Cochlear implants (CIs) can improve auditory detection and speech perception for people with severe-to-profound hearing loss. Accordingly, CI benefit is usually quantified in the clinic with speech perception assessment tools in an auditory-only format (e.g., auditory word and sentence recognition tests). However, successful real-world speech perception relies on the integration of auditory and visual input, and vision has been shown to play an important role in speech intelligibility for people with normal hearing and those with hearing loss (Br J Audiol. 1987;21:131; Ear Hear. 2007;28:656). Furthermore, complementary visual and auditory speech cues are particularly important for pre-lingually deafened individuals who must rely on the degraded auditory signal from a CI to develop spoken language (Ear Hear. 2001;22:236).
In fact, some neuroimaging studies have shown that the way the brain processes simple visual stimuli is related to CI users’ proficiency in auditory speech perception. Specifically, good performers demonstrate cortical responses to visual stimuli that are mostly restricted to the visual cortex—responses that are similar to those of normal-hearing listeners. On the other hand, poor performers show cortical responses to visual stimuli that are more widespread across the brain than observed in normal-hearing listeners, with activation not only in the visual cortex but also in regions that are typically important for processing auditory stimuli (e.g., Brain. 2006;129:3376; Int J Psychophysiol. 2015;95:135). This evidence suggests that, in addition to differences in auditory speech perception performance, good CI users and poor CI users might process visual cues differently, and there may be a relationship between a CI user's visual processing abilities and his or her auditory speech perception performance.
These brain imaging studies provide valuable insights into the potential relationship between cortical representation of visual stimuli and CI users’ auditory speech perception outcomes. However, to fully characterize an individual's visual processing abilities, it is necessary to evaluate visual perception using a behavioral task. Thus, in a recent report, Jahn, et al., used a behavioral measure of visual temporal acuity to quantify visual processing abilities in a sample of 10 pre-lingually deafened adult CI users (Ear Hear. 2017;38:236). While there are many ways to quantify visual performance, good visual temporal acuity is important in perceiving dynamic visual cues such as motion and in integrating audiovisual information for speech perception (e.g., Exp Brain Res. 2013;227:249).
ASSESSING VISUAL TEMPORAL ACUITY
Jahn and colleagues measured visual temporal acuity using a visual temporal order judgment (vTOJ) task (Ear Hear. 2017). The vTOJ is a simple behavioral task that can be easily administered in a clinical or laboratory setting in approximately seven minutes per participant. Furthermore, similar tasks have been successfully implemented in young children (e.g., Dev Sci. 2012;1467:7687). During the vTOJ task, two visual stimuli (i.e., white circles) are presented in succession on a computer screen. One stimulus flashes above a central fixation point, and the other stimulus flashes below the fixation point. After each trial, the participant indicates which stimulus (top or bottom) flashed first, and responses are scored as either “correct” or “incorrect” for each trial. The amount of time between the presentation of the top versus the bottom stimulus varies for each trial. A visual threshold is calculated at the end of the task, representing the individual's visual temporal acuity. Like a hearing threshold on an audiogram, a lower visual threshold represents better visual temporal acuity, whereas a higher visual threshold represents poorer temporal acuity.
VISUAL TEMPORAL PROCESSING AND AUDITORY SPEECH PERCEPTION
Performance on the visual task was compared with the participants’ auditory speech perception performance, which was measured using two assessments for CI outcomes: consonant-nucleus-consonant (CNC) monosyllabic word recognition and AzBio sentence recognition (J Speech Hear Disord. 1962;27:62; Ear Hear. 2012:33:112).
Results showed a strong, significant correlation between visual temporal acuity and auditory speech perception performance for the pre-lingually deafened CI users in the study (CNC words: r = -0.87, p = 0.001; AzBio sentences: r = -0.94, p < 0.001). That is, individuals who had better visual temporal acuity (a lower threshold on the visual task) also had better auditory word and sentence recognition scores (Fig. 1). Furthermore, the participants were separated into two groups based on their auditory speech perception performance: “proficient” and “non-proficient.” Proficient CI users were defined as individuals with CNC word recognition scores that were above the group mean, while non-proficient CI users were defined as those whose CNC word recognition scores fell below the group mean. The “proficient” CI users had significantly better visual temporal acuity (lower visual thresholds) than “non-proficient” CI users (Fig. 2; p = 0.01).
Speech perception is a multisensory process, and accurate identification of speech stimuli requires precise integration of auditory and visual information. Existing behavioral and neuroimaging evidence shows that visual processing in adult CI users is related to their proficiency on clinical, auditory-only speech perception measures. Although CI outcomes are most often assessed clinically using auditory-only tests, evaluating performance in other sensory modalities such as vision may also provide valuable insights into CI proficiency. A multifaceted understanding of a patient's sensory experience can assist clinicians with optimally evaluating CI candidacy and outcomes, and can facilitate improved counseling for these individuals.
This research highlighted promising areas for future inquiry. To continue characterizing the clinical utility of these data, subsequent investigations should extend behavioral analyses of visual processing to larger samples, to post-lingually deafened adult CI users, and to children. Additionally, there is a need to evaluate the relationship of pre-implant visual processing to post-implant outcomes and the efficacy of visual or multisensory post-implant training paradigms.