Regular articleMusical training improves the ability to understand speech-in-noise in older adults
Introduction
Difficulties with hearing are one of the most commonly reported health issues in older adults. Rates of hearing loss approximately double from the second through seventh decade of life, with the degree of hearing loss defined by a pure-tone average (PTA; 0.5, 1, 2, and 4 kHz) of greater than 25 dB in the better ear (Yamasoba et al., 2013). Nearly 80% of adults over age 80 meet the criteria for hearing loss (Yamasoba et al., 2013). Age-related decline in auditory perception can vary substantially between individuals and often includes difficulties understanding speech in adverse listening situations, such as when there is significant background noise (Pichora-Fuller et al., 1995, Robert Frisina and Frisina, 1997, Schneider et al., 2010). These age-related changes in auditory perception are thought to reflect both bilateral sensorineural hearing loss, due to physical changes in the inner ear (Gates and Mills, 2005, Stenklev and Laukli, 2004), and changes in the central auditory system (Alain et al., 2006, Schneider et al., 2010). In addition to the social isolation that can arise from hearing-related communication difficulties, age-related decline in hearing has also been associated with cognitive decline (Lin et al., 2013, Mick et al., 2014). Given the prevalence and negative outcomes of age-related decline in hearing abilities, finding ways to prevent, mitigate, or delay these changes is of utmost importance, and evidence suggests that musical training may be a useful intervention for preserving or enhancing auditory abilities in older adults.
It is well known that musicians have enhanced auditory processing abilities (Kraus and Chandrasekaran, 2010), and these benefits are paralleled by an enhanced ability to understand speech in noisy environments (Parbery-clark et al., 2009, Zendel et al., 2015). Findings from cross-sectional studies suggest that musical training causes neuroplasticity along the auditory pathway from the brainstem to the cortex, and this neuroplasticity leads to enhanced auditory abilities. Recent work suggests that the benefit of musical training may be related to enhanced connections between the auditory and motor systems (Du and Zatorre, 2017). Musical training could therefore facilitate speech processing via the speech-motor system, which has been shown to be an important component of speech perception, particularly when speech is presented in background noise (Du et al., 2014). Electrophysiological studies have shown that musicians exhibit enhanced frequency-following responses and auditory event-related potentials (ERPs; i.e., N1-P2) compared with nonmusicians (e.g., Koelsch et al., 1999, Pantev et al., 1998, Pantev et al., 2001, Shahin et al., 2003, Shahin et al., 2005, Wong et al., 2007). Longitudinal research in younger adults has provided support for the idea that improved auditory processing observed in musicians is due to neuroplasticity. For instance, several studies with random assignment and control groups have demonstrated that after musical training, participants have enhanced auditory abilities that are related to enhanced neurophysiological measurements (Fujioka et al., 2006, Kraus and White-Schwoch, 2015, Lappe et al., 2008, Tierney et al., 2015). Emerging evidence suggests that these enhanced auditory abilities can persist into old age, with older musicians being able to understand speech in noisy environments better than older nonmusicians (Parbery-Clark et al., 2011, Zendel and Alain, 2012). Further support for this idea comes from longitudinal research that used a nonmusic-based auditory training intervention and found that the ability to understand speech in noise can be improved in older adults with training (Anderson et al., 2013). However, no study has yet examined whether musical training in older adults can improve the ability to understand speech in noise.
Understanding speech in noise is a hierarchical process that occurs in multiple subcortical and cortical structures, and evidence suggests that musicianship and musical training can alter neural functions related to processing speech (Coffey et al., 2017). In older musicians, there is evidence that enhanced endogenous or attention-dependent processing contributes to the auditory benefit (Zendel and Alain, 2013, Zendel and Alain, 2014). Using ERPs recorded during a task that required perceptual segregation of concurrently occurring sounds, older musicians had enhanced late positivities that were dependent on attention being directed toward the task, compared with older nonmusicians and younger nonmusicians (Zendel and Alain, 2013, Zendel and Alain, 2014). Enhancements to subcortical processing of speech-in-noise in older musicians have also been observed (Parbery-Clark et al., 2012); however, these benefits are smaller than the subcortical enhancements in speech-in-noise processing observed in younger musicians, compared with nonmusicians (Parbery-clark, Skoe and Kraus, 2009). This pattern of results suggests that the benefit of musical training shifts from an exogenous processing benefit to an endogenous processing benefit as musicians age (Alain et al., 2014), which could be related to preserved cognitive abilities in older musicians including nonverbal memory and executive processes (Hanna-Pladdy and MacKay, 2011).
