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date: 19 October 2017

Auditory Processing in the Aging Brain

Summary and Keywords

Age-related hearing loss affects over half of the elderly population, yet it remains poorly understood. Natural aging can cause the input to the brain from the cochlea to be progressively compromised in most individuals, but in many cases the cochlea has relatively normal sensitivity and yet people have an increasingly difficult time processing complex auditory stimuli. The two main deficits are in sound localization and temporal processing, which lead to poor speech perception. Animal models have shown that there are multiple changes in the brainstem, midbrain, and thalamic auditory areas as a function of age, giving rise to an alteration in the excitatory/inhibitory balance of these neurons. This alteration is manifest in the cerebral cortex as higher spontaneous and driven firing rates, as well as broader spatial and temporal tuning. These alterations in cortical responses could underlie the hearing and speech processing deficits that are common in the aged population.

Keywords: aging, age-related hearing loss, auditory processing, ascending auditory system, auditory cortex, primate, rodent

Introduction

Neural representations are continuously changing throughout one’s lifetime. Starting early in development, dramatic changes take place in the number of neurons, synaptic strengths, dendritic and axonal arborizations, and myelination. These processes are believed to be largely completed in early adulthood, but functional changes can continue to occur throughout the lifespan. This “adult plasticity” is thought to be largely related to changes in behavioral and perceptual abilities, and in that sense it is adaptive for the individual. However, detrimental changes are also recognized, for example, in cases of tinnitus (see Eggermont & Tass, 2015) or phantom limb pain (see Luo & Anderson, 2016). These are examples of maladaptive plasticity that occur in some people, however natural aging also results in profound changes in the ability of most people and animals to process and perceive sensory stimuli. These perceptual deficit have been shown in all sensory systems, and some of them can be attributed to problems in the sensory periphery, such as the optics of the eye, changes in skin dynamics, and cochlear pathology. However, changes noted in the cerebral cortex are not fully explained by these peripheral changes (Frisina & Frisina, 1997; Wang et al., 2005; David-Jurgens et al., 2008; Yang et al., 2008; Juarez-Salinas et al., 2010; Engle & Recanzone, 2013). Studies in the auditory system have begun to shed new light on how natural aging can alter not only the periphery, but also neural processing all along the ascending neural pathways through the brainstem, midbrain, thalamus and cortex. While most studies have been done in rodents or humans, more recent studies in nonhuman primates are beginning to provide further clues as to how cortical activity could potentially account for age-related hearing deficits. This article summarizes some of the key studies in this area but is in no way exhaustive.

Age-Related Hearing Loss

Age-related hearing loss, or presbycusis, is a major sensory deficit afflicting the aged. Study results vary, but it has been estimated that across the U.S. population, age-related hearing loss starts in middle age (~2 percent for adults aged 45–54 years) and progresses, with increasing numbers of adults suffering disabling hearing loss (8.5 percent for those aged 55–64 years) until nearly a quarter of early retirees (65–74 years) and half of those over 75 years of age are afflicted (NIDCD). While these rather large numbers are startling, they do not encompass all of the individuals who also suffer from age-related hearing deficits. In this instance, a person may have a normal audiogram, and therefore can “hear fine,” and yet is still unable to process complex auditory signals as well as when he or she was younger. This is most prevalent as deficits in understanding speech, particularly in noisy environments (see Gordon-Salant, 2005). These deficits can lead to social isolation, depression, dementia, and other mental disorders as the individuals withdraw from society owing to their lack of communication skills (see Genther et al., 2015; Deal et al., 2016; Nirmalasari et al., 2016). Pinpointing what specific processing deficits exist in aged human subjects can provide some insights into the neural changes that could underlie these deficits.

Psychophysically Measured Deficits

In the laboratory, age-related hearing deficits can be broadly placed into spatial and temporal categories. In most studies of human subjects, the intensity of the stimuli is equated with the audiogram of the individual, so that the sensation level is the same across subjects. This leaves only the processing itself that is being tested, as the stimuli are the same “loudness” across subjects. Such studies have indicated that aged humans have spatial processing deficits across a number of different stimuli (Abel et al., 2000; Dobreva et al., 2011; Otte et al., 2013). The consequences of these conditions have been suggested to partially underlie speech processing deficits in noisy environments, such as the “cocktail party” environment. If one cannot accurately localize the sound source of interest, it is more difficult to allocate attention to that particular location in space. Thus, one question that arises is how aging affects the auditory regions that are processing spatial information, particularly in the superior olivary complex and the cerebral cortex.

