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Refractory Effects of the N1 Event-‐Related Potential in Experienced Cochlear 1 Implant Patients 2

Christopher D. Cowper-‐Smith1, Janet Green1, Heather Maessen2, 3 Manohar Bance3, & Aaron J. Newman1,4 4

5 6 7

1. Department of Psychology, Dalhousie University, Halifax, Nova Scotia, 8 Canada 9

2. Nova Scotia Hearing and Speech Centers, Halifax, Nova Scotia, Canada 10

3. Division of Otolaryngology, Capital Health District. Department of Surgery, 11 School of Human Communication Disorders, and School of Biomedical 12 Engineering, Dalhousie University, Halifax, Nova Scotia 13

4. Departments of Psychiatry, Surgery (Division of Otolaryngology), and 14 Pediatrics (Division of Neurology), Dalhousie University, Halifax, Nova Scotia 15

16

This research was funded by the Nova Scotia Health Research Foundation. AJN was 17 supported by the Canada Research Chairs program. CCS was supported by a CGS 18 Scholarship from Canadian Institutes of Health Research. 19 20 21 22 IN PRESS — INTERNATIONAL JOURNAL OF AUDIOLOGY 23 DOI: 10.3109/14992027.2012.743044 24 25 26

For Correspondence: 27 Aaron J. Newman 28 Department of Psychology 29 Box 15000 30 Dalhousie University 31 Halifax, NS B3H 4R2 32 Canada 33 Tel: +1-‐902-‐494-‐6959 34 E-‐mail: [email protected] 35

36

Auditory Refractory Period in Cochlear Implant Patients

2

Abstract 37 38

Objective: To determine if CI patients exhibit a temporal processing deficit for 39 auditory stimuli, by examining refractory effects of the N1 event-‐related potential 40 (ERP) component. 41

Design: Cochlear implant patients and normally hearing controls were tested in an 42 auditory refractory period paradigm while ERP recordings were collected across the 43 scalp. Participants were presented with brief 500 Hz tones that were separated by 44 inter-‐stimulus intervals (ISIs) of 500, 1000, or 3000 ms. The amplitude of the N1 45 was examined as a function of ISI within each group. 46

Study Sample: Ten adult CI patients and 13 age-‐matched normally hearing controls 47 were tested. Patients had long-‐lasting severe or profound sensorineural hearing loss 48 prior to implantation, and a minimum of 2 years experience with CI activation. 49

Results: Unlike normally hearing controls, CI users showed no refractory effect for 50 tones at 500 ms ISIs compared to 1000 ms. However, similar to controls, recovery 51 from refractoriness was observed in anterior locations at 3000 ms. 52

Conclusion: The refractory period threshold, defined as the minimum ISI where 53 different N1 amplitudes are elicited, is greater than 1000ms in CI patients; at least 54 double that of normally hearing controls. 55 56 57 58 59 60 61 62 63 64 Keywords: Cochlear Implant, EEG, hearing loss, auditory evoked potential (AEP), 65 auditory refractory period 66 67 Acronyms & Abbreviations: cochlear implants (CIs); elecroencephalography 68 (EEG); event related potentials (ERPs); late auditory evoked potential (LAER); 69 hearing in noise test (HINT); inter-‐stimulus-‐interval (ISI); independent components 70 analysis (ICA); linear mixed effects (LME) 71 72 73


3

The current most effective rehabilitative option for severe to profound 74

sensorineural hearing loss, and some forms of auditory neuropathy is surgical, using 75

cochlear implants (CIs) (Isaacson, 2010). The success of CI treatment remains highly 76

variable, and is affected by many variables including the level, laterality, and 77

duration of hearing loss. Following deafness greater than 4 years, adults treated 78

with CIs often exhibit only moderate improvements in speech comprehension, 79

which typically plateau within 1 year of implantation, and thereafter remain 80

independent of the duration of CI experience. Improvements in speech 81

comprehension that do occur are better for closed-‐set (constrained) tasks, and 82

worse for open-‐set task performance (for review, see Peterson et al. 2010). 83

The limited capacity for speech comprehension improvements in CI recipients with 84

prior long-‐term deafness may arise from deprivation and/or nonuse of the auditory 85

cortex (cf. Kral et al. 2007). Prolonged lack of auditory stimulation may lead to 86

reduced responsiveness and less precise tuning of neural responses to sound. As 87

well, some evidence suggests takeover of auditory association cortices by visual 88

processing, at least in the case of congenital deafness (Buckley et al. 2011; Lomber 89

et al. 2010). Either or both of these phenomena could contribute to less-‐than-‐ideal 90

outcomes of cochlear implantation in deaf adults. 91

One contributor to speech comprehension deficits in CI users might be reduced 92

temporal acuity, since speech comprehension depends on the ability to represent 93

rapidly changing sequences of sound. Consistent with temporal processing deficits, 94


4

unilateral CI users exhibit increased gap detection thresholds (e.g. Garadat et al. 95

