J Audiol Otol Search

CLOSE


J Audiol Otol > Volume 30(3); 2026 > Article
Uzut: Age-Dependent Auditory Plasticity: Critical Periods in Subcortical and Cortical Encoding

Abstract

Auditory plasticity refers to the capacity of the auditory system to reorganize in response to experience and represents a fundamental feature of neural development. This scoping review synthesizes evidence on age-dependent plasticity at both subcortical and cortical levels, with a particular emphasis on critical and sensitive periods. A systematic search of PubMed/MEDLINE, Scopus, and Web of Science databases (1963-2025) was conducted in accordance with the PRISMA-ScR guidelines. A total of 2,437 records were screened, of which 78 studies were included in the review. Data were analyzed using thematic synthesis. Four major contributions are presented: 1) an appraisal of methodological limitations; 2) the Graded Windows Model (GWM), a conceptual framework proposing that plasticity may be organized as overlapping and interacting windows along the auditory neuraxis; 3) five testable hypotheses; and 4) clinical recommendations graded based on evidence level and study type. Human and animal evidence were distinguished. The traditional dichotomy that the brainstem matures early, whereas cortical plasticity persists later, may represent an oversimplification. Auditory plasticity appears to involve graded and hierarchically organized windows. Overall, this framework may inform the intervention timing and help prevent maladaptive plasticity.

Introduction

The auditory system is a remarkably adaptive neural network capable of adjusting its response properties to the demands of the acoustic environment. From the cochlear nucleus (CN) to the primary auditory cortex, neurons at every level of the hierarchy exhibit plastic change capacity: modifications in synaptic strength, receptor composition, and network connectivity alter how sounds are encoded and represented in the brain. This phenomenon, termed auditory plasticity, is not uniformly distributed across the lifespan; instead, it shows a striking age dependence, with periods of heightened flexibility known as critical periods and sensitive periods [1,2]. The concept of critical periods was first established in the visual system by Hubel and Wiesel [3], and subsequent research extended this framework to the auditory modality [4,5]. The distinction between critical and sensitive periods is important both theoretically and clinically [6,7]. For the purposes of this review, these terms are defined as follows. A critical period refers to a strictly time-limited developmental window during which specific neural circuits are highly susceptible to environmental input; disruption during this window produces lasting, largely irreversible consequences [1,2]. A sensitive period refers to a broader, more graded window of heightened plasticity that may be modulated by experience but does not carry the same sharp boundaries or obligatory consequences as a critical period [6,7]. The term plasticity window is used throughout this review as a general, inclusive term encompassing both critical and sensitive periods across any level of the auditory neuraxis. These distinctions are maintained consistently throughout the manuscript.
Increasing evidence challenges the assumption that subcortical auditory structures mature rapidly and then remain static. Auditory brainstem response (ABR) and complex ABR (cABR) studies have shown that brainstem development extends well beyond the age of two years [8,9]. At the cortical level, the molecular mechanisms governing critical period timing are becoming increasingly well characterized: maturation of parvalbumin-expressing (PV+) interneurons, formation of perineuronal nets (PNNs), the Lynx1 protein, and neuromodulatory regulation are among the key players [1,10,11].
A significant limitation of the current literature is that subcortical and cortical plasticity have been largely investigated within independent research traditions. Brainstem studies employ ABR-based electrophysiological paradigms, while cortical studies rely on optogenetics, chemogenetics, and single-nucleus RNA sequencing. This methodological dissociation makes it difficult to understand the interaction between the two levels. This scoping review aims to bridge this gap by proposing an integrative model.
This scoping review aims to present a unified account of age-dependent auditory plasticity by integrating findings from animal and human research. It is organized around five main themes: 1) literature search methodology, 2) subcortical plasticity mechanisms and timelines, 3) cortical critical period regulation, 4) an integrative model with testable hypotheses, and 5) translational clinical implications. To facilitate clarity, the manuscript is intentionally structured around three conceptually distinct components. The first component—comprising the sections on Lifelong Subcortical Auditory Plasticity, Critical Periods in the Auditory Cortex, and Subcortical- Cortical Plasticity Interaction—provides an empirical synthesis of the included literature, organized by neuraxis level. The second component—the Proposed Model: Graded Plasticity Windows—presents the Graded Windows Model (GWM) as a theoretical integrative framework derived from, but not directly validated by, the reviewed evidence; it should be read as hypothesis-generating rather than conclusive. The third component—Clinical Implications and Recommendations—translates the synthesized evidence into clinical guidance, explicitly graded by evidence level and evidence type. These components are conceptually distinct but interrelated; each can be read and cited on its own terms.

Methods

This scoping review was conducted in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guideline [12].

Search strategy

A systematic search was performed in PubMed/MEDLINE, Scopus, and Web of Science databases for the period January 1963 to December 2025. The lower date boundary was chosen to capture foundational work on critical periods originating with Hubel and Wiesel [3], while the upper boundary ensured inclusion of the most recent molecular and clinical evidence. Searches were conducted independently in each database using the following search string, applied consistently across all three platforms: (“auditory plasticity” OR “critical period” OR “sensitive period”) AND (“subcortical” OR “brainstem” OR “inferior colliculus” OR “medial geniculate” OR “cortical” OR “auditory cortex”) AND (“age” OR “development” OR “aging” OR “maturation”). In PubMed/MEDLINE, search terms were additionally mapped to Medical Subject Headings (MeSH) where available; free-text searching was used in parallel to maximize retrieval sensitivity. No language filter was applied at the database search stage. Reference lists of all included articles were additionally hand-searched to identify relevant studies not captured by the electronic search alone.

