Jean Hong1, Phil Gander2, Joel Berger2, Timothy Griffiths3, Inyong Choi1,4
1Department of Otolaryngology – Head and Neck Surgery, University of Iowa Hospitals and Clinics, Iowa City, USA 
2Department of Neurosurgery, University of Iowa Hospitals and Clinics, Iowa City, USA 
3Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK  
4Department of Communication Sciences and Disorders, University of Iowa

Most cochlear implant (CI) users struggle with understanding speech in noisy environments. This challenge may be due to difficulty in separating the target stream from the mixture of sounds. Our previous work demonstrated that figure-ground perception, the ability to detect a ‘figure’ consisting of temporally-coherent tones among less-coherent ‘background’ components, is a strong predictor for successful speech-in-noise perception in normal hearing listeners (Holmes & Griffiths, 2019). However, it is unclear if this temporal coherence-based grouping mechanism predicts CI users’ speech-in-noise ability as well. To address this question, we recruited forty-seven CI users who completed speech-in-noise and figure-ground tasks. In the figure-ground task a sound complex consisting of a figure component that was either fixed (present) or random (absent) in frequency was played simultaneously with a background component of random tones; the participant was asked to detect the presence of the figure component. To isolate the contribution of electric hearing to figure detection we band-passed the figure component from 1-8 kHz and ensured half octave separation among the coherent frequencies to reduce cochlear implant channel interaction. The speech-in-noise task consisted of single words presented in multi-talker babble (4AFC). The results from across-subject correlation analysis indicated that successful figure-ground performance was also a strong predictor for successful speech-in-noise performance among CI users. This research can provide new insights on how to better assess speech-in-noise deficits among CI users.