Fawen Zhang

Changes Across Time in Spike Rate and Spike Amplitude of Auditory Nerve Fibers Stimulated by Electric Pulse Trains

We undertook a systematic evaluation of spike rates and spike amplitudes of auditory nerve fiber (ANF) responses to trains of electric current pulses. Measures were obtained from acutely deafened cats to examine time-related changes free from the effects of hair-cell and synaptic adaptation. Such data relate to adaptation that likely occurs in ANFs of cochlear-implant users. A major goal was to determine and compare rate adaptation observed at different pulse rates (primarily 250, 1000, and 5000 pulse/s) and describe them using decaying exponential models similar to those used in acoustic studies. Rate-vs.-time functions were best described by two-exponent models and produced time constants similar to (although slightly greater than) the “rapid” and “short-term” components described in acoustic studies. There was little dependence of these time constants on onset spike rate, but pulse-rate effects were noted. Spike amplitude changes followed a time course different from that of rate adaptation consistent with a process related to ANF interspike intervals. The fact that two time constants governed rate adaptation in electrically stimulated and deafened fibers suggests that future computational models of adaptation should not only include hair cell and synapse components, but also components determined by fiber membrane characteristics.

Electrical Excitation of the Acoustically Sensitive Auditory Nerve: Single-Fiber Responses to Electric Pulse Trains

Nearly all studies on auditory-nerve responses to electric stimuli have been conducted using chemically deafened animals so as to more realistically model the implanted human ear that has typically been profoundly deaf. However, clinical criteria for implantation have recently been relaxed. Ears with “residual” acoustic sensitivity are now being implanted, calling for the systematic evaluation of auditory-nerve responses to electric stimuli as well as combined electric and acoustic stimuli in acoustically sensitive ears. This article presents a systematic investigation of single-fiber responses to electric stimuli in acoustically sensitive ears. Responses to 250 pulse/s electric pulse trains were collected from 18 cats. Properties such as threshold, dynamic range, and jitter were found to differ from those of deaf ears. Other types of fiber activity observed in acoustically sensitive ears (i.e., spontaneous activity and electrophonic responses) were found to alter the temporal coding of electric stimuli. The electrophonic response, which was shown to greatly change the information encoded by spike intervals, also exhibited fast adaptation relative to that observed in the “direct” response to electric stimuli. More complex responses, such as “buildup” (increased responsiveness to successive pulses) and “bursting” (alternating periods of responsiveness and unresponsiveness) were observed. Our findings suggest that bursting is a response unique to sustained electric stimulation in ears with functional hair cells.

The adaptive pattern of the late auditory evoked potential elicited by repeated stimuli in cochlear implant users.

Abstract To describe the adaptive pattern of cortically generated auditory evoked potentials elicited by repeated stimuli via cochlear implants (CIs), the late auditory evoked potential (LAEP) was collected from nine postlingually deafened adult CI users. Tone bursts were presented in 30 trains consisting of 10 tone bursts each, with inter-stimulus intervals (ISIs) of 0.7 ms and inter-train intervals (ITIs) of 15s. The response to the first stimulus and the response to later tone bursts in the train were compared. Results showed that the LAEP for the first tone burst was larger than that for later tone bursts, displaying an adaptive pattern. This pattern appeared to be more prominent in CI users with good speech perception performance than in those with poorer performance. This finding is meaningful in the context of our future research to restore normal adaptation in CI users to improve their speech perception performance. Sumario Para describir el patrón adaptativo de los potenciales auditivos generados en la corteza, evocados por estímulos repetidos por la vía de los implantes cocleares (CI), se colectaron los potenciales evocados auditivos tardíos de nueve pacientes sordos post-lingüísticos usuarios de CI. Se presentaron 30 series de 10 burst tonales cada uno con intervalos entre los estímulos (ISI) de 0.7 ms e intervalos entre las series de 15 segundos. La respuesta a estos primeros estímulos y la respuesta a burst tonales posteriores en la serie fueron comparados. Los resultados demostraron que los LAEP para este primer burst tonal fueron más prolongados que para los burst tonales posteriores, desplegándose un patrón adaptativo. Este patrón pareció ser más prominente en usuarios de CI con buen desempeño en la percepción del lenguaje que en aquellos con un desempeño pobre. Este hallazgo es significativo en el contexto de nuestra investigación a futuro para restablecer la adaptación normal en usuarios de CI para mejorar su desempeño en la percepción del lenguaje.