Overall, these findings suggest that musical training could be used in older adults as an engaging form of auditory training with the potential to improve the ability to understand speech in noisy environments. To determine if this is a possibility, we conducted a three-arm, single-blind, longitudinal training study with random assignment, where one group of older participants received musical training, one group served as an active control group by playing a 3D video-game, and one served as a no-contact control group. Previous studies where older adults were randomized into a musical training intervention and then compared to control groups have demonstrated that musical training can be used to improve cognitive abilities, mood, and quality of life (Bugos et al., 2007, Seinfeld et al., 2013). Thus, the goal of the present study was to examine if musical training could improve the ability to understand speech in noise by modifying the underlying functional neurophysiology. The ability to understand speech in noise and the associated event-related brain responses were assessed at 3 different timepoints: before training, midway through training, and after training.
There are a number of ways to assess the ability to understand speech in noise by varying both the target and the background noise. For example, different studies have used tones, phonemes, words, or full sentences as the target stimuli, and white noise, filtered white noise, or various forms of single- or multi-talker babble noise as the background noise (e.g., Billings et al., 2009, Kaplan-Neeman et al., 2006, Martin et al., 1997, Parbery-Clark et al., 2012, Pichora-Fuller et al., 1995). To best understand if musical training can improve the ability to understand speech-in-noise in the real world, we aimed to use ecological stimuli when possible. Accordingly, this paradigm included real words as the target stimuli and multi-talker babble as the background noise. This paradigm was similar to one used previously, where younger musicians exhibited an enhanced ability to understand words in background noise compared with younger nonmusicians (Zendel et al., 2015). In the study by Zendel et al. (2015), early event-related brain responses related to stimulus encoding were enhanced, whereas later responses related to semantic processing were reduced, in younger musicians compared with younger nonmusicians. This suggests that musical training enhanced the representation of an incoming speech stimulus, which facilitated later semantic access. This paradigm is therefore well suited to examine the impact of music lessons on older adults, as it is sensitive to the impact of musical training for both behavioral and neurophysiological measures and it is based on natural speech sounds.
Section snippets
Design
The study was designed as a three-arm single-blind longitudinal training study with random assignment. Participants were randomized into 3 groups using a stratified covariate-adaptive procedure (see below). Participants took part in 3 testing sessions. The pre-training session (Pre) took place before the intervention, the mid-training session (Mid) took place 3 months after the start of the intervention, and the post-training session (Post) took place 6 months after the onset of the
Results
The critical effects in the data analyses were based on Group by Session interactions, followed-up by a significant main effect of Session in the Music group, and nonsignificant effects of Session in the other 2 groups. To fully explore the data, other effects are reported as well. The 2 training groups (Music & Video) trained for a similar amount of time during the six-month training period [Music: 86.4 hours, SD = 34.4; Video: 72.3 hours, SD = 11.3; t (18) = 1.12, p = 0.28]. Alpha for
Discussion
Six months of self-directed music lessons improved the ability to understand speech in background noise in older adults. This improvement was related to an increased positivity over frontal-left electrodes from 200 to 1000 ms after the onset of a word. No increased positivity was observed during the passive listening condition, suggesting that the benefit was due to an attention-dependent cognitive mechanism. There was, however, a musical training–related increase in N1 amplitude during passive
Disclosure statement
The authors have no actual or potential conflicts of interest.
Acknowledgements
The authors thank Olivier Dussault, Charles-David Tremblay, Samira Mellah, and Mihaela Felezeu for assistance with data collection. Support for this research came from the Canada Research Chairs program, the GRAMMY Foundation, Fondation Caroline Durant, Fonds de Recherche du Québec–Santé, and Natural Sciences and Engineering Research Council of Canada Collaborative Research and Training Experience Program in Auditory Cognitive Neuroscience (NSERC–CREATE–ACN).
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