of the sea, the ebullition of boiling water, or the rustling of the wind among trees, accompanied sometimes with noise in the head, exists in almost every case of deafness, to whatever cause the deafness may be owing.” Tinnitus is considered the result of maladaptive brain plasticity induced by hearing loss. I previously extracted tinnitus prevalence in the general population from three reviews and the original publications contributing to those overviews and from more recent papers not included in those three reviews (Eggermont, 2012). Among the reviews that were covered, Hoffman and Reed (2004) provided an in-depth reanalysis of a few large epidemiology studies, Davis and El-Rafaie (2000) also covered some older epidemiology where different criteria for inclusion of tinnitus were used, and Sanchez (2004) presented a more general (but without a prevalence by age group) overview of a larger number of epidemiology studies. All in all they covered 14 studies that illustrate an upward trend of tinnitus prevalence with age that plateaux around age 70 and that is generally the same for all studies but where the absolute levels depend on the questions asked and the type of tinnitus included. The prevalence of significant tinnitus (lasting .5 minutes, excluding the transient form following noise exposure) by age group of some representative individual studies is shown in Fig. 1.9A (Eggermont, 2014). The overall prevalence of tinnitus in the sample groups was: United Kingdom 10.1%, Sweden 14.2%, United States 8.4%,
<10
(B)
10–19 20–29 30–39 40–49 50–59 60–69 70–79 80–84 Age (years) Male
Female
FIGURE 1.9 (A) Mean prevalence of significant tinnitus for adults. The UK (NHS) data are from Davis and El-Rafaie (2000), the US (NHIS) data are from Nondahl et al. (2002) and Shargorodsky et al. (2010), the Swedish data are from Axelsson and Ringdahl (1989), and the Norwegian study was by Tambs et al. (2003). (B) Gender- and age-specific incidence rates of clinically significant tinnitus. Source: (A) From Eggermont, 2014. Noise and the Brain. Experience Dependent Developmental and Adult Plasticity. Academic Press, London, UK. With permission from Elsevier. (B) From Martinez, C., Wallenhorst, C., McFerran, D., Hall, D.A., 2015. Incidence rates of clinically significant tinnitus: 10-year trend from a cohort study in England. Ear Hear. 36, e69 e75. With permission from Wolters Kluwer Health.
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70
Prevalence (%)
60
Mean tinnitus HL > 25 dB HL
50 40 30 20 10 0 20
30
40
50
60
70
80
Age (±5 years)
FIGURE 1.10 Prevalence of significant tinnitus (average of several studies, details in Eggermont, J.J., 2012. The Neuroscience of Tinnitus. Oxford University Press, Oxford) and of hearing loss .25 dB HL (data from Davis, A.C., 1989. The prevalence of hearing impairment and reported hearing disability among adults in Great Britain. Int. J. Epidemiol. 18, 911 917). Source: From Eggermont, J.J., 2014. Noise and the Brain. Experience Dependent Developmental and Adult Plasticity. Academic Press, London, UK. With permission from Elsevier.
and Norway 15.1%. The three studies with the lower prevalence used a more stringent criterion: the tinnitus should be bothersome. In a more recent large UK study, Dawes et al. (2014) found that the prevalence of tinnitus was 16.9% (95% CI 5 16.6% 17.1%). This was considerably higher than the earlier UK (NHS) study of Davis and El-Rafaie (2000), which averaged at about 12.5% for the age group from 45 to 75 years of age. Underlying the plateaux, Martinez et al. (2015) found that the incidence of tinnitus decreases sharply above 70 years of age (Fig. 1.9B). Note that prevalence is the proportion of a population that has a condition at a specific time. Incidence reflects the rate at which new cases of disease are being added to the population and become prevalent cases. Averaging the data from two Scandinavian countries, two US studies, and the United Kingdom gives the general trend as shown in Fig. 1.10. There is a tendency for the prevalence of tinnitus to level off in the seventh decade of life. In contrast, the prevalence for significant hearing loss (.25 dB HL, from 0.5 to 4 kHz) continues to increase (Davis, 1989).
1.6 SUMMARY The ARHI-associated changes occur in at least three levels, including the peripheral auditory system, central auditory system, and cognitive
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functions. In hearing-impaired elderly patients, the age-related declines of peripheral and central auditory processing interact with the diminished cognitive functions and support, leading to reduced auditory perception of speech (Li-Korotsky, 2012). An important aspect is that auditory stimuli, especially to voice, activate neurons in the prefrontal and other nonauditory areas. In studies of the connectome in aging (Chapter 8), these areas are often implicated as covariants with declining speech discrimination. It is thus clear that the auditory brain extends well beyond the classical auditory areas in the temporal lobe.
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