In addition to spatial processing deficits, temporal processing deficits have also been demonstrated in a number of different ways. As speech can be parsed into a number of different acoustic structures, these basic elements have been tested in young versus aged humans (see Gordon-Salant, 2005; Gordon-Salant et al., 2011). For example, stop-consonants result in a break in the acoustic stream, which can be modeled by varying the duration of a gap in a noise burst. Such studies have demonstrated that older subjects need longer gap lengths for them to perceive that there were two noise bursts instead of one (Ozmeral et al., 2016). Similarly, the envelope of a speech signal, which parses the different syllabi, is an important component of speech perception (He et al., 2008) and can explain much of the success of cochlear implants, particularly those with few electrodes (Kalkman et al., 2016). This can be modeled in the laboratory as varying the depth and/or frequency of an amplitude-modulated noise. Such studies are also consistent in that older subjects have a more difficult time discriminating different temporal aspects of sounds (Fitzgibbons & Gordon-Salant, 1996; Gordon-Salant, 2005; He et al., 2008). Thus, these spatial and temporal processing deficits that likely underlie the speech processing deficits experienced by aged subjects can be used in animal studies to help determine how neural processing changes could underlie these deficits.

Anatomical Changes Throughout the Ascending Auditory System

Cochlea

Early studies by Schuknecht and colleagues investigated cochlear histopathologies in subjects who died within six months of measurements of their audiograms (Schuknecht, 1955, 1964; Ramadan & Schuknecht, 1989). These studies indicated that four main cochlear histopathologies could underlie audiometric deficits. The first three included degradation of the neural elements of the cochlea, the inner hair cells, outer hair cells, and spiral ganglion cells. The fourth was the thickness of the stria vascularis, which supports the cochlear high K+ environment of the scala media, that is, the “cochlear battery.” These ideas have been tested in various animal models and recently in the macaque monkey. The macaque monkey ages at about three times the rate of humans (Davis & Leathers, 1985). Recent studies using the auditory brainstem response to test hearing ability across monkeys spanning the equivalent of 30–90+ human years of age indicate that this species suffers from age-related hearing loss across their lifespan in a manner similar to that seen in humans and other mammals (Ng et al., 2015). In a subset of these monkeys, Engle et al. (2013) investigated the cochlear histopathologies of monkeys with varying degrees of age and age-related hearing loss and compared these histopathologies to the measured hearing ability of that particular animal. This study revealed the surprising finding that there was no consistent relationship either with age, with the hearing ability, or any single histopathology. Instead, it was the number of histopathologies that increased with increasing age. Thus, for two monkeys with what would be considered mild hearing loss, one monkey could have a reduction in inner hair cells, whereas the other could have a reduction in spiral ganglion cells. Similarly, two monkeys with more severe hearing loss would have two deficits (i.e., inner and outer hair cell loss) but not necessarily the same two.

If we consider that a similar phenomenon occurs in humans, where different cochlear histopathologies arise over the course of time but at different time courses in different individuals, it could account for the wide variability that is observed in the aged human population. It also has treatment implications, as hearing aids could be very beneficial for someone with outer hair cell damage but not necessarily effective for someone with spiral ganglion cell damage. In the end, of course, the results of these different cochlear histopathologies will result in a decrease in the excitatory output from the cochlea to the central nervous system. How, then, can the central nervous system respond to this decreased excitatory drive from the cochlea?