Inclusion and exclusion criteria

Inclusion criteria were: 1) experimental or review studies examining auditory plasticity at subcortical and/or cortical levels; 2) studies directly addressing age-dependent changes, critical periods, or sensitive periods in the auditory system; 3) peer-reviewed articles published in English. Exclusion criteria were: 1) studies addressing only peripheral hearing loss at the cochlear level without examining central auditory consequences; 2) studies focused exclusively on other sensory modalities (e.g., visual, somatosensory) with no generalization to the auditory system; 3) case reports, editorials, conference abstracts, and letters to the editor; 4) non-English language publications. Studies using visual or somatosensory models were retained when they provided direct mechanistic evidence applicable to auditory critical period regulation (e.g., PNN biology, excitatory/inhibitory [E/I] balance).

Screening process and data synthesis

A total of 3,128 records were retrieved across the three databases. Duplicate removal was performed using reference management software (Zotero v6.0; Corporation for Digital Scholarship), with automated detection supplemented by manual verification, yielding 2,437 unique records. All 2,437 records underwent title and abstract screening against the inclusion and exclusion criteria, after which 312 full texts were retrieved for detailed assessment. Of these 312 full texts, 234 were excluded for the following reasons: focused exclusively on peripheral cochlear pathology without addressing central plasticity (n=89); non-auditory sensory modality with no generalization to auditory system (n=54); case reports, editorials, or conference proceedings (n= 47); insufficient data on age-dependent or critical/sensitive period plasticity (n=31); non-English language (n=13). This yielded 78 studies meeting all inclusion criteria (Fig. 1). Of these, 31 examined subcortical plasticity primarily, 29 examined cortical critical periods primarily, and 18 investigated both levels or clinical applications. All 78 included studies informed the thematic synthesis; a representative subset is directly cited in the narrative text, while the complete set of included studies, organized by developmental stage and auditory neuraxis level, is presented in Supplementary Table 1 (in the online-only Data Supplement). Data charting was performed by a single reviewer (S.E.U.) using a standardized extraction form. Each included study was coded for: 1) level of investigation (subcortical/cortical/both); 2) species model (human/ rodent/non-human primate/mixed); 3) primary methodology (electrophysiology/molecular/imaging/behavioral/clinical/review); 4) age group or developmental stage examined; and 5) main finding relevant to auditory plasticity. Thematic synthesis was used to integrate findings across studies, with themes generated inductively from the data and then organized according to the GWM principles.

Bibliographic profile of included studies

A descriptive bibliographic profile of the 78 included studies revealed several notable patterns. The field has grown rapidly over the past two decades, with 50% of included studies (n=39) published between 2010 and 2019 and a marked shift from descriptive phenomenology toward molecular and mechanistic investigation. Rodent models predominated (45%, n=35), while human studies accounted for 35% (n=27), highlighting an important translational gap. Electrophysiological recordings were the most common primary method (42%, n=33), and the proportion of longitudinal designs was notably low (n=8, 10%), representing a key methodological limitation. Publications were concentrated in basic neuroscience journals (the Journal of Neuroscience alone contributed 21.8%), with relatively limited representation in clinical audiology outlets.

Lifelong Subcortical Auditory Plasticity

Note on species comparisons: evidence reviewed in this section derives from both human electrophysiological studies (primarily ABR and cABR recordings) and rodent experimental models. Because the auditory brainstem develops on substantially different timescales across species—rat hearing onset occurs at approximately postnatal day (P) 10–12, whereas human auditory brainstem responses are detectable from the third trimester of gestation—direct numerical equivalences between postnatal rodent days and human ages should be interpreted with caution. The species model for each cited study is indicated; conclusions are qualified accordingly, and rodent-derived timelines are not assumed to translate directly to human clinical contexts.

Developmental trajectory of the auditory brainstem

The traditional view holds that ABR properties reach adultlike maturity within the first two postnatal years [13]. This long-standing view was substantially revised by the landmark study of Skoe, et al. [9], who recorded ABR to both click and speech stimuli in 586 normal-hearing individuals. Their findings suggest that developmental changes extend well beyond 2 years of age, that a pronounced developmental “overshoot” period may exist between ages 5–11, and that different response components follow independent developmental trajectories. This finding suggests that the brainstem may not be a monolithic structure but rather an assembly of functionally specialized circuits developing along independent timelines.
However, the cross-sectional design of Skoe, et al. [9] limits causal inferences; longitudinal data are needed. The scarcity of data from the 1–2 year age range prevents complete mapping of developmental transitions. Future studies should prioritize longitudinal designs and source localization methods.

Experience-dependent plasticity in the brainstem

Johnson, et al. [8] provided pioneering evidence for brainstem plasticity in humans. While click-evoked responses were identical across age groups, speech-evoked responses in the 3–4 year group showed delayed latencies and reduced synchronization. Musical training is one of the most comprehensively studied models: Skoe and Kraus [14] showed that musicians exhibit enhanced brainstem responses during childhood and in advanced age. Chandrasekaran and colleagues’ [15,16] integrative model proposes continuous modulation of brainstem encoding through corticofugal predictive coding. Self-selection bias remains a critical issue in music studies; the observed neural differences may reflect genetic predispositions rather than training effects. Randomized controlled trials (RCTs) are necessary [17].

