Research Article: J Phonet and Audiol
doi: 10.4172/2471-9455.1000120
Roberta M DiDonato and Aimée M Surprenant
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Keywords
Memory; Learning; Aging; Speech perception; Comprehension; Age-related hearing loss; Musicianship; Auditory processing; Aging cognition
Introduction
There is no doubt that older adults perform worse than younger adults on a variety of different memory tasks [1]. Cognitive explanations for this age-related memory decline have been focused on older adults’ reduced working memory capacity [2], slowed speed of processing [3] and decreased inhibitory control [4,5]. However, some types of memory appear to be either less prone to decline as a function of aging or are differentially affected by aging. For example, episodic memory (e.g., the recall of studied lists of words), shows a steep trajectory of decline, compared to semantic memory, (e.g., facts, vocabulary, general knowledge) which shows a gradual increase with age with a shallow trajectory of decline in the oldest adults [6]. Further, even within the same type of memory task (free-recall) there are large within and between-individual variations in performance [7].
Salthouse summarized the age differences in memory as follows: older adults have been shown to perform more poorly than younger adults on episodic, short- and long-term memory, and memory tasks that require explicit and controlled processes for a free-recall type response (e.g., the stimuli and task that will be used in the present study; recalling a novel set of medical instructions). Conversely, older adults perform similarly to younger adults when the memory is testing semantic information (such as facts or vocabulary), remote memories (from young adulthood), and those tasks that engage automatic and implicit processes for a recognition-type response (e.g. recognizing a synonym for a given word).
Thus, although there is agreement that some aspects of memory decline as a function of age, not all older adults will be similarly affected and not all types of memory abilities will decline to the same degree or with the same pattern [8]. Understanding the source of this variability advances understanding of the causal mechanisms that underlie the differences in performance between and within age groups. A growing body of evidence points to the possibility that reduced cognitive functioning is related to and could be substantially affected by, reductions in lower-level perceptual processing [9-14]. Therefore, the present study considers the hearing-listening changes that occur as a function of aging as a potential source for this variability [15].
Sensory and cognitive abilities are highly correlated. Understanding the nature of the relationship between cognition and hearing is particularly relevant since age-related hearing loss (ARHL) is the 3rd most prevalent chronic disorder among older adults [16]. Baltes and Lindenberger found that 94% of age-related variance in intellectual functioning was accounted for by perceptual functioning (vision and hearing). These authors concluded that the findings of a strong connection between sensory-perceptual and cognitive function in the aging adult requires investigations into the sources, factors and the mechanisms that are common to both domains [9].
In order to examine this relationship between ARHL and memory performance, we considered the complex ways in which hearinglistening abilities change as a function of aging. Therefore, we used a definition of ARHL that includes those aspects of hearing-listening that influence signal detection and processing for speech discrimination and language comprehension for communication purposes. ARHL is defined broadly as a combination of those auditory perceptual and processing deficits that occur as a function of age, with these changes beginning early in midlife [17-22].
There are several ways in which aspects of ARHL might interfere with the sub-lexical and lexical processes for communication success and listening ease [23-31]. The increased cognitive load arises from the need to recruit the additional top-down processes such as working memory, inhibition, monitoring, and attention for comprehension of the message for communication [32-40].
Importantly, ARHL is correlated with cognitive decline in the older adult population, specifically on tests of memory and executive dysfunction. Several recent studies demonstrated that the more significant the hearing loss, the greater the risk of developing dementia [41,42]. In addition, greater hearing loss was associated with a faster rate of incident cognitive impairment [43]. However, as [43] indicate, these findings demonstrate associative relationships through correlational analysis and therefore, do not imply causation or the direction of causation. The authors do suggest further research is needed into the potential causal mechanisms that may account for these associative relationships. The present study considers one suggested causal mechanism, that is, it is the listening effort arising from ARHL which interferes with the ability to encode sufficiently for recall memory performance [44].
Listening effort has been described previously as those attention and cognitive resources required for perceptual processing that supports speech perception for communication. This listening effort is greater for older adults compared to younger adults [45-47].
