This study examines how cochlear implant users understand and comprehend speech in realistic communication situations. Through six experiments measuring listening effort via pupillometry and discourse comprehension, we will investigate how linguistic context, cognitive demands, and processing time affect speech understanding in CI users, and in normal-hearing controls) to identify factors underlying communication resilience versus vulnerability and develop improved, ecologically valid assessment and rehabilitation strategies.
Subjects will be otherwise healthy normal-hearing and cochlear implant (CI) adult listeners (between 18 and 80 years old).
Individuals below 18 years of age.
Individuals with evidence of neurologic, vascular or psychiatric disease or dementia, and taking medications that might interfere with task performance.
Individuals with a history of language disorders (besides those associated with hearing loss for the CI users). Individuals who are non-native speakers of American English.
Parallel
Experiment 1: Syntactic and Semantic Context
Behavioral* Recall of meaningful sentences, anomalous word strings, and unstructured word lists * Measurement of syntactic and semantic gain * Pupillometry during auditory and visual presentation
Experiment 2: False Hearing and Context Overuse
Behavioral* Two-choice word recognition task with semantic priming/luring in multi-talker babble * Three Signal-to-Noise Ratio (SNR) levels (heavy, medium, light noise) * Confidence ratings for responses * Pupillometry measurement
Experiment 3: Two-Sentence Problem
Behavioral* Speech recognition and recall of single sentences vs. paired sentences * Manipulation of inter-sentence semantic predictability (high vs. low) * Four test conditions: 1-sentence, 2-sentences, 2-sentences+pre-prompt, 2-sentences+post-prompt * Pupillometry during task
Experiment 4: Cascading Effects on Discourse Comprehension
Behavioral* Recall of 27 narrative passages (67-97 words each) * Propositional analysis scoring (main ideas, mid-level ideas, details) * Measurement of semantic hierarchy effect * Pupillometry during listening
Experiment 5: Self-Paced Discourse Comprehension
Behavioral* 24 discourse passages (150 words each): 12 narrative, 12 expository * Continuous presentation vs. self-paced presentation (stops at clause/sentence boundaries) * Measurement of pause times and comprehension recall * Pupillometry during task
Experiment 6: Clinical Application
Behavioral* Self-Paced Sentence Comprehension * Sentences with varying syntactic complexity (active-conjoined, subject-relative, object-relative) * Continuous vs. self-paced (with pause at major clause boundary) presentation * True/false comprehension verification statements * Pupillometry measurement
Percent correct Consonant-Nucleus-Consonant (CNC) words across experiments 1-3
Participants' ability to recognize individual spoken words will be assessed using the Consonant-Nucleus-Consonant (CNC) word test. Outcome is based on the percent of key words correctly repeated. Higher score indicate better speech understanding.
Percent correct AzBio sentences across experiments 1-3
The AzBio sentence test consists of 15 lists of 20 sentences each. AzBio sentences are spoken by different talkers in a conversational style with limited contextual cues that the listener can use to predict or 'fill in' unintelligible words. Outcome is based on the percent of AzBio sentences correctly repeated. Higher score indicate better speech understanding.
Error rates for word identification tasks across experiments 1-3
Percentage of propositions recalled from narrative passages
Subjects will hear 24 150- word passages, with one half of the passages being narrative (tell a story with a setting, theme, plot, etc.) and the other half being expository (e.g. instructions from a health care provider). After each passage the subject will be asked to recall as much of the passage content as possible. Higher score indicate better speech understanding.
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NYU Langone Health
Lead sponsor
National Institute on Deafness and Other Communication Disorders (NIDCD)
Collaborator
