Submitted:
12 August 2026
Posted:
18 August 2026
You are already at the latest version
Abstract
The following review is an integration and synthesis of a subset of the central auditory nervous system (CANS) and auditory processing (AP) literature of the last 25 years. It encompasses many different aspects of AP, and aims to contribute to an auditory neuroscience knowledgebase suitable for audiologists. ‘Nature’ enables the neonate to be born with an innate and immature auditory nervous system. It is then the turn of ‘nurture’ to play its part, with activity and experiences driving the development. An early ‘nurturing’ experience is when caregivers sing lullabies to infants, with this serving to enhance the fundamental amplitude modulation components that contribute to the formation of a linguistic brain. With the auditory cortical circuits, maturation is a prolonged process, and it is at least adolescence before they approach the precision of the adult brain. Throughout the course of maturation the CANS is constantly and continuously being remodelled, reflecting the dynamic, protracted and activity-dependent nature of most brain development. One consequence of the combination of a prolonged CANS maturation and the unique listening experiences of a childhood is that it is the norm for there to be individual differences in the AP capabilities of similar aged schoolchildren. Negative listening experiences during childhood may sometimes sufficiently hinder an individual's auditory system development to be the cause of listening difficulties. Such listening difficulties can be experienced by children even though the outcome of their standard hearing test is a ‘normal’ pure tone audiogram. Auditory training (AT) offers treatment for some, and equates to additional and intensive ‘nurturing’ of the CANS.
Keywords:
central auditory nervous system
; central auditory nervous system maturation
; auditory skill development
; auditory deprivation
; listening difficulties
; auditory training
; central auditory processing disorder
1. Introduction
Over the last two decades scientific articles and the clinical practice guidelines produced by audiology organizations have recommended that audiologists complete auditory neuroscience education before they undertake the evaluation and treatment of auditory processing (AP) dysfunction in children. More specifically, they must understand the anatomy, physiology and plasticity of the central auditory nervous system (CANS), and its prolonged maturation [1,2,3,4]. Here, the focus of this narrative review is the lengthy development of the CANS, the importance of enriched acoustic experiences throughout the years of its development, the related progressive acquisition of different AP skills, the possibility for the CANS to fail to reach a fully developed state or to lag maturationally compared to similar aged children, how listening difficulties can sometimes be the consequence of complications with CANS maturation, and finally, the role auditory training (AT) can potentially play in rectifying CANS immaturities through the exploitation of CANS plasticity. The review is an integration and synthesis of the last 25 years of the relevant CANS and AP literature and involved a comprehensive literature search across major electronic databases (e.g., PubMed, Europe PMC, Google Scholar), as well as the websites of multiple major audiology and speech-language organizations (e.g., American Speech-Language-Hearing Association, British Society of Audiology). The review encompasses many different aspects of AP, and aims to contribute to an auditory neuroscience knowledgebase suitable for audiologists.
‘Nature’ and its genetic programs guide the formation and the initial development of the human cortical neural networks, leading to the establishment of an innate and immature nervous system [5,6]. This process begins in utero, and by birth these networks have developed into simple and basic wiring plans [7]. ‘Nurture’ then takes over, development is now driven by activity and by experience, with the human brain becoming progressively more and more fine-tuned to its environment [8]. The maturation of the auditory system is prolonged, in some ways it never stops, and it is at least adolescence before the auditory cortical circuits begin to approach the precision of the adult brain [7].
2. The Need for the ‘Nurturing’ of the Auditory System
Hearing becomes functional in utero and this, when combined with prenatal and neonatal exposure to a rich acoustic environment, induces a rapid initial plasticity in the auditory system [9]. Infants are typically born with a full capacity to track voice pitch, with music exposure during pregnancy known to improve this capability [9]. During the first month of life, with acoustical stimulation, the encoding of the temporal fine structure of speech develops rapidly [9]. Ambient sound stimulation during postnatal development increases the activity of auditory axons and enhances myelin thickness [10]. Maturational plasticity leads to a continuous increase in white matter myelination, with the myelin ensuring fast and reliable conduction of action potentials along auditory axons [8]. Enriched experience with sound is fundamental and critical to auditory development [11], with auditory input acting as a biological driver of synaptic organization, dendritic arborization, and thalamocortical connectivity within the auditory pathways [12]. The absence of early and prolonged acoustic stimulation has the opposite effect; it delays neuronal maturation, reduces synaptic density, and can lead to atypical CANS development [6,12,13]. A complex acoustical environment shapes the development of auditory perception, including its functional properties and the connectivity of higher-order auditory areas [14], with auditory experience remaining a powerful influence on central function throughout an individual’s lifespan [15]. In-school music training has been shown to have the potential to alter the course of brain development, with adolescent pupils who received music training found to have an earlier emergence of adult cortical responses [16]. Enriched experience with sound is beneficial not just in the early years but also in adolescence, and then throughout life, as it is required to sustain the myelin along auditory circuitry [17].
3. The Prolonged Maturation of the CANS
While the peripheral auditory system is structurally and functionally ‘adult-like’ at birth, the CANS exhibits progressive anatomical and physiological changes until early adulthood [11,13,15,18,19,20,21,22,23,24]. By some measures the prolonged development is not complete until the late 20’s in females and around 30 years of age in males [25].
Auditory cortex (AC) synaptogenesis begins in the first two months after birth with maximum density between 4 and 12 months. This is then followed by a gradual reduction of neurons (known as pruning), with this reduction process heavily dependent upon environmental sound exposure [6]. Synaptic exuberance, subsequent pruning, and myelination events extend through childhood and into adolescence [26]. Changes continue in the patterns of connectivity, with neural circuitry continuously being remodelled, reflecting the dynamic, protracted and activity-dependent nature of brain development [27]. There are developmental ‘critical periods’, times during which specific environmental experiences are essential for the maturation of specific brain regions. Specific auditory experiences result in modifications to brain organization and function, with such changes occurring early in development. There are also developmental ‘sensitive periods’, during which the brain is ‘unusually responsive’ to a wide-range of auditory experiences. ‘Sensitive periods’ occur throughout brain development [25]. Two particular ‘sensitive’ times are the early postnatal years and then during adolescence [25]. The age-appropriate morphofunctional maturation of the CANS determines the normal trajectory of a child’s auditory and speech development [28]. CANS maturation develops in a ‘bottom-up’ direction as children age [28]. The cortical and subcortical auditory function maturation extends over two decades [29], with age-dependent AP abilities showing considerable variability between individuals [30,31].
