Dataset Information

The Association Between Cognitive Performance and Speech-in-Noise Perception for Adult Listeners: A Systematic Literature Review and Meta-Analysis.

ABSTRACT: Published studies assessing the association between cognitive performance and speech-in-noise (SiN) perception examine different aspects of each, test different listeners, and often report quite variable associations. By examining the published evidence base using a systematic approach, we aim to identify robust patterns across studies and highlight any remaining gaps in knowledge. We limit our assessment to adult unaided listeners with audiometric profiles ranging from normal hearing to moderate hearing loss. A total of 253 articles were independently assessed by two researchers, with 25 meeting the criteria for inclusion. Included articles assessed cognitive measures of attention, memory, executive function, IQ, and processing speed. SiN measures varied by target (phonemes or syllables, words, and sentences) and masker type (unmodulated noise, modulated noise, >2-talker babble, and ?2-talker babble. The overall association between cognitive performance and SiN perception was r?=?.31. For component cognitive domains, the association with (pooled) SiN perception was as follows: processing speed ( r?=?.39), inhibitory control ( r?=?.34), working memory ( r?=?.28), episodic memory ( r?=?.26), and crystallized IQ ( r?=?.18). Similar associations were shown for the different speech target and masker types. This review suggests a general association of r?.3 between cognitive performance and speech perception, although some variability in association appeared to exist depending on cognitive domain and SiN target or masker assessed. Where assessed, degree of unaided hearing loss did not play a major moderating role. We identify a number of cognitive performance and SiN perception combinations that have not been tested and whose future investigation would enable further fine-grained analyses of these relationships.

SUBMITTER: Dryden A

PROVIDER: S-EPMC5734454 | biostudies-literature | 2017 Jan-Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The Association Between Cognitive Performance and Speech-in-Noise Perception for Adult Listeners: A Systematic Literature Review and Meta-Analysis.

Dryden Adam A Allen Harriet A HA Henshaw Helen H Heinrich Antje A

Trends in hearing 20170101

Published studies assessing the association between cognitive performance and speech-in-noise (SiN) perception examine different aspects of each, test different listeners, and often report quite variable associations. By examining the published evidence base using a systematic approach, we aim to identify robust patterns across studies and highlight any remaining gaps in knowledge. We limit our assessment to adult unaided listeners with audiometric profiles ranging from normal hearing to moderat ...[more]

PMID: 29237334

Similar Datasets

Project description:Speech perception in background noise is difficult for many individuals, and there is considerable performance variability across listeners. The combination of physiological and behavioral measures may help to understand sources of this variability for individuals and groups and prove useful clinically with hard-to-test populations. The purpose of this study was threefold: (1) determine the effect of signal-to-noise ratio (SNR) and signal level on cortical auditory evoked potentials (CAEPs) and sentence-level perception in older normal-hearing (ONH) and older hearing-impaired (OHI) individuals, (2) determine the effects of hearing impairment and age on CAEPs and perception, and (3) explore how well CAEPs correlate with and predict speech perception in noise.Two groups of older participants (15 ONH and 15 OHI) were tested using speech-in-noise stimuli to measure CAEPs and sentence-level perception of speech. The syllable /ba/, used to evoke CAEPs, and sentences were presented in speech-spectrum background noise at four signal levels (50, 60, 70, and 80 dB SPL) and up to seven SNRs (-10, -5, 0, 5, 15, 25, and 35 dB). These data were compared between groups to reveal the hearing impairment effect and then combined with previously published data for 15 young normal-hearing individuals to determine the aging effect.Robust effects of SNR were found for perception and CAEPs. Small but significant effects of signal level were found for perception, primarily at poor SNRs and high signal levels, and in some limited instances for CAEPs. Significant effects of age were seen for both CAEPs and perception, while hearing impairment effects were only found with perception measures. CAEPs correlate well with perception and can predict SNR50s to within 2 dB for ONH. However, prediction error is much larger for OHI and varies widely (from 6 to 12 dB) depending on the model that was used for prediction.When background noise is present, SNR dominates both perception-in-noise testing and cortical electrophysiological testing, with smaller and sometimes significant contributions from signal level. A mismatch between behavioral and electrophysiological results was found (hearing impairment effects were primarily only seen for behavioral data), illustrating the possible contributions of higher order cognitive processes on behavior. It is interesting that the hearing impairment effect size was more than five times larger than the aging effect size for CAEPs and perception. Sentence-level perception can be predicted well in normal-hearing individuals; however, additional research is needed to explore improved prediction methods for older individuals with hearing impairment.