2011), reflecting difficulty in detecting brief acoustic transients. In addition, bilateral 96

CI users appear to depend on interaural level rather than interaural time differences 97

in sound localization tasks, suggesting that temporal cues are not effectively 98

transmitted or used (Aronoff et al. 2010). Finally, many CI recipients exhibit a 99

reduced ability to detect changes in stimulus duration, as well as stimulus frequency 100

and intensity (Sandmann et al. 2010). 101

A well-‐established approach for studying the time course of cortical responses to 102

auditory information is to measure event-‐related potentials (ERPs), which are the 103

summed electrical potentials of large fields of coherently-‐activated neurons as 104

recorded from the scalp. One component of this is the so-‐called late auditory evoked 105

response (LAER). The LAER is a complex of 3 components, P1-‐N1-‐P2, which peak in 106

healthy adults at approximately 50, 100, and 200 ms after an onset, change (e.g. of 107

frequency or intensity), or offset of an auditory stimulus (Martin et al. 2008; Woods 108

1995). Modulation of LAER amplitude and latency occurs as a function of stimulus 109

intensity, frequency, and duration in normally hearing adults (Rosburg et al. 2002; 110

Woods 1995). The LAER is also thought to critically underlie mechanisms 111

responsible for normal speech perception, and it is reliably elicited and modulated 112

by acoustic changes in naturally occurring speech sounds (Martin et al. 2008). 113

Moreover, auditory neuropathy patients (who exhibit speech-‐comprehension 114

deficits that are disproportionately large when compared to their absolute pure-‐115


5

tone hearing loss), exhibit entirely absent or distorted LAERs as a consequence of 116

disrupted neural synchrony (Cowper-‐Smith et al. 2010). 117

In an effort to understand speech-‐comprehension deficits following cochlear 118

implantation, several groups have investigated the LAER in CI users (e.g. Gilley et al. 119

2008; Hoppe et al. 2001; Sandmann et al. 2010; Sharma et al. 2007; Zhang et al. 120

2010). Although CI users may demonstrate similar modulations of the LAER by 121

stimulus intensity and frequency changes (Hoppe et al. 2001), their responses tend 122

to be reduced in amplitude and increased in latency (relative to normally-‐hearing 123

people; Ponton et al. 2001; Sharma et al. 2005), an effect that is consistent with 124

reduced or slowed neural responsiveness to modulations in sound stimuli. 125

One aspect of the neural response to sound that has not been extensively 126

investigated is refractoriness in CI users. The amplitude of the P1-‐N1-‐P2 complex, 127

and particularly the N1, is monotonically reduced with declining interstimulus 128

intervals (ISI) when brief, consecutive auditory stimuli are presented (Budd et al. 129

1998; Coch et al. 2005; Friesen & Picton, 2010; Martin et al. 2008; Woods 1995). The 130

decline in N1 amplitude with decreasing ISIs appears to be closely related to 131

behavioral thresholds for the detection of distinct stimuli at short ISIs; below the ISI 132

where two distinct stimuli can be discriminated, no N1 is observed for the second 133

stimulus (Coch et al. 2005; Fitzpatrick et al. 1999). Budd et al. (1998) showed that 134

the modulation of N1 amplitude by ISI is more consistent with refractoriness than 135

with habituation. As such, this N1 effect reflects “temporal limitations inherent in 136


6

the physiochemical mechanisms underlying N1 generation” (Budd et al., 1998, p. 137

52), and not habituation to specific stimulus characteristics that may be 138

counteracted by an orienting response to a novel stimulus. Moreover, while N1 139

latency may be related to the speed of the onset of neural processing, the refractory 140

period effect represents a different measure of the speed of neural responsiveness, 141

related to how quickly the system can recover. It is reasonable to expect that this 142

speed of recovery is critical to the processing of tightly-‐spaced temporal acoustic 143

cues, such as speech perception. As such, it is of interest whether CI users show 144

extended refractory responses. 145

Previous work has investigated refractory effects in the auditory responses of CI 146

users. Zhang et al., (2009) demonstrated a non-‐linear recovery function of the LAEP 147

in CI users; in contrast, young healthy controls showed a linear pattern of recovery 148

where increasing ISI was associated with larger N1-‐P2 amplitudes. This result is 149

consistent with the disruption of refractory effects in auditory cortex of CI users. 150

Zhang et al., (2010) subsequently reported refractory effects on the N1-‐P2 complex 151

in CI users using trains of stimuli separated by 700 ms, which were more 152

pronounced in those with higher speech comprehension scores. Finally, Friesen and 153

Picton (2010) showed that CI users’ N1-‐P2 complexes exhibit refractory effects at 154

500 ms ISI relative to 3000 ms ISI. However, none of these studies compared CI 155

users to age-‐matched normally hearing controls. Furthermore, although Zhang et al. 156

(2009) examined the LAEP across several different levels of ISI, they only reported 157


