Objective Biological Measures for the Assessment and Management

Objective Biological Measures for the Assessment and Management
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Current Pediatric Reviews, 2011, 7, 252-261
Objective Biological Measures for the Assessment and Management of
Auditory Processing Disorder
Jane Hornickel1 and Nina Kraus*,1,2
1
Auditory Neuroscience Lab, Department of Communication Sciences and Disorders, Northwestern University, USA
2
Departments of Neurobiology and Physiology, Otolaryngology, Northwestern University, USA
Abstract: Auditory processing impairments negatively impact language learning, the ability to listen effectively in noisy
environments, and the development of reading skills. Behavioral assessments of auditory processing provide valuable
insight into auditory function but lack information about the biological health of the auditory pathway, and can be
complicated by comorbid disorders, alertness, and motivation. The speech-evoked auditory brainstem response has
recently been linked to communication skills such as speech-in-noise perception and reading ability and provides
additional insight for the diagnosis and management of auditory processing disorders. This paper reviews how objective
biological measures of auditory function can be used to reveal auditory system dysfunction in the absence of hearing loss.
Keywords: Auditory brainstem, auditory processing disorders, children, electrophysiology, neurophysiology, speech-in-noise
perception.
INTRODUCTION
Hearing is fundamental to the development of successful
language skills; deficits in hearing acuity and auditory
processing can profoundly obstruct effective communication.
Proper encoding of sound by the auditory system is especially important for the perception and discrimination of
speech sounds, particularly consonants that can be difficult
to perceive in noise [1, 2]. While hearing loss impedes the
development of language and communication skills [3-9],
many children with normal hearing exhibit impairments in
auditory processing that likely contribute to and reflect
deficits in reading and listening to speech in noise. Deficits
in auditory processing skills such as tempo/rhythm perception, frequency discrimination, sounds-in-noise perception,
pattern detection, and speech sound discrimination have been
found for children with language learning disorders but
normal hearing [10-16]. These children also show marked
deficits in auditory nervous system function, both in the
auditory cortex and auditory brainstem [17-29]. While the
click-evoked auditory brainstem response has been used for
decades in hearing assessments [30, 31], the speech-evoked
brainstem response has recently been linked to speech-innoise listening and reading skills [17-23, 32]. The speechevoked auditory brainstem response offers a unique vantage
point for assessing auditory function due to its remarkably
faithful representation of the stimulus acoustics [33].
Auditory deficits contributing to impaired language and
listening abilities in children are likely due to a complex
interaction between sensory function and cognition. Once
thought to be simply a sensory relay to the cortex, the
auditory brainstem has been shown to be vastly malleable
through meaningful interaction with sound [19, 34-48]. Due
to the complex interaction between sensory and cognitive
*Address correspondence to this author at the 2240 Campus Drive,
Evanston, IL 60208, USA; Tel: 847-491-3181; Fax: 847-491-2523; E-mail:
[email protected].edu; Web: www.brainvolts.northwestern.edu
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functions that likely occurs in impaired auditory processing,
auditory brainstem measures may be particularly useful in
revealing the biological correlates of communication. This
paper reviews how objective biological measures of auditory
function provide new insight into the diagnosis and
management of auditory processing disorders (APD) and can
be used to reveal auditory system dysfunction in the absence
of hearing loss.
A PATIENT WITH APD
Imagine a mother bringing her nine year old son to see
his doctor because he is having difficulty understanding his
teacher and following directions. He seems to be able to
focus his attention, but appears to not understand what is
being said. Additionally, he has difficulty understanding
people speaking in the presence of background noise and
often “tunes out” of conversations at birthday parties and in
the cafeteria at lunch. His performance in school is affected
by his inability to follow spoken directions and he’s getting
lost in the noise from the other students in his large
classroom. Based on these symptoms, this child could have
an auditory processing impairment, but how should he be
evaluated?
His symptoms may be due to a number of sensory and/or
cognitive deficits and so a differential diagnosis is needed.
First, does the patient have peripheral hearing loss? A
sensorineural or conductive hearing loss would impede his
ability to understand spoken language and perceive speech in
background noise. Pure tone thresholds can predict approximately 50% of the variance in speech-in-noise perception in
adults [49]. Chronic otitis media and unaided sensorineural
hearing loss relate to language delays and learning
impairments, likely due to reduced auditory input during
critical language-learning periods [3-9]. Transient hearing
loss could be treatable with medication, while a genetic or
induced permanent hearing loss could be aided by hearing
© 2011 Bentham Science Publishers Ltd.