Therefore, two related hypotheses were considered for the present study. According to the effortfulness hypothesis [11,47-50] when individuals listen to a degraded signal (speaker, listener or environmental issues), successful speech discrimination comes at the cost of the limited capacity attentional resources for decoding the message for communication success [51]. In a similar manner, according to the Ease of Language Understanding model (ELU) [35], if the match between the stimuli and the long-term representation of the target in memory is rapid, automatic and implicit, then fewer explicit resources will be needed for comprehension of the message. If we can modify the speech message with enhancements (e.g., time-expansion) that precisely increases the fidelity of the speech message (e.g., increased vowel space, pause lengths, durations of consonant-vowel transitions) that promotes listening ease or a rapid match, then the explicit cognitive-linguistic resources should become more available for perceptual learning, comprehension, and elaborate encoding for later recall. Both of these hypotheses suggest that easier sub-lexical and lexical decoding of the auditory-verbal message for communication should result in more efficient learning and memory encoding for later recall. Also the suggestion is that resources for listening, learning, and remembering processes are limited and must be shared or re-allocated as needed. Therefore, these hypotheses suggest that those with ease of auditory processing (sub-lexical), exceptional listening abilities (precisely tuned neural encoding of pitch, timing and timbre), or greater cognitive-linguistic resources should experience less effort or cognitive load and have more resources to allocate to encoding the information for later recall [52].
The main objective of this research is to determine whether the cognitive load (the accumulative processing demands) arising from the listening effort is a possible mechanistic pathway through which ARHL influences memory performance decline in the aging adult. Additionally, this study was designed to determine if the effortful listening arising from ARHL is a modifiable risk factor that could be potentially managed by realistic hearing-listening enhancements and/or listening training/expertise. If so, will these factors narrow the gap between the younger and older adults’ memory performances and perhaps provide a mechanism to slow the cognitive decline in older adults?
The present study investigated how age-related-hearing changes might contribute to memory deficits and whether an enhanced message can facilitate memory employing more ecologically valid methods than has been done previously [52]. Auditory enhancements should reduce the listening effort or reduce the cognitive load and free up those resources required for memory encoding resulting in better free-recall memory performance. The research question is, if older adults can listen like younger adults will they remember more similarly to the younger adult, and if younger adults listen like older adults will they remember more similarly to older adults? Ultimately the goal is to investigate whether the interaction of age-related acuity deficits and age-related spectral-temporal processing changes (the timecompressed listening condition) contributes to listening effort, and whether auditory-verbal enhancements and/or listening training/ expertise mitigate these deficits. If the hypotheses are supported, there should be a main effect of listening condition: Relative to the degraded listening condition, the enhanced listening condition will result in better immediate and delayed memory performance. Further, considering the growing empirical support that musicianship enhances the sub-cortical or sub-lexical processes for speech perception, we hypothesized that these more preserved temporal-spectral processing abilities would contribute to listening ease and/or a more rapid match of the stimuli to the target in memory [53]. Therefore, consistent with the ELU [35] and effortfulness hypotheses [48], the older musicians should perform more similarly to the younger adults, and demonstrate significantly better memory performance compared to the older nonmusicians. If listening ‘expertise’ further reduces the listening effort then there should be a main effect of group with the younger and older musicians performing more similarly to each other and better in immediate and delayed memory than the older non-musicians.
If experience-dependent perceptual learning or adaptation [54] is influenced by the enhanced listening condition then listening order and listening condition will interact. This finding would suggest that the previous experience with a higher fidelity speech message effectively decreased the degradation effect so that the within-subject difference for the memory performances in the two listening condition is smaller when enhanced listening condition is heard first compared to degraded heard first [52].
In addition, if listening effort interacts with cognitive abilities then those individuals with relative strengths in cognitive-linguistic abilities should demonstrate better memory performance than those with relative weaknesses in those areas. Finally, strengths in hearinglistening abilities and/or cognitive-linguistic processes should be associated with better delayed memory performance for the degraded than the enhanced listening conditions.
Previous work in our lab investigated whether an enhanced message (i.e., spoken with a “clear speech” technique) decreased listening effort by promoting speech intelligibility, and improved both comprehension and recall of medical instructions in two groups of older adults, one group who heard the passages in quiet and a second group who listened in noise [52]. The results showed that when older adults with normal to moderate hearing loss heard complex medical instructions in a relatively enhanced listening condition (clear speech) their learning and memory of these passages was better compared to their performance while listening to conversational speech.