7

data from a single electrode location (Cz), and used ISIs that were 700 ms or longer. 158

Consequently, it remains unclear whether CI users’ LAER responses have a different 159

“time constant” of recovery for shorter ISIs (which might be particularly important 160

for speech sounds) that relates to their poorer temporal acoustic processing, and if 161

so, whether this is true across multiple electrode locations. 162

In the present study we therefore examined the distribution and amplitude of the 163

N1 component of the LAER as a function of auditory ISI in a group of experienced CI 164

users (> 2 years with an activated implant), compared to normally hearing controls. 165

Our analyses focused on the N1, because it is a sensitive measure of temporal 166

processing and stimulus detection, and is the most reliably elicited component of 167

the LAER by an auditory stimulus onset in both normally-‐hearing adults and CI 168

patients with high open-‐set speech comprehension (Hoppe et al. 2001; Martin et al. 169

2008; Schmidt et al. 2005). Given evidence for slower temporal responses and 170

impaired temporal processing of acoustic stimuli in CI users, we predicted that CI 171

users would show increased refractoriness of the N1 (i.e., less recovery of N1 172

amplitude at short ISIs) compared with normally-‐hearing people. Such a finding 173

would be consistent with auditory temporal processing deficits in CI users. 174

Methods 175

Participants 176

Ten adult unilateral CI users (mean age = 47, ranging from 22 to 69) and 14 177

approximately age-‐matched control subjects (mean age = 42, ranging from 22 to 66) 178


8

with normal or corrected-‐to-‐normal vision were tested. All controls and 10 of 11 179

patients were right handed (Oldfield, 1971). Participants reported no history of 180

developmental, neurological, or psychiatric disorders (other than hearing loss in the 181

CI group). Patients had a minimum of 2 years of experience with an activated CI 182

(mean experience = 6.1 years, ranging from 2 to 11 years), and all had experienced 183

chronic severe or profound sensorineural hearing loss prior to implantation. 184

Patients’ mean time since their subjective onset of hearing loss was 31.2 years, 185

(ranging from 15–49 years), while the mean time since the onset of profound 186

hearing loss was 19 years (ranging from 1–49 years), although for some or all of this 187

time, most patients used some form or forms of hearing aid. When hearing outcomes 188

were considered at a plateau by their audiologist, CI users were tested for open-‐set 189

speech comprehension using the Hearing in Noise Test (HINT; Nilsson et al. 1994). 190

Individual background information for each patient is provided in Table 1. All 191

participants gave written, voluntary consent. Participants were compensated $20.00 192

for their participation. This study was approved by the Capital District Health 193

Authority (CDHA) Research Ethics Board. 194

Stimuli 195

Stimuli were 500 Hz tones (standards) and a spoken syllable, /ba/ (targets; 196

recorded from a male voice). All stimuli were 50ms in duration and were presented 197

as bursts without onset or offset ramps; the speech syllable was trimmed and 198

compressed slightly to shorten it to 50 ms. 199


9

Stimulus Delivery 200

The stimulus presentation program was built in Matlab software using the 201

Psychophysics toolbox (Brainard 1997). Auditory stimuli were delivered free-‐field 202

from speakers mounted on either side of the television screen. Sounds were 203

presented at each subject’s most comfortable listening level (MCL), which ranged 204

between 50 and 60 dB SPL, and was determined based on participant feedback. 205

Although we allowed a small range of intensity levels to ensure participants could 206

hear the stimuli, we were not concerned that stimulus intensity would affect the 207

amplitude of the N1 based on recent work demonstrating that the amplitude of the 208

N1 response is not systematically varied by stimulus intensity between 30 and 80 209

dB SPL (Czarniak, 2012). This procedure was successfully employed in recent 210

studies examining refractory effects in CI users (Friesen & Picton, 2010; Zhang et al., 211

2010). 212

Protocol 213

Participants were seated in a sound-‐attenuating booth, centered approximately 110 214

cm away from a 46” Samsung LN46A650 LCD television screen. Participants were 215

instructed to maintain visual fixation on a centrally presented fixation cross (0.5 216

visual degrees in height and width) while listening to the auditory stimuli. A total of 217

550 stimuli were presented in a single, continuous stimulus train during the 218

experiment; 500 of these (91%) were standards (tones), while the other 50 (9%) 219

were targets (syllables). Of the 500 standards, only 450 were used in the LAER 220


10

analysis; the trials that immediately followed each target (50 in total) were 221

discarded to ensure that any responses evoked by the syllabic stimuli did not affect 222

the data used in the LAER analysis. The ISI between each pair of tones was 223

randomized. Of the 450 standards used in the LAER analysis, 150 were preceded by 224

each ISI (500, 1000, and 3000 ms); the tones following targets were all preceded by 225

a 1000 ms ISI. Targets were preceded by equal numbers of each of the three ISIs. 226