Age-related decline and homeostatic plasticity

Aging triggers significant changes in subcortical processing beyond peripheral loss. Caspary, et al. [18] reported progressive decline of GABAergic/glycinergic inhibition from the CN to the inferior colliculus (IC) and cortex. GABAA and glycine receptor subunit shifts reduce functional inhibition. Parthasarathy and Bartlett [19] reported that the relationship between ABR wave amplitudes and frequency-following responses changes asymmetrically in aged rats, pointing to possible alterations in central gain mechanisms. Anderson, et al. [20] showed that short-term auditory training may partially reverse neural timing delays in older adults. Whether age-related central changes result from chronological aging or cumulative peripheral deafferentation remains unresolved. Turrigiano’s [21] homeostatic plasticity framework provides an important conceptual foundation, but its auditory system-specific validation is limited.

Critical Periods in the Auditory Cortex

Note on species comparisons: the majority of mechanistic evidence on auditory cortical critical periods derives from rodent models, primarily rats and mice. Unless otherwise indicated, timelines expressed in postnatal days (P) refer to rodent data. Human cortical auditory development follows a substantially more prolonged trajectory; the human auditory cortex exhibits a more complex laminar architecture and is embedded in a richer experiential context than any currently available rodent model. While core molecular mechanisms such as E/I balance regulation, PNN formation, and Lynx1-mediated closure may be conserved across species, quantitative timelines and functional equivalences remain largely unvalidated in humans. Where human data are available, these are explicitly identified and distinguished from animal findings.

Tonotopic critical period

Barkat, et al. [4] showed in mice that tone exposure altered primary auditory cortex (A1) tonotopic maps within a three-day window but did not change maps in the ventral medial geniculate body (MGBv), a finding consistent with cortical primacy during thalamocortical development. Deletion of the Icam5 molecule accelerated spine maturation, shifting the critical period earlier. de Villers-Sidani, et al. [5] defined the spectral tuning critical period as P11–P13 and frequency sweep sensitivity as approximately P14 in rats. Current single-nucleus RNA sequencing (snRNA-seq) studies revealed that tone exposure alters gene expression patterns in interneurons (Kcnc1, Nrgn increase), reduces myelin genes (Mbp) in oligodendrocytes, and reverses PNN core protein expression [22].

Inhibitory circuits and molecular brakes as gatekeepers

The E/I balance hypothesis proposes that maturation of PV+ interneurons initiates the critical period, while consolidation of PNNs closes it [1,23]. PNNs are chondroitin sulfate proteoglycan networks surrounding the soma and proximal dendrites of PV+ cells. They form in an activity-dependent manner during development and function as molecular brakes restricting plasticity upon maturation [24-26]. Cisneros-Franco and de Villers-Sidani [10] showed that chemogenetic silencing of PV+ interneurons in the adult auditory cortex reactivated critical period-like plasticity, paralleled by anatomical changes in PNN expression. Takesian, et al. [27] showed that L1 interneurons serve as a nodal point where thalamocortical inputs and neuromodulatory signals converge, and that the Lynx1 protein may contribute to critical period closure by modulating nicotinic acetylcholine receptor (nAChR) sensitivity.
Rupert and Shea [28] summarized shared features of plasticity during developmental critical periods and adult learning: 1) cortical disinhibition through decreased stimulus-evoked firing rates of PV+ cells, 2) connectivity remodeling of PV+ inputs to pyramidal cells, and 3) elevation of PV and PNN expression marking window closure. These shared mechanisms suggest that developmental and adult plasticity may share overlapping molecular substrates, although direct causal evidence in the human auditory system remains limited.
cMost cortical critical period literature derives from rodent models. The human auditory cortex has a much longer developmental trajectory, complex laminar architecture, and species-specific experiences. Rodent timelines cannot be directly transferred; however, core mechanisms such as E/I balance, PNNs, and Lynx1 may be conserved. Human-scale biomarkers are urgently needed, such as GABA-edited MR spectroscopy and electroencephalography (EEG) gamma oscillations.

Sequential critical periods and hierarchical organization

The cortex does not have a single monolithic critical period but rather temporally sequenced multiple windows. Tonotopic map reorganization closes earliest; tuning bandwidth, binaural processing, and frequency modulation selectivity follow sequentially [29,30]. Kral [2] proposed that this sequencing reflects a transition from feature representation to object representation. Environmental acoustic enrichment can support restoration of degraded cortical processing [31,32].

Subcortical-Cortical Plasticity Interaction

The relationship between subcortical and cortical plasticity is not unidirectional. The corticofugal projection system, consisting of descending fibers from the auditory cortex to the IC, MGB, and CN, provides top-down modulation of subcortical responses [33,34] (see Principle 2 in Fig. 2). The evidence for this bidirectional interaction derives predominantly from animal studies using lesion, optogenetic, and electrophysiological approaches; direct human evidence for corticofugal plasticity remains limited to indirect observations such as training-induced changes in brainstem encoding [14,16]. Whether subcortical plasticity is de novo or inherited from cortical changes is an open question. Barkat, et al. [4] reported findings consistent with cortical primacy during thalamocortical development in mice, while in adults, local mechanisms (homeostatic plasticity, receptor changes) may become increasingly important. The degree to which these rodent findings generalize to the human auditory system requires dedicated investigation.

