Auditory Stream Segregation and Selective Attention for Cochlear Implant Listeners: Evidence From Behavioral Measures and Event-Related Potentials

Abstract

The role of the spatial separation between the stimulating electrodes (electrode separation) in sequential stream segregation was explored in cochlear implant (CI) listeners using a deviant detection task. Twelve CI listeners were instructed to attend to a series of target sounds in the presence of interleaved distractor sounds. A deviant was randomly introduced in the target stream either at the beginning, middle or end of each trial. The listeners were asked to detect sequences that contained a deviant and to report its location within the trial. The perceptual segregation of the streams should, therefore, improve deviant detection performance. The electrode range for the distractor sounds was varied, resulting in different amounts of overlap between the target and the distractor streams. For the largest electrode separation condition, event-related potentials (ERPs) were recorded under active and passive listening conditions. The listeners were asked to perform the behavioral task for the active listening condition and encouraged to watch a muted movie for the passive listening condition. Deviant detection performance improved with increasing electrode separation between the streams, suggesting that larger electrode differences facilitate the segregation of the streams. Deviant detection performance was best for deviants happening late in the sequence, indicating that a segregated percept builds up over time. The analysis of the ERP waveforms revealed that auditory selective attention modulates the ERP responses in CI listeners. Specifically, the responses to the target stream were, overall, larger in the active relative to the passive listening condition. Conversely, the ERP responses to the distractor stream were not affected by selective attention. However, no significant correlation was observed between the behavioral performance and the amount of attentional modulation. Overall, the findings from the present study suggest that CI listeners can use electrode separation to perceptually group sequential sounds. Moreover, selective attention can be deployed on the resulting auditory objects, as reflected by the attentional modulation of the ERPs at the group level.

Keywords: auditory attention; auditory scene analysis; build-up; cochlear implant; event-related potentials; segregation.

FIGURE 1

Schematic representation of the electrodogram for each of the four deviant conditions. Black and gray markers represent the target and the distractor sounds, respectively. The deviant triplet is shown with blue markers.

FIGURE 2

Schematic representation of the electrodogram for each of the four electrode separation conditions. Black and gray markers represent the target and the distractor sounds, respectively. On each trial, the distractor stream started before the target stream and ended after the target stream, with a random number of one to four sounds.

FIGURE 3

Boxplot of the sensitivity scores (d′) to the deviant triplet for each electrode separation and deviant triplet location. The color of the boxes represents the electrode separation condition. (A) Effect of the deviant triplet for each electrode separation condition. (B) Effect of the electrode separation for each deviant triplet location. Results from the statistical contrasts are indicated with lowercase letters. Conditions sharing one or more letters are not significantly different (significance level α = 0.05).

FIGURE 4

Averaged ERP waveform across the four deviant triplet conditions. The active listening condition is shown in red and the passive listening condition in blue. The blue and gray shaded areas indicate the N1 ERP component time window for the target and the distractor sounds, respectively. Each trace represents the average across nine front-central electrodes (Fz, AFz, FCz, F1, F2, FC1, FC2, AF3, AF4). The scalp topography of the response to a target and a distractor sound is shown for each of the listening conditions and their difference.

FIGURE 5

Averaged ERP waveform for the early (top) and late (bottom) deviant conditions. The active listening condition is shown in red and the passive listening condition in blue. The blue and gray shaded areas indicate the N1 ERP component time window for the target and the distractor sounds, respectively. Each trace represents the average across nine front-central electrodes (Fz, AFz, FCz, F1, F2, FC1, FC2, AF3, AF4). The scalp topography of the response to a target and a distractor sound is shown for each of the listening conditions and their difference.

FIGURE 6

N1 attentional modulation of the target and distractor sounds for each deviant condition. A negative value represents an enhanced N1 response in the active condition. (A) Averaged N1 attentional modulation across the three sounds of each triplet. (B) Averaged N1 attentional modulation across the three triplets for each sound. A statistically significant difference from zero is indicated by one asterisk if 0.05 > p > 0.01, two asterisks if 0.01 > p > 0.001 and three asterisks if p < 0.001. The p-values were corrected for multiple comparisons using the Bonferroni correction.

FIGURE 7

Scatterplots of the d′ scores as a function of the average N1 attentional modulation for each listener and condition. Behavioral d′ scores from the ERP session are shown in (A) (no overlap condition). The d′ scores from the behavioral session are shown in (B) for the no overlap condition, in (C) for the apical overlap condition and in (D) for the basal overlap condition. Kendall rank correlation coefficients and p-values are shown in the bottom-right corner of each panel.