4. CANS Maturation and the Timeline of AP Skills
Babies in utero are able to detect the melodic cadence of their mothers’ language [32]. At only a few weeks old, newborns are able to distinguish between ‘adult-directed’ and ‘infant-directed’ speech, and can analyze the rhythmic structure of sound sequences. Sensitivity to rhythm is a precursor to speech segmentation [33]. At birth, infants already encode pitch trends predictively [32]. They can differentiate between sounds and phonemes, and begin to learn categories of phonemes, and to group phonemes. This automaticity (an automatic, unconscious and cognitively efficient behaviour) means attentional resources are then available for other tasks, such as the learning of word meanings [34]. Infants in the first few months learn how to perceive a change in sound frequencies, with ‘adult-like’ performance attained between 6 and 12 months [19]. There is significant improvement in F1 neural encoding (an essential component of vowel recognition) during this time [35]. The maturation of the basic neural machinery necessary for efficient language learning is rapid and sustained through these early months [35]. There is a reduction in neural phase-locking onset to the sound stimulus envelope from birth to 6 months, with this stabilizing by 12 months [36]. Temporal fine structure encoding matures rapidly from birth to six months, and the first six months of life are of critical importance in the maturation of the neural encoding mechanisms needed for language discrimination [36]. Infants start becoming attuned to their natural language vowels at around 4 to 6 months of age, and to consonants at 8 to 10 months of age [37]. By 8 months infants are already using transitional probabilities of syllable pairs to segment continuous speech. Statistical learning (SL) enables pattern extraction (e.g., of an auditory or visual nature) present in the environment, and unconscious prediction processing modulates responses to sensory input from 6 months of age [32,38,39]. From an early age, infants employ ‘top-down’ mechanisms that seek adaptation to their experiences. As infants get exposed to and experiment with language, ‘top-down’ predictions are used to refine ‘bottom-up’ representations of linguistic input. The dramatic increase in linguistic abilities that are observable in typical developmental trajectories are linked to the amount, and to the quality of speech exposure (and especially to caregiver vocalizations) [32]. Children differ in their ability to learn statistically, according to their language proficiency [32]. During the childhood years, the CANS continues to mature structurally and functionally, enabling continuous and notable improvements in auditory performance [40]. Temporal resolution (TR) skills usually develop up to 6 or 7 years of age. While some children demonstrate ‘adult-like’ TR abilities as young as 5 years of age, individual differences in maturational trajectories can be substantial [31,41]. ‘Perceptual weighting shift’ (where children move away from using speech cues that are dynamic to those that are more static) occurs at around 7 years of age [42]. As well as conscious goals, prior experiences can influence auditory selective attention, with auditory selective attention requiring at least 7 years to mature [43,44]. When compared to older children, children between the ages of 7 and 9 years typically demonstrate a less consistent right ear advantage and greater variability in dichotic performance. These developmental trends are associated with the ongoing maturation of the corpus callosum [49]. Although the extraction of prosodic cues from ‘clear speech’ occurs relatively early, this capability in a multi-talker background continues to mature up to the age of 9 years. The extraction of the ‘subtle information’ provided by syllables is achieved at 9 years, but again, this skill in noisy backgrounds requires a few more years to become ‘adult-like’ [45]. Binaural integration (BI), the ability to process and combine the different information simultaneously arriving at the two ears, is a key auditory function that supports sound localization, as well as source segregation in the auditory scene [41]. While BI is present in newborns as young as 4 days old [41], the BI ability develops progressively throughout childhood, with significant changes occurring between the ages of 7 and 12 years [46]. Young children have high gap detection thresholds, with this threshold reducing between the ages of 7 and 12 years [41]. With respect to performance on auditory pattern recognition tasks, this typically improves steadily with age, reaching ‘adult-like’ accuracy levels by 11 to 12 years [40]. Temporal sequencing capability develops gradually until ‘adult-like’ performance is reached between the ages of 10 and 12 years. As with auditory detection and auditory discrimination abilities, auditory identification improves substantially with age, reaching ‘adult-like’ performance levels by the age of 10 to 12 years [41]. Children, even by the age of 14 years, are less sensitive to auditory modulation detection than adults [47]. Phonological categorization, monaural temporal resolution, and the ‘precedence effect’ (the ignoring of sound reflections) all remain immature until late-childhood [37,48]. Binaural resolution capability (i.e., ITD and ILD thresholds) only reaches maturity in late adolescence [46]. Auditory spatial processing (SP) skills mature throughout childhood. The maturation and the adaption of auditory cortical processing from childhood to adolescence enables the auditory system to maintain SP abilities [26,30]. Sound localization requires constant re-calibration as the gradually increasing size of the head, body, pinna and ear canal throughout childhood and adolescence modifies the primary sound localization cues (e.g., ITD and ILD) [41]. With auditory stream segregation there is a protracted development, with the automatic-driven and the attention-driven mechanisms underlying stream segregation having a progressive maturation that extends into early adulthood [49,50,51]. Children do not reach ‘adult-like’ speech recognition performance in noisy and reverberant environments until 14 to 15 years of age [52]. Reverberation typically exhibits consistent statistical properties which can be used to separate sound sources from their environments, but this requires prior experience of a particular environment and the internalization of its acoustical properties [53,54]. Such sets of statistics are learnt during childhood and throughout life.
Multi-sensory (MS) inputs (in this case audio and visual) need to be seamlessly integrated to form coherent perceptual representations [41,55,56]. Neurons in the neonate brain are not capable of MS integration, and the development of this process is not predetermined [57]. There is a gradual emergence of MS neurons, and early experience is critical to their development. Infants less than one month old have preferential reactions to MS stimuli, and by 12 months the temporal binding window is much reduced [58]. By adolescence it is a more visually dominant MS integration, with reactions to MS stimuli faster than reactions to uni-sensory stimuli [59]. When audio and visual inputs differ, vision plays a key role in aligning the audio and visual neural representations of space. Audio-visual (AV) spatial information integration has been observed in 5 year old children, immediate AV spatial recalibration emerges not before 6 to 7 years of age, while cumulative AV recalibration is typically only seen after 9 years of age [60]. MS integration is another experience-dependent process that tunes itself to the parameters of its environment over time [61]. Everyday life may not always be enough on its own to promote the ‘coupling’ of cross-modal cues. AV integration capabilities can however be rapidly developed through training in a clinical setting, using a single set of AV stimuli [62]. The development and plasticity of MS processes across the lifespan accommodate the physical characteristics (the statistics) of stimuli in the environment, as well as the dynamic reweighting between these stimulus characteristics, and the learned associations that shape MS processing [55].
5. Problems with the Maturation of the CANS
There are several different reasons why CANS maturation can be compromised. Many of these reasons relate to ‘nurturing’ (or lack of). As has been described above, enriched experience with sound is fundamental and critical to auditory development [11]. An individual that misses out on significant stimulation during childhood will suffer deleterious effects on the organization of the auditory pathways and cortex [18]. The effects could be limited to a maturational lag or to something more permanent. During the early developmental ‘critical periods’, impoverished experiences may result in irreversible changes in brain organization and function [25]. The period from 25 weeks’ gestation up to 6 months of age is critical to auditory brainstem maturation and this is likely to be negatively affected by a premature birth [4,18,21,22,63]. Inhibitory circuits serve to sharpen auditory responses to rapidly varying signals, and profound changes in the balance of inhibition and excitation naturally occur during early development. However, auditory deprivation during this period can disrupt the maturation of inhibition along the full lengths of the auditory pathways [64]. Ascending processes of the auditory nerve form progressively more branching synaptic endings, which eventually envelop the cell bodies of (bushy cell) neurons in the (anterior ventral) cochlear nucleus. Auditory deprivation during early development can cause profound morphological changes in the maturation of these contacts [64]. Degraded auditory signals result in dys-synchronized activity at the AC and negatively affect its maturation [65].
Cochlear Implant (CI) research has meant a greater understanding of some of the consequences of auditory deprivation. Without the early implantation of a CI the AC is at risk of recruitment from other sensory modalities, such as visual processing taking place in an auditory cortical area [6,66,67]. When bilaterally deaf individuals were fitted with a second CI (Left) several years after the fitting of their first CI (Right), it triggered a cortical re-organization. However, the result was an atypical left-hemispheric bias across both ears and not the contralateral-dominant activation observed in normal hearing individuals [68]. Those with single-sided deafness typically exhibit a symmetrical response between the bilateral auditory cortices (once again in contrast to the contralateral-dominant activation observed in normal hearing individuals) [67]. Continuing aural deprivation will eventually lead to a delay in CANS maturation, disrupt BI, reorganize the neural network, and change the synaptic transmission in the primary AC (or at lower levels of the auditory system) [69].