Project description:The most common complaint of older hearing impaired (OHI) listeners is difficulty understanding speech in the presence of noise. However, tests of consonant-identification and sentence reception threshold (SeRT) provide different perspectives on the magnitude of impairment. Here we quantified speech perception difficulties in 24 OHI listeners in unaided and aided conditions by analyzing (1) consonant-identification thresholds and consonant confusions for 20 onset and 20 coda consonants in consonant-vowel-consonant (CVC) syllables presented at consonant-specific signal-to-noise (SNR) levels, and (2) SeRTs obtained with the Quick Speech in Noise Test (QSIN) and the Hearing in Noise Test (HINT). Compared to older normal hearing (ONH) listeners, nearly all unaided OHI listeners showed abnormal consonant-identification thresholds, abnormal consonant confusions, and reduced psychometric function slopes. Average elevations in consonant-identification thresholds exceeded 35 dB, correlated strongly with impairments in mid-frequency hearing, and were greater for hard-to-identify consonants. Advanced digital hearing aids (HAs) improved average consonant-identification thresholds by more than 17 dB, with significant HA benefit seen in 83% of OHI listeners. HAs partially normalized consonant-identification thresholds, reduced abnormal consonant confusions, and increased the slope of psychometric functions. Unaided OHI listeners showed much smaller elevations in SeRTs (mean 6.9 dB) than in consonant-identification thresholds and SeRTs in unaided listening conditions correlated strongly (r = 0.91) with identification thresholds of easily identified consonants. HAs produced minimal SeRT benefit (2.0 dB), with only 38% of OHI listeners showing significant improvement. HA benefit on SeRTs was accurately predicted (r = 0.86) by HA benefit on easily identified consonants. Consonant-identification tests can accurately predict sentence processing deficits and HA benefit in OHI listeners.

Project description:Hearing aids (HAs) only partially restore the ability of older hearing impaired (OHI) listeners to understand speech in noise, due in large part to persistent deficits in consonant identification. Here, we investigated whether adaptive perceptual training would improve consonant-identification in noise in sixteen aided OHI listeners who underwent 40 hours of computer-based training in their homes. Listeners identified 20 onset and 20 coda consonants in 9,600 consonant-vowel-consonant (CVC) syllables containing different vowels (/ɑ/, /i/, or /u/) and spoken by four different talkers. Consonants were presented at three consonant-specific signal-to-noise ratios (SNRs) spanning a 12 dB range. Noise levels were adjusted over training sessions based on d' measures. Listeners were tested before and after training to measure (1) changes in consonant-identification thresholds using syllables spoken by familiar and unfamiliar talkers, and (2) sentence reception thresholds (SeRTs) using two different sentence tests. Consonant-identification thresholds improved gradually during training. Laboratory tests of d' thresholds showed an average improvement of 9.1 dB, with 94% of listeners showing statistically significant training benefit. Training normalized consonant confusions and improved the thresholds of some consonants into the normal range. Benefits were equivalent for onset and coda consonants, syllables containing different vowels, and syllables presented at different SNRs. Greater training benefits were found for hard-to-identify consonants and for consonants spoken by familiar than unfamiliar talkers. SeRTs, tested with simple sentences, showed less elevation than consonant-identification thresholds prior to training and failed to show significant training benefit, although SeRT improvements did correlate with improvements in consonant thresholds. We argue that the lack of SeRT improvement reflects the dominant role of top-down semantic processing in processing simple sentences and that greater transfer of benefit would be evident in the comprehension of more unpredictable speech material.

Project description:Healthy aging leads to complex changes in the functional network of speech processing in a noisy environment. The dual-route neural architecture has been applied to the study of speech processing. Although evidence suggests that senescent increases activity in the brain regions across the dorsal and ventral stream regions to offset reduced periphery, the regulatory mechanism of dual-route functional networks underlying such compensation remains largely unknown. Here, by utilizing functional near-infrared spectroscopy (fNIRS), we investigated the compensatory mechanism of the dual-route functional connectivity, and its relationship with healthy aging by using a speech perception task at varying signal-to-noise ratios (SNR) in healthy individuals (young adults, middle-aged adults, and older adults). Results showed that the speech perception scores showed a significant age-related decrease with the reduction of the SNR. The analysis results of dual-route speech processing networks showed that the functional connection of Wernicke's area and homolog Wernicke's area were age-related increases. Further to clarify the age-related characteristics of the dual-route speech processing networks, graph-theoretical network analysis revealed an age-related increase in the efficiency of the networks, and the age-related differences in nodal characteristics were found both in Wernicke's area and homolog Wernicke's area under noise environment. Thus, Wernicke's area might be a key network hub to maintain efficient information transfer across the speech process network with healthy aging. Moreover, older adults would recruit more resources from the homologous Wernicke's area in a noisy environment. The recruitment of the homolog of Wernicke's area might provide a means of compensation for older adults for decoding speech in an adverse listening environment. Together, our results characterized dual-route speech processing networks at varying noise environments and provided new insight for the compensatory theories of how aging modulates the dual-route speech processing functional networks.

Dataset Information

The Association Between Cognitive Performance and Speech-in-Noise Perception for Adult Listeners: A Systematic Literature Review and Meta-Analysis.

Publications

The Association Between Cognitive Performance and Speech-in-Noise Perception for Adult Listeners: A Systematic Literature Review and Meta-Analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets