<figure><img src="image_1.png" /></figure>

HAL
open science

# Moderate presbycusis boosts audio-visual integration, but not lip-reading

Tanguy Delmas, Mathieu Pham van Cang, Grégory Gerenton, Jérôme Lefeuvre, Keith B Doelling, Luc H Arnal, Diane S. Lazard

<figure><img src="image_2.png" /></figure>

## To cite this version:

Tanguy Delmas, Mathieu Pham van Cang, Grégory Gerenton, Jérôme Lefeuvre, Keith B Doelling, et al.. Moderate presbycusis boosts audio-visual integration, but not lip-reading. Hearing Research, 2025, 465, pp.109355. 10.1016/j.heares.2025.109355. hal-05308991

HAL Id: hal-05308991

https://hal.science/hal-05308991v1

Submitted on 10 Oct 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_3.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
<figure><img src="image_4.png" /></figure>

Research Paper

# Moderate presbycusis boosts audio-visual integration, but not lip-reading

<figure><img src="image_5.png" /></figure>

Tanguy Delmas<sup>a,b,*</sup>, Mathieu Pham Van Cang<sup>a</sup>, Grégory Gerenton<sup>a</sup>, Jérôme Lefeuvre<sup>b</sup>, Keith B. Doelling<sup>a</sup>, Luc H. Arnal<sup>a</sup>, Diane S. Lazard<sup>a,c</sup>

ARTICLE INFO

Keywords:

Audio-visual integration

Lip-reading

Hearing impairment

Age

Presbycusis

Cognition

Speech in noise

ABSTRACT

In audiological practice, speech comprehension is typically assessed in the auditory modality alone (speech in quiet or noise). However, in real-life communication when the auditory input is degraded - due to noise or hearing loss (HL) - individuals rely on ancillary signals to enhance speech perception. Audio-visual (AV) integration is particularly effective in improving speech perception in noisy environments, yet the influence of HL and aging on this ability remains underexplored.

This study aims to disentangle the effects of HL and age on visual aspects of speech processing, both unimodal (lip-reading) and bimodally (AV integration). In sixty-five participants aged 50 and older, with hearing abilities ranging from normal to moderate HL (from 4 to 63 dB HL), we tested speech comprehension in challenging auditory, visual (lip-reading) and AV conditions using an adaptive procedure. AV gain (AV performance minus Auditory-alone performance) served as a measure of audio-visual integration.

Using multiple linear regressions and causal inference to account for the relative impact and potential interactions between HL and age, our results show that mild to moderate HL does not improve unimodal visual processing but does improve AV gain. In contrast, aging negatively impacts visual speech processing but does not directly affect AV gain.

These findings suggest that mild to moderate HL enhances the integration of visual and auditory speech cues to improve AV performance without affecting the efficacy of the visual information processing itself, while age-related decline in visual speech processing does not appear to effect overall AV integration. We propose that this reflects a form of central plasticity, in which moderate HL drives adaptive changes at high-order multimodal levels, counterbalancing age-related sensory decline in visual speech processing to maintain AV speech integration. Future research should explore how this plasticity evolves with more severe HL.

1. Introduction

In both normal and hearing-impaired individuals, the ability to comprehend auditory speech in challenging situations often depends on the use of complementary sensory cues. (Ross et al., 2007; Sumby & Pollack, 2005; van de Rijt et al., 2019). Visual cues, e.g. facial or lip movements, in particular, provide crucial timing cues and help disambiguate certain phonemes (Arnal et al., 2009, 2011; Peelle & Sommers, 2015; Wassenhove et al., 2005). This reliance is even more important when sensory signals are degraded such as in noisy environments or because of hearing loss (HL). At the neural level, auditory and visual cues are jointly processed (integrated) at multisensory levels to improve comprehension (Bernstein et al., 2004; Grant et al., 1998b; Grant &

Seitz, 2000; Peelle & Sommers, 2015). The beneficial effects of audio-visual (AV) integration on speech perception increase under challenging listening conditions (Ross et al., 2007; Sumby & Pollack, 2005; van de Rijt et al., 2019) up to a limit at which relevant information cannot be extracted anymore (inverse effectiveness, Tye-Murray et al., 2010; van de Rijt et al., 2019), resulting in a drop in comprehension. However, AV gain substantially varies across individuals (Grant & Seitz, 1998; Le Rhun et al., 2024; Llorach et al., 2022) and is influenced by lip-reading abilities (Le Rhun et al., 2024; Llorach et al., 2022; Dias et al., 2021). Little is known about the factors that influence audio-visual integration in normal-hearing individuals, and this is even less clear in the case of hearing loss, where the use of visual cues appears crucial.

In a landmark study, Rouger et al (2007) showed that adults with

<footnote><sup>a</sup> Université Paris Cité, Institut Pasteur, AP-HP, INSERM, CNRS, Fondation Pour l'Audition, Institut de l'Audition, IHU reConnect, F-75012 Paris, France</footnote>

<footnote><sup>b</sup> ECLEAR, Audition Marc Boulet, Audition Lefeuvre, France</footnote>

<footnote><sup>c</sup> Princess Grace Hospital, ENT Surgery Department, Monaco</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail address: tanguy.delmas@pasteur.fr (T. Delmas).</footnote>
severe-to-profound hearing loss who use cochlear implants appear to better integrate audio-visual information than normal-hearing participants. However, Zhou et al. (2019) did not confirm this result when equalizing difficulty in the auditory modality (by adjusting the signal-to-noise ratio to achieve 50% comprehension) between cochlear implant users and normal-hearing controls. When considering lip-reading abilities, several studies have reported that cochlear implant users outperform normal-hearing individuals (Layer et al., 2022; Rouger et al., 2007; Schreitmüller et al., 2018; Stropahl et al., 2015; Stropahl & Debener, 2017; Weglage et al., 2024). However, a few studies (to our knowledge) failed to replicate this result (Strelnikov et al., 2009; Zhou et al., 2019).

In mild to moderate HL, the existing literature provides even fewer clear conclusions (Grant et al., 1998b; Hygge et al., 1992; Middelweerd & Plomp, 1987; Tye-Murray et al., 2007). This may be attributed to a wide variability in experimental paradigms, which do not always equalize the level of difficulty between modalities (auditory, visual and audio-visual), to non-matched groups, or to inconsistencies in the way AV integration is assessed.

Another important consideration is that the most common etiology of mild to moderate HL is presbycusis. Presbycusis, or age-related HL, is the third most common health condition affecting older adults (Collins, 1997) and is associated with cognitive decline and social difficulties such as isolation or depression (Ciorba et al., 2012; Lin et al., 2013; Mick et al., 2014). As such, age constitutes a potential confounding factor in the assessment of AV integration in mild to moderate HL: although presbycusis is used as a model for this degree of hearing loss, the age factor was not always controlled (e.g. Grant et al., 1998a; Middelweerd & Plomp, 1987). Although some studies used age-matched groups to control age effects (Hygge et al., 1992; Tye-Murray et al., 2007), this method does not explore a possible interaction between age and hearing loss. In normal-hearing listeners, age and cognitive decline have a degrading effect on lip-reading performance (Feld & Sommers, 2009; Sommers et al., 2005). However, its influence on AV integration is still debated, leading in some instances to an increase in the effect (Baum & Stevenson, 2017; Dias et al., 2021; Stevenson et al., 2015) and in others to no improvement (Tye-Murray et al., 2010).