Otitis Media (OM) is a common cause of pediatric temporary conductive hearing loss, with a high persistence in approximately 10% of cases [70]. Compared to controls, children with a history of OM frequently show a poorer performance on most behavioral and electrophysiological tests [23,24,71]. Group differences have been shown with gap-in-noise test results, with frequency pattern test results, and with auditory brainstem response latencies. When retested after a period of several months, test scores can often be seen to be more like those of their unaffected (by OM) peers. However, lengthy and frequent conductive loss may sometimes lead to central impairments that persist after the peripheral loss has been resolved [65,72]. A recent study showed children with a history of early OM (when compared to children with no such history) demonstrating, perhaps surprisingly, enhanced neural coding and increased reliance on Working Memory (WM) when undertaking sentence-in-noise perception and digit-span WM tasks [73]. These cognitive adaptions appeared to enable test performance levels comparable to peers (without a history of OM) and they likely act as compensatory mechanisms [73].
Any form of asymmetric hearing loss degrades spatial hearing. Adaption following a partial hearing loss in one ear may be achieved by the learning of a new relationship between the altered spatial cues and directions in space. However, this neuroplastic adaption becomes a maladaption if it persists when normal hearing returns. Similarly, prolonged periods of hearing loss in one ear can lead to amblyaudia, where hearing has been fully restored, but the individual is unable to fully exploit the acoustical input of the once affected ear [74].
During adolescence, exposure to noise and sounds is a prerequisite for developing advanced AP skills (such as auditory scene analysis). Excessive avoidance of exposure to noise by using noise-cancelling headphones (or other forms of ‘over-protection’) could hinder, even impair the development of the auditory system [13,75,76]. Reverberation exhibits consistent statistical properties which can be used to separate sound sources from their environments [53], but lack of experience of a particular environment means the internalization of its acoustical properties does not take place [32]. Diminished auditory experience can compromise the myelination of auditory brainstem circuitry, or prevent this myelin from being maintained [17].
6. Delayed CANS Maturation and Listening Difficulties
A number of different explanations have been put forward over many years as to the reason why, in comparison to children of a similar age, a small percentage of children experience listening difficulties (such as hearing speech in background noise). This is despite a standard hearing test showing a normal pure tone audiogram [1,2,3,4,18,21,22,23,24,28,31,40,71,77,78,79,80,81,82,83,84,85,86,87,88,89]. Several scientific papers have proposed that ‘delayed maturity’ of the CANS is a likely underlying cause of such difficulties [2,22,77,89]. The prolonged CANS maturation timeline and the not insignificant variations between individual listening experiences during childhood, mean that it is inevitable that there are differences in AP maturation between children of a similar age [31,41]. The cortical auditory evoked potential (CAEP) P1 response is present at birth (occurring at around 300 milliseconds post-stimulation) with this decreasing systematically until adulthood (to approximately 60 milliseconds) [90]. The biphasic response of the CAEP P1-N1 complex is exhibited in infancy and gradually develops into the ‘adult-like’ multiphasic response in late adolescence. Both of these CAEP measured changes reflect the development/maturation of the CANS, including myelination and functional synaptic contact formation [26]. Such CAEP responses can be used to determine if auditory cortical developmental maturation is normal or delayed [90]. The P1 and other CAEP measures have frequently been used in auditory processing disorder (APD) and OM impact studies. A 2016 study using the CAEP early components found that children clinically diagnosed with an APD had significantly increased latencies and significantly reduced amplitudes compared to controls. These results were seen as “consistent with the immaturity of the CANS” being an underlying cause of APD in children, and consistent also with the description of childhood APD “as a neurodevelopmental disorder” [84]. The same CAEP P1-N1 complex has been used in the past for tracking the maturation of the CANS in children with a peripheral hearing impairment [90]. A 2019 study found the listening difficulties of children to be a “reflection of the overall development of the CANS”, with neural dysfunction (including slower processing) and neurocognitive dysfunction contributing to difficulties in the discrimination of both speech and non-speech sounds. Auditory middle latency responses (AMLR) and auditory P300 latency responses have both been found to be sensitive to listening difficulties [87]. Using auditory event-related potentials (AERP), a 2019 study found that children with APD had a maturational delay, an affected auditory pathway neuronal transmission, and they exhibited basic AP dysfunction. The AERP P1/P2 complex (an index of the encoding of acoustic sound features) and AERP N2 (which represents a synthesis of these features into a sensory representation) demonstrated slower responses in the children with APD when compared to controls [91]. A 2025 review described electrophysiological and imaging studies that had identified central auditory delays and white-matter changes in children with a history of OM. In many cases these problems were seen to normalize over time. CAEP measures (including P300) have been able to identify reduced amplitudes and increased latencies, indicating that OM impacts upon early sensory encoding and higher-order AP. The risk of residual AP problems was found to be dependent upon the extent of OM recurrence, the OM burden, and its timing relative to CANS development ‘sensitive’ periods [92]. An article in ‘The Hearing Review’ suggested that both a slower course of myelination and auditory deprivation can result in a CANS neuromaturational delay, and that children with APD display myelin abnormalities in multiple brain regions associated with AP [85]. The myelination of structures higher in the auditory pathway has a particularly protracted timeline, taking at least until adolescence [17,24]. Any form of hearing impairment (otitis media for example) jeopardizes myelin development along auditory brainstem circuitry, and in turn, CANS maturation [23]. A 2005 review paper included a maturationally delayed CANS as a cause of childhood APD [79], as did a 2015 paper [83]. A 2024 review paper found that some children show AP improvements over time, “indicating that there could have been a delay in the maturation of their AP abilities” [89]. Two APD articles (2001 and 2003) aimed primarily at audiologists, state that a delay in the maturation of the CANS can be responsible for childhood APD, and that when this is the case, the APD will sometimes resolve with time [77,78]. Likewise, an ‘AudiologyOnline’ course explains that many central auditory processing disorder (CAPD) cases are the result of a neurodevelopmental delay, and that this results in the delayed maturation of AP abilities [21]. This course (CAPD Fundamentals) is approved for ‘continuing education’ (CE) by multiple major audiology and speech-language organizations (such as AAA, ACAud, BAA, CAA, NZAS, SAC). Two further and more recent CE courses, one from ‘StatPearls’ [23] and a further course from ‘AudiologOnline’ [24], state that delayed CANS maturation is a likely cause of pediatric listening difficulties. The latter (Understanding CAPD and Treatment Recommendations) is approved for CE by the organizations listed above and additionally by ASHA. The ‘AAA Clinical Practice Guidelines for CAPD’, the ‘Canadian Guidelines for APD’, and the ‘New Zealand Guidelines for APD’ all describe a delayed neurological maturation of AP capabilities as a likely reason for a child’s listening difficulties [2,22,31]. Both the ‘ASHA CAPD (2005)’ document [1] and the current online ‘ASHA CAPD Practice Portal (2026)’ advise that “Knowledge of the neuroanatomy and physiology of the CANS is essential for understanding & interpreting the underlying processes and deficits”, and that CAPD involves “deficits in the neural processing of auditory information in the CANS” [4]. The only major audiology organization not linking APD with the CANS is the BSA. In their ‘white paper’ the ‘BSA APD (2013) Special Interest Group (SIG)’ describe a developmental APD as when a child has listening difficulties, but has “normal audiometry with no other known etiology”, and also that this has been “presumably present from birth” [82] (p11). Members of the same BSA SIG contributed to an APD article (2016) aimed at audiologists which stated that it is “inappropriate to assume that the CANS is the site of problems underlying APD” [3]. The subsequent ‘BSA Practice Guidance: Auditory Processing Disorder’ document (2018) stated that “evidence suggests APD may be due to language and other cognitive processing” [86]. The current online ‘ASHA CAPD Practice Portal (2026)’ does recognise that there are some who suggest that an APD diagnosis may in fact “indicate a broader language-based disorder” [4]. A 2003 study concluded that “auditory deficits appear not to be causally related to language disorders, but only occur in association with them” [93]. More recently, through the use of several different neurophysiological procedures, AP dysfunction has been shown to have a definite causal role in language disorders [94,95,96,97]. These objective procedures offer to capture the neural responses to sound and speech, enable infants as well as young children to be tested, and enable the discovery of dysfunction likely to result in a future language disorder [96]. The automatic alignment of brain rhythms with the rhythm patterns of speech being listened to, is critical for the acquisition of language. With children who have developmental language disorder (DLD) this unconscious alignment process was found to be atypical [96].