Contralateral suppression of distortion product otoacoustic emissions: Effect of the primary frequency in Dpgrams

The amplitude of the 2f1–f2 distortion product otoacoustic emission (DPOAE) can be suppressed by presenting contralateral acoustic stimulation. To test the hypothesis that DPOAE contralateral suppression is influenced by the primary frequency in DPgrams, DPgrams were recorded at resolutions of 1, 8, and 17 pts/octave, in the absence and presence of contralateral broadband noise (BBN). Participants were 20 normal-hearing human adults. In DPgrams with higher frequency resolutions, DPOAE suppression at amplitude peaks in DPgrams (8 pts/octave: Mean = − 0.92 dB, SD = 0.71 for BBN at 60 dB SPL; 17 pts/octave: Mean = − 0.25 to −1.44 dB, SD = 0.51 to 0.86 for BBN at 40 to 70 dB SPL, respectively) was larger than the suppression at the dips in DPgrams (8 pts/octave: Mean = − 0.13 dB, SD = 1.00; 17 pts/octave: Mean = − 0.03 to −0.73 dB, SD = 0.55 to 0.91). A larger intersubject variability in DPOAE contralateral suppression was observed at the dips. The results suggest that measuring DPOAE contralateral suppression at the primary frequencies corresponding to the peaks in DPgrams with higher frequency resolutions may improve the assessment of the efferent system function.

Accumulated source imaging of brain activity with both low and high-frequency neuromagnetic signals

Recent studies have revealed the importance of high-frequency brain signals (>70 Hz). One challenge of high-frequency signal analysis is that the size of time-frequency representation of high-frequency brain signals could be larger than 1 terabytes (TB), which is beyond the upper limits of a typical computer workstations memory (<196 GB). The aim of the present study is to develop a new method to provide greater sensitivity in detecting high-frequency magnetoencephalography (MEG) signals in a single automated and versatile interface, rather than the more traditional, time-intensive visual inspection methods, which may take up to several days. To address the aim, we developed a new method, accumulated source imaging, defined as the volumetric summation of source activity over a period of time. This method analyzes signals in both low- (1~70 Hz) and high-frequency (70~200 Hz) ranges at source levels. To extract meaningful information from MEG signals at sensor space, the signals were decomposed to channel-cross-channel matrix (CxC) representing the spatiotemporal patterns of every possible sensor-pair. A new algorithm was developed and tested by calculating the optimal CxC and source location-orientation weights for volumetric source imaging, thereby minimizing multi-source interference and reducing computational cost. The new method was implemented in C/C++ and tested with MEG data recorded from clinical epilepsy patients. The results of experimental data demonstrated that accumulated source imaging could effectively summarize and visualize MEG recordings within 12.7 h by using approximately 10 GB of computer memory. In contrast to the conventional method of visually identifying multi-frequency epileptic activities that traditionally took 2–3 days and used 1–2 TB storage, the new approach can quantify epileptic abnormalities in both low- and high-frequency ranges at source levels, using much less time and computer memory.

Auditory Nerve Fiber Responses to Combined Acoustic and Electric Stimulation

Persons with a prosthesis implanted in a cochlea with residual acoustic sensitivity can, in some cases, achieve better speech perception with “hybrid” stimulation than with either acoustic or electric stimulation presented alone. Such improvements may involve “across auditory-nerve fiber” processes within central nuclei of the auditory system and within-fiber interactions at the level of the auditory nerve. Our study explored acoustic–electric interactions within feline auditory nerve fibers (ANFs) so as to address two goals. First, we sought to better understand recent results that showed non-monotonic recovery of the electrically evoked compound action potential (ECAP) following acoustic masking (Nourski et al. 2007, Hear. Res. 232:87–103). We hypothesized that post-masking changes in ANF temporal properties and responsiveness (spike rate) accounted for the ECAP results. We also sought to describe, more broadly, the changes in ANF responses that result from prior acoustic stimulation. Five response properties—spike rate, latency, jitter, spike amplitude, and spontaneous activity—were examined. Post-masking reductions in spike rate, within-fiber jitter and across-fiber variance in latency were found, with the changes in temporal response properties limited to ANFs with high spontaneous rates. Thus, our results suggest how non-monotonic ECAP recovery occurs for ears with spontaneous activity, but cannot account for that pattern of recovery when there is no spontaneous activity, including the results from the presumably deafened ears used in the Nourski et al. (2007) study. Finally, during simultaneous (electric+acoustic) stimulation, the degree of electrically driven spike activity had a strong influence on spike rate, but did not affect spike jitter, which apparently was determined by the acoustic noise stimulus or spontaneous activity.

The adaptive pattern of the auditory N1 peak revealed by standardized low-resolution brain electromagnetic tomography.

The N1 peak in the late auditory evoked potential (LAEP) decreases in amplitude following stimulus repetition, displaying an adaptive pattern. The present study explored the functional neural substrates that may underlie the N1 adaptive pattern using standardized Low Resolution Electromagnetic Tomography (sLORETA). Fourteen young normal hearing (NH) listeners participated in the study. Tone bursts (80 dB SPL) were binaurally presented via insert earphones in trains of 10; the inter-stimulus interval was 0.7s and the inter-train interval was 15s. Current source density analysis was performed for the N1 evoked by the 1st, 2nd and 10th stimuli (S(1), S(2) and S(10)) at 3 different timeframes that corresponded to the latency ranges of the N1 waveform subcomponents (70-100, 100-130 and 130-160 ms). The data showed that S(1) activated broad regions in different cortical lobes and the activation was much smaller for S(2) and S(10). Response differences in the LAEP waveform and sLORETA were observed between S(1) and S(2), but not between the S(2) and S(10). The sLORETA comparison map between S(1) and S(2) responses showed that the activation was located in the parietal lobe for the 70-100 ms timeframe, the frontal and limbic lobes for the 100-130 ms timeframe, and the frontal lobe for the 130-160 ms timeframe. These sLORETA comparison results suggest a parieto-frontal network that might help to sensitize the brain to novel stimuli by filtering out repetitive and irrelevant stimuli. This study demonstrates that sLORETA may be useful for identifying generators of scalp-recorded event related potentials and for examining the physiological features of these generators. This technique could be especially useful for cortical source localization in individuals who cannot be examined with functional magnetic resonance imaging or magnetoencephalography (e.g., cochlear implant users).