The aim of the current study is to disentangle the effects of mild to moderate HL, age and hearing aid (HA) use on the visual contributions to speech perception, either unimodally (lip-reading) and/or through AV integration, while carefully equalizing the level of difficulty of the auditory and audio-visual conditions between normal and impaired listeners. We tested speech processing abilities in a sample of 65 participants aged 50 years and older, with a hearing continuum ranging from normal hearing to moderate HL (70 dB HL maximum). We used an adaptive procedure assessing speech sentence comprehension under challenging conditions (individual speech reception threshold of 80 % —or SRT80— with a fixed noise at 65 dB; Brand et al., 2011; Brand & Kollmeier, 2002). We carefully distinguished and systematically evaluated visual-only processing (lip-reading) and audio-visual processing. We assessed lip-reading using a standardized and reproducible test based on recorded sentences. To quantify the benefit of audio-visual integration, we calculated the AV gain, i.e. the improvement in comprehension when participants combined auditory and visual information compared to auditory-only performance. We then used statistical analyses to examine how hearing loss, age, and hearing aid use affected performance across the different modalities (auditory, visual, and audio-visual).

We assumed that a moderate HL should induce sufficient pressure on information processing needs to induce plasticity and integration changes at the unimodal and/or at the bimodal level. Our first objective is to assess whether mild to moderate hearing impairment influences visual processing of speech either directly or through its modulation of auditory processing (audio-visual integration). We hypothesize that HL related plasticity plays a positive role in potentiating both lip-reading ability and AV synergy. The second objective is to characterize the

effect of age on the same two variables.

## 2. Material and methods

### 2.1. Ethics statement

This project was approved by the Ethics committee CPP Tours-Region Centre-Ouest 1 (project identification number 2020T317 RIPH3 HPS). Participants were recruited in ENT clinics or audiology centers (mainly Audition Lefeuvre and Audition Marc Boulet). They all gave written informed consent and received financial compensation.

### 2.2. Participants

Inclusion criteria were age between 55 and 85 years, French native language, normal hearing to moderate HL. Exclusion criteria were conductive or mixed HL, HL since birth or childhood, visual deficit without recent correction, and having undergone speech therapy.

Sixty-five participants (46 women) aged between 55 and 85 years (70.4 ±7.6 years) were included. They all underwent a pure-tone audiogram in a dedicated sound-attenuated booth. Pure tone averages (PTA, average of hearing thresholds at 500, 1000, 2000, 4000 Hz) ranged from 4 to 63 dB HL (29 ±16 dB HL, Supplementary Figure S1). According to the BIAP classification (BIAP recommendation 02/1), 25 participants had normal hearing (0-20 dB HL), 17 had mild HL (20-40 dB HL) and 23 had moderate HL (40-70 dB HL). Twenty-six participants (65% of the hearing-impaired participants) had been using bilateral hearing aids for a mean of 5 years (±4.4 years). The average time between HL diagnosis and their first use of hearing aids was 8 years (±13.8).

Cognitive assessment was carried out using the Montreal Cognitive Assessment (MoCA - French 8.3) for participants who wished to do so (4 refused). We checked that the instructions were understood with the hearing aids, as there is no French version of this test for the hearing-impaired (Dawes et al., 2023). A score between 26 and 30 is considered normal. Thirty-three participants (50%) scored between 19 and 25. They had abnormal hearing in 48% of cases. MoCA scores did not correlate with age or PTA (Pearson correlation, rho = - 0.07, p = 0.61 and rho = - 0.19, p = 0.14, respectively).

### 2.3. Paradigm

To assess auditory comprehension (auditory-only modality without any hearing aids), lip-reading skills (visual-only modality), and AV gain (benefits of adding visual speech cues to auditory cues), the participants completed the AV version of the French Matrix Sentence Test (MST). This test is a standardized, automated and reproducible measure of speech comprehension in the three modalities (Le Rhun et al., 2024). We used this test to equalize the level of difficulty of uni- and bimodal processing between participants. For the auditory-only and AV modalities, the test uses an adaptive procedure with a fixed background noise, presented at 65 dB SPL. The intensity of the signal presentation varies to reach a defined individual speech comprehension target (% of words correctly identified). A speech reception threshold of 80% (SRT80), expressed in dB SNR (signal-to-noise ratio), was used for the auditory and AV conditions to avoid ceiling effects in the AV conditions. Indeed, some participants can understand more than 50% of the content by lip-reading alone (Le Rhun et al., 2024; Llorach et al., 2022). For the visual-only condition, we removed the auditory track from the video and measured the percentage of words correctly understood from the visual stimulus alone. Because lip-reading often occurs as a result of background noise in real life and because the other modalities were tested in noise, the visual-only condition was also presented in background noise, as in the validated AV FrMST (Le Rhun et al., 2024).
## 2.4. Experimental set up

The experiment was conducted in a soundproof booth. Participants watched videos of speakers on a monitor at a viewing distance of 80 cm and listened to the auditory stimuli through binaural audiometric insert earphones (Etymotic Research, ER-2), without hearing aids. Participants who required visual correction (glasses or contact lenses) wore them during the test. The videos and the sound were played using Matlab (version R2022b) and VLC® (version 3.0.16). The acoustic signal was sent through an SLL 2 sound card. Sound levels were calibrated using an artificial ear connected to a sound level meter.

## 2.5. Stimuli

Each video featured the recording of a female face against a green background, and began with a 500 ms still face. Participants were tested in noise with the long-term stationary noise of the average speech spectrum (LTASS) from the original French MST. We used a standard adaptive procedure (Brand et al., 2011; Brand & Kollmeier, 2002). The presentation level of the sentences started at 60 dB SPL, with a fixed noise level of 65 dB SPL. The stimuli consisted of sentences from the French MST, composed of five words (name, verb, number, object, color), and were presented in three modalities: auditory only, visual only and audio-visual, as described in detail in Le Rhun et al. (2024).

## 2.6. Experimental conditions and Procedure

Each modality was tested with a list of 20 sentences. Responses were recorded in a closed set format. The test began with a training phase consisting of two lists of sentences presented in the AV modality in background noise, followed by random presentations of the auditory only (Ao), visual only (Vo) or audio-visual (AV) conditions.

## 2.7. Statistical analyses

Comprehension performance is assessed using the SRT80, i.e. the SNR level at which 80% of words are correctly reported. At the group level, results are expressed as means ± standard deviation. To measure the benefit of adding visual cues to auditory information, the AV gain was calculated as the difference between the SRT80 obtained in the Ao condition and the SRT80 obtained in the AV condition. This AV gain metric provides a behavioral measure of the ability to combine visual and auditory inputs as compared to Ao, while controlling for interindividual hearing loss severity. This score was used as a proxy for AV integration in this study.