Assessment and Management of Auditory Processing Disorder
aids or cochlear implants. In either case, this child’s poor
listening performance is due to impaired audibility, which
may be at least partly treatable. Second, does the child have
typical attention behaviors? Children who have AttentionDeficit Hyperactivity Disorder (ADHD), particularly the
Inattentive subtype, exhibit many of the characteristics of
auditory processing disorders, including distractibility and
difficulty following directions [50-52]. Nevertheless, audiologists and physicians ranked the most representative
characteristics of the two disorders as being distinct, with
Inattentive ADHD best characterized by inattentiveness, and
auditory processing disorders being characterized by asking
for things to be repeated and poor listening skills [50].
Because attention disorders are an overarching impairment,
children would be impaired on both auditory and visual tasks
[51]. Therefore, Inattentive ADHD may be distinguished
from auditory processing disorders based on performance on
visual attention tasks, which would be poor in a child with
ADHD and typical in a child with impairments solely in
auditory processing.
Assessment of auditory processing disorders typically
includes behavioral tests that challenge the child’s perceptual
skills. Auditory processing skills may be measured with tests
of detection, discrimination, or identification [51-54].
Stimuli can be presented to one or both ears, with the same
(diotic listening) or different (dichotic listening) stimuli
presented to the two ears simultaneously [51-54]. Particular
skills that are important for efficient auditory processing and
speech perception include temporal processing, pattern
detection, and word or sentence recognition [51, 54].
Therefore, particular tests incorporate different types of tasks
(detection, discrimination, identification), presentation
(monaural, binaural), and skills (temporal processing, pattern
detection, word or sentence recognition). Examples include
dichotic digit identification, tone pattern sequencing, and
temporal gap detection. Additionally, speech-in-noise perception tasks may be employed, which incorporate ecologically-valid speech stimuli and listening conditions. In all
cases norms are available to compare an individual’s
performance to that of a group of same-aged peers and a
positive diagnosis is based on abnormal performance across
a number of measures.
Although auditory processing disorder batteries are
meant to be comprehensive and allow for a differential diagnosis, the methods of testing are complicated by behavioral
factors [52]. Poor performance on a given behavioral test
may be due to a number of contributing factors other than
auditory processing disorder. For example, if stimuli are
verbal (i.e., speech) and the child has a reading disorder or
language impairment, his/her performance might be
compromised because of the verbal nature of the stimuli and
not because of an auditory processing impairment. As mentioned above, attention deficit disorders may result in poor
performance on psychophysical tasks overall, without an
auditory-specific deficit. Performance on behavioral measures is also complicated by factors such as wakefulness,
mood, and motivation that could impact performance on
challenging tasks. Although some assessments may be more
resistive to the effects of hearing loss, peripheral hearing loss
of any kind could contribute to poor performance on
behavioral assessments of auditory processing. Objective,
biological measures of auditory processing sidestep some of
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the potential complications inherent to behavioral assessments and, most significantly, can elucidate the biological
factors contributing to auditory processing. As discussed
below, these objective measures of sensory function are
highly related to cognitive skills such as speech-in-noise
perception and auditory memory and make considerable
contributions to the delineation of factors underlying
auditory processing disorders.
BIOLOGICAL CORRELATES-AUDITORY BRAINSTEM RESPONSES
Recent recommendations for evaluating auditory processing include electrophysiological and electroacoustic measures of auditory function [51, 54, 55]. Evoked auditory
brainstem responses are remarkably reliable and consistent
across multiple assessments and are indicative of peripheral
and central auditory function [30, 31, 56-59]. Click-evoked
brainstem responses have been utilized as measures of
peripheral hearing and central auditory function since the
mid 1970s [30, 31]. Auditory brainstem responses to clicks
have highly regular morphologies and response peak timing
reflecting distinct neural generators. Because click responses
are so highly regular, deviations in response peak timing of
fractions of a millisecond are clinically meaningful. Abnormal response morphology or interpeak timing can be indicative of auditory pathway tumors or neural dysfunction
such as neuropathy or demyelination due to multiple
sclerosis [30]. The response to click stimuli also adapts to
changes in stimulus level in characteristic ways, making
these responses useful for assessing hearing thresholds in
infants and those who are unable to respond to traditional
audiometric testing [31]. The pattern of peak timing in
response to decreasing stimulus level is indicative of the type
and magnitude of hearing loss or central nervous system
dysfunction [60]. For example, timing (latencies) outside
normal limits for all presentation levels indicate a conductive
hearing loss, while latencies outside normal limits only for
lower stimulus levels indicate sensorineural hearing loss
[60]. Absence of response peaks at any level may reflect
neural dysfunction such as a tumor or profound sensorineural
hearing loss [30]. Importantly, auditory brainstem responses
are collected passively and are objective measures free of the
attentional, motivational, and alertness factors that may
complicate behavioral assessments of auditory function.
Speech-evoked brainstem responses faithfully represent
many acoustic elements of the stimulus, including stimulus
timing, fine structure (harmonics), and the fundamental frequency (pitch; see Fig. (1) and [33] for a review). The
fundamental frequency of the stimulus and its lower
harmonics are represented through neural phaselocking, with
harmonics above the phaselocking limits of the brainstem,
approximately 1200 Hz, likely reflected in response timing
[18, 61-63]. As with click-evoked responses, deviations in
response timing of fractions of milliseconds may indicate a
peripheral hearing impairment. Additionally, for children
with normal hearing thresholds and click-evoked responses,
deviations in response timing can differentiate poor readers
from good readers [17]. While the click-evoked response is
mature by approximately age 3 [31, 60], the speech-evoked
brainstem response does not appear to be mature until
approximately age 5 [57]. Both click and speech-evoked
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Hornickel and Kraus
Fig. (1). Brainstem responses to speech sounds faithfully represent stimulus timing, pitch, and harmonics. A) The stimulus [da], shifted in
time for visual purposes to reflect the neural conduction lag. B) The auditory brainstem response to [da] visually mimics the waveform of the
stimulus in absolute timing as well as in periodicity. The portion of the response enlarged in the bottom panel is marked with black lines.
Stimulus timing, pitch, and harmonics are preserved in the response, with pitch and harmonic representation best revealed in the frequency
spectrum of the response (bottom right).
responses are extremely reliable and replicable across multiple test sessions [30, 31, 56-59].
In children with normal peripheral hearing (as assessed
by an audiogram and click-evoked brainstem responses), the
speech-evoked brainstem response can be predictive of
speech-in-noise perception and reading ability. Recent
analytical modeling revealed that reading and speech-innoise perception have largely independent neural correlates,
but are both related to certain neural measures [32]. While
reading impairments and auditory processing disorders are
often co-occurring, we will focus our discussion on the
neural correlates of speech-in-noise perception as poor
understanding of speech in noisy backgrounds is a hallmark
characteristic of auditory processing impairments.
Representation of Vocal Pitch
Successful speech-in-noise perception relies on the
ability to isolate and track a target voice in a complex
auditory environment [64, 65]. Many cues enable the listener
to distinguish and follow one voice from others, including
spatial location, loudness, temporal continuity, vocal quality,
and linguistic content of the message [64, 66]. One cue,
vocal pitch, may be especially important [66]. Increasing the
difference in fundamental frequency (an important element
for the perception of pitch, [67]) between two competing
speech streams makes the target stream more salient and
distinguishable from a competitor or when in the presence of
background noise [68-70]. Because vocal pitch is an
important cue for isolating and following a target speech
stream in background noise, we hypothesized that brainstem
encoding of the fundamental frequency of speech sounds
would be related to speech-in-noise perception. Children
with poor speech-in-noise perception do indeed have weaker
representation of the fundamental frequency than children
with good speech-in-noise perception, see Fig. (2A) [21].
Speech-in-noise perception was assessed with the Hearing In
Noise Test [71] and children were grouped based on their
performance when the speech and the background noise
came from the same spatial location, i.e., when pitch cues
might be the most beneficial for perceiving the target speech
over the background noise [21]. The same effect was found
for young adults when responses were recorded to speech
stimuli presented in noise, with poor speech-in-noise
perceivers having weaker representation of the fundamental
frequency than good speech-in-noise perceivers in increasing
background noise [56]. In both studies these differences
were largest for the response to the formant transition
portion of the syllable [da], which represents the most
acoustically complex and time-varying portion of the signal
that is vulnerable to misperception in noisy listening conditions [1, 2]. Importantly, good and poor speech-in-noise
perception groups were equated on IQ, audiometric
threshold, and click-evoked brainstem responses [21], and
speech-evoked brainstem representation of the fundamental
frequency and audiometric threshold were not correlated
[56]. The absence of differences in peripheral hearing indi-
Assessment and Management of Auditory Processing Disorder
cates that speech-in-noise perception is linked to aspects of
auditory function that are independent of hearing sensitivity.