Further, explicit cognitive-linguistic abilities (working memory, executive control and lexical abilities) were positively associated with memory performance with a greater magnitude in the suboptimal listening condition (conversational speech). We concluded that, consistent with the ELU [37] and the effortfulness hypotheses [48], the relatively degraded listening (i.e., typical conversational speech) required the allocation of cognitive-linguistic resources to decipher the message for comprehension, where the relative ease of listening of the clear speech passages freed up these same limited capacity resources for encoding into memory for later recall. However, since the effects were small, the motivation for the present study is to use more controlled stimulus manipulations for enhancements (to mimic younger adult listening in optimal listening) and degradation (to mimic older adult listening in typically adverse listening) to further explore how aspects of age-related hearing changes interact with cognitive processes and influence learning and memory performance.
Materials and Methods
Participants
Ethics clearance was obtained from Memorial University’s Interdisciplinary Committee on Ethics in Human Research (ICEHR) in accordance with the Tri-Council Policy Statement on Ethical Conduct involving Humans (TCPS-2). This study was carried out in accordance with the recommendations of TCPS-2 guidelines, and ICEHR with written informed consent from all participants prior to engaging in this study. Sixty-one adults participated, divided into three groups: older musicians (21), younger non-musicians (20), and older non-musicians (20). All participants received $10 an hour for their participation. Inclusion criteria: healthy community-dwelling adults (younger 18-30 years; older 55+ years). Exclusion criteria: a known medical event that may affect cognition; failed cognitive screening metric [55], inadequate vision for completing the experiment; and hearing loss that exceeded the capacity of the speakers (90dB).
Musicians were defined as those individuals who considered themselves to be musicians, had initiated formal musical training by 10 years of age or younger, had a minimum of 12 years musical experience and had been actively engaged in music, currently performing, teaching and/or practicing on average 6 times a week for 1 hour or more daily (Appendix A). They were 55-84 years old (12 females). A musicianship score was calculated based on the responses regarding life-long musical experience/training that were included on the demographic questionnaire (Appendix B). The musicianship classification score was an ordinal scale in which a higher value reflected more experience/training with music. These criteria were established to be similar to studies that have investigated musical training and its impact on hearing and listening performance [56,57] and its relationship with auditory perceptual and processing abilities in behavioral and electrophysiological studies [58-61]. One older musician wore bilateral hearing aids and wore the hearing aids for the entire study except in the enhanced listening in which he wore the 3A E.A.R.toneTM insertion earphones that all the participants used in the experiment for that condition. Forty non-musicians were selected as a comparison group. The two non-musician groups had very minimal to no exposure to music. The younger non-musicians were 20 Memorial University of Newfoundland students, 19-26 years old (12 females). The older non-musicians were 20 community-dwelling adults, 56-84 years old (10 females) (Table 1 for demographic means and standard deviations; Figure 1 for audiogram data).
Younger Non-Musicians
Older Musicians
Older Non-Musicians
M
SD
M
SD
M
SD
Sensation Level dB SLa
45.00
3.63
42.14
9.30
44.50
6.26
MCL in dB HLb
49.50
4.26
58.81
4.15
57.75
6.78 **
Table 1: Intensity level of stimuli presentation;Means and (standard deviations in parenthesis) for the intensity level of the stimuli in the degraded and enhanced listening conditions. aSensation Level (SL) is the difference in decibels (dB) of the participants’ speech reception threshold (SRT) and the presentation level in dB Hearing Level (HL) of the stimuli. This dB SL level reflects the intensity level of the stimuli perceived by the participant. bMost Comfortable Loudness listening level (MCL) is the presentation level in which the stimuli were delivered to the speaker in sound field or to the insert earphones. Bolded mean value indicates this group differed from other groups on this variable(**p < .01).
Figure 1: Mean audiogram profile;Hearing thresholds of all participants in this study. Mean audiogram profile of younger nonmusician group, older non-musician and older musician group for right ear and left ear. Bars represent 95% confidence intervals.
Preliminary measures
: No participant was excluded from the study due to vision, hearing or cognitive screening (e.g., passing score on MMSE >23. The hearing-listening and cognitive-linguistic measures obtained for all participants were the same as a previous study, [52] for a more detailed description of each test.