Proposed Model: Graded Plasticity Windows

Based on the literature synthesis, we propose the GWM of age-dependent auditory plasticity as a conceptual framework. It is important to emphasize that the GWM is a theory-generating model rather than an established empirical finding; its core principles are derived from converging but indirect lines of evidence across species and levels, and each principle requires direct experimental validation. The model offers a unified interpretive framework for understanding the temporal, mechanistic, and functional relationships of plasticity across different neuraxis levels (Fig. 2 and Table 1).

Core principles

Principle 1—Graded Opening/Closing: plasticity windows open sequentially along the auditory neuraxis from bottom to top. Each level is governed by its own molecular onset and closure triggers. Supporting evidence includes: early maturation of auditory brainstem responses [13] and rodent evidence showing defined cortical critical periods in A1 [4,5]; ABR components mature earlier than cortical CAEP components in humans [7,9]. Unresolved questions: whether windows overlap partially or are strictly sequential in humans; which molecular signals initiate opening at subcortical levels. Testable prediction: see Hypothesis 2. Principle 2—Bidirectional Coupling: subcortical and cortical plasticity interact in both directions. During development, cortical maturation appears to influence subcortical encoding via corticofugal pathways; in adulthood, local homeostatic mechanisms become more prominent. Supporting evidence includes (primarily animal): corticofugal projections modulate subcortical responses [33,34]; musical training effects on human brainstem encoding are consistent with top-down modulation, though causality has not been established [14,16]. Unresolved question: whether subcortical plasticity in humans is primarily driven by cortical input or local mechanisms. Testable prediction: see Hypothesis 1. Principle 3—Feature-Specific Timing: different auditory features have distinct critical/sensitive period timelines. Simpler features (e.g., basic frequency tuning) close earlier; complex features (e.g., binaural processing, speech-in-noise) close later. Supporting evidence includes: feature-dependent sensitive periods in rodent A1 [29,30]; de Villers- Sidani, et al. [5] identified distinct windows for spectral tuning (P11–P13) and frequency sweep sensitivity (approximately P14) in rats. Unresolved question: precise human timelines for feature-specific windows remain unmapped. Testable prediction: see Hypothesis 2. Principle 4—Reverse Cascade: in aging, peripheral deafferentation triggers a maladaptive cascade of central reorganization that propagates from lower to higher neuraxis levels. Supporting evidence includes (primarily rodent): age-related GABAergic and glycinergic decline in CN and IC [18]; altered central gain in aged rats [19]. Unresolved questions: whether the cascade is sequential or parallel across levels; whether early amplification can interrupt its propagation. Testable prediction: see Hypothesis 3.

Testable hypotheses

The following hypotheses are derived from the GWM to enable experimental testing:
Hypothesis 1: optogenetic silencing of corticofugal pathways during development will reduce subcortical plasticity during the cortical critical period but will have minimal effect during the subcortical critical period (test of Principle 2).
Hypothesis 2: different components of the brainstem response (onset latency vs. frequency encoding vs. response consistency) will have different developmental peaks, and experience-dependent plasticity will be observed only in components where developmental change continues (test of Principle 3).
Hypothesis 3: in age-related hearing loss, early amplification (hearing aid) will preserve inhibitory neurotransmitter levels in the CN and IC compared to unamplified controls (test of Principle 4).
Hypothesis 4: chemogenetic silencing of PV+ interneurons or enzymatic degradation of PNNs in the adult auditory cortex, combined with auditory training, will produce greater frequency map reorganization than training alone (pharmacological reopening hypothesis).
Hypothesis 5: in late-implanted children (>7 years), subcortical cABR components (temporal processing) will show greater improvement than cortical P1 components, because the subcortical window closes later than the cortical window (clinical prediction of the GWM).
The GWM is a conceptual framework, not an empirically established model. Its principles are drawn from converging but indirect evidence across species and levels of analysis. None has been validated through simultaneous multi-level recordings in the same organism across the full lifespan. Principle 1 (graded sequencing) is inferred from separate studies at different neuraxis levels, often in different species. Direct validation requires simultaneous multi-level recordings in the same individual. Principle 2 (bidirectional coupling) rests primarily on animal optogenetic and chemogenetic data; its relevance to humans remains inferential. Principle 3 (feature-specific timing) is well-supported in rodents but has not been systematically mapped in humans. Principle 4 (reverse cascade) is consistent with epidemiological and rodent data; whether aging changes develop sequentially or in parallel requires longitudinal verification. The five testable hypotheses below are designed to address these gaps and provide empirical grounding for each principle.

Clinical Implications and Recommendations

The clinical recommendations in this section are explicitly graded according to both evidence level and evidence type. Human data take precedence over animal data; prospective cohort studies and RCTs are weighted more heavily than cross-sectional or retrospective designs. Each recommendation specifies whether its supporting evidence is derived from human studies, animal models, or a combination of the two. Recommendations based primarily on preclinical or animal evidence are labeled as hypothesis-generating and should not be interpreted as practice-guiding in the absence of confirmatory human data.