Studies of speech-in-noise perception in adults further
support the notion that speech-in-noise perception deficits
can occur independently of peripheral hearing impairment
[49, 72]. Deficits in impaired auditory working memory and
attention can contribute to impairments in speech-in-noise
perception in older adults with normal hearing [49, 64, 72].
If successful speech-in-noise perception relies on identifying
and tracking one voice in competing background noise, then
simple perception of the voice of interest is not sufficient.
Instead, the linguistic message must be followed and
understood over time, likely relying on auditory working
memory. Adult musicians, who could be considered auditory
experts, have better speech-in-noise perception and better
auditory working memory than non-musicians, with both
groups having normal audiometric hearing [73]. While
musicians show enhanced auditory working memory and
speech-in-noise perception, children with poor auditory
processing appear to have weaker auditory working memory
skills. A large-scale assessment of auditory processing skills
in school-aged children found that inconsistent performance
on the auditory processing tasks, which the authors suggest
is reflective of poor auditory attention, correlated with parent
reports of speech-in-noise perception [74]. As stated above,
many symptoms of auditory processing disorder and attention deficit disorder are similar [50], however deficits were
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only found for auditory processing and not visual, highlighting that the impairments were modality specific and not
a global attention deficit. Given these links, it is likely that
children with poor speech-in-noise perception have impaired
auditory working memory and additionally auditory brainstem dysfunction (e.g., weaker encoding of the fundamental
frequency), again highlighting the interplay between
cognitive and sensory functions indicative of central auditory
processing disorders.
Pattern Detection
A key aspect of utilizing signal-specific cues for speechin-noise perception is the ability to identify an acoustic
element as a continuous and meaningful signal, in other
words, the ability to detect patterns in the acoustic environment. We have found that neural representation of lower
speech harmonics, those important for the perception of
pitch, is enhanced when the syllable [da] is presented in a
predictable (repetitive) sequence relative to when it is presented intermixed with seven other speech stimuli occurring
randomly [19]. We suggest that the nervous system is able to
benefit from the predictability of a stimulus by increasing the
representation of repeating acoustic elements, which may aid
in isolating and locking on to one voice in competing noise
[19]. This effect is also seen in adults in response to musical
notes, where the response to the whole musical phrase is
improved over the course of the recording and the response
Fig. (2). Speech-in-noise perception is dependent on pitch representation and pattern detection, both aspects important for tracking one target
voice over time. A) Good speech-in-noise (SIN) perceivers (black) have more robust encoding of the fundamental frequency of the speech
sound [da] presented in quiet than poor SIN perceivers (red). Strength of fundamental frequency encoding is correlated with speech-in-noise
perception across the whole group. *Note, the y-axis has been inverted to be more cohesive with the lower panel. The direction of good and
poor SIN perception is marked. B) Brainstem representation of pitch-related harmonics is enhanced when the [da] stimulus is presented in a
Predictable condition (gray) relative to a Variable condition (black). The degree of enhancement with repetition is correlated with SIN
perception and absent in poor readers. The direction of good and poor SIN perception is marked.
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to the second note of a repeated sequence shows even greater
enhancement with repetition [75]. In children, the degree of
benefit from repetition correlates with speech-in-noise performance, with better speech-in-noise perceivers showing the
greatest benefit from repetition, see Fig. (2B) [19]. Children
with poor reading ability showed no benefit from repetition
[19]. Previous studies of sound perception and discrimination in children with dyslexia suggest that they are unable to
lock onto and benefit from repetition of sounds to be used as
standards in the listening tasks, suggesting they are unable to
form “perceptual anchors” [76]. Theories of language learning suggest that young children are able to utilize the
regularities and patterns of speech in their environment to
determine which speech sounds are meaningful in their
language [77-79]. The inability to identify patterns in the
environment could affect early language learning, the
creation of sound-to-meaning relationships, and lead to impaired speech-in-noise perception. In support of this theory,
children with language impairments are unable to make use
of patterns in their auditory environment when learning a
pseudo-language [16], suggesting that pattern detection
mechanisms can continue to be impaired throughout
childhood.