Hearing-listening measures: Audiometric tests were conducted in a single-walled sound attenuated chamber using a Grason Stadler Instruments Audiometer (GSI-61), Telephonics TDH50P headphones, E.a.r.ToneTM 3A insert earphones and free-field speakers calibrated to specification (American National Standards Institute ANSI S3.62004, 2004). Standardized procedures were used to obtain pure-tone hearing thresholds for right (R) and left (L) ears (Katz, 1978). Pure tone average-4 (PTA4), the average threshold of the four speech frequencies, (0.5 kHz, 1 kHz, 2 kHz, and 4 kHz) was the metric used to indicate degree of auditory acuity deficit consistent with the WHO definition (PTA4>25 dB HL) (World Health Organization (WHO) Prevention of Blindness and Deafness Program, 2014). The Speech Reception Threshold SRT and the phonetically balanced (PB) maxmost comfortable loudness level (PB max-MCL) were used to calculate the sensation level in which participants experienced the stimuli.
The Quick Speech-In-Noise test (QuickSIN): Etymotic Research, Elk Grove, IL; [62] was the metric used to assess listening-in-noise ability. The Hearing Handicap Inventory for Adults HHIA [63] was the standardized and normed self-assessment used to determine the individual’s self-perception of the degree to which they experience a handicap due to hearing loss [64].
Cognitive-linguistic measures: All participants completed the following cognitive-linguistic metrics: Listening span (L-span) a working memory (WM) task that is similar to the reading span measure except sentences are presented auditorily [65,66]. Backward Digit Span (BDS), in which participants hear lists of digits and recreate them in reverse order [67]. Boston Naming Test (BNT) is a standardized and normed confrontation picture-naming task [68]. Verbal Fluency Measure (FAS) correlates with other metrics that measure executive function [69].
The auditory-verbal stimuli
The fictionalized medical prescription vignettes created and used in this study were the same ones used in [52] (Appendix C for the two vignettes and the training passage). The vignettes were matched for linguistic and non-linguistic aspects of speech to equate them for complexity, while at the same time maintaining their ecological validity [52]. Each vignette comprised 10 sentences, with 37 critical units (CU) to report. The 37 CU were the content words within each phrase that carried the most important salient meaning in order to use these fictional medications. Critical units may be a single word, compound word or multiple words (e.g., out of reach). The two vignettes were spoken at their original-conversational rate, 192.5 syllables per minute (spm). Avid Pro-tools 8.0.5 computer software was used to manipulate the original sound files for the training passage and experimental vignettes to ensure that the recordings were equated for loudness across the stimuli and throughout the passages via Root Mean Squared (RMS) for amplitude and to create the two listening conditions.
Degraded speech listening condition: Using an algorithm that uses a pseudo-sampling technique to alter the wave file, the original speech sound file was compressed to 65% of the original length, while maintaining normal speech contours so that it sounded naturally fast. At a specified rate throughout the sound file, small acoustic bits were deleted equally in the voiced and voiceless segments of the wave file, the remaining sound file was abutted in time, so that the sound file was compressed relative to its original length. This method deletes segments from both words and pauses at a specified rate throughout; the resultant stimulus retains the temporal patterning of the original preserving the pitch and prosody [70].
Enhanced speech listening condition: Using the original sound file the speech was expanded to 120% of the original length, while maintaining normal speech contours so that it sounded naturally slow. At a specified rate throughout the sound file, small acoustic bits were reiteratively resampled equally in the voiced and voiceless segments of the wave file, the entire sound file was then abutted in time, so that the sound file is expanded relative to its original length. In this way the duration of the speech elements such as vowel duration and silent intervals were lengthened equally throughout; the resultant expanded speech retains again the temporal patterning of the original speech and preserves the pitch and prosody [70].
Figure 2 depicts the waveforms of the sentence ‘wash your hands’ from the vignette ‘medipatch’ in its original format, conversational speech technique, 196 (spm), with the clear speech technique (152 spm) [52], and for this study enhanced, 120% time-expanded (165 spm), and degraded, 65% time-compressed (304 spm) (Praat; Boersma & Weenick, 2014). In this experiment these two listening conditions were relatively degraded/enhanced with respect to each other such that degraded mimics ‘older-listening’ and enhanced mimics ‘youngerlistening’.
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