Cochlear implantation timing

Sharma, et al. [7,35] identified a sensitive period of approximately 3.5 years using the cortical auditory evoked potential (CAEP) P1 component as a biomarker. In a study of 245 congenitally deaf children, the majority implanted before age 3.5 achieved normal P1 latencies, while nearly all implanted after age 7 showed abnormal responses. Results between 3.5–7 years were variable. Earlier cochlear implantation has been associated with more favorable central auditory development and auditory outcomes [7,35]. Cross-modal reorganization (visual and somatosensory areas invading the auditory cortex) observed in late-implanted children is thought to constitute a key biological basis of the sensitive period [36,37], although the causal relationship between cross-modal reorganization and outcomes remains an area of active investigation. Clinical Recommendation 1 (Evidence Level: Moderate-High | Evidence Type: human prospective cohort data and CAEP biomarker studies; no RCT is ethically feasible for this outcome): the available human evidence suggests that cochlear implantation in congenitally deaf children is associated with more favorable outcomes when performed before 3.5 years of age, with the strongest outcomes associated with implantation within the first year of life. Late implantation should not be abandoned; the GWM predicts that subcortical plasticity windows close later than cortical ones (Hypothesis 5), suggesting that subcortical components of auditory rehabilitation may remain partially accessible even after the cortical sensitive period has closed. Rehabilitation strategies for late-implanted children should therefore explicitly target subcortical as well as cortical levels.

Age-graded auditory training

Experience-dependent plasticity provides a neurobiological basis for age-targeted auditory training programs. Training paradigms have shown improvements in brainstem encoding in children with dyslexia [38], neural timing in older adults [20], and frequency tracking in tonal language learning [17]. Musical training is one of the rare interventions that appears to target multiple plasticity windows simultaneously, with effects documented at both subcortical and cortical levels [14,39,40]. Clinical Recommendation 2 (Evidence Level: Moderate | Evidence Type: Human quasi-experimental and correlational studies; limited RCT support; window-specific age assignments partially derived from rodent models): auditory training programs are most likely to be effective when matched to the plasticity windows appropriate for the targeted skill. The following age-based guidelines are suggested on the basis of converging human electrophysiological data and rodent sensitive period mapping: 0–5 years for basic frequency discrimination; 5–12 years for temporal processing and speech-in-noise skills; adulthood and elderly for speech envelope tracking and cognitive-auditory integration. The specific age boundaries are derived partly from rodent data and partly from cross-sectional human studies; direct prospective human evidence for window-specific training efficacy remains limited. These guidelines should be treated as evidence-informed starting points rather than established protocols, and prospective controlled studies in each age group are needed.

Neuroprotective amplification

Central changes in presbyacusis extend beyond peripheral loss. Human epidemiological evidence consistently links untreated hearing loss to accelerated cognitive decline and increased dementia risk [41,42], suggesting that peripheral deafferentation has consequences extending well into the central nervous system. Mechanistic evidence from rodent studies indicates that peripheral deafferentation drives progressive central inhibitory decline and maladaptive gain changes at multiple neuraxis levels [18,19], providing a plausible neurobiological basis for the neuroprotective amplification hypothesis. However, it should be noted that while the association between hearing loss and dementia is robust in human data, the causal role of central maladaptive plasticity in this relationship—and the capacity of hearing aids to interrupt it—has not been established in prospective RCTs. Ongoing trials (e.g., the ACHIEVE study) are expected to provide more definitive evidence. Clinical Recommendation 3 (Evidence Level: Moderate | Evidence Type: Human epidemiological data for the hearing loss-dementia association; rodent mechanistic data for central pathway preservation; no prospective RCT yet available for hearing aid neuroprotection): early and sustained amplification should be considered not only for the purpose of peripheral gain but also to minimize central deafferentation and its downstream consequences. The concept of neuroprotective amplification—fitting hearing aids earlier and more consistently than currently practiced—is supported by the available evidence but awaits confirmation from prospective human studies.

Pharmacological plasticity enhancement

Clinical Recommendation 4 (Evidence Level: Low | Evidence Type: Rodent in vivo and in vitro models only; no human data available): pharmacological strategies targeting the molecular brakes of cortical critical periods—including chemogenetic silencing of PV+ interneurons [10], enzymatic degradation of PNNs [25], and Lynx1 inhibition—have shown proof-of-concept in rodent models. These approaches are entirely preclinical and must not be applied in clinical practice outside of properly approved research protocols. Their inclusion here is intended solely to highlight a promising future research direction. Translation to humans would require extensive safety profiling, dose-response characterization, and human trial phases. The combination of such approaches with intensive auditory rehabilitation, once safety is established, represents a high-priority experimental paradigm.
Table 2 summarizes the key mechanisms, critical period timelines, species models, and clinical relevance for each level of the auditory neuraxis, and provides a concise reference for matching intervention strategies to the appropriate developmental stage and evidence level.

Future Directions and Conclusion

Open questions

First priority: molecular timers of subcortical critical periods (PNNs, PV+ maturation, myelin) should be characterized in the IC and CN. Second priority: subcortical-cortical causality should be tested through optogenetic/chemogenetic manipulation of corticofugal projections during developmental windows. Third priority: human-scale plasticity biomarkers should be developed using combinations of cABR, N1/P2, GABA-MRS, and gamma EEG. Fourth priority: The auditory plasticity-cognitive decline relationship should be investigated to understand the mechanistic basis of hearing loss as a dementia risk factor [41,42].