‘Infant-directed’ speech and the rhythmic singing of lullabies to young infants are common to many cultures. Both can enhance the fundamental amplitude modulation components that contribute to building a linguistic brain. This is a good example of how timely acoustic experience provides essential ‘nurturing’ of the auditory system [94,97].
7. Delayed CANS Maturation and Auditory Training
Auditory training (AT) programs typically provide a structured set of repetitive listening exercises that are designed to enhance specific auditory skills [24]. They can be used to accelerate the normal maturational process when CANS immaturities are found [84]. AT exploits the plasticity of the CANS, and equates to additional and intensive ‘nurturing’ [2,21,22,23,24,31,80,83,84,92,98]. An AT review (2020) concluded that training (in combination with hearing aids) enhances auditory rehabilitation [99], whilst a more recent review found that a majority of AT protocols examined promoted improvements in auditory performance [100]. A 2022 study concerning individuals with Neurofibromatosis (Type 1) found post-AT improvements in the performance of the central auditory system, evidence of a reorganization of neural pathways, and changes that were maintained over at least 4 months [101]. A series of studies with young adults (2024) showed that AT was responsible for improved: speech-in-noise scores, encoding of pitch-related cues, neural synchrony, and response latencies. These improvements were not seen in control groups, and were retained six months later [102]. A study using ferrets (2025) found AT elicited widespread alterations in the cortical representation of complex sounds [103]. An AT review (2019) concerned with pediatric CI recipients found post-AT performance improvements in the trained tasks in all of the reviewed studies. Evidence for the transfer of improvements to other domains and the retention of benefits over time was found, but only a small number of the reviewed studies included the testing required to collect this data [104]. Another study with CI recipients (2024) found speech understanding in noise scores improved for those given AT, improvements that were not seen with the control group [105]. A 2026 study involving children with a CI was able to show post-training improvements in auditory pitch discrimination performance [106]. A significant improvement in SP ability was found with children who had previously been diagnosed with SP disorder and then undertook LiSN & Learn AT. This improvement was not seen with those children who received a different type of AT (Earobics) [107]. In a study involving children with amblyaudia, AT was found to improve interaural asymmetries. Greater ear symmetry is thought to be achieved through increased inhibition (in dominant pathways), as well as the maturation and myelination of the auditory pathway (including portions of the corpus callosum) [108].
The AT studies described above mostly used a combination of behavioral and electrophysiological tests to measure AT outcomes. The evidence for AT is not unequivocal, with some questioning its utility. In particular it is criticised for being near-transfer (rather than far-transfer), as the training often fails to generalize to broader, more ecologically relevant outcomes [92]. Others have raised questions about the utility of decontextualized auditory interventions for school-aged children [109]. In contrast, a recent review described AT as a “cornerstone of rehabilitation“ and offering significant benefits [98]. The current online ‘ASHA CAPD Practice Portal (2026)’ appears to be neutral on this subject, stating “some clinicians support direct skills remediation” while “others have provided scrutiny” [4].
8. Concluding Remarks
By the time of birth, ‘nature’ has enabled a CANS that equates to a simple, basic and immature wiring plan [7]. A prolonged ‘nurturing’ phase then begins. Using rhythmic speech with young infants enhances the fundamental amplitude modulation components that contribute to building a linguistic brain [96]. Throughout childhood and adolescence a continuing enriched experience with sound remains fundamental and critical to auditory system development [11]. The enriched experience shapes functional properties and the connectivity of the higher-order auditory areas [14]. Along this lengthy developmental pathway are ‘critical periods’, when specific environmental experiences are required for the maturation of specific brain regions, and in which impoverished experiences have the potential to cause irreversible changes in brain organization and function [25]. During the childhood years, with continuing acoustic stimulation, the CANS matures both structurally and functionally, thereby enabling continuous and notable improvements in auditory performance [40]. While some develop considerably earlier, several AP skills only become ‘adult-like’ with adulthood [20]. Audio-vision (MS) integration is also an experience-dependent process that tunes itself to the parameters of its environment over time [58]. Statistical learning enables the extraction of sound signal patterns present in the environment and the subsequent unconscious predictive processing [39]. Throughout the course of maturation the auditory neural circuitry is continuously being remodelled, reflecting the dynamic, protracted and activity-dependent nature of most brain development [27]. A consequence of the lengthy CANS maturation timeline, combined with the large variations between childhood listening experiences, is that it is inevitable for there to be individual differences in AP development between children of a similar age [31,41]. Negative listening experiences may sufficiently hinder auditory system maturation to be the cause of an individual’s listening difficulties [11,65,69,72]. Such difficulties can be experienced by children and adolescents despite standard hearing test results showing a ‘normal’ pure tone audiogram. AT offers intervention possibilities, exploits the plasticity of the CANS, and equates to additional and intensive ‘nurturing’ [83,84,92,98]. Neurophysiological procedures offer the potential to identify AP dysfunction in infants that predict future language difficulties [96].
Here, the literature review of the CANS and AP literature has facilitated an examination of the critical role played by acoustical stimulation during the development of the CANS, the timeline of the maturation of the CANS and the associated development of auditory skills, and how listening difficulties can be the consequence of AP maturation differences between children of a similar age. It encompasses many different aspects of AP and aims to contribute to an auditory neuroscience knowledgebase suitable for audiologists.
With all narrative reviews author judgements bring a potential for bias. However, it has enabled coverage of a broader range of AP skills than is the norm in similar literature, and a combining of fragmented findings into a cohesive story. These include findings concerning predictive processing, statistical learning, the precedence effect, the rhythmic alignment of auditory processing with a speech stream, and audio-visual processing.
9. Future Directions
The ‘nurturing’ of the CANS requires further investigation, in particular what constitutes effective and efficient auditory training/therapy for the attainment of AP skills, for enhancing immature auditory skills, and for the recovery of lost auditory skills. Also of particular interest is the infant found using neurophysiological procedures to have AP dysfunction that predicts a future language disorder, and the subsequent ‘nurturing’ that can prevent this future outcome [96]. Most training improvements need to be far-transfer and not near-transfer, and for this the AT requires ecologically valid tasks [92].
Funding
This research received no external funding.
Institutional Review Board Statement
Not applicable.
Data Availability Statement
No new data were created.
Conflicts of Interest
The author declares no conflicts of interest.