Participants were instructed to respond to the target stimuli (the syllable /ba/) as 227

quickly and accurately as possible by pressing a button on a gamepad with their 228

right hand. While refractory effects on the LAER can be obtained in the absence of 229

attention (Friesen & Picton, 2010), we reasoned that the directing attention to the 230

stimuli would serve to amplify the evoked neural responses. 231

Data Collection and Preprocessing 232

EEG Recording. Two types of EEG caps were used for collection of ERP data: a 60-‐233

channel Electro-‐Cap International (ECI; Ohio) system and a 66-‐channel Advanced 234

Neuro Technology (ANT; Enschende, The Netherlands) system. This was 235

necessitated by a failure of some ANT caps partway through the data collection 236

phase of our study; all other data collection equipment (amplifiers, recording 237

computers, etc.) was held constant across all participants. A total of 4 patients and 6 238

controls were run with the ECI caps, while the remaining 6 patients and 8 controls 239

were run with the ANT caps. The two recording caps had 56 electrode positions in 240

common; only these electrode positions (shown in Figure 1) were used in the 241


11

analyses. While we did not expect that the choice of cap would affect data quality, 242

we note that since roughly equal numbers of people in each group were run with 243

each cap type, any differences should not contribute to any observed within-‐ or 244

between-‐group differences. 245

For each participant, it was not possible to record EEG from some electrodes due to 246

interference from the CI transducer; data from these electrodes were interpolated 247

during post-‐processing (see below). Electrodes were also placed above and below 248

the left eye and on the outer canthi of both eyes to monitor for ocular artifacts. The 249

EEG was sampled and digitized at a rate of 256 Hz using a ANT model Refa8-‐64 250

amplifier, amplified by a factor of 20, lowpass filtered at 69.12 Hz and recorded on a 251

computer (Dell Inspiron 6000) using ASA Recorder software (ANT). 252

Insert Figure 1 about here 253

Offline, EEG data were digitally filtered using a finite impulse response filter, first 254

with a high pass cutoff of 0.5Hz and then with a low pass cutoff of 40Hz in EEGLAB 255

Version 9.02 (Delorme et al. 2004). Continuous EEG data was segmented into 256

epochs that started 250 ms prior to, and lasted 600ms after, each stimulus tone 257

(speech syllables were used as targets for the purpose of maintaining subjects’ 258

attention to the stimuli, but ERP to these were not of interest in this study). Epochs 259

in which excessive noise artifact was observed were semi-‐automatically identified 260

(using a maximum peak-‐to-‐peak amplitude threshold tailored to each participant’s 261

dataset, combined with visual inspection) and removed from subsequent analyses. 262


12

Data were next submitted to independent component analysis (ICA) in EEGLAB 263

(Delorme & Makeig, 2004). Components identified in ICA that contained CI artifact, 264

ocular artifacts, or noise isolated to a single electrode were identified and 265

subsequently removed. As described previously, ICA effectively removes CI artifact 266

in ERP data with no, or minimal, residual artifact (Castaneda-‐Villa & James, 2008; 267

Debener et al. 2008; Gilley, Sharma & Dorman, 2008; Martin, 2007; Viola et al., 2011; 268

Zhang et al. 2010). Viola et al. (2011) further showed that removal of CI artifact does 269

not distort the cortical ERPs. It is also worth noting that even if any residual CI 270

artifact had remained in our data, its effects would be negligible due to the design of 271

the study: we compared within-‐subjects differences in the amplitude of the N1 LAER 272

component between identical acoustic stimuli that varied only in their ISI. Thus, as 273

Friesen & Picton (2010) demonstrated, CI artifacts will cancel out in such 274

subtractions since they are highly stable across repetitions of the same stimuli. 275

Statistical Analysis 276

N1 ERP data were extracted as an adaptive mean amplitude, calculated from an 277

average of 7 data points centered on the peak amplitude value (i.e. 3 samples before 278

and 3 samples after the peak value were included) within a 70–140 ms time window 279

following stimulus presentation. This time window was chosen based on the timing 280

of the N1 in the previous literature, as well as visual inspection of the ERP 281

waveforms. 282


13

These data were extracted for each trial, at each electrode, from each participant 283

and submitted to linear mixed effects (LME) modelling (Baayen et al. 2008; Pinheiro 284

et al. 2000) using the function lmer() from the lme4 library in R version 2.10 285

(http://www.R-‐project.org). LME is a relatively recent approach in computational 286

statistics based on restricted maximum-‐likelihood estimation. The use of LMER for 287

EEG data analyses was promoted by Bagiella, Sloan, & Heitja (2000), and has been 288

applied recently by our own lab (Newman et al. 2011) and several other groups. 289

LME models are a form of the general linear model including both fixed effects and 290

random effects parameters. LME modeling offers several advantages over more 291

traditional GLM approaches (Baayen et al. 2008; Bagiella et al. 2000; Pinheiro and 292