Conclusion

In this scoping review, we mapped and synthesized the available evidence on the mechanisms, developmental timelines, and clinical implications of age-dependent auditory plasticity across subcortical and cortical levels. Four contributions emerged: 1) critical methodological appraisals, including identification of a persistent translational gap between rodent and human data; 2) the GWM—a conceptual framework proposing that plasticity is organized as a series of hierarchically sequenced windows with distinct molecular timers at each neuraxis level; 3) five testable hypotheses to provide empirical grounding for the model’s principles; and 4) clinical recommendations graded by evidence level and type, with human and animal evidence clearly distinguished. Auditory plasticity is not a single window but a series of windows that open and close in a graded manner for different levels and features. If validated, the GWM may have important implications for cochlear implant rehabilitation, auditory training design, and neuroprotective amplification. Rigorously testing the hypotheses it generates is the necessary next step.

Supplementary Materials

The online-only Data Supplement is available with this article at https://doi.org/10.7874/jao.2026.00164.
Supplementary Table 1.
Comprehensive summary of studies included in the thematic synthesis (n = 78)
jao-2026-00164-Supplementary-Table-1.docx

Notes

Conflicts of Interest

The author has no financial conflicts of interest.

Funding Statement

None

Acknowledgments

None

Fig. 1.
PRISMA-ScR flow diagram of the study selection process. Records were retrieved from three databases (PubMed/MEDLINE, Scopus, Web of Science; January 1963–December 2025). Following duplicate removal (n=691), title/abstract screening (n=2,437), and full-text assessment (n=312), 78 studies met all inclusion criteria. Full-text exclusion reasons are shown within the diagram.
jao-2026-00164f1.jpg
Fig. 2.
Graded Windows Model of auditory plasticity across the neuraxis. How to read this figure: the y-axis (bottom to top) represents ascending levels of the auditory neuraxis. The x-axis shows the developmental timeline, with rodent postnatal day (P) stages on the upper row and approximate human age equivalents in italics on the lower row; species equivalences are approximate and should not be interpreted as direct numerical conversions (see Methods, Note on species comparisons). Each colored band represents the relative plasticity window at a given neuraxis level: band width reflects the duration of the window, and band height reflects its relative magnitude. The shaded red zone at the right (Aging, >60 years) indicates the maladaptive plasticity phase across all levels. Annotated elements: the blue diagonal arrow illustrates Principle 1 (graded bottom-to-top sequential opening of plasticity windows); orange dashed arrows represent Principle 2 (corticofugal top-down modulation of subcortical plasticity); the red vertical dashed arrow indicates Principle 4 (reverse maladaptive cascade propagating bottom-to-top during aging); the yellow annotation box marks the known molecular brakes of cortical critical period closure (PV+ interneurons, PNNs, Lynx1); the red dotted vertical line marks the cortical auditory evoked potential-defined cochlear implant sensitive period boundary (approximately 3.5 years). Principle 3 (feature-specific timing) is described in the caption text rather than annotated in the figure to reduce visual density: each auditory feature has its own critical/sensitive period—simple features close early, complex features close late. MGB, medial geniculate body; PNN, perineuronal net.
jao-2026-00164f2.jpg
Table 1.
Graded Windows Model: schematic representation of plasticity window states across the auditory neuraxis
Age period CN/IC MGB/Thalamus A1 cortex Higher cortex
Prenatal-P10 Open Opening Closed* Closed*
P10-P15 (rat) Closing Open Peak Opening*
P15-P30 (rat) Residual* Closing Closing Peak
Juvenile-Adolesc. Stable Stable Residual* Open
Adult Low Low Low Residual*
Elderly (>60 yr) Maladaptive Maladaptive Maladaptive Maladaptive

How to read this table: marks reflect relative plasticity magnitude, assigned by integrating three parameters: 1) reported magnitude of experience-dependent response changes; 2) duration of the plasticity window; and 3) number of independent studies reporting significant plasticity at that level and period.

* narrow/low-magnitude window, limited evidence;

moderate window, consistent evidence;

broad, high-magnitude window, convergent evidence.

Ratings are qualitative synthesis judgments, not quantitative thresholds. P-day values refer to rodent data; human equivalents are shown in Fig. 2. Plasticity states—Open: window actively open; Peak: maximum magnitude; Closing: window narrowing; Residual: low-level residual; Stable: plateau, minimal change; Low: minimal plasticity; Maladaptive: pathological reorganization. Rodent–human equivalents: P0-P10≈prenatal/neonatal; P10-P15≈0-6 months; P15-P30≈6 months–2 years (approximate; see Fig. 2). CN, cochlear nucleus; IC, inferior colliculus; MGB, medial geniculate body; A1, primary auditory cortex.