We used linear regression models to understand which factors among PTA, age, cognitive assessment, and hearing aid use (independent variables) influence Vo, Ao, AV performance and AV gain (dependent variables) and to understand their relative contributions or potential interactions (Matlab, R2024a). As is standard, linear regression models included an intercept term, representing the expected value of the dependent variable when all predictors are null. Independent and dependent variables were normalized (z-scored) to facilitate interpretation of regression coefficients and to avoid potential numerical instability. To clarify the relationships between variables, a correlation matrix including all dependent and independent variables was computed (Supplementary Table S1). This matrix provides an overview of the associations between behavioral outcomes (Vo, Ao, AV, and AV gain) and predictors (age, PTA, MoCA, Vo, and hearing aid use).

To visualize the relationship between two variables while controlling for confounding factors, we used a residual-based approach. Specifically, we first fitted linear regression models predicting each variable of interest from the relevant covariates. The residuals extracted from these models represent the variance in each variable that is not explained by the covariates. We then plotted the residuals of the dependent variable against the residuals of the independent variable to illustrate their

association after accounting for potential confounders. This method allows for a clearer representation of the relationship of interest while minimizing the influence of external factors.

To strengthen causal interpretations, we applied causal inference principles to design the analysis plan and interpret the regression results. Causal inference refers to a set of statistical techniques used to identify and estimate the causal relationships between variables, rather than simply observing correlations (Holland, 1986). It helps understand how one variable may directly affect another. Specifically, we constructed causal graphs, based on the literature, for each model to explicitly represent our hypotheses about the mechanisms underlying each dependent variable. A causal graph is a visual representation of the assumed causal relationships among variables, where blocks represent variables and arrows denote the presumed direction of causality. These graphs help clarify how the independent variables influence the dependent variables and guide the interpretation of the regression results (SRT80_Ao, Vo performance, SRT80_AV, or AV gain, in Supplementary Figures S2a, S3a, S4a, S5a). The literature used to construct these causality graphs is provided in the supplementary file.

The variability of AV gain increased with PTA, and the Breusch-Pagan test revealed significant heteroscedasticity in the model residuals ($p = 0.02$). To address this issue and ensure the robustness of our results, we fitted a generalized linear model (GLM) with a gamma distribution and a log link.

We conducted a one-way analysis of variance (ANOVA) to examine whether AV gain varied across hearing ability categories based on BIAP classification, followed by a post-hoc comparison using the Tukey-Kramer correction.

To account for potential effects of auditory rehabilitation, hearing aid use (categorical variable: user versus non-user) was included as an additional independent variable in the linear regression models assessing lip-reading performance and AV gain.

# 3. Results

## 3.1. Unimodal conditions

In the auditory-only condition, the mean SRT (SRT80_Ao) was 2.6 dB SNR (±6.9), ranging from 26.8 to -4.8 dB SNR. Fig. 1a shows the individual results as a function of PTA, the more negative the value, the better the performance. The linear regression model SRT80_Ao ~ Intercept + age x PTA + MoCA ($R^2$ = 0.61, Supplementary S2b) showed a significant effect of PTA ($\beta$ = 0.82, $p < 10^{-3}$, Fig. 1b), but not of age ($p$ = 0.47), MoCA ($p$ = 0.99) nor the interaction age x PTA ($p$ = 0.19) on SRT80_Ao. However, in accordance with our causal graph (Supplementary S2a), the total influence (direct and indirect) of age on SRT80_Ao, assessed by the linear regression model SRT80_Ao ~ Intercept + age ($R^2$ = 0.10, Supplementary S2c), showed a significant influence of age on SRT80_Ao ($\beta$ = 0.32, $p$ = 0.009, Supplementary S6a). This suggests that age influences SRT80_Ao mainly through its influence on PTA. The overall influence of PTA was also assessed but showed no difference from the previous relationships (Supplementary S2d). These results are in line with existing knowledge that increased hearing thresholds negatively affect speech comprehension in the auditory modality.

Regarding the influence of hearing impairment on lip-reading performance, we hypothesized that HL-related plasticity might enhance lip-reading ability, while age would negatively affect it. The visual-only modality was assessed by lip-reading performance, which ranged from 1% to 61%, with a mean of 24.7% ±15 (chance threshold = 10%). Fig. 2a shows the individual results as a function of age. The linear regression model Lip-reading ~ Intercept + age x PTA + MoCA ($R^2$ = 0.20, Supplementary S3b) shows that age directly influences lip-reading performance ($\beta$ = -0.42, $p$ = 0.004, Fig. 2b). However, the model did not show any influence of PTA ($p$ = 0.65), MoCA ($p$ = 0.83) nor interaction age x PTA ($p$ = 0.17) on lip-reading performance. Fig. 2c shows
<figure><img src="image_6.png" /><figcaption>**Fig. 1.** SRT80 in the Auditory-only (Ao, left box) and audio-visual (AV, right box) conditions as a function of raw PTA (a and c) and residuals (b and d, factoring out age and MoCA scores).</figcaption></figure>

PTA has a negative effect on auditory-only and audio-visual SRT.

Black dots represent individual data. Red crosses represent the mean. Dashed lines represent the BIAP classification: normal hearing (0-19 dB HL), mild hearing loss (20-39 dB HL) and moderate hearing loss (40-70 dB HL). The left box shows the auditory-only condition (Ao, in dB SNR) with raw SRT80 according to raw PTA (a, in dB HL) and SRT80 residuals according to PTA residuals, when controlling for age and MoCA scores (b). The right box shows the audio-visual condition (AV, in dB SNR) with raw SRT80 according to raw PTA (c, in dB HL) and SRT80 residuals according to PTA residuals, when controlling for age, MoCA scores and lip-reading scores (d).

individual scores as a function of PTA and Fig. 2d shows individual scores as a function of PTA after controlling for age. The global effect of PTA on lip-reading performance can be assessed using the linear regression model Lip-reading ~ Intercept + PTA + age (Supplementary S3c). It did not show any significant effect. The total influence of age was also assessed but did not show any difference from the previous relationships (Supplementary S3d). Contrary to our hypothesis, our results did not show an effect of hearing loss on lip-reading abilities but did confirm a decline in performance with age.

## 3.2. Bimodal conditions

In the AV condition, the mean SRT (SRT80_AV) was -1.9 dB SNR (±4.7), ranging from 20.1 to -8.7 dB SNR. Fig. 1c shows the individual results as a function of PTA, the more negative the value, the better the performance. The linear regression model SRT80_AV ~ Intercept + age x PTA + Lip-reading + MoCa (R² = 0.63, Supplementary S4b) showed a significant influence of PTA (β = 0.66, p < 10⁻³, Fig. 1d), lip-reading performance (β = -0.28, p = 0.004, Supplementary S7a), and interaction age x PTA (β = 0.18, p = 0.05), but not of age (p = 0.85) nor MoCA (p = 0.57) on SRT80_AV. However, the total influence of age on SRT80_AV can be assessed using the linear regression model SRT80_AV

~ Intercept + age (R² = 0.22, Supplementary S4c). This latter showed a significant effect (β = 0.46, p < 10⁻³, Supplementary S6b). The total influence of PTA was also assessed but did not show any difference from the previous relationships (Supplementary S4d). These findings are consistent with existing knowledge that increased hearing thresholds negatively affect speech comprehension in the AV modality, whereas age alone does not (Gordon & Allen, 2009; Huyse et al., 2014; Tye-Murray et al., 2010).

We hypothesize that hearing loss might enhance speech audio-visual integration. AV gain, which quantifies the behavioral benefit of adding visual cues to auditory information, varied from -0.5 to 22.4 dB SNR with a mean of 4.5 dB SNR (±4). Fig. 3a shows the individual results as a function of PTA. Three participants had no or negative AV gain (-0.58, -0.39, -0.14 dB SNR). The linear regression model AV Gain ~ Intercept + age x PTA + Lip-reading + MoCa (R² = 0.33, Supplementary S5b) showed a significant influence of PTA (β = 0.63, p < 10⁻³, Fig. 3b) and lip-reading performance (β = 0.25, p = 0.05, Supplementary S6b), but not of age (p = 0.22), MoCA (p = 0.64) nor interaction age x PTA (p = 0.93) on AV gain. The total effect of age on AV gain was assessed with the linear regression model AV Gain ~ Intercept + age (Supplementary S5c). It did not show any influence. The total influence of PTA was also assessed but did not show any difference from the previous relationships
<figure><img src="image_7.png" /><figcaption>**Fig. 2.** Lip-reading scores (Visual-only) as a function of age (a: raw data) and residuals (b, factoring out PTA and MoCA scores), and as a function of PTA (c: raw data) and residuals (d, factoring out age and MoCA scores).</figcaption></figure>

Age has a negative effect on lip-reading ability; PTA has no effect when age is factored out.

Black dots represent individual data. The red cross represents the mean. Dashed lines represent the BIAP classification: normal hearing (0-19 dB HL), mild hearing loss (20-39 dB HL) and moderate hearing loss (40-70 dB HL). The left box shows the effect of age (in years) on lip-reading scores: raw data in a (% of words correctly understood), residuals when controlling for PTA and MoCA scores in b. The right box shows the effect of PTA (dB HL) on lip-reading scores: raw data in c, residuals when controlling for age and MoCA scores in d.

(Supplementary S5d). Despite the significant relationship observed in the linear regression model, visual inspection of Fig. 3b suggests that AV gain and PTA do not follow a strictly linear pattern. The variability of AV gain appears to increase with PTA. We found significant heteroscedasticity in the residuals of the model (Breusch-Pagan test, p = 0.02). To ensure that these limitations did not significantly affect our results, we fitted a generalized linear model (GLM) with a gamma distribution and a log link ($R^2 = 0.33$) and obtained similar results.

Given the observed variability in AV gain, we further examined whether AV gain differed across hearing categories based on the BIAP classification. Looking at the distribution of the individual data in Fig. 3a and b, which plots AV gain as a function of PTA, we observe a trend towards better AV gain improvement once the hearing threshold reaches 40 - 50 dB HL (BIAP cut-off for moderate HL). Therefore, we categorized the data based on the BIAP classification and performed an ANOVA and *post-hoc* comparison with Tukey-Kramer correction. This analysis revealed a significant group effect (F=7.4, p=0.001), with the moderate HL group (mean: 6.0 dB SNR) showing significantly (p<10⁻³) greater AV gain than the normal-hearing group (mean: 2.9 dB SNR). Our results confirm our hypothesis that AV gain is enhanced from a certain degree of hearing loss.

### 3.3. Hearing aid use

To further investigate the potential role of auditory rehabilitation, we included hearing aid use as an additional independent variable in the regression models. This variable was coded as binary (user vs non-user). When added to the model Lip-reading ~ Intercept + age + MoCa + PTA x HA use, no significant effect of hearing aid use was observed on lip-reading performance (β = -0.17, p = 0.66). This result suggests that the absence of auditory rehabilitation does not enhance visual-only speech perception in case of mild to moderate HL. Including the HA variable in our model did not change previous results.

In contrast, we observed a significant negative effect of hearing aid use on AV gain in the model AV Gain ~ Intercept + age + Lip-reading + MoCa + PTA x HA use (β = -1.01, p = 0.002), These findings suggest that auditory rehabilitation reduces the audio-visual compensation induced by hearing loss. As mentioned above, including the HA variable in our model did not change previous results.

## 4. Discussion

The aim of this study was to clarify the different factors that may positively and negatively influence AV integration of speech in case of mild to moderate HL. We tested a cohort of 65 participants aged 50 to 85
AV Gain

<figure><img src="image_8.png" /><figcaption>**Fig. 3.** Audio-visual (AV) gain in function of raw PTA (a) and residuals (b) when age, MoCA scores and lip-reading scores are controlled. AV gain increases with mild to moderate hearing loss. Black dots represent individual data. The red cross represents the mean. a) Raw AV gain (dB SNR) according to raw PTA (dB HL). Dashed lines represent the BIAP classification: normal hearing (0-19 dB HL), mild hearing loss (20-39 dB HL) and moderate hearing loss (40-70 dB HL). b) Regression showing AV gain residuals according to PTA residuals when age, MoCA scores and lip-reading scores are controlled.</figcaption></figure>

years, ranging from normal hearing to moderate HL (PTA: 4 to 63 dB HL). The distribution according to the BIAP classification was relatively balanced (40% of normal-hearing, 25% of mild HL, 35% of moderate HL), providing a continuum from normal to moderate hearing impairment. The etiology of the hearing deficit was presbycusis. Among the hearing-impaired participants, 65% had been wearing hearing aids for an average of 5 years (1 week to 19 years). All subjects had normal or corrected-to-normal vision. Half of the participants exhibited mild cognitive impairment (19<MoCA<26), evenly distributed between normal-hearing and hearing-impaired participants. Cognitive decline was not associated with age or hearing thresholds. However, we included the cognitive score as a covariate in the statistical models to control for its potential confounding effect on the results.

## 4.1. Auditory speech comprehension declines with hearing loss

As expected, and in line with the literature, auditory comprehension in noise was negatively influenced by HL severity, when controlling for age and cognition (Bestel et al., 2022), and negatively influenced by age (when assessing its total – direct and indirect– influence; Figure 4a; Schneider et al., 2002; Tun et al., 2012).

## 4.2. Visual speech comprehension (lip-reading) declines with age but does not increase with hearing loss

Lip-reading was assessed by a validated, standardized and reproducible test (Audio-visual French Matrix Le Rhun et al., 2024), which measured the number of words correctly identified within sentences. We used a closed-set format, as the open-set format proved too difficult for the participants. Test variability was comparable to that reported for other audio-visual matrix tests (Jamaluddin, 2016; Llorach et al., 2022; O'Beirne et al., 2015; Trounson, 2012; van de Rijt et al., 2019).

