Verbal Processing Speed and Executive Functioning in Long-Term Cochlear Implant Users

AuBuchon, Angela M.; Pisoni, David B.; Kronenberger, William G.

doi:10.1044/2014_jslhr-h-13-0259

Cited by 29 publications

(32 citation statements)

References 67 publications

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“…Of particular interest to the present study are the Hearing in Noise Test Sentences for Children (HINT-C; Nilsson, Soli, & Gelnett, 1996); Peabody Picture Vocabulary Test–Fourth Edition (PPVT-4; Dunn & Dunn, 2007); and the Clinical Evaluation of Language Fundamentals–Fourth Edition (CELF-4; Semel, Wiig, & Secord, 2003), Forward and Backward Digit Spans, Non-Verbal IQ, and McGarr Sentence Speaking Durations. Additional methodological information regarding the HINT-C, PPVT-4, and CELF-4 can be found in Ruffin et al (2013); methodological information regarding the Forward and Backward Digit Span tasks and Non-Verbal IQ can be found in Kronenberger, Pisoni, Henning, and Colson (2013); and methodological information regarding McGarr Sentence Speaking Duration can be found in AuBuchon, Pisoni, and Kronenberger (in press).…”

Section: Methodsmentioning

confidence: 99%

Speech Intelligibility in Deaf Children After Long-Term Cochlear Implant Use

Montag

AuBuchon

Pisoni

et al. 2014

J Speech Lang Hear Res

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Purpose This study investigated long-term speech intelligibility outcomes in 63 prelingually deaf children, adolescents, and young adults who received cochlear implants (CIs) before age 7 (M = 2;11 [years;months], range = 0;8–6;3) and used their implants for at least 7 years (M = 12;1, range = 7;0–22;5). Method Speech intelligibility was assessed using playback methods with naïve, normal-hearing listeners. Results Mean intelligibility scores were lower than scores obtained from an age- and nonverbal IQ–matched, normal-hearing control sample, although the majority of CI users scored within the range of the control sample. Our sample allowed us to investigate the contribution of several demographic and cognitive factors to speech intelligibility. CI users who used their implant for longer periods of time exhibited poorer speech intelligibility scores. Crucially, results from a hierarchical regression model suggested that this difference was due to more conservative candidacy criteria in CI users with more years of use. No other demographic variables accounted for significant variance in speech intelligibility scores beyond age of implantation and amount of spoken language experience (assessed by communication mode and family income measures). Conclusion Many factors that have been found to contribute to individual differences in language outcomes in normal-hearing children also contribute to long-term CI users’ ability to produce intelligible speech.

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Section: Methodsmentioning

confidence: 99%

Speech Intelligibility in Deaf Children After Long-Term Cochlear Implant Use

Montag

AuBuchon

Pisoni

et al. 2014

J Speech Lang Hear Res

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“…Thus, individual differences and variability in conventional outcome measures can be traced back to more elementary component processes of neurocognition and information processing that reflect differences in speed of information processing operations such as verbal rehearsal, scanning and retrieval of items in verbal short-term memory and the rate of encoding phonological and lexical information in verbal working memory. 42 …”

Section: Challenge No 1: Individual Differences and Variability In Omentioning

confidence: 99%

Three challenges for future research on cochlear implants

Pisoni¹,

Kronenberger²,

Harris³

et al. 2017

World j. otorhinolaryngol.-head neck surg.