Bates 2000), which deal appropriately with unbalanced data, missing data, and non-‐293

sphericity, and increase the accuracy and generalizability of the parameter 294

estimates. For a detailed discussion of the advantages of LME modelling in ERP data 295

analysis, please see Newman et al. (2011) and Bagiella et al. (2000). 296

Identification of the optimal mixed-‐effects model was performed for the dependent 297

measure N1 amplitude through a series of iterative tests in which progressively 298

simpler models were systematically compared to more complex models using log-‐299

likelihood ratio testing (Baayen, et al., 2008; Pinheiro & Bates, 2000). Starting with 300

the most sophisticated mixed-‐effects model (including the interaction among all 301

fixed effects, and all lower-‐order interactions), interactions that did not explain a 302

significant amount of variance were removed in a stepwise manner, one at a time. A 303


14

simpler model (i.e. which excluded a non-‐significant interaction from the previous 304

model) was accepted if the log-‐likelihood test did not reveal a significant difference 305

between the next-‐most complex model. This process continued until the simplest 306

model was identified, defined as the model that had the fewest factors and 307

interactions, while accounting for more variance than the next less-‐complex model. 308

This process was first conducted for the random effects structure of the model, then 309

for the fixed effects structure. Using the simplest model, potential main effects and 310

interactions were examined using F tests. Significant interactions were further 311

analyzed using polynomial contrast sets. Denominator degrees of freedom (df) were 312

calculated as the number of data points minus the number of degrees of freedom 313

used up by the fixed effects and the number of random effects in the model. This 314

allowed the use of lower-‐bound probability values. 315

Target detection accuracy data was analyzed using generalized linear mixed 316

modeling, as implemented in the glmm() function in R, using the logit link function 317

to assume the variance follows a binomial distribution (Faraway, 2006). This is a 318

form of logistic regression using maximum likelihood estimation as in LME. LMER 319

was used to compare reaction time (RT) data between groups and across each level 320

of ISI, using the same procedures described for the ERP data above. 321


15

Results 322

Behavioral Data 323

The optimal generalized linear mixed model for the accuracy data included both 324

fixed effects factors Group and ISI, and a random effects structure that accounted for 325

subject-‐specific variance at each level of ISI. Accuracy was significantly better in the 326

control group compared to CI users, z = -‐2.02, p < .05. 327

The optimal LMER model for RT data included both fixed effects factors, Group and 328

ISI, and random effects for subjects. There was a significant interaction between 329

group and ISI, F(2,664) = 3.5, p < .05, although there were neither main effects of group, 330

F(1,664) = 0.83 p = .36, nor ISI, F(1,664) = 1.83, p = .16. Investigation of the interaction 331

with post hoc tests did not reveal significant differences between the groups for any 332

ISI. Rather, the interaction appeared to stem from the fact that for normally hearing 333

controls, RTs were reliably slower at the 3000 ms ISI than at either the 1000 ms, t= 334

2.5, p < .01, or 500 ms, t = 2.74, p < .01, ISIs. 335

ERP Data 336

The tones reliably elicited P1-‐N1-‐P2 components in both normally hearing controls 337

and CI users. Figure 2 shows the group-‐average LAERs for controls and CI users at 338

the 6 midline electrodes, where the N1 component was largest. In controls, these 339

plots revealed pronounced N1 effects across all levels of ISI at anterior electrode 340

sites (Fz, FCz, Cz, and CPz), a relatively diminished N1 at Pz and little or no N1 at the 341

most posterior electrode, POz. The distribution of the N1 at each ISI is also shown in 342


16

the topographical scalp maps in Figure 3. In CI users, the amplitude of the N1 was 343

reduced overall, relative to controls. These differences can be seen in the right-‐hand 344

panels of Figures 2 and 3. Figure 2 also shows evidence of refractoriness: the N1 345

(and P2) was largest for the 3000 ms ISI, and smaller for the shorter ISIs. 346



Our initial analysis was conducted across all scalp electrodes. Electrodes were 349

grouped into 9 regions of interest arranged in a 3 X 3 grid over the scalp, which was 350

parameterized as two fixed-‐effect factors in the LME analysis, left–right (Left–Right) 351

and anterior–posterior (Ant–Post). We also included as fixed effects the factors 352

group (control or patient) and inter-‐stimulus interval (ISI). The optimal LME model, 353

based on log-‐likelihood ratio testing, included all four independent factors (Group, 354

ISI, AP, & Left–Right) and a random effects structure that included subject-‐specific 355

slopes for AP, Left–Right, and ISI. The 4-‐way Group X ISI X Ant–Post X Left–Right and 356

3-‐way Group X ISI X Left–Right interactions did not explain significant amounts of 357

variance and so were not included in the final model. All other interactions were 358

significant and thus included in the optimal LME model (Table 2). The lack of a 3-‐359

way interaction between Group, ISI, and Left–Right indicated that ISI did not 360

systematically modulate the amplitude of the N1 between controls and patients as a 361

function of Left–Right distribution. Given that the N1 was maximal over midline 362

electrodes, consistent with previous studies (Coch et al. 2005), we conducted more 363