Table 2.
Summary of mechanisms, critical period timelines, and clinical relevance across the auditory neuraxis
Level Critical period Key mechanisms Species (evidence) Clinical relevance
Cochlear nucleus PN 1-3 weeks (rodent)≈Prenatal-0 months (human) Glycinergic inhibition refinement; tonotopic map development; GABA switch Rat, human (indirect) ABR diagnosis; early hearing screening
Inferior colliculus PN 2-4 weeks (rodent)≈0-6 months (human) GABAergic maturation; central gain calibration; frequency-following refinement Rat, mouse (rodent only) Tinnitus; central gain dysregulation
MGB/thalamus Approx. cortical CP (rodent timing) Thalamocortical axon refinement; topographic map consolidation Mouse (rodent only) Sensory gating; thalamocortical dysmaturation
A1 cortex P11-P15 (rat)≈0-3.5 years (human) E/I balance; PV+interneuron maturation; PNN consolidation; Lynx1; Icam5 Mouse, rat; human (CAEP biomarker) CI timing; speech perception
Higher cortex Extends to adolescence≈7-18 years (human) Cross-modal reorganization; corticocortical connectivity; top-down modulation Human (primary); rodent (limited) Language; reading; cognitive-auditory integration

Species column: “Rodent only” indicates human-equivalent evidence is not yet available; clinical extrapolation should be made cautiously. Human evidence is indicated where prospective or biomarker data exist. Evidence levels for clinical relevance—High (human prospective data): CI timing; Moderate (epidemiological + rodent mechanistic): ABR diagnosis, tinnitus; Low/Preclinical (rodent only): sensory gate, neuroprotective amplification. MGB, medial geniculate body; A1, primary auditory cortex; PN, postnatal; CP, critical period; E/I, excitatory/inhibitory balance; PV+, parvalbumin-positive interneurons; PNN, perineuronal net; CI, cochlear implant; CAEP, cortical auditory evoked potential; ABR, auditory brainstem response.

REFERENCES

1. Hensch TK. Critical period plasticity in local cortical circuits. Nat Rev Neurosci 2005;6:877–88.
crossref pmid pdf
2. Kral A. Auditory critical periods: a review from system’s perspective. Neuroscience 2013;247:117–33.
crossref pmid
3. Hubel DH, Wiesel TN. Receptive fields of cells in striate cortex of very young, visually inexperienced kittens. J Neurophysiol 1963;26:994–1002.
crossref pmid
4. Barkat TR, Polley DB, Hensch TK. A critical period for auditory thalamocortical connectivity. Nat Neurosci 2011;14:1189–94.
crossref pmid pmc pdf
5. de Villers-Sidani E, Chang EF, Bao S, Merzenich MM. Critical period window for spectral tuning defined in the primary auditory cortex (A1) in the rat. J Neurosci 2007;27:180–9.
crossref pmid
6. Kral A, Sharma A. Developmental neuroplasticity after cochlear implantation. Trends Neurosci 2012;35:111–22.
crossref pmid
7. Sharma A, Dorman MF, Spahr AJ. A sensitive period for the development of the central auditory system in children with cochlear implants: implications for age of implantation. Ear Hear 2002;23:532–9.
crossref pmid
8. Johnson KL, Nicol T, Zecker SG, Kraus N. Developmental plasticity in the human auditory brainstem. J Neurosci 2008;28:4000–7.
crossref pmid pmc
9. Skoe E, Krizman J, Anderson S, Kraus N. Stability and plasticity of auditory brainstem function across the lifespan. Cereb Cortex 2015;25:1415–26.
crossref pmid
10. Cisneros-Franco JM, de Villers-Sidani É. Reactivation of critical period plasticity in adult auditory cortex through chemogenetic silencing of parvalbumin-positive interneurons. Proc Natl Acad Sci U S A 2019;116:26329–31.
crossref pmid pmc
11. Takesian AE, Hensch TK. Balancing plasticity/stability across brain development. Prog Brain Res 2013;207:3–34.
crossref pmid
12. Tricco AC, Lillie E, Zarin W, O’Brien KK, Colquhoun H, Levac D, et al. PRISMA extension for scoping reviews (PRISMA-ScR): checklist and explanation. Ann Intern Med 2018;169:467–73.
crossref
13. Salamy A. Maturation of the auditory brainstem response from birth through early childhood. J Clin Neurophysiol 1984;1:293–329.
crossref
14. Skoe E, Kraus N. Musical training heightens auditory brainstem function during sensitive periods in development. Front Psychol 2013;4:622
crossref pmid pmc
15. Chandrasekaran B, Kraus N. The scalp-recorded brainstem response to speech: neural origins and plasticity. Psychophysiology 2010;47:236–46.
crossref pmid
16. Chandrasekaran B, Skoe E, Kraus N. An integrative model of subcortical auditory plasticity. Brain Topogr 2014;27:539–52.
crossref pmid pdf
17. Song JH, Skoe E, Wong PC, Kraus N. Plasticity in the adult human auditory brainstem following short-term linguistic training. J Cogn Neurosci 2008;20:1892–902.
crossref pmid pmc pdf
18. Caspary DM, Ling L, Turner JG, Hughes LF. Inhibitory neurotransmission, plasticity and aging in the mammalian central auditory system. J Exp Biol 2008;211(Pt 11):1781–91.
crossref pmid pmc pdf
19. Parthasarathy A, Bartlett EL. Age-related auditory deficits in temporal processing in F-344 rats. Neuroscience 2011;192:619–30.
crossref pmid
20. Anderson S, White-Schwoch T, Parbery-Clark A, Kraus N. Reversal of age-related neural timing delays with training. Proc Natl Acad Sci U S A 2013;110:4357–62.
crossref pmid pmc
21. Turrigiano GG. The self-tuning neuron: synaptic scaling of excitatory synapses. Cell 2008;135:422–35.
crossref pmid pmc
22. Kalish BT, Barkat TR, Diel EE, Zhang EJ, Greenberg ME, Hensch TK. Single-nucleus RNA sequencing of mouse auditory cortex reveals critical period triggers and brakes. Proc Natl Acad Sci U S A 2020;117:11744–52.
crossref pmid pmc
23. Fagiolini M, Hensch TK. Inhibitory threshold for critical-period activation in primary visual cortex. Nature 2000;404:183–6.
crossref pmid pdf
24. Dityatev A, Brückner G, Dityateva G, Grosche J, Kleene R, Schachner M. Activity-dependent formation and functions of chondroitin sulfate-rich extracellular matrix of perineuronal nets. Dev Neurobiol 2007;67:570–88.
crossref pmid
25. Fawcett JW, Oohashi T, Pizzorusso T. The roles of perineuronal nets and the perinodal extracellular matrix in neuronal function. Nat Rev Neurosci 2019;20:451–65.
crossref pdf
26. Sorg BA, Berretta S, Blacktop JM, Fawcett JW, Kitagawa H, Kwok JC, et al. Casting a wide net: role of perineuronal nets in neural plasticity. J Neurosci 2016;36:11459–68.
crossref pmid pmc
27. Takesian AE, Bogart LJ, Lichtman JW, Hensch TK. Inhibitory circuit gating of auditory critical-period plasticity. Nat Neurosci 2018;21:218–27.
crossref pmid pmc pdf
28. Rupert DD, Shea SD. Parvalbumin-positive interneurons regulate cortical sensory plasticity in adulthood and development through shared mechanisms. Front Neural Circuits 2022;16:886629
crossref pmid pmc
29. Insanally MN, Köver H, Kim H, Bao S. Feature-dependent sensitive periods in the development of complex sound representation. J Neurosci 2009;29:5456–62.
crossref pmid pmc
30. Polley DB, Thompson JH, Guo W. Brief hearing loss disrupts binaural integration during two early critical periods of auditory cortex development. Nat Commun 2013;4:2547
crossref pmid pmc pdf
31. Zhou X, Panizzutti R, de Villers-Sidani E, Madeira C, Merzenich MM. Natural restoration of critical period plasticity in the juvenile and adult primary auditory cortex. J Neurosci 2011;31:5625–34.
crossref pmid pmc
32. Zhu X, Wang F, Hu H, Sun X, Kilgard MP, Merzenich MM, et al. Environmental acoustic enrichment promotes recovery from developmentally degraded auditory cortical processing. J Neurosci 2014;34:5406–15.
crossref pmid pmc
33. Bajo VM, Nodal FR, Moore DR, King AJ. The descending corticocollicular pathway mediates learning-induced auditory plasticity. Nat Neurosci 2010;13:253–60.
crossref pmid pdf
34. Suga N, Ma X. Multiparametric corticofugal modulation and plasticity in the auditory system. Nat Rev Neurosci 2003;4:783–94.
crossref pmid pdf
35. Sharma A, Dorman MF, Kral A. The influence of a sensitive period on central auditory development in children with unilateral and bilateral cochlear implants. Hear Res 2005;203:134–43.
crossref pmid
36. Sharma A, Gilley PM, Dorman MF, Baldwin R. Deprivation-induced cortical reorganization in children with cochlear implants. Int J Audiol 2007;46:494–9.
crossref pmid
37. Kral A, Eggermont JJ. What’s to lose and what’s to learn: development under auditory deprivation, cochlear implants and limits of cortical plasticity. Brain Res Rev 2007;56:259–69.
crossref pmid
38. Chandrasekaran B, Hornickel J, Skoe E, Nicol T, Kraus N. Context-dependent encoding in the human auditory brainstem relates to hearing speech in noise: implications for developmental dyslexia. Neuron 2009;64:311–9.
crossref pmc
39. Kraus N, Chandrasekaran B. Music training for the development of auditory skills. Nat Rev Neurosci 2010;11:599–605.
crossref pmid pdf
40. Parbery-Clark A, Anderson S, Hittner E, Kraus N. Musical experience offsets age-related delays in neural timing. Neurobiol Aging 2012;33:1483.e1-4
crossref pmid
41. Livingston G, Huntley J, Sommerlad A, Ames D, Ballard C, Banerjee S, et al. Dementia prevention, intervention, and care: 2020 report of the Lancet Commission. Lancet 2020;396:413–46.
crossref pmid pmc
42. Lin FR, Metter EJ, O’Brien RJ, Resnick SM, Zonderman AB, Ferrucci L. Hearing loss and incident dementia. Arch Neurol 2011;68:214–20.
crossref pmid pmc
TOOLS
Share :
Facebook Twitter Linked In Google+
METRICS Graph View
  • 0 Crossref
  • 0 Scopus
  • 740 View
  • 38 Download


ABOUT
ARTICLES

Browse all articles >

ISSUES
TOPICS

Browse all articles >

AUTHOR INFORMATION
Editorial Office
SMG–SNU Boramae Medical Center,
20 Boramae-ro 5-gil, Dongjak-gu, Seoul 07061, Korea
Tel: +82-2-3784-8551    Fax: +82-0505-115-8551    E-mail: jao@smileml.com                

Copyright © 2026 by The Korean Audiological Society and Korean Otological Society. All rights reserved.

Developed in M2PI

Close layer
prev next