Brainstem and Midbrain

One experimental strategy that has been used to understand changes throughout the auditory nervous system is to stain neurons with antibodies or other markers associated with excitatory or inhibitory transmission. Popular targets include glutamate receptors and GABA receptor precursors (Tadros et al., 2007; Caspary et al., 2008; Wang et al., 2011). Other targets have included calcium-binding proteins such as calbindin, calretinin, and parvalbumin. These studies in both rodents and nonhuman primates are all converging on the same general notions that there are widespread changes in the excitatory/inhibitory balance as well as in the regulation of intracellular calcium throughout the ascending auditory system as a function of age and hearing deficits. These changes, however, show considerable differences between different species (i.e., mice, rats, monkeys, and likely humans), but also in some cases in different strains of the same species (reviewed by Ouda et al., 2015; Gray & Recanzone, 2016).

The cochlear nucleus (CN) is the first central auditory structure to receive input from the cochlea via the auditory nerve. The CN can be subdivided into three distinct nuclei, all of which receive input from each spiral ganglion cell leaving the cochlea: the dorsal cochlear nucleus (DCN), anterior ventral cochlear nucleus (AVCN), and the posterior ventral cochlear nucleus (PVCN; Ehret & Romand, 1997). In mice, if one looks at the distribution of the calcium-binding proteins parvalbumin, calbindin and calretinin, there is an increase in both the DCN and PVCN, but not AVCN, despite a decline in total cell density (Idrizbegovic et al., 2003, 2004, 2006; Zettel et al., 2003). Analogous research in monkeys is sparse, but one study found that parvalbumin expression remained constant with age across the three subdivisions of the CN (Gray et al., 2014a). However, given the large number of different calcium binding proteins and calcium-dependent proteins, it could be that the monkey has a different cellular mechanism to adapt to the decreased excitatory drive from the cochlea. For example, the same study in monkeys saw an increase in the density of neurons containing the molecule NADPHd (nicotinamide adenine dinucleotide hydrogen phosphate diaphorase), but only within the PVCN. This molecule has been associated with calbindin in other brain structures in the monkey, but that was not tested in the Gray et al. (2014a) study, so it is unknown which CaBPs, if any, NADPHd co-localizes with in the primate CN. Additionally, as Gray et al. (2014a) tested only PV, there are likely age-related changes in the cell densities of neurons expressing other CaBPs in the aged CN of the macaque.

The next main structure in the ascending auditory system is the superior olivary complex (SOC). This structure is divided into the medial and lateral superior olive (MSO and LSO, respectively) and the nucleus of the trapezoid body (NTB). The SOC is the first region of binaural integration in the auditory system (Reuss, 2000; Tollin, 2003) and processes the three major cues for sound localization along the horizon. Differences in the time and phase that the sounds reach the two ears are processed in the MSO, which is responsive primarily to low frequencies where these cues are less ambiguous. The differences in the intensity of the sound between the two ears are processed in the LSO, where high frequencies provide the most salient information (Jeffress, 1948; Galambos et al., 1959; Boudreau & Tsuchitani, 1968; Guinan et al., 1972). The emphasis of these different frequency ranges is reflected in the size of the nuclei based on the hearing range of the particular species. For example, the MSO is greatly reduced in rodents compared to macaques, since most rodents, such as mice and rats, have a higher frequency hearing range compared to macaques (Yin, 2002; Heffner & Heffner, 2007). The NTB is a source of input to both the MSO and LSO. It receives excitatory input from the contralateral CN and then sends glycinergic inhibitory outputs to the MSO and LSO, which also receive direct excitatory input from the ipsilateral CN (Banks & Smith, 1992; Thompson & Schofield, 2000). Our current understanding is that the comparisons between these excitatory and inhibitory inputs play a significant role in the representation of interaural difference cues in the SOC.

As noted above, sound localization deficits are a hallmark of age-related hearing loss, so how this structure is affected by natural aging is of key interest. Unfortunately, given its location and the small size of this structure, it has been little studied beyond in the cat (see Yin & Chan, 1990; Joris & Yin, 1998; Tollin et al., 2009a, 2009b). Age-related studies have shown that the rodent NTB has the most pronounced anatomical changes (Casey, 1990), and both CaBPs and NADPHd increase as well (O’Neill et al., 1997; Reuss, 2000). Gray et al. (2013a) reported that PV and NADPHd increases are localized exclusively to the macaque MSO, and not the NTB or LSO. Functionally, these interspecies differences can be accounted for by the differences in hearing abilities between rodents compared to primates, as discussed earlier.