Age had a negative impact on visual (lip-reading) performance (Fig. 4a). This age-related decline in lip-reading abilities has been well-documented in the normal-hearing population (Irion et al., 1971; Sommers et al., 2005; Tye-Murray et al., 2010, 2016), even when controlling for visual acuity. Previous studies have attributed poorer lip-reading in older adults to age-related decline in spatial working memory and processing speed (Feld & Sommers, 2009). In addition, slower access to long-term memory and reduced rehearsal speed, both strongly associated with age, negatively affect visual speech decoding (Rönnberg, 1990). Although we did not find a relationship between MoCA scores and lip-reading performance, existing literature suggests that lip-reading performance is related to cognitive abilities, which are known to decline with age. As a screening test, the MoCA may not be sufficient to fully capture the effects described above.

Conversely, mild to moderate HL had no positive effect on visual-only performance, and did not prevent the age-related decline, suggesting auditory deficits do not drive compensatory effects in unimodal visual processing of speech. Although counterintuitive, these findings have been previously reported in the literature (Tye-Murray et al., 2007). Our test material, which equally challenges both unimodal and bimodal processing in normal-hearing listeners and hearing-impaired listeners, combined with the statistical models we used, confirms that mild to moderate HL does not influence lip-reading improvement in adults over 50. Similarly, the use of hearing aids did not affect visual speech processing in this population.

Interestingly, as HL progresses from severe to profound, some studies have reported enhanced lip-reading performance in participants with severe to profound HL (prior to cochlear implantation) compared to normal-hearing listeners (Anderson et al., 2017; Rouger et al., 2007; Stropahl et al., 2017; Weglage et al., 2024). We hypothesize that this improvement in lip-reading may occur after a certain period of auditory deprivation and/or HL severity (Fig. 4b). These results raise the possibility of HL-induced plasticity within speech and phonological networks. Previous work has shown that cochlear implant candidates (individuals with severe HL) exhibit greater recruitment of the phonological network while watching silent lip movements compared to normal-hearing controls (Burton et al., 2005; Suh et al., 2009). This enhancement of neural activity correlates significantly with lip-reading performance (Lee et al., 2007; Suh et al., 2009), has been described as a predictor of cochlear implant success and protects against the maladaptive reorganization of right hemisphere networks (Lazard et al., 2014; Lazard & Giraud, 2017). Functional imaging data examining lip-reading processing in mild to moderate hearing-impaired listeners are lacking. However, in this population, Campbell & Sharma (2014) showed changes in cortical resource allocation, with a decreased activation in the temporal cortex and an increased activation in frontal areas, associated with poorer speech understanding in noise. We hypothesize that severe HL exerts a top-down plastic pressure on frontal and occipital areas, enhancing visual processing (Fig. 4b). A cohort of more severe hearing-impaired listeners should be recruited to confirm this hypothesis and to disentangle the effects of deafness duration and HL severity.

## 4.3. Audio-visual comprehension declines with hearing loss

Audio-visual performance was negatively influenced by HL and
a

<figure><img src="image_9.png" /></figure>

<figure><img src="image_10.png" /><figcaption>Fig. 4. Schematic representation of the influence of moderate (a) and severe (b) hearing loss, age and hearing aid use on unimodal modalities and audio-visual integration (AVI)</figcaption></figure>

The grey rectangles represent the modalities: Ao for Auditory only, processed in the primary auditory cortex in the superior temporal gyrus; Vo for Visual only, processed in the primary visual cortex in the occipital cortex; AVG for audio-visual gain, which was used as a proxy for AVI in the present study. The superior temporal sulcus (STS) is the putative functional area for AV integration (Arnal et al., 2009). Green arrows indicate a positive influence, red arrows indicate a negative influence of the tested factors: hearing loss (HL), age and hearing aid (HA) use on the performance of the three modalities.

a) Influence of moderate hearing loss (Mod HL), age and hearing aid (HA) use.

Age has a negative effect on lip-reading abilities (Vo) but does not affect auditory comprehension (Ao) and audio-visual (AV) gain. In contrast, moderate hearing loss has a negative effect on auditory comprehension (Ao) but no effect on lip-reading ability (Vo). However, it has a positive effect on AV gain (AVG). Hearing aid (HA) use decreases significantly AV gain, counteracting the effect of moderate hearing loss.

The box “Mild cognitive decline” means that cognitive assessment was included in the statistical models used to draw these conclusions. We found no effect of this latter but believe that some performance is related to cognitive abilities, which are known to decline with age. The MoCA used here may not be sufficient to fully capture subtle effects. In conclusion, we hypothesize that hearing loss induces positive plastic changes in high-level multimodal integration areas, which partially compensates for the negative effect of age on visual-only processing and the negative effect of hearing loss on auditory processing.

b) Extrapolation to severe hearing loss (Sev HL) based on the literature (Campbell & Sharma, 2014; Lazard et al., 2014; Lazard & Giraud, 2017; Lee et al., 2007; Strelnikov et al., 2013; Suh et al., 2009). Once HL is severe, the literature shows improved lip-reading abilities and increased activation of the visual phonological network (including frontal cortex, represented by the pink rectangle). Involvement of this network correlates with lip-reading performance and predicts CI success. We suggest a positive top-down plastic pressure of severe HL on visual processing in primary areas and at a higher central level, from the moment visual information becomes indispensable.

positively by lip-reading when controlling for age and cognition. Age had a negative influence, mainly through its effects on HL and lip-reading ability. While these effects demonstrate overall performance effects in audio-visual conditions, they cannot help us to assess whether these effects are due to changes in auditory processing alone, visual, or the integration of the two. To focus on AV integration we used AV gain (AV – Ao) to assess how visual input can modulate auditory processing.

## 4.4. Audio-visual integration increases with hearing loss

Audio-visual gain was positively influenced by HL and, to a lesser extent by lip-reading ability. This suggests that visual information increasingly complements auditory input as hearing loss progresses (Fig. 3b and model in Fig. 4a). This compensatory mechanism appears to operate specifically at the level of AV integration, as reflected by AV gain. In line with this interpretation, we found that hearing aid use significantly reduced AV gain, suggesting that auditory rehabilitation reduces the plastic pressure driving enhanced AV integration. Conversely, age had no significant effect on AV gain, either when controlling for other variables (direct influence) or when assessing its overall contribution (total effect). This suggests that the effect of age on Ao and AV performance may influence a shared component of both tasks (such as auditory processing or working memory, Tun et al., 2012). Nevertheless, we hypothesize that hearing loss induces positive plastic changes in high-level multimodal integration areas, which partially compensates for the negative effect of age on visual-only processing and

the negative effect of hearing loss on auditory processing.