17

detailed analyses that were restricted to the midline electrodes and that included 6 364

Ant-‐Post levels. 365

Each Ant-‐Post level in the midline analyses included three electrodes (treated as 366

repeated measures of that level) aligned in the same row, which we refer to here 367

using the nomenclature of the International 10-‐20 System (see Figure 1). The 368

optimal model included fixed effects factors group, ISI, and Ant–Post, and a random-‐369

effects structure that accounted for subject-‐specific variance in the distribution of 370

effects over the Ant–Post dimension and across levels of ISI. Main effects of Group, 371

F(1, 129983)= 6.38, p < .01, ISI, F(2, 129983) = 24.54, p < .001, and Ant–Post, F(5, 129983) = 372

6.93, p < .001, were qualified by a significant 3-‐way interaction, Group X ISI X Ant–373

Post, F(10, 129983)=4.80, p < .0001, which confirmed the findings of the analysis over all 374

electrodes, that the refractory effects were modulated by both group and electrode 375

position. 376

Mean amplitudes across the electrodes at each ROI are shown in Figure 4. In order 377

to further explore the distribution of ERP effects in each group along the Ant–Post 378

dimension, and test our predictions that ISI would modulate ERP amplitude 379

parametrically (with increasing N1 amplitudes from 500 – 3000 ms), we conduced 380

pairwise contrasts between adjacent levels of ISI, for controls and patients 381

separately at each level of Ant–Post; Sidak corrections were applied to p values to 382

correct for multiple comparisons (number of comparisons arising from contrasting 383

ISI 500 vs 1000, and 1000 vs 3000 [2], multiplied by levels of Ant–Post [6], 384


18

multiplied by groups [2] = 24). Normally-‐hearing controls showed the expected 385

refractory effects, with significantly (p < .05, corrected) greater N1 amplitude at 386

3000 compared to 1000 ms, and at 1000 compared to 500 ms ISIs, at the 2 most 387

anterior levels of Ant–Post (F, FC, C), as well as at the next-‐most anterior level (CP) 388

for the 1000 vs. 500 ms comparison. In contrast, CI users showed no significant 389

differences in the amplitude of the N1s elicited by tones at 500 and 1000 ms ISIs, 390

but significant differences between 1000 and 3000 ms ISIs the 2 most anterior 391

levels (F, FC). Detailed statistics are presented in Table 3. 392


Discussion 394

The present study compared the temporal response properties of auditory 395

processing using an ERP measure of LAER refractoriness in experienced CI users 396

relative to normally hearing controls. Auditory refractoriness is considered a 397

measure of how quickly physiochemical mechanisms underlying the LAER can 398

recover from the processing of a sound event (Budd et al. 1998), and therefore 399

provides a useful tool for the study of one dimension of temporal processing in the 400

auditory system. Given the documented deficits of temporal processing in people 401

who received CIs as adults (e.g. Aronoff et al. 2010; Garadat et al. 2011; Sandmann et 402

al. 2010), we predicted longer refractory periods in CI users than normally hearing 403


19

controls, reflecting slowed recovery and thus decreased temporal sensitivity of 404

auditory cortical responses1. 405

The data confirmed our hypothesis. Normally hearing controls showed recovery of 406

N1 amplitudes at 1000 relative to 500 ms ISIs over frontal and central-‐parietal 407

midline electrodes (positions F, FC, C, and CP), and additional recovery between 408

1000 and 3000 ms ISIs at the more frontal electrodes (F, FC, and C). In contrast, CI 409

users showed no reliable differences in N1 amplitude between 500 and 1000 ms. 410

Rather, recovery was only evident between the 1000 and 3000 ms ISIs, and these 411

differences were restricted to the more frontal electrode positions (levels F, and FC 412

only). 413

Coch et al. (2005) found that the lower limit of the refractory period, defined as the 414

minimum ISI capable of eliciting different N1 amplitudes, is likely somewhere 415

between 200 and 500 ms in normally hearing individuals. Correspondingly, we 416

expected to observe progressively larger N1 amplitudes for stimuli separated by 417

500, 1000, and 3000 ms in normally hearing controls, and indeed this is what we 418

found. However, the present data indicate that the lower limit of the refractory 419

period is longer in CI patients than normally hearing controls. Specifically, because 420

500 and 1000 ms ISIs elicited equivalent N1 amplitudes across all 6 levels of the 421

1 It is important to note that our results reflect decreased temporal resolution of the cortical response, rather than a broader deficit in temporal processing. For example, while the CI and the subcortical auditory processing system may be able to represent rapidly changing temporal information, our results suggest that temporal processes appear to be disrupted at higher levels of processing.