As inputs ascend throughout the brainstem, there is an obligatory input to the inferior colliculus (IC) in the midbrain, which receives inputs from the SOC (Webster, 1995; Oliver, 2000; Reuss, 2000), as well as from fusiform cells of the DCN, which are tuned to sound locations in elevation (Young & Davis, 2002). This convergence of spatial information suggests that the IC can represent sound source location in two-dimensional space (Zwiers et al., 2004). Interestingly, the IC is also the first nucleus to show pronounced separation of the PV- and CB-defined parallel processing pathways characteristic of the ascending auditory system (see Jones, 2003), demonstrating that along with functional specificity, the IC contains a level of chemical specificity not seen in lower auditory nuclei. Specifically, the lemniscal (direct) pathway ascends through the central nucleus of the IC (ICc) and is primarily PV positive, whereas the nonlemniscal (indirect) pathway ascends through the peripheral cortex region of the IC (ICx) and is primarily CB positive.

Age-related histochemical studies have been conducted in both rodents and monkeys. Overall, these results vary between species and even between different strains of the same species. For example, age-related increases in PV and decreases in CB and CR have been reported (Ouda et al., 2008, 2012), whereas other studies have seen increases in CR (Zettel et al., 1997, 2001). In the macaque both the ICc and the ICx increase PV expression with age (Engle et al., 2013). PV was the only CaBP tested in that study, but NADPHd expression was also investigated and found to be unchanged. Unlike cortical PV and CB expressing neurons, the neurons of the auditory brainstem and midbrain have been shown to co-localize with markers of both GABAergic and glutamatergic transmission in both rodents and macaques (Fredrich & Reisch, 2009; Gray et al., 2014b).

Thalamus and Auditory Cortex

The medial geniculate nucleus (MGN) of the thalamus, like the IC, has subdivisions that correspond to either lemniscal or nonlemniscal regions (Hu, 2003; Jones, 2003). The MGN can be divided into the ventral (vMGN), dorsal (dMGN), and magnocellular (mMGN). In the macaque, like most mammals, the lemniscal pathway ascends through the vMGN, which primarily stains positively for PV. Conversely, the nonlemniscal pathway ascends through the dMGN, which primarily stains positively for CB. The mMGN shares characteristics with both pathways and is generally considered an intermediate nucleus. Not surprisingly, the MGN shows different age-related changes in different histochemical markers. The rodent MGN shows decreases in CB and NADPHd with age, and these changes are only observed in the vMGN (Ouda et al., 2008; Villena et al., 2003; Ouda et al., 2012). The macaque MGN, unlike the rodent MGN, displays strong immunoreactivity to PV. Consistent with the rodent, changes are only observed in the vMGN (not the dMGN), except that the age-related changes are increases (Gray et al., 2013b). These changes in the vMGN are greater than that seen in the adjacent lateral geniculate nucleus (LGN). This indicates that these changes are at least in part specific to the auditory system, and not a general mechanism employed by multiple systems or a general effect of aging on primate tissue.

Finally, similar changes in the expression of different anatomical markers are noted in the primary auditory cortex, a cortical region that is found across mammalian species and receives the majority of its input from the vMGN. There, declines in immunoreactivity to both PV and CB have been reported in rodents (Ouda et al., 2008, 2012). Unfortunately, there have been no reports of similar studies in primates, so it is only possible to speculate how changes, if any, would occur in the auditory cortex.

In summary, histochemical age-related changes along the ascending auditory pathway have been described in the brainstem, midbrain, and thalamus in both rodents and primates. However, the direction, magnitude, and location of these changes differ between rodents and primates, and therefore cannot be completely generalized between these two animal models (see Ouda et al., 2015; Gray & Recanzone, 2016). Curiously, some nuclei have shown large changes that differ between species, and others have not been demonstrated to show any type of change. While some of this could be attributed to the behavioral relevance of different acoustic frequencies given the differences in hearing range, it is also important to remember that numerous calcium-binding proteins and other structures remain untested in any species, and it may well be that across nuclei species-specific changes are potentially compensating for the decreased excitatory drive from the cochlea.