In comparison with the literature, a study based on a similar paradigm (speech comprehension task in background noise) found no greater AV gain in mild hearing-impaired listeners compared to normal-hearing listeners (Middelweerd & Plomp, 1987). These results suggest that the impact of HL on AV integration may become more pronounced as HL severity increases. Another study comparing elderly participants with normal and moderate HL did not find better AV integration skills in the second group (Tye-Murray et al., 2007). However, only the Ao condition was set to an individual SRT50 (rather than SRT80), and the corresponding individual SNR was used to test consonant, word, and sentence recognition across the three modalities. This paradigm did not account for inter-individual variability in the Vo condition and may not have sufficiently engaged AV integration mechanisms in normal-hearing listeners, as the tasks were likely too easy for them. By contrast, our choice of an individual SRT80 assessed for both unimodal and bimodal processing may have better revealed specific AV integration abilities in hearing-impaired participants. Our finding suggests that AV gain increases above a certain HL threshold, which may explain the lack of differences between normal-hearing listeners and mild hearing-impaired listeners reported by Middelweerd & Plomp (1987).

Unfortunately, the population with severe HL has been poorly studied in terms of AV integration, as the Ao component becomes barely usable under noisy conditions and without hearing aids. Related studies have tested Ao and Vo performance, but to our knowledge, none have directly assessed AV integration in this population (Jeong Lee et al.,
2005; Lazard et al., 2014; Suh et al., 2009). Fig. 4b is therefore hypothetical, based on extrapolations from our data and the results of Jeong Lee et al. (2005), Suh et al. (2009), and Lazard et al. (2014). It refers only to Vo test results, as no AV data is currently available for this clinical sample. We encourage future studies to investigate AV integration across the full spectrum of hearing, from normal to severe HL, in order to identify critical stages of plastic adaptation, and to use neurofunctional imaging to assess our hypotheses outlined in Fig. 4.

## 5. Conclusion

This work investigates auditory, visual and combined speech processing using AV gain as a proxy for AV integration in a sample of over-50s with normal to moderately impaired hearing. Our findings show that mild to moderate HL does not improve lip-reading ability, challenging the clinical assumption that lip-reading dependence increases linearly with hearing loss severity. This assumption may hold only for moderate to severe hearing deficits, where reliance on lip-reading becomes mandatory. Conversely, age negatively affected visual (lip-reading) performance, but showed no direct impact on auditory or AV speech processing. HL severity has a direct positive effect on AV integration, without influencing visual speech processing. We therefore speculate that hearing loss induces positive plastic changes on high-order multi-modal integration areas, which partially compensates for the negative effect of age on visual-only processing and the negative effect of hearing loss on auditory processing. Importantly, hearing aid use was associated with reduced AV gain, suggesting that auditory restoration moderates the compensatory mechanisms driven by mild to moderate HL.

Building on the literature indicating that cochlear implant candidates show improved lip-reading abilities, we hypothesize that severe HL triggers top-down plastic changes that enhance visual speech processing by recruiting additional unimodal and multimodal areas. These hypotheses need to be confirmed by neurofunctional imaging.

From our behavioral results, we conclude that mild to moderate HL enhances AV integration by improving the benefit gained from adding visual cues to auditory speech, despite the negative influence of age on unimodal processing. However, due to limited research on individuals with severe HL, the trajectory of AV integration across the full spectrum of hearing loss remains unclear.

## CRediT authorship contribution statement

**Tanguy Delmas:** Writing – review & editing, Writing – original draft, Methodology, Investigation, Formal analysis, Conceptualization.
**Mathieu Pham Van Cang:** Writing – review & editing, Formal analysis.
**Grégory Gerenton:** Writing – review & editing, Software, Methodology.
**Jérôme Lefeuvre:** Writing – review & editing, Keith B. Doelling: Writing – review & editing, Methodology, Funding acquisition, Formal analysis, Conceptualization.
**Luc H. Arnal:** Writing – review & editing, Supervision, Project administration, Methodology, Funding acquisition.
**Diane S. Lazard:** Writing – review & editing, Writing – original draft, Supervision, Project administration, Methodology, Funding acquisition, Conceptualization.

## Acknowledgments

We thank Audition Lefeuvre, Audition Marc Boulet, Audition Santé and Centre Audition Godinho for their help in recruiting participants.

This work was funded by Fondation Pour l'Audition (FPA IDA06). This work has benefited from a French government grant managed by the Agence Nationale de la Recherche under the France 2030 program, reference ANR-23-IAHU-0003. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

## Supplementary materials

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.heares.2025.109355.

## Data availability

Data will be made available on request.

## References

Anderson, C.A., Lazard, D.S., Hartley, D.E.H., 2017. Plasticity in bilateral superior temporal cortex: Effects of deafness and cochlear implantation on auditory and visual speech processing. Hear. Res. 343, 138-149. https://doi.org/10.1016/j.heares.2016.07.013.

Arnal, L.H., Morillon, B., Kell, C.A., Giraud, A.L., 2009. Dual neural routing of visual facilitation in speech processing. Journal of Neuroscience 29 (43), 43. Article.

Arnal, L.H., Wyart, V., Giraud, A.L., 2011. Transitions in neural oscillations reflect prediction errors generated in audiovisual speech. Nat. Neurosci. 14 (6), 797-801. https://doi.org/10.1038/nn.2810.

Baum, S.H., Stevenson, R., 2017. Shifts in Audiovisual Processing in Healthy Aging. Curr. Behav. Neurosci. Rep. 4 (3), 198-208. https://doi.org/10.1007/s40473-017-0124-7.

Bernstein, L.E., Auer, E.T., Takayanagi, S., 2004. Auditory speech detection in noise enhanced by lipreading. Speech. Commun. 44 (1), 5-18. https://doi.org/10.1016/j.specom.2004.10.011.

Bestel, J., Legris, E., Rembaud, F., Mom, T., Iii, J.J.G., 2022. Speech understanding in diffuse steady noise in typically hearing and hard of hearing listeners. PLoS. One 17 (9), e0274435. https://doi.org/10.1371/journal.pone.0274435.

Brand, T., Kissner, S., Jürgens, T., Berg, D., & Kollmeier, B. (2011, mars 5). Adaptive Algorithmen zur Bestimmung der 80%-Sprachverständlichkeitsschwelle.

Brand, T., Kollmeier, B., 2002. Efficient adaptive procedures for threshold and concurrent slope estimates for psychophysics and speech intelligibility tests. J. Acoust. Soc. Am. 111 (6). https://doi.org/10.1121/1.1479152. Article 6.

Burton, M.W., LoCasto, P.C., Krebs-Noble, D., Gullapalli, R.P., 2005. A systematic investigation of the functional neuroanatomy of auditory and visual phonological processing. Neuroimage 26 (3), 647-661. https://doi.org/10.1016/j.neuroimage.2005.02.024.

Campbell, J., Sharma, A., 2014. Cross-Modal Re-Organization in Adults with Early Stage Hearing Loss. PLoS. One 9 (2), e90594. https://doi.org/10.1371/journal.pone.0090594.

Ciorba, A., Bianchini, C., Pelucchi, S., Pastore, A., 2012. The impact of hearing loss on the quality of life of elderly adults. Clin. Interv. Aging 159. https://doi.org/10.2147/CIA.S26059.

