Recording EEG in Cochlear Implant Users: Guidelines for Experimental Design and Data Analysis for Optimizing Signal Quality and Minimizing Artifacts

Artifact removal by template subtraction enables recordings of the frequency following response in cochlear-implant users

Electrically evoked frequency-following responses (eFFRs) provide insight in the phase-locking ability of brainstem of cochlear-implant (CI) users. eFFRs can potentially be used to gain insight in the individual differences in the biological limitation on temporal encoding of the electrically stimulated auditory pathway, which can be inherent to the electrical stimulation itself and/or the degenerative processes associated with hearing loss. One of the major challenge of measuring eFFRs in CI users is the process of isolating the stimulation artifact from the neural response, as both the response and the artifact overlap in time and have similar frequency characteristics. Here we introduce a new artifact removal method based on template subtraction that successfully removes the stimulation artifacts from the recordings when CI users are stimulated with pulse trains from 128 to 300 pulses per second in a monopolar configuration. Our results show that, although artifact removal was successful in all CI users, the phase-locking ability of the brainstem to the different pulse rates, as assessed with the eFFR differed substantially across participants. These results show that the eFFR can be measured, free from artifacts, in CI users and that they can be used to gain insight in individual differences in temporal processing of the electrically stimulated auditory pathway.

Intracranial electrophysiology of spectrally degraded speech in the human cortex

Introduction

Cochlear implants (CIs) are the treatment of choice for severe to profound hearing loss. Variability in CI outcomes remains despite advances in technology and is attributed in part to differences in cortical processing. Studying these differences in CI users is technically challenging. Spectrally degraded stimuli presented to normal-hearing individuals approximate input to the central auditory system in CI users. This study used intracranial electroencephalography (iEEG) to investigate cortical processing of spectrally degraded speech.

Methods

Participants were adult neurosurgical epilepsy patients. Stimuli were utterances /aba/ and /ada/, spectrally degraded using a noise vocoder (1-4 bands) or presented without vocoding. The stimuli were presented in a two-alternative forced choice task. Cortical activity was recorded using depth and subdural iEEG electrodes. Electrode coverage included auditory core in posteromedial Heschl's gyrus (HGPM), superior temporal gyrus (STG), ventral and dorsal auditory-related areas, and prefrontal and sensorimotor cortex. Analysis focused on high gamma (70-150 Hz) power augmentation and alpha (8-14 Hz) suppression.

Results

Chance task performance occurred with 1-2 spectral bands and was near-ceiling for clear stimuli. Performance was variable with 3-4 bands, permitting identification of good and poor performers. There was no relationship between task performance and participants demographic, audiometric, neuropsychological, or clinical profiles. Several response patterns were identified based on magnitude and differences between stimulus conditions. HGPM responded strongly to all stimuli. A preference for clear speech emerged within non-core auditory cortex. Good performers typically had strong responses to all stimuli along the dorsal stream, including posterior STG, supramarginal, and precentral gyrus; a minority of sites in STG and supramarginal gyrus had a preference for vocoded stimuli. In poor performers, responses were typically restricted to clear speech. Alpha suppression was more pronounced in good performers. In contrast, poor performers exhibited a greater involvement of posterior middle temporal gyrus when listening to clear speech.

Discussion

Responses to noise-vocoded speech provide insights into potential factors underlying CI outcome variability. The results emphasize differences in the balance of neural processing along the dorsal and ventral stream between good and poor performers, identify specific cortical regions that may have diagnostic and prognostic utility, and suggest potential targets for neuromodulation-based CI rehabilitation strategies.

Audiovisual integration in children with cochlear implants revealed through EEG and fNIRS

Sensory deprivation can offset the balance of audio versus visual information in multimodal processing. Such a phenomenon could persist for children born deaf, even after they receive cochlear implants (CIs), and could potentially explain why one modality is given priority over the other. Here, we recorded cortical responses to a single speaker uttering two syllables, presented in audio-only (A), visual-only (V), and audio-visual (AV) modes. Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) were successively recorded in seventy-five school-aged children. Twenty-five were children with normal hearing (NH) and fifty wore CIs, among whom 26 had relatively high language abilities (HL) comparable to those of NH children, while 24 others had low language abilities (LL). In EEG data, visual-evoked potentials were captured in occipital regions, in response to V and AV stimuli, and they were accentuated in the HL group compared to the LL group (the NH group being intermediate). Close to the vertex, auditory-evoked potentials were captured in response to A and AV stimuli and reflected a differential treatment of the two syllables but only in the NH group. None of the EEG metrics revealed any interaction between group and modality. In fNIRS data, each modality induced a corresponding activity in visual or auditory regions, but no group difference was observed in A, V, or AV stimulation. The present study did not reveal any sign of abnormal AV integration in children with CI. An efficient multimodal integrative network (at least for rudimentary speech materials) is clearly not a sufficient condition to exhibit good language and literacy.

Objective discrimination of bimodal speech using frequency following responses

Bimodal hearing, in which a contralateral hearing aid is combined with a cochlear implant (CI), provides greater speech recognition benefits than using a CI alone. Factors predicting individual bimodal patient success are not fully understood. Previous studies have shown that bimodal benefits may be driven by a patient's ability to extract fundamental frequency (f0) and/or temporal fine structure cues (e.g., F1). Both of these features may be represented in frequency following responses (FFR) to bimodal speech. Thus, the goals of this study were to: 1) parametrically examine neural encoding of f0 and F1 in simulated bimodal speech conditions; 2) examine objective discrimination of FFRs to bimodal speech conditions using machine learning; 3) explore whether FFRs are predictive of perceptual bimodal benefit. Three vowels (/ε/, /i/, and /ʊ/) with identical f0 were manipulated by a vocoder (right ear) and low-pass filters (left ear) to create five bimodal simulations for evoking FFRs: Vocoder-only, Vocoder +125 Hz, Vocoder +250 Hz, Vocoder +500 Hz, and Vocoder +750 Hz. Perceptual performance on the BKB-SIN test was also measured using the same five configurations. Results suggested that neural representation of f0 and F1 FFR components were enhanced with increasing acoustic bandwidth in the simulated "non-implanted" ear. As spectral differences between vowels emerged in the FFRs with increased acoustic bandwidth, FFRs were more accurately classified and discriminated using a machine learning algorithm. Enhancement of f0 and F1 neural encoding with increasing bandwidth were collectively predictive of perceptual bimodal benefit on a speech-in-noise task. Given these results, FFR may be a useful tool to objectively assess individual variability in bimodal hearing.