Examples of Electrophysiological Function of Neurons Expressing Different Calcium-Binding Proteins in the Central Auditory System

There is a good understanding of the response properties of some neurons that express different CaBPs compared to others that do not (Carder et al., 1996; Parent et al., 1996; Prensa et al., 1998; Cicchetti et al., 2000). A good example is from the neurons in the cerebral cortex and hippocampus that express PV. These neurons are GABAergic basket neurons with narrow action potential waveforms and short, nonadapting interspike latencies (Kawaguchi et al., 1987; Kawaguchi & Kubota, 1997; Gibson et al., 1999; Ascoli et al., 2008; Xu & Callaway, 2009; Rudy et al., 2011). These properties make them powerful inhibitors, and this inhibition is thought to be critical in defining the receptive fields of neurons within the local circuitry. Thus, it is tempting to interpret increases in PV staining neurons to indicate an increase in inhibition, which seems counterintuitive given the decreased excitatory drive from the cochlea. However, studies in the brainstem of both rodents and nonhuman primates indicate that these neurons are likely not inhibitory, but rather excitatory as they co-localize with glutamatergic, and not GABAergic, markers (Fredrich & Reisch, 2009; Gray et al., 2014b). These same studies show that neurons in the auditory midbrain (IC) are primarily (but not exclusively) GABAergic.

To complicate matters further, the extent to which PV+ and CB+ cells co-localize with GABA and glutamate also changes with age. For example, in parts of the SOC, PV co-localizes less with GABA, whereas CB+ cells co-localize more with GABA with increasing age in the macaque (Gray et al., 2014b), and ICc neurons become more GABAergic. These results indicate that a great deal of imbalance between the excitatory and inhibitory inputs is occurring with natural aging. Clearly, these anatomical experiments will not suffice to provide a clear understanding of the functional consequences of the age-related changes in the expression of CaBPs seen throughout the auditory system. Future work is necessary to make coherent sense of how the ascending auditory nervous system is attempting to compensate for the decreased excitatory output from the cochlea.

How Anatomical Changes Potentially Relate to Electrophysiological Properties

Correlation with ABR Recordings

Depending on the species, electrophysiological studies in the brainstem can be extremely difficult. Thus, the auditory brainstem response (ABR) has been used as a proxy to the overall neural activity in early brainstem areas. This technique relies on surface recordings from the scalp to average the responses across several hundred stimulus repetitions, and the resulting waveforms can be attributed to the function of the different early ascending auditory areas (Møller & Burgess, 1986). This technique has been extremely helpful in studying primate physiology of early auditory areas (Allen & Starr, 1978; Torre & Fowler, 2000; Torre et al., 2004; Fowler et al., 2010; Ng et al., 2015).

By recording ABRs in animals where different CaBPs have also been determined, Gray et al. (2013a, 2014a) noted that the densities of PV neurons were correlated with responses to high-stimulus frequencies, but not low-stimulus frequencies, in the CN and SOC. Interestingly, the greater the PV staining (and greater the age), the lower the amplitude of the ABR waveforms related to these auditory structures. This may seem counterintuitive given that PV is presumably related to excitatory neurons (but see above), and greater excitation should lead to greater amplitudes of the ABR signal. However, the ABR does not measure the overall amplitude of the neural signal; rather, it measures the ability of the neurons to synchronize with each other. Thus, it may well be that the neuron-by-neuron coherence is what is most affected by aging (a potential substrate for temporal processing deficits seen at the psychophysical level), and either the increase in PV neurons cannot compensate for this or they may indeed be firing out of synchrony with the other excitatory neurons.