Volumetric imaging of brain activity with spatial-frequency decoding of neuromagnetic signals.

BACKGROUND The brain generates signals in a wide frequency range (∼2840 Hz). Existing magnetoencephalography (MEG) methods typically detect brain activity in a median-frequency range (1-70 Hz). The objective of the present study was to develop a new method to utilize the frequency signatures for source imaging. NEW METHOD Morlet wavelet transform and two-step beamforming were integrated into a systematic approach to estimate magnetic sources in time-frequency domains. A grid-frequency kernel (GFK) was developed to decode the correlation between each time-frequency representation and grid voxel. Brain activity was reconstructed by accumulating spatial- and frequency-locked signals in the full spectral data for all grid voxels. To test the new method, MEG data were recorded from 20 healthy subjects and 3 patients with verified epileptic foci. RESULTS The experimental results showed that the new method could accurately localize brain activation in auditory cortices. The epileptic foci localized with the new method were spatially concordant with invasive recordings. COMPARISON WITH EXISTING METHODS Compared with well-known existing methods, the new method is objective because it scans the entire brain without making any assumption about the number of sources. The novel feature of the new method is its ability to localize high-frequency sources. CONCLUSIONS The new method could accurately localize both low- and high-frequency brain activities. The detection of high-frequency MEG signals can open a new avenue in the study of the human brain function as well as a variety of brain disorders.

Neural Adaptation and Behavioral Measures of Temporal Processing and Speech Perception in Cochlear Implant Recipients

The objective was to determine if one of the neural temporal features, neural adaptation, can account for the across-subject variability in behavioral measures of temporal processing and speech perception performance in cochlear implant (CI) recipients. Neural adaptation is the phenomenon in which neural responses are the strongest at the beginning of the stimulus and decline following stimulus repetition (e.g., stimulus trains). It is unclear how this temporal property of neural responses relates to psychophysical measures of temporal processing (e.g., gap detection) or speech perception. The adaptation of the electrical compound action potential (ECAP) was obtained using 1000 pulses per second (pps) biphasic pulse trains presented directly to the electrode. The adaptation of the late auditory evoked potential (LAEP) was obtained using a sequence of 1-kHz tone bursts presented acoustically, through the cochlear implant. Behavioral temporal processing was measured using the Random Gap Detection Test at the most comfortable listening level. Consonant nucleus consonant (CNC) word and AzBio sentences were also tested. The results showed that both ECAP and LAEP display adaptive patterns, with a substantial across-subject variability in the amount of adaptation. No correlations between the amount of neural adaptation and gap detection thresholds (GDTs) or speech perception scores were found. The correlations between the degree of neural adaptation and demographic factors showed that CI users having more LAEP adaptation were likely to be those implanted at a younger age than CI users with less LAEP adaptation. The results suggested that neural adaptation, at least this feature alone, cannot account for the across-subject variability in temporal processing ability in the CI users. However, the finding that the LAEP adaptive pattern was less prominent in the CI group compared to the normal hearing group may suggest the important role of normal adaptation pattern at the cortical level in speech perception.

Spatiotemporal and frequency signatures of word recognition in the developing brain: A magnetoencephalographic study

High-frequency oscillations in the brain open a new window for studies of language development in humans. The objective of this study is to determine the spatiotemporal and frequency signatures of word processing in healthy children. Sixty healthy children aged 6-17 years were studied with a whole-cortex magnetoencephalography (MEG) system using a word recognition paradigm optimized for children. The temporal signature of neuromagnetic activation was measured using averaged waveforms. The spatial and frequency signatures of neuromagnetic activation were assessed with wavelet-based beamformer analyses. The results of waveform analyses showed that the latencies of the first and third neuromagnetic responses changed with age (p<0.01). The source imaging data revealed a clear lateralization of source activation in the 70-120 Hz range in children within the age range of 6 to 13 years of age (p<0.01). Males and females demonstrated different developmental trajectories over the age range of 9 to 13 years of age (p<0.01). These findings suggest that left-hemisphere language processing emerges from early bilateral brain areas with gender optimal neural networks. The neuromagnetic signatures of language development in healthy children may be used as references for future identification of aberrant language function in children with various disorders.