20

Ant–Post dimension, the lower limit of the refractory period in CI users must be 422

greater than 1000 ms; i.e., over double that of normally hearing controls. These data 423

add to previous findings using similar paradigms. Zhang et al. (2010) showed 424

refractoriness for stimuli separated by 700 ms, but only relative to the first stimulus 425

of a train, which would have had a particularly long ISI preceding it. Friesen and 426

Picton (2010) contrasted 500 and 3000 ms ISIs and found refractory effects in CI 427

users, as we did, but did not test the intermediate 1000 ms ISI nor did they have a 428

normally-‐hearing control group. The present results support our prediction that CI 429

users would exhibit disrupted neural refractory processes. These data suggest the 430

presence of a temporal processing deficit (cf. Fitzpatrick et al. 1999) whereby the 431

LAERs of CI users do not differentiate between tones separated by 500 or 1000 ms. 432

This suggests a slowed recovery period of the neural generators of the N1 433

component, which are primarily located in the superior temporal gyrus (Woods, 434

1995). 435

In addition to a heightened lower limit of the refractory period, the scalp 436

distribution of N1 refractory period effects appeared to be more focal in CI users: 437

refractory effects were found at frontal, central, and central-‐parietal electrode sites 438

in normally hearing people but only at frontal sites in CI users. As described in the 439

introduction, depriving the auditory cortex of acoustic information is likely to result 440

in long-‐lasting reductions in connectivity, and impaired decoding of sound 441

information delivered by a CI. The more focal distribution of the N1 over the scalp in 442


21

CI users may be the consequence of a reduced cortical area responsive to sound, 443

and/or reduced neural synchrony leading to both reduced amplitude and spatial 444

extent. Another possibility is that the orientation of dipoles in auditory cortex is 445

altered in a way that results in a more focal distribution of the N1 in CI users. 446

Given that our patients all had a minimum of 2 years’ experience with their CI 447

activated, and research demonstrating that the most dramatic changes in hearing 448

abilities occur within the first year post-‐implantation (Peterson et al. 2010), our 449

data are consistent with the view that the neuroplastic capacity of the auditory 450

system of adult CI users is limited. This could result from cross-‐modal take-‐over of 451

the auditory cortex by visual processing functions (Sandmann et al., 2012), from 452

reduced spontaneous activity and unusually high synchrony of electrically evoked 453

activity in the auditory nerve (e.g. Pagialonga et al., 2010), or some combination of 454

these factors. Consequently, adult CI recipients appear unlikely to undergo complete 455

recovery on a neurophysiological level. 456

Interestingly, these persistent deficits in temporal processing at the 457

electrophysiological level occurred even in the context of relatively good hearing —458

most of our participants had speech comprehension scores of 90% or above. This 459

result must be interpreted cautiously, since the HINT sentences were administered 460

in quiet, and presentation of the same sentences in noise (or other tests that better 461

simulated real-‐world listening conditions) may have revealed poorer performance 462

relative to people with normal hearing. We note that two of our participants had 463


22

dramatically poorer speech comprehension scores than the others; however when 464

we repeated the statistical analyses with these two subjects omitted, the pattern of 465

results did not change. Thus while the small sample size and bimodal distribution of 466

HINT scores did not lend these data to a correlational analysis between the N1 467

refractory period effects and HINT scores, we found no evidence that the 468

electrophysiological effects were closely related to speech comprehension in quiet. 469

Conclusion 470

The present findings reveal a temporal auditory processing deficit in CI users, 471

evidenced through a disruption of normal refractory effects. In particular, the 472

refractory period threshold, defined as the minimum ISI where different N1 473

amplitudes are elicited, is greater than 1000ms in CI patients; at least double that of 474

normally hearing controls. 475

Future Directions 476

While evidence for a temporal processing deficit in CI users were provided from the 477

lack of differential N1 amplitudes observed between stimuli separated by 500 or 478

1000 ms in the present study, a more thorough characterization of this temporal 479

processing deficit may be advantageous. Specifically, although the present data 480

indicate the refractory threshold of CI users, i.e. the minimum ISI required to evoke 481

different N1 amplitudes, is somewhere between 1000 and 3000ms, the precise 482

timing of the refractory threshold remains an open question. Establishing the lower 483

limit of refractory period effects in individual patients may be useful for optimizing 484


23

CI stimulation parameters in an attempt to compensate for the altered temporal 485

resolution of auditory processing, thereby promoting perception of temporally-‐486

defined sound information. Moreover, it is likely that the modulation of N1 487

amplitude by ISI may be different depending on the types of auditory stimuli 488

presented; such a proposal is supported by research demonstrating different N1 489

amplitudes for stimuli of different frequencies (Martin et al. 2008; Woods 1995). 490