Changes in Response Properties in the Auditory Cortex

Recently, the effects of natural aging on the response properties of auditory cortical neurons have been investigated by several studies in alert macaque monkeys. The primate auditory cortex is made up of multiple cortical fields organized into a core–belt–parabelt fashion (Kaas & Hackett, 2000; Rauschecker & Tian, 2000; Hackett et al., 2001). The core is made up of primary auditory cortex (A1), a more rostral field (R), and a thChanges in spontaneous activityird field located rostral to R, called RT. Surrounding these core fields are the belt fields, largely denoted by their relative anatomical position. Of interest is the field located caudal and lateral to A1, the caudolateral field (CL). Physiological studies have indicated that the neurons in area CL have broader spectral tuning than those of A1 (Merzenich & Brugge, 1973; Rauschecker et al., 1997; Recanzone et al., 2000a; Tramo et al., 2005). In contrast, neurons in CL have sharper spatial tuning (Recanzone et al., 2000b; Tian et al., 2001; Woods et al., 2006; Juarez-Salinas et al., 2010; Engle & Recanzone, 2013). Further, the sharper tuning of single CL neurons is sufficient to account for sound localization ability of primates (Miller & Recanzone, 2009), indicating that this region forms part of a spatial processing stream, similar to the dorsal processing stream of visual cortex (Rauschecker & Tian, 2000).

Changes in spontaneous activity

A pressing question is how the decreased excitatory drive from the cochlea, the decreased amplitude and/or synchrony of neural responses in the brainstem, the pervasive histochemical changes throughout the ascending auditory pathway, and the large individual variability in auditory perception with age, is ultimately manifest in the activity of auditory cortical neurons. Several experiments in the alert macaque monkey have indicated that there are dramatic changes in the response properties of neurons in auditory cortex, both in the core area A1 and in the belt area CL.

The initial observation in the alert macaque auditory cortex was that there was a several-fold increase in the spontaneous activity (Juarez-Salinas et al., 2010; Engle & Recanzone, 2013). This was true in both A1 and CL. This finding is consistent with that seen in rodent A1 (De Villers-Sidani et al., 2010; Hughes et al., 2010), as well as rodent inferior colliculus (e.g., Palombi & Caspary, 1996; Walton et al., 1997, 2008). While this may seem surprising given the decreased excitatory drive from the cochlea, it indicates a severe imbalance of excitation and inhibition in the aged nervous system, ultimately leading to an overall decrease in inhibition and increased activity of these cortical neurons.

These changes in auditory cortex are not specific for the auditory system, as they have also been seen in primary visual cortex (V1, Wang et al., 2005) as well as secondary areas V2 (Wang et al., 2005), the middle temporal area MT (Yang et al., 2008; Liang et al., 2010), and the hippocampus of aged monkeys (Thome et al., 2015). Similar findings have been made in the somatosensory cortex in both the rat (e.g., Benali et al., 2008; David-Jurgens et al., 2008) and human (e.g., Kalisch et al., 2009; Lenz et al., 2012; Canu et al., 2012). Thus, there is a general decrease in inhibition and/or suppression across the different cerebral cortical areas as well as across different species, giving rise to these increased spontaneous rates, presumably due to decreased excitatory drive from the sensory periphery resulting from decreased optics (i.e., cataracts) and tactile receptors and the physical properties of the skin, gait, and other factors (e.g., see David-Jurgens et al., 2008).

Changes in Driven Activity: Spatial Tuning

Given the changes in spontaneous activity, the question becomes, whether driven activity is also altered? Thus far, the most salient information in the auditory system of primates comes from studies of A1 and CL with respect to the representation of acoustic space. Multiple psychophysical studies have noted that humans and macaque monkey share similar sound localization abilities across stimulus frequencies, spectral content, azimuth, elevation, and stimulus intensity (Recanzone et al., 1998; Recanzone et al., 2000b; Su & Recanzone, 2001; Recanzone & Beckerman, 2004; Miller & Recanzone, 2009). As noted above, neurons in area CL have sharper spatial tuning than those of A1, and this spatial tuning is sufficient to account for human sound localization ability across azimuth and stimulus intensity (Woods et al., 2006; Miller & Recanzone, 2009). Thus, since a hallmark of age-related hearing deficits is in sound localization, the question becomes how the neurons in A1 and CL respond as a function of spatial location. The initial studies indicated that, while the spontaneous activity was higher in aged than in younger animals, the spatial tuning of A1 neurons was about the same in aged monkeys compared to younger monkeys (Juarez-Salinas et al., 2010). When CL neurons were examined, however, they were no more sharply tuned to the spatial location of the stimulus than were A1 neurons, which was clearly different from what was seen in the younger animals (Juarez-Salinas et al., 2010). In other words, there was not the progressive sharpening of spatial tuning between A1 and CL in aged monkeys that was seen in younger ones. This is similar in many respects to what was seen in the visual cortex of aged monkeys, where the orientation selectivity and the direction selectivity of individual neurons was broader in aged animals than in younger animals (Wang et al., 2005; Yang et al., 2008; Liang et al., 2010).