Abbreviations
The following abbreviations are used in this manuscript:
| AC | Auditory Cortex |
| AP | Auditory Processing |
| AT | Auditory Training |
| AV | Audio-Visual |
| BI | Binaural Integration |
| CANS | Central Auditory Nervous System |
| CI | Cochlear Implant |
| ILD | Interaural Level Difference |
| ITD | Interaural Time Difference |
| OM | Otitis Media |
| SP | Spatial Processing |
| AAA | American Academy of Audiology |
| ACAud | Australian College of Audiology |
| ASHA | American Speech-Language-Hearing Association |
| BAA | British Academy of Audiology |
| BSA | British Society of Audiology |
| CAA | Canadian Academy of Audiology |
| NZAS | New Zealand Audiological Society |
| SAC | Speech-Language & Audiology Canada |
References
- (Central) Auditory Processing Disorders; Technical Report; American Speech-Language-Hearing Association, 2005.
- Diagnosis, Treatment and Management of Children and Adults with Central Auditory Processing Disorder; Clinical practice guidelines; American Academy of Audiology, 2010.
- Moore, D. R. What’s New in Auditory Processing? ENT Audiol. News 2016, 23. [Google Scholar]
- American Speech-Language-Hearing Association - Central Auditory Processing Disorder. Available online: https://www.asha.org/practice-portal/clinical-topics/central-auditory-processing-disorder/?srsltid=AfmBOopFoNRDffc_wMi2SilxsR9aKSwMfOxWXlWMTS5FGNMls5OBVYOX (accessed on 2026-08-01).
- Xu, W.; Löwel, S.; Schlüter, O. M. Silent Synapse-Based Mechanisms of Critical Period Plasticity. Front. Cell. Neurosci. 2020, 14, 213. [Google Scholar] [CrossRef] [PubMed]
- Fliegelman, J. What Role Does Age-Associated Neuroplasticity Play in the Efficacy of Cochlear Implantation? Sci. J. Lander Coll. Arts Sci. 2020, 14(1), 14–21. [Google Scholar]
- Shatz, C. J. Dynamic Interplay between Nature and Nurture in Brain Wiring. annuaire-cdf 2012, 111, 894–896. [Google Scholar] [CrossRef]
- Schneider, P.; Engelmann, D.; Groß, C.; Bernhofs, V.; Hofmann, E.; Christiner, M.; Benner, J.; Bücher, S.; Ludwig, A.; Serrallach, B. L.; Zeidler, B. M.; Turker, S.; Parncutt, R.; Seither-Preisler, A. Neuroanatomical Disposition, Natural Development, and Training-Induced Plasticity of the Human Auditory System from Childhood to Adulthood: A 12-Year Study in Musicians and Nonmusicians. J. Neurosci. 2023, 43(37), 6430–6446. [Google Scholar] [CrossRef] [PubMed]
- Escera, C. Contributions of the Subcortical Auditory System to Predictive Coding and the Neural Encoding of Speech. Curr. Opin. Behav. Sci. 2023, 54, 101324. [Google Scholar] [CrossRef]
- Stancu, M.; Wohlfrom, H.; Heß, M.; Grothe, B.; Leibold, C.; Kopp-Scheinpflug, C. Ambient Sound Stimulation Tunes Axonal Conduction Velocity by Regulating Radial Growth of Myelin on an Individual, Axon-by-Axon Basis. Proc. Natl. Acad. Sci. U.S.A. 2024, 121(11), e2316439121. [Google Scholar] [CrossRef] [PubMed]
- Jutras, B.; Lagacé, J.; Koravand, A. The Development of Auditory Functions. In Handbook of Clinical Neurology; Elsevier, 2020; Vol. 173, pp. 143–155. [Google Scholar] [CrossRef] [PubMed]
- Tumuklu, K.; Gunsoy, B. Early Auditory Stimulation, Not Device Type: Comparable Cortical Maturation in Children Using Cochlear Implants or Hearing Aids. Children 2026, 13(5), 657. [Google Scholar] [CrossRef] [PubMed]
- Kulawiak, P. R. Academic Benefits of Wearing Noise-Cancelling Headphones during Class for Typically Developing Students and Students with Special Needs: A Scoping Review. Cogent Educ. 2021, 8(1), 1957530. [Google Scholar] [CrossRef]
- Moseley, S. M.; Meliza, C. D. A Complex Acoustical Environment During Development Enhances Auditory Perception and Coding Efficiency in the Zebra Finch. J. Neurosci. 2025, 45(7), e1269242024. [Google Scholar] [CrossRef] [PubMed]
- Moore, D. R. Auditory Development and the Role of Experience. Br. Med. Bull. 2002, 63(1), 171–181. [Google Scholar] [CrossRef] [PubMed]
- Tierney, A. T.; Krizman, J.; Kraus, N. Music Training Alters the Course of Adolescent Auditory Development. Proc. Natl. Acad. Sci. U.S.A. 2015, 112(32), 10062–10067. [Google Scholar] [CrossRef] [PubMed]
- Long, P.; Wan, G.; Roberts, M. T.; Corfas, G. Myelin Development, Plasticity, and Pathology in the Auditory System. Dev. Neurobiol. 2018, 78(2), 80–92. [Google Scholar] [CrossRef] [PubMed]
- Bamiou, D.-E. Aetiology and Clinical Presentations of Auditory Processing Disorders---a Review. Arch. Dis. Child. 2001, 85(5), 361–365. [Google Scholar] [CrossRef] [PubMed]
- Litovsky, R. Development of the Auditory System. In Handbook of Clinical Neurology; Elsevier, 2015; Vol. 129, pp. 55–72. [Google Scholar] [CrossRef] [PubMed]
- Fitzroy, A. B.; Krizman, J.; Tierney, A.; Agouridou, M.; Kraus, N. Longitudinal Maturation of Auditory Cortical Function during Adolescence. Front. Hum. Neurosci. 2015, 9. [Google Scholar] [CrossRef] [PubMed]
- Chermak, G. AudiologyOnline. 20Q: CAPD - Fundamentals 17765. 2016. Available online: https://www.audiologyonline.com/articles/20q-capd-fundamentals-17765 (accessed on 2026-08-01).
- Keith, W.; Purdy, S.; Baily, M.; Kay, F. New Zealand Guidelines on Auditory Processing Disorder; New Zealand Audiological Society, 2019. [Google Scholar]
- Aristidou, I. L.; Hohman, M. H. Central Auditory Processing Disorder. In StatPearls [Internet]; StatPearls Publishing: Treasure Island (FL), 1 Mar 2023; Available online: https://www.ncbi.nlm.nih.gov/books/NBK587357/ (accessed on 2026-08-01).
- Mongelli, J. AudiologyOnline. Understanding Central Auditory Processing Disorder and Treatment Recommendations 29400. Available online: https://www.audiologyonline.com/articles/understanding-central-auditory-processing-disorder-29400 (accessed on 2026-08-01).
- Kolb, B. Critical and Sensitive Periods in Brain Development. In Oxford Research Encyclopedia of Psychology; 2025. [Google Scholar]
- Wang, X.; Nie, S.; Wen, Y.; Zhao, Z.; Li, J.; Wang, N.; Zhang, J. Age-Related Differences in Auditory Spatial Processing Revealed by Acoustic Change Complex. Front. Hum. Neurosci. 2024, 18, 1342931. [Google Scholar] [CrossRef] [PubMed]
- Jernigan, T. L.; Stiles, J. Construction of the Human Forebrain. WIRES Cogn. Sci. 2017, 8(1–2), e1409. [Google Scholar] [CrossRef] [PubMed]
- Savenko, I. V.; Garbaruk, E. S.; Boboshko, M. Yu. Рsychoacoustic Testing to Assess the Functional Maturation of the Central Audiotory System. Sensornye Sist. 2023, 37(4), 348–362. [Google Scholar] [CrossRef]
- Krizman, J.; Tierney, A.; Fitzroy, A. B.; Skoe, E.; Amar, J.; Kraus, N. Continued Maturation of Auditory Brainstem Function during Adolescence: A Longitudinal Approach. Clin. Neurophysiol. 2015, 126(12), 2348–2355. [Google Scholar] [CrossRef] [PubMed]
- Kühnle, S.; Ludwig, A. A.; Meuret, S.; Küttner, C.; Witte, C.; Scholbach, J.; Fuchs, M.; Rübsamen, R. Development of Auditory Localization Accuracy and Auditory Spatial Discrimination in Children and Adolescents. Audiol. Neurotol. 2013, 18(1), 48–62. [Google Scholar] [CrossRef] [PubMed]
- Canadian Guidelines on Auditory Processing Disorder in Children and Adults: Assessment and Intervention; CISG-SLPA, 2012.
- Ramacciotti, M. C. C. RECENTS ADVANCES IN NEUROBIOLOGICAL DOMAINS: STATISTICAL LEARNING AND PREDICTIVE PROCESSING FOR LANGUAGE. 2026. [Google Scholar] [CrossRef]
- Kujala, T.; Partanen, E.; Virtala, P.; Winkler, I. Prerequisites of Language Acquisition in the Newborn Brain. Trends Neurosci. 2023, 46(9), 726–737. [Google Scholar] [CrossRef] [PubMed]
- Kujala, T. Revealing Speech Perception in the Newborn Brain with the Means of Mismatch Negativity. aasf 2025, No. 1, 28–41. [Google Scholar] [CrossRef]
- Ribas-Prats, T.; Cordero, G.; Lip-Sosa, D. L.; Arenillas-Alcón, S.; Costa-Faidella, J.; Gómez-Roig, M. D.; Escera, C. Developmental Trajectory of the Frequency-Following Response During the First 6 Months of Life. J. Speech Lang. Hear Res. 2023, 66(12), 4785–4800. [Google Scholar] [CrossRef] [PubMed]
- Puertollano, M.; Ribas-Prats, T.; Gorina-Careta, N.; Ijjou-Kadiri, S.; Arenillas-Alcón, S.; Mondéjar-Segovia, A.; Dolores Gómez-Roig, M.; Escera, C. Longitudinal Trajectories of the Neural Encoding Mechanisms of Speech-Sound Features during the First Year of Life. Brain Lang. 2024, 258, 105474. [Google Scholar] [CrossRef] [PubMed]
- Hegde, M.; Nazzi, T.; Cabrera, L. An Auditory Perspective on Phonological Development in Infancy. Front. Psychol. 2024, 14, 1321311. [Google Scholar] [CrossRef] [PubMed]
- Rapaport, H.; Seymour, R. A.; Benikos, N.; He, W.; Pellicano, E.; Brock, J.; Sowman, P. F. Investigating Predictive Coding in Younger and Older Children Using MEG and a Multi-Feature Auditory Oddball Paradigm. Cereb. Cortex 2023, 33(12), 7489–7499. [Google Scholar] [CrossRef] [PubMed]
- Maravall, M.; De Hoz, L. Setting the Stage for Statistical Learning? Sensitivity to Environmental Statistics in Early Sensory Processing. Curr. Opin. Neurobiol. 2025, 95, 103139. [Google Scholar] [CrossRef] [PubMed]
- Khavarghazalani, B.; Heidari, A.; Emadi, M.; Shahtaheri, S. M. M. Age-Dependent Maturation of Central Auditory Processing Skills in School-Aged Children: A Multi-Domain Behavioral Study. Int. J. Pediatr. Otorhinolaryngol. 2025, 198, 112565. [Google Scholar] [CrossRef] [PubMed]
- Russo, N.; Cascio, C. J.; Baranek, G. T.; Woynaroski, T. G.; Williams, Z. J.; Green, S. A.; Schaaf, R.; Autism Sensory Research Consortium. A Cascading Effects Model of Early Sensory Development in Autism. Psychol. Rev. 2026, 133(2), 450–487. [Google Scholar] [CrossRef] [PubMed]
- Leibold, L. J.; Buss, E. Masked Speech Recognition in School-Age Children. Front. Psychol. 2019, 10, 1981. [Google Scholar] [CrossRef] [PubMed]
- Jones, P. R.; Moore, D. R.; Amitay, S. Development of Auditory Selective Attention: Why Children Struggle to Hear in Noisy Environments. Dev. Psychol. 2015, 51(3), 353–369. [Google Scholar] [CrossRef] [PubMed]
- Addleman, D. A.; Jiang, Y. V. Experience-Driven Auditory Attention. Trends Cogn. Sci. 2019, 23(11), 927–937. [Google Scholar] [CrossRef] [PubMed]
- Bertels, J.; Niesen, M.; Destoky, F.; Coolen, T.; Vander Ghinst, M.; Wens, V.; Rovai, A.; Trotta, N.; Baart, M.; Molinaro, N.; De Tiège, X.; Bourguignon, M. Neurodevelopmental Oscillatory Basis of Speech Processing in Noise. Dev. Cogn. Neurosci. 2023, 59, 101181. [Google Scholar] [CrossRef] [PubMed]
- Syeda, A.; Nisha, K. V.; Jain, C. Age Differences in Binaural and Working Memory Abilities in School-Going Children. Int. J. Pediatr. Otorhinolaryngol. 2023, 171, 111652. [Google Scholar] [CrossRef] [PubMed]
- Yuvaraj, P.; Chacko, K. S.; Roy, R.; Abubacker, R.; Rajasekaran, A. K. Does Binaural Stimulation Enhance Temporal Processing in Young Children? Cureus 2023. [Google Scholar] [CrossRef] [PubMed]
- Litovsky, R. Y.; Godar, S. P. Difference in Precedence Effect between Children and Adults Signifies Development of Sound Localization Abilities in Complex Listening Tasks. J. Acoust. Soc. Am. 2010, 128(4), 1979–1991. [Google Scholar] [CrossRef] [PubMed]
- Calcus, A. Development of Auditory Scene Analysis: A Mini-Review. Front. Hum. Neurosci. 2024, 18, 1352247. [Google Scholar] [CrossRef] [PubMed]
- Benocci, E.; Calcus, A. Stream Segregation, Musical Abilities, and the Development of Speech Perception in Noise. JASA Express Lett. 2024, 4(12), 124401. [Google Scholar] [CrossRef] [PubMed]
- Benocci, E.; Alain, C.; Calcus, A. Neural Signatures of Stream Segregation from Childhood to Adulthood. Sci. Rep. 2026, 16(1), 16977. [Google Scholar] [CrossRef] [PubMed]
- Wróblewski, M.; Lewis, D. E.; Valente, D. L.; Stelmachowicz, P. G. Effects of Reverberation on Speech Recognition in Stationary and Modulated Noise by School-Aged Children and Young Adults. Ear Hear. 2012, 33(6), 731–744. [Google Scholar] [CrossRef] [PubMed]
- Traer, J.; McDermott, J. H. Statistics of Natural Reverberation Enable Perceptual Separation of Sound and Space. Proc. Natl. Acad. Sci. U.S.A. 2016, 113(48). [Google Scholar] [CrossRef] [PubMed]
- Willmore, B. D. B.; King, A. J. Adaptation in Auditory Processing. Physiol. Rev. 2023, 103(2), 1025–1058. [Google Scholar] [CrossRef] [PubMed]
- Murray, M. M.; Lewkowicz, D. J.; Amedi, A.; Wallace, M. T. Multisensory Processes: A Balancing Act across the Lifespan. Trends Neurosci. 2016, 39(8), 567–579. [Google Scholar] [CrossRef] [PubMed]
- McCormick, C. A. The Importance of Sensory Experiences for Young Children; California State University: Sacramento, USA, 2022. [Google Scholar]