Future research may therefore aim to determine the minimum ISI required for 491

larger N1 amplitudes using a variety of different stimulus types. Of particular 492

relevance to CI users, it may be useful to adapt the present task to utilize naturally 493

occurring speech sounds (such as the presentation of a brief vowel sound). 494

The present data provide a further basis for future work aiming to improve the CI 495

signal delivered to the auditory nerve in order to enhance the delivery and 496

processing of sound information reliant on temporal acuity. Currently, several lines 497

of research in animal models are focused on replicating normal neural 498

responsiveness to sound information delivered via CI in the auditory nerve, 499

brainstem, and cortex (e.g. Loquet et al., 2004). While this line of research can allow 500

for detailed explorations of neurophysiological responses to CI stimulation in animal 501

models, it is equally important to determine if relatively normal patterns of auditory 502

processing activity can be obtained in human CI users. The present paradigm may 503

be adopted for this purpose in future studies, in an effort to determine if different 504

patient etiologies, CI stimulation parameters and/or rehabilitation approaches 505


24

during speech therapy are effective in replicating relatively normal LAER 506

amplitudes and distributions. Using this approach, it may be possible to further 507

improve CI treatment outcome. 508

509

510


25

References 511

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633


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Table 1. Background Patient Information. At the time of implantation, all 634

patients had severe or profound hearing loss and all patients were unilaterally 635

implanted. On the date of EEG testing, all patients had a minimum of 2 years CI 636

experience. *HINT scores were obtained using HINT sentences presented at 55 dB 637

HL / 70 dB SPL, in the absence of noise. 638

639

Age (years)

Sex Duration of Subjective Hearing Loss prior to CI

implant (years)

CI Experience (years)

HINT Date (post-‐CI)

HINT Score*

Patients PHD_03 47 F 37 5 1 yr 2% PHD_05 56 M 33 10 9 yr 100% PHD_06 22 M 22 10 -‐ 0% PHD_07 44 M 10 11 6 yr 52% PHD_08 66 F 15 8 2 yr 90% PHD_09 29 F 10 3 2 mo 98% PHD_10 44 F 16 8 4 yr 99% PHD_17 20 M 18 10 9 yr 84% PHD_18 54 M 34 2 1yr 96% PHD_19 53 M 47 5 5yr 100%

640

641


30

642 Table 2. ANOVA table of the optimal linear mixed effects model including all 643

scalp electrodes. 644

F P df Group 0.66 .41 1 410486 ISI 246.94 .0001 2 410486 AP 337.23 .0001 2 410486 LR 189.97 .0001 2 410486 Group x ISI 1.85 .0001 2 410486 Group x AP 81.56 .16 2 410486 ISI x AP 27.53 .0001 4 410486 Group x LR 146.15 .0001 4 410486 AP x LR 103.82 .0001 4 410486 ISI x LR 13.86 .0001 4 410486 Group x ISI x AP 9.65 .0001 4 410486 Group x AP x LR 14.29 .0001 4 410486 ISI x AP x LR 3.11 .005 8 410486

645

646


31

647 Table 3. Results of pairwise contrast sets comparing ISI 500 vs ISI 1000 and 648

ISI 1000 vs ISI 3000 at each level of the anterior-‐posterior (Ant–Post) dimension. 649

ROI labels are the capital letters in common to all electrodes within the ROI taken 650

from the 10-‐20 international system. Values represent the absolute value of t-‐651

statistics; p values were corrected using Sidak’s correction for the 24 comparisons 652

shown. Ant-‐Post levels are labeled as: frontal (F), fronto-‐central (FC), central (C), 653

central-‐parietal (CP), parietal (P), and parietal-‐occipital (PO). 654

655 Controls Patients 500 vs 1000 1000 vs 3000 500 vs 1000 1000 vs 3000 Ant-‐Post level

t p t p t p t P

F 4.80 .0001 3.60 .005 0.39 1 5.36 .0001 FC 5.13 .0001 4.70 .0001 0.36 1 3.85 .001 C 3.54 .005 4.69 .0001 1.73 .5 0.9 1 CP 3.24 .01 0.17 1 1.04 1 2.21 .16 P 0.32 1 2.31 .13 0.93 1 0.67 1

656

657


32

Figure Captions 658

Figure 1. Channel locations used for data analyses. Dashed lines separate the 9 659

regions of interest used in preliminary analyses determining the overall distribution 660

of ERP effects. The solid line encloses 6 rows of electrodes that were included in the 661

midline analyses. Midline analyses focused on characterizing how ERP effects 662

differed between patients and controls in the midline. 663

Figure 2. Grand average waveforms at midline electrodes, elicited in response to 664

stimuli separated by an ISI of 500, 1000, and 3000 ms in each group. 665

Figure 3. Scalp voltage maps illustrating the distribution of the N1 ERP component 666

(averaged over 90–110 msec) at each level of ISI. 667

Figure 4. Amplitude of the N1 component in CI users and Controls, averaged over all 668

midline electrodes at each level of the anterior-‐posterior dimension as defined in 669

Table 1. 670

671


33

FIGURE 1 672

673

674


34

FIGURE 2 675

676

677


35

FIGURE 3 678

679


36

FIGURE 4 680

681

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