Contribution of formant frequency information to vowel perception in steady-state noise by cochlear implant users

The Acoustic Change Complex in Response to Frequency Changes and Its Correlation to Cochlear Implant Speech Outcomes

One of the biggest challenges that face cochlear implant (CI) users is the highly variable hearing outcomes of implantation across patients. Since speech perception requires the detection of various dynamic changes in acoustic features (e.g., frequency, intensity, timing) in speech sounds, it is critical to examine the ability to detect the within-stimulus acoustic changes in CI users. The primary objective of this study was to examine the auditory event-related potential (ERP) evoked by the within-stimulus frequency changes (F-changes), one type of the acoustic change complex (ACC), in adult CI users, and its correlation to speech outcomes. Twenty-one adult CI users (29 individual CI ears) were tested with psychoacoustic frequency change detection tasks, speech tests including the Consonant-Nucleus-Consonant (CNC) word recognition, Arizona Biomedical Sentence Recognition in quiet and noise (AzBio-Q and AzBio-N), and the Digit-in-Noise (DIN) tests, and electroencephalographic (EEG) recordings. The stimuli for the psychoacoustic tests and EEG recordings were pure tones at three different base frequencies (0.25, 1, and 4 kHz) that contained a F-change at the midpoint of the tone. Results showed that the frequency change detection threshold (FCDT), ACC N1' latency, and P2' latency did not differ across frequencies (p > 0.05). ACC N1'-P2 amplitude was significantly larger for 0.25 kHz than for other base frequencies (p < 0.05). The mean N1' latency across three base frequencies was negatively correlated with CNC word recognition (r = -0.40, p < 0.05) and CNC phoneme (r = -0.40, p < 0.05), and positively correlated with mean FCDT (r = 0.46, p < 0.05). The P2' latency was positively correlated with DIN (r = 0.47, p < 0.05) and mean FCDT (r = 0.47, p < 0.05). There was no statistically significant correlation between N1'-P2' amplitude and speech outcomes (all ps > 0.05). Results of this study indicated that variability in CI speech outcomes assessed with the CNC, AzBio-Q, and DIN tests can be partially explained (approximately 16-21%) by the variability of cortical sensory encoding of F-changes reflected by the ACC.

Saliency of Vowel Features in Neural Responses of Cochlear Implant Users

Cochlear implants restore hearing in deaf individuals, but speech perception remains challenging. Poor discrimination of spectral components is thought to account for limitations of speech recognition in cochlear implant users. We investigated how combined variations of spectral components along two orthogonal dimensions can maximize neural discrimination between two vowels, as measured by mismatch negativity. Adult cochlear implant users and matched normal-hearing listeners underwent electroencephalographic event-related potentials recordings in an optimum-1 oddball paradigm. A standard /a/ vowel was delivered in an acoustic free field along with stimuli having a deviant fundamental frequency (+3 and +6 semitones), a deviant first formant making it a /i/ vowel or combined deviant fundamental frequency and first formant (+3 and +6 semitones /i/ vowels). Speech recognition was assessed with a word repetition task. An analysis of variance between both amplitude and latency of mismatch negativity elicited by each deviant vowel was performed. The strength of correlations between these parameters of mismatch negativity and speech recognition as well as participants' age was assessed. Amplitude of mismatch negativity was weaker in cochlear implant users but was maximized by variations of vowels' first formant. Latency of mismatch negativity was later in cochlear implant users and was particularly extended by variations of the fundamental frequency. Speech recognition correlated with parameters of mismatch negativity elicited by the specific variation of the first formant. This nonlinear effect of acoustic parameters on neural discrimination of vowels has implications for implant processor programming and aural rehabilitation.

Deactivating cochlear implant electrodes to improve speech perception: A computational approach

A potential bottleneck to improving speech perception performance in cochlear implant (CI) users is that some of their electrodes may poorly encode speech information. Several studies have examined the effect of deactivating poorly encoding electrodes on speech perception with mixed results. Many of these studies focused on identifying poorly encoding electrodes by some measure (e.g. electrode discrimination, pitch ordering, threshold, CT-guided, masked modulation detection), but provide inconsistent criteria about which electrodes, and how many, should be deactivated, and without considering how speech information becomes distributed across the electrode array. The present simulation study addresses this issue using computational approaches. Previously validated models were used to generate predictions of speech scores as a function of all possible combinations of active electrodes in a 22-electrode array in three groups of hypothetical subjects representative of relatively better, moderate, and poorer performing CI users. Using high-performance computing, over 500 million predictions were generated. Although deactivation of the poorest encoding electrodes sometimes resulted in predicted benefit, this benefit was significantly less relative to predictions resulting from model-optimized deactivations. This trend persisted when using novel stimuli (i.e. other than those used for optimization) and when using different processing strategies. Optimum electrode deactivation patterns produced an average predicted increase in word scores of 10% with some scores increasing by more than 20%. Optimum electrode deactivation patterns typically included 11 to 19 (out of 22) active electrodes, depending on the performance group. Optimal active electrode combinations were those that maximized discrimination of speech cues, maintaining 80%-100% of the physical span of the array. The present study demonstrates the potential for further improving CI users' speech scores with appropriate selection of active electrodes.