Timing Degradation in Noise
The degree to which neural timing is degraded by background noise is also predictive of speech-in-noise perception.
Young children, and those with reading impairments, are
Hornickel and Kraus
more adversely affected by increasing background noise than
older children and adults [10, 11, 80-83]. The increased
susceptibility of these populations to the degrading effects of
background noise is reflected by subcortical neural responses; the auditory system responds less robustly to speech
presented in background noise because the signal characteristics of the evoking stimulus are degraded. Auditory
brainstem responses are reduced in amplitude and also
delayed in time when stimuli are presented in background
noise [84]. Good and poor speech-in-noise perceiving
children have the same timing of response peaks when
speech is presented in quiet but the response timing delay
when speech is presented in background noise is much larger
for the poor speech-in-noise perceivers than the good
perceivers, see Fig. (3A) [20]. Along with pitch and spatial
location cues, temporal cues are important for auditory
stream segmentation [64, 66], and greater degradation of
response timing in noise may lead to impaired processing of
temporal cues in noise [20]. Adult musicians, who were
noted above to have better speech-in-noise perception than
non-musicians, additionally have more robust brainstem
responses to speech presented in background noise [36].
That the neural encoding of speech is malleable with lifelong musical training suggests that auditory-based training
may alleviate neural encoding deficits associated with
impaired speech-in-noise perception (more on this premise
below).
Fig. (3). Response timing reflects resistance to degradation in noise and differentiation of contrastive speech sounds, both linked to speechin-noise skills. A) Responses to [da] presented in noise (black) are delayed relative to responses to [da] in quiet (gray). Poor SIN perceivers
(red) have greater timing delays with the addition of noise than good SIN perceivers (black). B) Brainstem representations of [ga] (green),
[da] (red), and [ba] (blue) syllables follow and expected timing pattern that reflects the differing formant frequencies among the stimuli.
Good SIN perceivers (black) have significantly greater timing differences among the three responses, indicating better brainstem
differentiation, than poor SIN perceivers (red).
Assessment and Management of Auditory Processing Disorder
Timing to Represent Harmonic Differences
Stop consonants (such as ba, da, and ga) are notoriously
difficult to perceive in background noise because they are
comprised of rapid frequency changes and transient elements
[1, 2, 85]. The formant transition between a stop consonant
and a following vowel includes frequency sweeps of many
hundred Hertz (Hz) occurring over a fraction of a second
[85]. The exact configuration of formants defines which consonant and vowel are being produced. The ability of the
nervous system to fully represent formant-related harmonics
is crucial for the correct perception of consonants and, as a
result, the verbal message [86]. Although the auditory
brainstem is able to represent frequency content (such as the
lower harmonics discussed above) through phase-locking,
this method of representation is limited to ~1200 Hz [61,
62]. Higher frequency content, such as that corresponding to
most speech formants, occurs above the phaselocking limits
of the brainstem and appears to be encoded through response
timing [18, 63]. Responses to [ga] occur earlier than
responses to [da], which in turn occur earlier than responses
to [ba], reflecting the descending formant frequencies among
the three stimuli [18, 63]. Importantly, the presence and
magnitude of this latency pattern among responses correlates
with speech-in-noise perception [18]. Good speech-in-noise
perceivers have greater subcortical differentiation of these
three stimuli as reflected by greater timing differences
among responses to the three syllables, see Fig. (3B) [18].
Besides verbal content being another cue that may be used
for tracking one target voice over time in background noise
[64], the ability to understand the content of the message is
obviously crucial for successful speech-in-noise perception
and communication. Stream segmentation skills are useless
if comprehension of the verbal message is impaired.
In sum, converging evidence indicates that speech-innoise perception depends on the ability of the nervous
system to isolate and track a target voice in competing
background noise (using various cues such as vocal pitch
and tempo), robustly represent target sounds in the presence
of background noise, and faithfully represent acoustic
elements important for the comprehension of the verbal
message. Importantly, these nervous system functions can be
measured objectively and reliably in humans.
AUDITORY PROCESSING AND READING ABILITY
Children with learning and language disorders can have
impaired speech-in-noise perception relative to their
typically-developing peers and perform poorly on a number
of psychophysical tests of auditory perception [10-15].
Additionally, auditory processing skills and speech-in-noise
perception in young children are predictive of later scholastic
achievement [87-89]. One might hypothesize that the neural
correlates of reading overlap with those of speech-in-noise
perception and that some children with reading impairments
could qualify as having auditory processing disorders based
on behavioral and neural measures. That both hypotheses are
supported by recent results highlights the complex relationship between auditory function and reading ability. The neural measures reflecting pattern detection, timing degradation
in noise, and timing to represent harmonics discussed above
are also related to reading ability [18-20], and recent ana-
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257
lytical modeling of the neural correlates of reading and
speech-in-noise perception found that measures of pattern
detection significantly predicted variance in both reading and
speech-in-noise skills in a group of children with a wide
range of reading abilities [32]. Additionally, reading disorders and auditory processing disorders often co-occur [23,
25, 90]. Of a cohort of children with suspected auditory
processing disorders, almost 50% of children had additional
impairments in reading or language functions [90]. In a
similar study of children with developmental dyslexia, all
children performed poorly on at least one measure of auditory processing and 70% were classified as having auditory
processing disorders (performance at least 2 standard deviations below the mean on two or more tests; [23]). The
remaining 30% had impaired brainstem encoding of the stop
consonant [da], suggesting that neural responses to speech
may identify children with auditory processing impairments
who have been missed by behavioral assessments [23]. This
highlights the potential impact of brainstem responses to
speech in the assessment and management of children with
communication disorders.
UTILITY OF BIOLOGICAL MEASURES
As discussed above, behavioral measures of auditory
processing and hearing thresholds are unable to provide
information about the biological nature of observed
impairments. Speech-evoked brainstem measures do yield
biological correlates of performance on certain language and
listening tasks. Importantly, they target the auditory pathway
as a site of dysfunction contributing to the presenting complaint. The specific aspect of impaired speech-evoked
brainstem activity, such as encoding of the fundamental
frequency, harmonic encoding and/or pattern processing
discussed above, yields considerable insight into the
biological nature of the auditory deficit. Moreover, objective
physiological measures sidestep some of the factors that can
limit behavioral assessments such as attention, alertness,
motivation, and comorbid language or reading impairments.
Survey measures used as screening tools are subjective, and
adult evaluations of a child’s auditory processing skills may
not truly reflect his/her auditory processing ability and risk
for APD [91]. Evoked auditory brainstem responses, on the
other hand, are objective and passively elicited. Speechevoked brainstem response measures are linked to speech-innoise perception, the child’s auditory experience, and may be
particularly reflective of auditory dysfunction, even in the
absence of poor performance on dichotic and diotic listening
tasks. Additionally, poor performance on behavioral measures may be corroborated or refuted by these neural
measures, which could serve as metric for ruling in or out
true auditory processing impairment as the cause of poor
behavioral performance. These objective, physiological
measures provide an additional viewpoint in the assessment
of auditory processing disorders and have the potential to
reveal underlying biological correlates of deficient auditory
processing. Because the auditory brainstem has been shown
to be malleable with life-long experience with sound [3439], as well as short-term auditory training [41-43], these
measures could be used to track training-related change in
neural function and, in conjunction with behavioral
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measures, best identify which children would benefit the
most from auditory training.
TRAINING-RELATED CHANGES IN AUDITORY
BRAINSTEM RESPONSES
While auditory brainstem responses are generally recorded during passive listening conditions, these responses
nonetheless reflect how sound has been used during a
lifetime. Auditory subcortical function is experience dependent; it is malleable through short-term and long-term
experience with sound [19, 34-47]. Numerous studies have
shown that musicians have enhanced brainstem responses
relative to non-musicians, likely due to their lifelong, multisensory interaction with music and the establishment of
sound-to-meaning relationships [34-36]. Musician-related
benefits are correlated with the starting age of musical
training and amount of practice at the time of testing [34, 35,
37], highlighting that benefits are seen only with active
interaction with meaningful sound. Similar effects are found
for life-long language experience. Speakers of tonal languages have more accurate brainstem encoding of meaningful
pitch contours in that language than non-tonal language
speakers; however, language-related benefits are not seen for
pitch contours that simply mimic the frequency change and
are not linguistically meaningful [38-40]. Additionally, animal studies have revealed rapid and long-lasting brainstem
neuroplasticity in response to behaviorally meaningful
stimuli [45-47]. These results suggest that neuroplasticity
arises from meaningful interaction with sound but not simply
from repeated exposure.