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123

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Cochlear implants (CIs) often work very well for many children and adults with profound sensorineural (SNHL) hearing loss. Unfortunately, while many CI patients display substantial benefits in recognizing speech and understanding spoken language following cochlear implantation, a large number of patients achieve poor outcomes. Understanding and explaining the reasons for poor outcomes following implantation is a very challenging research problem that has received little attention despite the pressing clinical significance. In this paper, we discuss three challenges for future research on CIs. First, we consider the issue of individual differences and variability in outcomes following implantation. At the present time, we still do not have a complete and satisfactory account of the causal underlying factors that are responsible for the enormous individual differences and variability in outcomes. Second, we discuss issues related to the lack of preimplant predictors of outcomes. Very little prospective research has been carried out on the development of preimplant predictors that can be used to reliably identify CI candidates who may be at high risk for a poor outcome following implantation. Other than conventional demographics and hearing history, there are no prognostic tools available to predict speech recognition outcomes after implantation. Finally, we discuss the third challenge — what to do with a CI-user who has a poor outcome. We suggest that new research efforts need to be devoted to studying this neglected clinical population in greater depth to find out why they are doing poorly with their CI and what novel interventions and treatments can be developed to improve their speech recognition outcomes. Using these three challenges as objectives for future research on CIs, we suggest that the field needs to adopt a new narrative grounded in theory and methods from Cognitive Hearing Science and information processing theory. Without knowing which specific biological and neurocognitive factors are responsible for individual differences or understanding the underlying sensory and neurocognitive basis for variability in performance, it is impossible to select a specific approach to habilitation after a deaf adult or child receives a CI. Deaf adults and children who are performing poorly with their CIs are not a homogeneous group and may differ in many different ways from each other, reflecting the dysfunction of multiple brain systems associated with both congenital and acquired deafness. Hearing loss is not only an ear issue, it is also a brain issue too reflecting close links between perception and action and brain, body and world working together as a functionally integrated information processing system to support robust speech recognition and spoken language processing after implantation.

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“…Storage represents only the second of three stages of memory: encoding, storage, and retrieval. Other research has shown that, when assessed independently, processing measures associated with all three stages-specifically encoding speed, verbal rehearsal speed during storage, and scanning of retrievable items in short-term memory-each predict individual variance in pediatric CI users' short-term and working memory performance (AuBuchon, Pisoni, & Kronenberger, 2015b;Burkholder & Pisoni, 2003;Pisoni & Cleary, 2003). However, each stage does not occur in isolation; therefore, it is important to obtain estimates of the relative contribution of phonological storage simultaneously with processes associated with each memory stage.…”

mentioning

confidence: 99%

Evaluating Pediatric Cochlear Implant Users' Encoding, Storage, and Retrieval Strategies in Verbal Working Memory

AuBuchon

Pisoni

Kronenberger

2019

J Speech Lang Hear Res

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Purpose The current study adopts a systematic approach to the examination of working memory components in pediatric cochlear implant (CI) users by separately assessing contributions of encoding, storage, and retrieval. Method Forty-nine long-term CI users and 56 typically hearing controls completed forward and backward span tasks with 3 stimulus sets: visually presented digits, pictures of concrete nouns, and novel symbols. In addition, measures associated with each memory stage were collected: Rapid digit naming provided an estimate of phonological recoding speed, nonword repetition assessed the robustness of representations within phonological storage, and vocabulary knowledge (as measured by the Peabody Picture Vocabulary Test; Dunn & Dunn, 1997 ) estimated redintegration abilities during retrieval. Results Linear mixed modeling revealed that digit naming speed and vocabulary knowledge were consistently related to short-term and working memory span in both CI users and typically hearing controls. However, nonword repetition only contributed to the model for short-term memory. Conclusions Nonword repetition, an index of phonological storage, explained little of the individual variability inworking memory differences between CI users and typically hearing peers. On the other hand, individual differences in encoding and retrieval explained a significant amount of outcome variability in both short-term and working memory tasks. Differences between CI users and typically hearing peers in working memory therefore appear to reflect process components of encoding and retrieval and not simply differences in memory storage. Supplemental Material https://doi.org/10.23641/asha.7849394

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Verbal Processing Speed and Executive Functioning in Long-Term Cochlear Implant Users

Cited by 29 publications

References 67 publications

Speech Intelligibility in Deaf Children After Long-Term Cochlear Implant Use

Speech Intelligibility in Deaf Children After Long-Term Cochlear Implant Use

Three challenges for future research on cochlear implants

Evaluating Pediatric Cochlear Implant Users' Encoding, Storage, and Retrieval Strategies in Verbal Working Memory

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