Collins, J.G., 1997. Prevalence of selected chronic conditions: United States, 1990-1992. Vital and Health Statistics. Series 10. Data from the National Health Survey 194, 1-89.

Dawes, P., Reeves, D., Yeung, W.K., Holland, F., Charalambous, A.P., Côté, M., David, R., Helmer, C., Laforce, R., Martins, R.N., Politis, A., Pye, A., Russell, G., Sheikh, S., Sirois, M.J., Sohrabi, H.R., Thodi, C., Gallant, K., Nasreddine, Z., Leroi, I., 2023. Development and validation of the Montreal cognitive assessment for people with hearing impairment (MoCA-H). J. Am. Geriatr. Soc. 71 (5), 1485-1494. https://doi.org/10.1111/jgs.18241.

Dias, J.W., McClaskey, C.M., Harris, K.C., 2021. Audiovisual speech is more than the sum of its parts: Auditory-visual superadditivity compensates for age-related declines in audible and lipread speech intelligibility. Psychol. Aging 36 (4), 520-530. https://doi.org/10.1037/pag0000613.

Feld, J.E., Sommers, M.S., 2009. Lipreading, Processing Speed, and Working Memory in Younger and Older Adults. Journal of Speech, Language, and Hearing Research : JSLHR 52 (6), 1555. https://doi.org/10.1044/1092-4388(2009/08-0137).

Gordon, M.S., Allen, S., 2009. Audiovisual speech in older and younger adults: Integrating a distorted visual signal with speech in noise. Exp. Aging Res. 35 (2), 202-219. https://doi.org/10.1080/03610730902720398.

Grant, K.W., Seitz, P.F., 1998. Measures of auditory-visual integration in nonsense syllables and sentences. J. Acoust. Soc. Am. 104 (4), 2438-2450. https://doi.org/10.1121/1.423751.

Grant, K.W., Seitz, P.F., 2000. The use of visible speech cues for improving auditory detection of spoken sentences. J. Acoust. Soc. Am. 108 (3), 1197-1208. https://doi.org/10.1121/1.1288668.

Grant, K.W., Walden, B.E., Seitz, P., 1998a. Auditory-visual speech recognition by hearing-impaired subjects: Consonant recognition, sentence recognition, and auditory-visual integration. J. Acoust. Soc. Am. 103 (5 Pt 1), 2677-2690. https://doi.org/10.1121/1.422788.

Grant, K.W., Walden, B.E., Seitz, P.F., 1998b. Auditory-visual speech recognition by hearing-impaired subjects: Consonant recognition, sentence recognition, and auditory-visual integration. J. Acoust. Soc. Am. 103 (5), 2677-2690. https://doi.org/10.1121/1.422788.

Holland, P.W., 1986. Statistics and Causal Inference. J. Am. Stat. Assoc. 81 (396), 945-960. https://doi.org/10.1080/01621459.1986.10478354.

Huyse, A., Leybaert, J., Berthommier, F., 2014. Effects of aging on audio-visual speech integration. J. Acoust. Soc. Am. 136 (4), 1918-1931. https://doi.org/10.1121/1.4894685.

Hygge, S., R, önnberg J., Larsby, B., Arlinger, S., 1992. Normal-Hearing and Hearing-Impaired Subjects' Ability to Just Follow Conversation in Competing Speech,
Reversed Speech, and Noise Backgrounds. Journal of Speech, Language, and Hearing Research 35 (1), 208-215. https://doi.org/10.1044/jshr.3501.208.

Irion, P.E., Oyer, H.J., Hardick, E.J., 1971. LIPREADING PERFORMANCE AS RELATED TO MEASUREMENTS OF VISION*. Optometry and Vision Science 48 (3), 231.

Jamaluddin, S. A. (2016). Development and evaluation of the digit triplet and auditory-visual matrix sentence tests in Malay.

Jeong Lee, H., Kang, E., Oh, S.H., Kang, H., Soo Lee, D., Chul Lee, M., Kim, C.S., 2005. Preoperative differences of cerebral metabolism relate to the outcome of cochlear implants in congenitally deaf children. Hear. Res. 203 (1), 2-9. https://doi.org/10.1016/j.heares.2004.11.005.

Layer, N., Weglage, A., Müller, V., Meister, H., Lang-Roth, R., Walger, M., Murray, M.M., Sandmann, P., 2022. Electrophysiological differences and similarities in audiovisual speech processing in CI users with unilateral and bilateral hearing loss. Curr. Res. Neurobiol. 3, 100059. https://doi.org/10.1016/j.crneur.2022.100059.

Lazard, D.S., Giraud, A.L., 2017. Faster phonological processing and right occipito-temporal coupling in deaf adults signal poor cochlear implant outcome. Nat. Commun. 8 (1). https://doi.org/10.1038/ncomms14872. Article 1.

Lazard, D.S., Innes-Brown, H., Barone, P., 2014. Adaptation of the communicative brain to post-lingual deafness. Evidence from functional imaging. Hear. Res. 307, 136-143. https://doi.org/10.1016/j.heares.2013.08.006.

Le Rhun, L., Llorach, G., Delmas, T., Suied, C., Arnal, L.H., Lazard, D.S., 2024. A standardised test to evaluate audio-visual speech intelligibility in French. Heliyon. 10 (2), e24750. https://doi.org/10.1016/j.heliyon.2024.e24750.

Lee, H.J., Truy, E., Mamou, G., Sappey-Marinier, D., Giraud, A.L., 2007. Visual speech circuits in profound acquired deafness: A possible role for latent multimodal connectivity. Brain 130 (11), 2929-2941. https://doi.org/10.1093/brain/awm230.

Lin, F.R., Yaffe, K., Xia, J., Xue, Q.L., Harris, T.B., Purchase-Helzner, E., Satterfield, S., Ayonayon, H.N., Ferrucci, L., Simonsick, E.M., Health ABC Study Group, for the, 2013. Hearing Loss and Cognitive Decline in Older Adults. JAMA Intern. Med. 173 (4), 293-299. https://doi.org/10.1001/jamainternmed.2013.1868.

Llorach, G., Kirschner, F., Grimm, G., Zokoll, M.A., Wagener, K.C., Hohmann, V., 2022. Development and evaluation of video recordings for the OLSA matrix sentence test. Int. J. Audiol. 61 (4), 311-321. https://doi.org/10.1080/14992027.2021.1930205.

Mick, P., Kawachi, I., Lin, F.R., 2014. The Association between Hearing Loss and Social Isolation in Older Adults. Otolaryngology-Head and Neck Surgery 150 (3), 378-384. https://doi.org/10.1177/0194599813518021.

Middelweerd, M.J., Plomp, R., 1987. The effect of speechreading on the speech-reception threshold of sentences in noise. J. Acoust. Soc. Am. 82 (6), 2145-2147. https://doi.org/10.1121/1.395659.

O'Beirne, G.A., Trounson, R.H., McClelland, A.D., Jamaluddin, S.A., Maclagan, M.A., 2015. Development of an auditory-visual matrix sentence test in New Zealand English. Journal of International Advanced Otology 11 (Supplement 1). Article Supplement 1. 12th European Federation of Audiology Societies (EFAS) Congress.

Peelle, J.E., Sommers, M.S., 2015. Prediction and constraint in audiovisual speech perception. Cortex 68, 169-181. https://doi.org/10.1016/j.cortex.2015.03.006.

Rönnberg, J., 1990. Cognitive and communicative function: The effects of chronological age and "handicap age. European Journal of Cognitive Psychology 2 (3), 253-273. https://doi.org/10.1080/09541449008406207.

Ross, L.A., Saint-Amour, D., Leavitt, V.M., Javitt, D.C., Foxe, J.J., 2007. Do You See What I Am Saying? Exploring Visual Enhancement of Speech Comprehension in Noisy Environments. Cerebral Cortex 17 (5), 1147-1153. https://doi.org/10.1093/cercor/bhl024.

Rouger, J., Lagleyre, S., Fraysse, B., Deneve, S., Deguine, O., Barone, P., 2007. Evidence that cochlear-implanted deaf patients are better multisensory integrators. Proc. Natl. Acad. Sci. U S A. 104 (17). https://doi.org/10.1073/pnas.0609419104. Article 17.

Schneider, B.A., Daneman, M., Pichora-Fuller, M.K., 2002. Listening in aging adults: From discourse comprehension to psychoacoustics. Canadian Journal of Experimental Psychology / Revue canadienne de psychologie expérimentale 56 (3), 139-152. https://doi.org/10.1037/h0087392.

Schreitmüller, S., Frenken, M., Bentz, L., Ortmann, M., Walger, M., Meister, H., 2018. Validating a Method to Assess Lipreading, Audiovisual Gain, and Integration During Speech Reception With Cochlear-Implanted and Normal-Hearing Subjects Using a

Talking Head. Ear Hear. 39 (3), 503. https://doi.org/10.1097/AUD.0000000000000502.

Sommers, M.S., Tye-Murray, N., Spehar, B., 2005. Auditory-Visual Speech Perception and Auditory-Visual Enhancement in Normal-Hearing Younger and Older Adults. Ear Hear. 26 (3), 263.

Stevenson, R.A., Nelms, C.E., Baum, S.H., Zurkovsky, L., Barense, M.D., Newhouse, P.A., Wallace, M.T., 2015. Deficits in audiovisual speech perception in normal aging emerge at the level of whole-word recognition. Neurobiol. Aging 36 (1). https://doi.org/10.1016/j.neurobiolaging.2014.08.003. Article 1.

Strelnikov, K., Rouger, J., Barone, P., Deguine, O., 2009. Role of speechreading in audiovisual interactions during the recovery of speech comprehension in deaf adults with cochlear implants. Scand. J. Psychol. 50 (5), 437-444. https://doi.org/10.1111/j.1467-9450.2009.00741.x.

Strelnikov, K., Rouger, J., Demonet, J.-F., Lagleyre, S., Fraysse, B., Deguine, O., Barone, P., 2013. Visual activity predicts auditory recovery from deafness after adult cochlear implantation. Brain, 136 (12), 3682-3695. https://doi.org/10.1093/brain/awt274.

Stropahl, M., Debener, S., 2017. Auditory cross-modal reorganization in cochlear implant users indicates audio-visual integration. Neuroimage Clin. 16, 514-523. https://doi.org/10.1016/j.nicl.2017.09.001.

Stropahl, M., Plotz, K., Schönfeld, R., Lenarz, T., Sandmann, P., Yovel, G., De Vos, M., Debener, S., 2015. Cross-modal reorganization in cochlear implant users: Auditory cortex contributes to visual face processing. Neuroimage 121, 159-170. https://doi.org/10.1016/j.neuroimage.2015.07.062.

Stropahl, M., Schellhardt, S., Debener, S., 2017. McGurk stimuli for the investigation of multisensory integration in cochlear implant users: The Oldenburg Audio Visual Speech Stimuli (OLAVS). Psychon. Bull. Rev. 24 (3). https://doi.org/10.3758/s13423-016-1148-9. Article 3.

Suh, M.W., Lee, H.J., Kim, J.S., Chung, K.C., Oh, S.H., 2009. Speech experience shapes the speechreading network and subsequent deafness facilitates it. Brain 132 (10), 2761-2771. https://doi.org/10.1093/brain/awp159.

Sumby, W.H., Pollack, I., 2005. Visual Contribution to Speech Intelligibility in Noise. J. Acoust. Soc. Am. 26 (2), 212-215. https://doi.org/10.1121/1.1907309.

Trounson, R. H. (2012). Development of the UC Auditory-Visual Matrix Sentence Test.

Tun, P.A., Williams, V.A., Small, B.J., Hafter, E.R., 2012. The Effects of Aging on Auditory Processing and Cognition. Am. J. Audiol. 21 (2), 344-350. https://doi.org/10.1044/1059-0889(2012)12-0030.

Tye-Murray, N., Sommers, M.S., Spehar, B., 2007. Audiovisual Integration and Lipreading Abilities of Older Adults with Normal and Impaired Hearing. Ear Hear. 28 (5), 656. https://doi.org/10.1097/AUD.0b013e31812f7185.

Tye-Murray, N., Sommers, M., Spehar, B., Myerson, J., Hale, S., 2010. Aging, Audiovisual Integration, and the Principle of Inverse Effectiveness. Ear Hear. 31 (5), 636-644. https://doi.org/10.1097/AUD.0b013e3181dd7ff.

Tye-Murray, N., Spehar, B., Myerson, J., Hale, S., Sommers, M., 2016. Lipreading and audiovisual speech recognition across the adult lifespan: Implications for audiovisual integration. Psychol. Aging 31 (4), 380-389. https://doi.org/10.1037/pag0000094.

van de Rijt, L.P.H., Roye, A., Mylanus, E.A.M., van Opstal, A.J., van Wanrooij, M.M., 2019. The Principle of Inverse Effectiveness in Audiovisual Speech Perception. Front. Hum. Neurosci. 13. https://www.frontiersin.org/articles/10.3389/fnhum.2019.00335.

Wassenhove, V.van, Grant, K.W., Poeppel, D., 2005. Visual speech speeds up the neural processing of auditory speech. In: Proceedings of the National Academy of Sciences of the United States of America, 102, p. 1181-1186. https://doi.org/10.1073/PNAS.0408949102.

Weglage, A., Layer, N., Meister, H., Müller, V., Lang-Roth, R., Walger, M., Sandmann, P., 2024. Changes in visually and auditory attended audiovisual speech processing in cochlear implant users: A longitudinal ERP study. Hear. Res. 447, 109023. https://doi.org/10.1016/j.heares.2024.109023.

Zhou, X., Innes-Brown, H., McKay, C.M., 2019. Audio-visual integration in cochlear implant listeners and the effect of age difference. J. Acoust. Soc. Am. 11.