The finding that CL neurons are no sharper in their spatial tuning than A1 neurons in aged animals suggests that, under “normal” circumstances, CL spatial tuning is shaped from the A1 inputs, likely through some form of inhibition or suppression. There is an anatomical substrate to support this hypothesis, as belt fields receive direct inputs from the core, and elimination of these inputs can dramatically affect the responses of belt field neurons (Rauschecker et al., 1997). Further, there are direct connections from the thalamus to each of the belt fields (Hackett, 2015; de la Mothe et al., 2012). To investigate this possibility given the data available, the responses across the population of A1 and CL neurons were plotted relative to the best direction for each individual neuron (Engle & Recanzone, 2013). This provides an overall population response for a stimulus presented from any given location. The results showed that in young A1, the shortest latency was for the best location and latencies increased as the stimulus moved to greater eccentricities, although there were clear responses at all locations tested. These latency differences were enhanced in CL, reflecting the sharper spatial tuning of individual neurons, and the locations that elicited a good response were cut nearly in half. These results indicate that the same latency increases and response decreases occur over a much smaller spatial range across the population of CL neurons compared to A1 neurons.

A very different result was noted in the aged monkeys. In this case, the latency difference as a function of spatial location was nearly absent in A1 as well as CL. Further, there were good (nearly equivalent) responses across all locations tested for both populations of neurons. Finally, the onset latencies in the aged monkeys not only did not vary across location, but they were in fact less than the shortest latencies noted in the A1 neurons of the younger animals, consistent with a lack of inhibition and/or suppression in the inputs to the cortex in aged monkeys. Thus, not only is the spatial and driven activity higher and spatially broader, but it also has a much shorter latency in the aged animals compared to the younger ones.

A second analysis technique applied in that study was to make the simple distinction between whether the response was less than, the same as, or greater than the spontaneous activity as a function of both spatial location and time. This provides a spatiotemporal profile of the relative amount of activity across the population of A1 and CL neurons. In young animals, there was clear suppression of the response at locations far from the best direction in A1, and this suppression was even greater in CL. Thus, at least one mechanism of sharpening spatial tuning between A1 and CL is by suppressing the flanks of the receptive fields. Again, in contrast to younger animals, in the aged animals there was virtually no suppression at any spatial location, at any time. These results indicate that during natural aging, there is a lack of suppression in the corticocortical connections. Thus, the imbalance of excitation and inhibition presumed to be occurring in the subcortical regions is manifest as a decrease in suppression at the cortical level and in the inability of receptive field refinement between cortical areas. These changes in spatial receptive fields are consistent with the decreased sound localization ability noted with increasing age.

Changes in Driven Activity: Temporal Tuning

A second age-related hearing deficit is in the inability to encode temporal information. For example, the gap detection thresholds for aged neurons are much greater than predicted by the psychophysical performance in younger monkeys (Recanzone et al., 2011). This is consistent with studies in rodent inferior colliculus, where increased gap thresholds are noted as a function of age (Walton et al., 1997, 1998).