- Stein, B. E.; Stanford, T. R.; Rowland, B. A. Development of Multisensory Integration from the Perspective of the Individual Neuron. Nat. Rev. Neurosci. 2014, 15(8), 520–535. [Google Scholar] [CrossRef] [PubMed]
- Choi, I.; Demir, I.; Oh, S.; Lee, S.-H. Multisensory Integration in the Mammalian Brain: Diversity and Flexibility in Health and Disease. Philos. Trans. R. Soc. B 2023, 378(1886), 20220338. [Google Scholar] [CrossRef] [PubMed]
- Lewkowicz, D. J.; Bremner, A. J. Chapter 4—The Development of Multisensory Processes for Perceiving the Environment and the Self. In Multisensory Perception; Academic Press, 2020; pp. 89–112. [Google Scholar]
- Hillock-Dunn, A.; Wallace, M. T. Developmental Changes in the Multisensory Temporal Binding Window Persist into Adolescence. Dev. Sci. 2012, 15(5), 688–696. [Google Scholar] [CrossRef] [PubMed]
- Vannasing, P.; Dionne-Dostie, E.; Tremblay, J.; Paquette, N.; Collignon, O.; Gallagher, A. Electrophysiological Responses of Audiovisual Integration from Infancy to Adulthood. Brain Cogn. 2024, 178, 106180. [Google Scholar] [CrossRef] [PubMed]
- Xu, J.; Yu, L.; Rowland, B. A.; Stein, B. E. The Normal Environment Delays the Development of Multisensory Integration. Sci. Rep. 2017, 7(1), 4772. [Google Scholar] [CrossRef] [PubMed]
- Van Dommelen, P.; De Graaff-Korf, K.; Verkerk, P. H.; Van Straaten, H. L. M. Maturation of the Auditory System in Normal-Hearing Newborns with a Very or Extremely Premature Birth. Pediatr. Neonatol. 2020, 61(5), 529–533. [Google Scholar] [CrossRef] [PubMed]
- Persic, D.; Thomas, M. E.; Pelekanos, V.; Ryugo, D. K.; Takesian, A. E.; Krumbholz, K.; Pyott, S. J. Regulation of Auditory Plasticity during Critical Periods and Following Hearing Loss. Hear. Res. 2020, 397, 107976. [Google Scholar] [CrossRef] [PubMed]
- Borges, L. R.; Sanfins, M. D.; Donadon, C.; Tomlin, D.; Colella-Santos, M. F. Long-Term Effect of Middle Ear Disease on Temporal Processing and P300 in Two Different Populations of Children. PLoS ONE 2020, 15(5), e0232839. [Google Scholar] [CrossRef] [PubMed]
- Kral, A.; Sharma, A. Crossmodal Plasticity in Hearing Loss. Trends Neurosci. 2023, 46(5), 377–393. [Google Scholar] [CrossRef] [PubMed]
- Qiao, Y.; Yang, J.; Zhu, M.; Liu, Q.; Long, Y.; Ke, H.; Cai, C.; Shang, Y. Concurrent Compensation for Auditory and Visual Processing in Individuals With Single-Sided Deafness. Ear Hear. 2025, 46(5), 1210–1221. [Google Scholar] [CrossRef] [PubMed]
- Anderson, C. A.; Cushing, S. L.; Papsin, B. C.; Gordon, K. A. Cortical Imbalance Following Delayed Restoration of Bilateral Hearing in Deaf Adolescents. Hum. Brain Mapp. 2022, 43(12), 3662–3679. [Google Scholar] [CrossRef] [PubMed]
- Chen, Z.; Yuan, W. Central Plasticity and Dysfunction Elicited by Aural Deprivation in the Critical Period. Front. Neural Circuits 2015, 9. [Google Scholar] [CrossRef] [PubMed]
- Gyawali, B. R.; Kharel, S.; Giri, S.; Ghimire, A.; Prabhu, P. Impact of Otitis Media With Effusion in Early Age on Auditory Processing Abilities in Children: A Systematic Review and Meta-Analysis. Ear Nose Throat J. 2024, 01455613241241868. [Google Scholar] [CrossRef] [PubMed]
- Konopka, A. K.; Kasprzyk, A.; Pyttel, J.; Chmielik, L. P.; Niedzielski, A. Etiology, Diagnostic, and Rehabilitative Methods for Children with Central Auditory Processing Disorders—A Scoping Review. Audiol. Res. 2024, 14(4), 736–746. [Google Scholar] [CrossRef] [PubMed]
- Moore, D. R.; Hartley, D. E. H.; Hogan, S. C. M. Effects of Otitis Media with Effusion (OME) on Central Auditory Function. Int. J. Pediatr. Otorhinolaryngol. 2003, 67, S63–S67. [Google Scholar] [CrossRef] [PubMed]
- Khalaila-Zbidat, A.; Gordin, A.; Karawani, H. Effects of Early Childhood Otitis Media–Related Conductive Hearing Loss on Speech Perception, Neural Processing, and Working Memory. Hear. Res. 2026, 471, 109540. [Google Scholar] [CrossRef] [PubMed]
- Keating, P.; King, A. J. Developmental Plasticity of Spatial Hearing Following Asymmetric Hearing Loss: Context-Dependent Cue Integration and Its Clinical Implications. Front. Syst. Neurosci. 2013, 7. [Google Scholar] [CrossRef] [PubMed]
- Carter, H. Hearing Practitioner Australia. Hearing Diagnostics study suggests headphones may change the way young people hear and localise sound. 2025. Available online: https://hearingpractitionernews.com.au/hearing-diagnostics-study-suggests-headphones-may-change-the-way-young-people-hear-and-localise-sound/ (accessed on 2026-08-01).
- Hewitt, D. ENT & Audiology News. Does the overuse of noise-cancelling headphones cause APD? 2025. Available online: https://www.entandaudiologynews.com/features/audiology-features/post/does-the-overuse-of-noise-cancelling-headphones-cause-apd (accessed on 2026-08-01).
- Chermak, G. D. Auditory Processing Disorder: An Overview for the Clinician. Hear. J. 2001, 54(7), 10–25. [Google Scholar] [CrossRef]
- Bellis, T. J. Auditory Processing Disorders: It’s Not Just Kids Who Have Them. Hear. J. 2003, 56(5), 10–19. [Google Scholar] [CrossRef]
- Matson, A. Central Auditory Processing: A Current Literature Review and Summary of Interviews with Researchers on Controversial Issues Related to Auditory Processing Disorders. In Independent Studies and Capstones; 2005. [Google Scholar]
- An Overview of Current Management of Auditory Processing Disorder (APD); Practice Guidance; British Society of Audiology, 2011.
- Auditory Processing Disorder (APD); Position statement; British Society of Audiology, 2011.