Neural changes can also be seen after short-term auditory
training for both adults and children with auditory or
language impairments. Adults with impaired speech-in-noise
perception who underwent targeted speech-in-noise training
showed greater efferent brainstem activity after training,
with auditory efferent activity before training predicting the
degree of improvement with training [43]. Children with
learning impairments who engaged in computer-based
auditory training games showed more robust brainstem
responses to speech presented in noise after completing the
training [41]. Similar improvements have been shown for
cortical responses to speech presented in noise, responses
reflecting attention to one speech stream over another, and
activity during reading-related tasks [29, 92-95]. Computerbased auditory training games can yield a number of benefits
in language and reading skills for children with a wide
variety of reading and language impairments, as well as for
children who are typically-developing [96-98]. Similarly,
enhanced auditory input of meaningful speech through a
classroom FM system can result in improvements in speechin-noise perception and classroom attention for children with
auditory processing disorders [99]. As discussed above, lifelong musical experience positively impacts auditory processing and neural function important for speech perception
[34-37] and evidence suggests that musical training in
children is linked to reading ability [100-102]. Active musical training may also serve as a particularly effective training
paradigm for children with poor auditory function that
affects communication skills [48, 103]. Thus, converging
evidence indicates that auditory training can enhance
Hornickel and Kraus
auditory function behaviorally and biologically in children
with auditory and learning impairments.
In all cases, training-related benefits are likely due to the
ability to relate sound to meaning. Although children show
improvement on language-related skills and in neural markers of directed attention, they do not necessarily improve on
the training games themselves [93, 96]. These results suggest
that auditory attention is a crucial element for engendering
training-related improvements. With improved auditory
attention, children learn to extract meaningful sound from
background noise, increasing the opportunity to establish
sound-to-meaning relationships. Animal studies have
revealed that brainstem plasticity is mediated by descending
modulation from the auditory cortex [45-47], and it is
possibly through auditory attention that cortical activity
influences brainstem function in humans. Therefore, children
with auditory processing impairments may benefit from
auditory training using computer-based games, assistive
listening devices, or experience with music through improvements in auditory attention and creation of sound-to-meaning
relationships. Due to its inherent stability yet malleability
with auditory experience and demonstrated link to cognitivelanguage skills (such as speech-in-noise perception), the
speech-evoked auditory brainstem response could be utilized
as a metric to assess training related change in auditory
function. Additionally, auditory brainstem responses before
training may be predictive of training-related gain, as was
demonstrated previously in adults [43].
CONCLUSIONS
Numerous studies have revealed that auditory processing
skills are crucial for successful language learning and later
academic achievement [3-15, 87-89]. Auditory processing
can be impaired in the absence of peripheral hearing loss and
in these cases central auditory dysfunction likely exists.
Multiple measures of the speech-evoked auditory brainstem
response are predictive of communication skills, such as
speech-in-noise perception and reading ability [17-24].
Beyond providing a biological dimension for assessing the
origin and nature of listening disorders, speech-evoked
responses add sensitivity to standard behavioral assessments.
Speech-evoked responses are objective, free of the subjectivity and inherent complications of behavioral tests, and
quick to measure. Coupled with the fundamental experiencedependence of the auditory system established through
decades of research on animal models [45-47, 104-106],
training-related improvements in auditory function in
humans suggest that children with auditory processing
disorders are likely to benefit from auditory training,
assistive listening devices, or musical experience [29, 41-43,
48, 92-95]. Through these meaningful experiences with
sound, auditory attention is increased, sound-to-meaning
relationships are developed, and children with auditory
processing impairments may show improvements in auditory
brainstem function due to cognitive-sensory interactions
common in the auditory system. As detailed in this review,
auditory brainstem function may serve as a key biological
indicator of auditory processing disorders, inform the aspects
of auditory processing that may be affected, suggest which
patients may be most likely to benefit from auditory training,
and provide a metric of improvement after remediation. The
Assessment and Management of Auditory Processing Disorder
reliability of responses within an individual in conjunction
with the tight links between auditory brainstem function and
cognitively-based communication skills recommend this
measure as an important addition to any APD testing battery.
Current Pediatric Reviews, 2011, Vol. 7, No. 3
[18]
[19]
CONFLICT OF INTEREST
The authors report no conflicts of interest, monetary or
otherwise.
ACKNOWLEDGEMENTS
We would like to thank Samira Anderson for her review
and critique of the manuscript. Work reviewed here was
supported by the National Science Foundation (BCS0921275) and the National Institutes of Health (DC010016).
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Accepted: May 20, 2011
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