A second series of studies in the primate auditory cortex indicates that the envelope of the speech signal is also degraded. Overton and Recanzone (2016) investigated the ability of A1 neurons to encode the envelope of an amplitude-modulated (AM) noise stimulus and compared those responses to the responses recorded in younger monkeys (Yin et al., 2011). In principle, neurons can encode the frequency of an AM noise stimulus in two ways. The first way is to try to replicate the stimulus envelope as accurately as possible, a phenomenon known as phase locking. In this instance, the neuron will respond only during a particular phase of the stimulus and not during the opposite phase. A neuron can therefore respond with more than one action potential for each phase, but the action potentials will be clustered into a regular series of “response epochs” and “no-response epochs” that corresponds to the AM stimulus frequency. For example, for a 10 Hz stimulus, the response of an average of 10 spikes/burst will be clustered every 100 msec, but for a 20 Hz stimulus the bursts could average 5 spikes/burst but would occur every 50 msec. Thus, the same number of spikes could nonetheless accurately encode different stimulus frequencies by when they occurred. This can be measured by various metrics, one of the more popular being the vector strength and its’ derivatives, where a value of 1.0 means that the action potentials are always at exactly the same phase of the stimulus, to 0.0 where the action potentials occur randomly compared to the stimulus frequency (Goldberg & Brown, 1969; Yin et al., 2011; Overton & Recanzone, 2016).

The second way that the AM rate can be encoded by the overall firing rate of the neuron, which would vary as a function of the AM rate, similar to intensity tuning in many auditory neurons or orientation tuning in visual cortical neurons. In young monkeys, both types of coding schemes are used, with over half of the neurons showing significant tuning using each metric. In contrast, in aged monkeys there are fewer neurons that encode AM using both a rate and temporal code; rather, a disproportionate number of neurons encode AM with only a firing rate code (Overton & Recanzone, 2016). Further, in younger monkeys those neurons that encode AM with only the firing rate do so with a reduced firing in about one-third of neurons. In contrast, the same population of cells in aged monkeys rarely shows decreases in their firing rate to encode AM, even though they have higher spontaneous activity. This again indicates that there is less suppression/inhibition at the cortical level than can be used to better encode the stimulus.

With respect to the temporal tuning, there was an overall decrease in neurons in aged monkeys that could encode the AM rate with synchronous firing to the stimulus, and those that did tended to have smaller vector strength metrics, indicating that they were not as precisely tuned as those in the younger animals. Finally, in younger animals there was a correlation between the best AM tuning using both the rate and temporal codes; that is, the AM rate that gave the highest firing rate usually was the rate that resulted in the highest vector strength. In contrast, these metrics were not correlated in aged monkeys, as the temporal code was mainly highest at the low AM rates and the firing rate mainly highest at the high AM rates, with considerable scatter between neurons. These results are again consistent with an imbalance of excitatory and inhibitory drive if one assumes that phase locking is dependent on enhancing responses at one phase of the stimulus and inhibiting/suppressing responses at the opposite phase.

Conclusions

Natural aging results in a wide variety of different anatomical and physiological consequences, all of which are highly variable between individuals. Starting at the cochlea, the number of different pathologies increases with increasing age, resulting in a decreased excitatory drive over time. This decreased excitatory drive is potentially compensated for by the differential expression of different calcium-binding proteins, likely reflecting different adjustments to the excitatory and inhibitory balance of the circuitry throughout the brainstem, midbrain, and thalamus. Presumably, these changes are initially compensatory, allowing the individual to maintain the same level of auditory perception in spite of differences coming from the cochlea. The predominant findings from mammals, including the nonhuman primate data, indicate that this occurs as early as middle age, and this may underlie the relatively small number of middle-aged humans who report age-related hearing deficits. However, as aging progresses, these compensatory mechanisms start becoming inadequate, and the response properties of auditory cortical neurons begin to degrade, consistent with the perceptual deficits common with aging. As the excitatory and inhibitory balance is upset, cortical neurons have higher spontaneous and driven firing rates, broader spatial tuning, poorer gap detection, and reduced AM rate encoding. Further, these deficits are enhanced in secondary auditory cortical fields as compared to primary auditory cortex. These cortical response differences are consistent with the decreased spatial and temporal resolution common in the aged. The pressing question, then, is how to either reduce or reverse these cortical changes, which would presumably be an effective treatment of age-related hearing deficits. Several strategies are possible; a promising one is behavioral training, which has been shown to be effective in the aged rat auditory cortex (DeVillers-Sidani & Merzenich, 2011). The precise training regimes and the details of how such manipulations could be most effective and efficient in ameliorating age-related hearing loss remains to be worked out.

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