- Moore, D. R.; Rosen, S.; Bamiou, D.-E.; Campbell, N. G.; Sirimanna, T. Evolving Concepts of Developmental Auditory Processing Disorder (APD): A British Society of Audiology APD Special Interest Group ‘White Paper. Int. J. Audiol. 2013, 52(1), 3–13. [Google Scholar] [CrossRef] [PubMed]
- Weihing, J.; Chermak, G.; Musiek, F. Auditory Training for Central Auditory Processing Disorder. Semin Hear 2015, 36(04), 199–215. [Google Scholar] [CrossRef] [PubMed]
- Tomlin, D.; Rance, G. Maturation of the Central Auditory Nervous System in Children with Auditory Processing Disorder. Semin Hear 2016, 37(01), 074–083. [Google Scholar] [CrossRef] [PubMed]
- Chermak, G. D.; Musiek, F. E.; Weihing, J. Beyond Controversies: The Science behind Central Auditory Processing Disorder. Hear Rev. 2017, 24. [Google Scholar]
- Moore, D.; Campbell, N.; Rosen, S.; Bamiou, D. E.; Sirimanna, T.; Grant, P.; Wakeham, K. Auditory Processing Disorder (APD); Position Statement & Practice Guidance; British Society of Audiology, 2018. [Google Scholar]
- Mattsson, T. S.; Lind, O.; Follestad, T.; Grøndahl, K.; Wilson, W.; Nicholas, J.; Nordgård, S.; Andersson, S. Electrophysiological Characteristics in Children with Listening Difficulties, with or without Auditory Processing Disorder. Int. J. Audiol. 2019, 58(11), 704–716. [Google Scholar] [CrossRef] [PubMed]
- Madruga-Rimoli, C. C.; Sanfins, M. D.; Skarżyński, P. H.; Ubiali, T.; Skarżyńska, M. B.; Colella Dos Santos, M. F. Electrophysiological Testing for an Auditory Processing Disorder and Reading Performance in 54 School Students Aged Between 8 and 12 Years. Med. Sci. Monit. 2023, 29. [Google Scholar] [CrossRef] [PubMed]
- Bigras, J.; Lagacé, J.; El Mawazini, A.; Lessard-Dostie, H. Interventions for School-Aged Children with Auditory Processing Disorder: A Scoping Review. Healthcare 2024, 12(12), 1161. [Google Scholar] [CrossRef] [PubMed]
- Sharma, A.; Click, H. Cortical Neuroplasticity in Hearing Loss: Why It Matters in Clinical Decision Making for Children and Adults. In Hear Rev.; MEDQOR, 2018; pp. 20–24. [Google Scholar]
- Morlet, T.; Nagao, K.; Greenwood, L. A.; Cardinale, R. M.; Gaffney, R. G.; Riegner, T. Auditory Event-Related Potentials and Function of the Medial Olivocochlear Efferent System in Children with Auditory Processing Disorders. Int. J. Audiol. 2019, 58(4), 213–223. [Google Scholar] [CrossRef] [PubMed]
- Khavarghazalani, B.; Emadi, M.; Heidari, A.; Nahrani, M. H.; Amini, S. Neurobiological Insights into Central Auditory Processing Dysfunction Following Early-Life Otitis Media. Brain Res. Bull. 2025, 232, 111593. [Google Scholar] [CrossRef] [PubMed]
- Rosen, S. Auditory Processing in Dyslexia and Specific Language Impairment: Is There a Deficit? What Is Its Nature? Does It Explain Anything? J. Phon. 2003, 31(3–4), 509–527. [Google Scholar] [CrossRef]
- Keshavarzi, M.; Richards, S.; Feltham, G.; Parvez, L.; Goswami, U. Neural Processing of Rhythmic Speech by Children with Developmental Language Disorder (DLD): An EEG Study. Imaging Neurosci. 2024, 2, imag–2–00382. [Google Scholar] [CrossRef] [PubMed]
- White-Schwoch, T.; Woodruff Carr, K.; Thompson, E. C.; Anderson, S.; Nicol, T.; Bradlow, A. R.; Zecker, S. G.; Kraus, N. Auditory Processing in Noise: A Preschool Biomarker for Literacy. PLoS Biol. 2015, 13(7), e1002196. [Google Scholar] [CrossRef] [PubMed]
- Wong, P. C. M.; Lai, C. M.; Chan, P. H. Y.; Leung, T. F.; Lam, H. S.; Feng, G.; Maggu, A. R.; Novitskiy, N. Neural Speech Encoding in Infancy Predicts Future Language and Communication Difficulties. Am. J. Speech Lang. Pathol. 2021, 30(5), 2241–2250. [Google Scholar] [CrossRef] [PubMed]
- Goswami, U. Language Acquisition and Speech Rhythm Patterns: An Auditory Neuroscience Perspective. R. Soc. Open sci. 2022, 9(7), 211855. [Google Scholar] [CrossRef] [PubMed]
- Cuda, D.; Mancini, P.; Chiarella, G.; Santarelli, R. Retrocochlear Auditory Dysfunctions (RADs) and Their Treatment: A Narrative Review. Audiol. Res. 2025, 16(1), 5. [Google Scholar] [CrossRef] [PubMed]
- Stropahl, M.; Besser, J.; Launer, S. Auditory Training Supports Auditory Rehabilitation: A State-of-the-Art Review. Ear Hear. 2020, 41(4), 697–704. [Google Scholar] [CrossRef] [PubMed]
- Silva, S. D. A.; Araújo, L. D. S.; Lima, D. O.; Rosa, M. R. D. D. The Use of Technology in the Rehabilitation of Central Auditory Processing Disorder: A Scoping Review. Audiol. Commun. Res. 2025, 30, e2987. [Google Scholar] [CrossRef]
- Fontanelli, R.; Aragão, M.; Pinho, R.; Gil, D. IMPROVEMENT IN PERFORMANCE OF THE CENTRAL AUDITORY SYSTEM IN TYPE 1 NEUROFIBROMATOSIS. J. Hear Sci. 2022, 12(3), 22–32. [Google Scholar] [CrossRef]
- Skoe, E.; Kraus, N. Neural Delays in Processing Speech in Background Noise Minimized after Short-Term Auditory Training. Biology 2024, 13(7), 509. [Google Scholar] [CrossRef] [PubMed]
- Atilgan, H.; Walker, K. M.; King, A. J.; Schnupp, J. W.; Bizley, J. K. Auditory Training Alters the Cortical Representation of Complex Sounds. J. Neurosci. 2025, 45(18), e0989242025. [Google Scholar] [CrossRef] [PubMed]
- Rayes, H.; Al-Malky, G.; Vickers, D. Systematic Review of Auditory Training in Pediatric Cochlear Implant Recipients. J. Speech Lang. Hear Res. 2019, 62(5), 1574–1593. [Google Scholar] [CrossRef] [PubMed]
- Lloret, G.; Vincent, C.; Risoud, M.; Beck, C.; Lemesre, P. E.; Renard, C.; André, J.; Toulemonde, P. Evaluation of a Personalized Auditory-Cognitive Training on the Improvement of Speech Understanding in Noise in Cochlear Implanted Patients. Cochlear Implant. Int. 2024, 25(6), 467–476. [Google Scholar] [CrossRef] [PubMed]
- Cameron, S.; Glyde, H.; Dillon, H. Efficacy of the LiSN & Learn Auditory Training Software: Randomized Blinded Controlled Study. Audiol. Res. 2012, 2(1), e15. [Google Scholar] [CrossRef] [PubMed]
- Gulli, A.; Geronazzo, M.; Fontana, F.; Järveläinen, H.; Muzzi, E.; Rebesco, R.; Orzan, E. Pitch Training for Children with Cochlear Implants: Negotiating Clinical Validity through Mobile Game-Based Design. Int. J. Child-Comput. Interact. 2026, 48, 100823. [Google Scholar] [CrossRef]
- Moncrieff, D.; Schmithorst, V. Behavioral and Cortical Activation Changes in Children Following Auditory Training for Dichotic Deficits. Brain Sci. 2024, 14(2), 183. [Google Scholar] [CrossRef] [PubMed]
- DeBonis, D. A. It Is Time to Rethink Central Auditory Processing Disorder Protocols for School-Aged Children. Am. J. Audiol. 2015, 24(2), 124–136. [Google Scholar] [CrossRef] [PubMed]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2026 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.