A point process framework for modeling electrical stimulation of the auditory nerve

Model-based studies of auditory nerve responses to electrical stimulation can provide insight into the functioning of cochlear implants. Ideally, these studies can identify limitations in sound processing strategies and lead to improved methods for providing sound information to cochlear implant users. To accomplish this, models must accurately describe auditory nerve spiking while avoiding excessive complexity that would preclude large-scale simulations of populations of auditory nerve fibers and obscure insight into the mechanisms that influence neural encoding of sound information. In this spirit, we develop a point process model of the auditory nerve that provides a compact and accurate description of neural responses to electric stimulation. Inspired by the framework of generalized linear models, the proposed model consists of a cascade of linear and nonlinear stages. We show how each of these stages can be associated with biophysical mechanisms and related to models of neuronal dynamics. Moreover, we derive a semi-analytical procedure that uniquely determines each parameter in the model on the basis of fundamental statistics from recordings of single fiber responses to electric stimulation, including threshold, relative spread, jitter, and chronaxie. The model also accounts for refractory and summation effects that influence the responses of auditory nerve fibers to high pulse rate stimulation. Throughout, we compare model predictions to published physiological data and explain differences in auditory nerve responses to high and low pulse rate stimulation. We close by performing an ideal observer analysis of simulated spike trains in response to sinusoidally amplitude modulated stimuli and find that carrier pulse rate does not affect modulation detection thresholds.Comment: 1 title page, 27 manuscript pages, 14 figures, 1 table, 1 appendi

On the mechanism of response latencies in auditory nerve fibers

Despite the structural differences of the middle and inner ears, the latency pattern in auditory nerve fibers to an identical sound has been found similar across numerous species. Studies have shown the similarity in remarkable species with distinct cochleae or even without a basilar membrane. This stimulus-, neuron-, and species- independent similarity of latency cannot be simply explained by the concept of cochlear traveling waves that is generally accepted as the main cause of the neural latency pattern. An original concept of Fourier pattern is defined, intended to characterize a feature of temporal processing—specifically phase encoding—that is not readily apparent in more conventional analyses. The pattern is created by marking the first amplitude maximum for each sinusoid component of the stimulus, to encode phase information. The hypothesis is that the hearing organ serves as a running analyzer whose output reflects synchronization of auditory neural activity consistent with the Fourier pattern. A combined research of experimental, correlational and meta-analysis approaches is used to test the hypothesis. Manipulations included phase encoding and stimuli to test their effects on the predicted latency pattern. Animal studies in the literature using the same stimulus were then compared to determine the degree of relationship. The results show that each marking accounts for a large percentage of a corresponding peak latency in the peristimulus-time histogram. For each of the stimuli considered, the latency predicted by the Fourier pattern is highly correlated with the observed latency in the auditory nerve fiber of representative species. The results suggest that the hearing organ analyzes not only amplitude spectrum but also phase information in Fourier analysis, to distribute the specific spikes among auditory nerve fibers and within a single unit. This phase-encoding mechanism in Fourier analysis is proposed to be the common mechanism that, in the face of species differences in peripheral auditory hardware, accounts for the considerable similarities across species in their latency-by-frequency functions, in turn assuring optimal phase encoding across species. Also, the mechanism has the potential to improve phase encoding of cochlear implants

Towards a better speech processor for cochlear implants : auditory- nerve responses to high-rate electric pulse trains

Thesis (Ph.D.)--Harvard--Massachusetts Institute of Technology Division of Health Sciences and Technology, 2002.Includes bibliographical references (p. 169-184).This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cochlear implants are prosthetic devices that seek to restore hearing in profoundly deaf patients by electrically stimulating the auditory-nerve (AN). With current implants, the representation of the sound waveform in temporal discharge patterns of the auditory nerve is severely distorted. The distortion is particularly significant at higher (>600 Hz) frequencies, for which the period of the electric stimulus is near the AN refractory period. For example, in response to a 1000-Hz pulse train, most AN fibers may fire on every other stimulus cycle, so that the AN population would represent half of the stimulus frequency rather than the actual frequency. Rubinstein et al. [Hearing. Res. 127, 108] proposed that the coding of electric waveforms in cochlear implants can be improved if a sustained, electric high-rate (5 kpps) desynchronizing pulse train (DPT) is presented in addition to the information-carrying electric stimulus. The DPT may amplify the inherent noise in ANfibers so as to produce ongoing, stochastic discharges similar to the spontaneous activity in a healthy hear. We tested this hypothesis by recording responses of ANfibers of deafened cats to sustained electric pulse trains. For most fibers, responses to the DPT showed adaptation during the first 2 minutes, followed by a sustained response for the remainder of the 10-minute stimulus. These sustained responses partially resembled spontaneous activity in terms of discharge rate and interspike interval distributions. AN fibers were extremely sensitive to modulations of the DPT, responding tomodulations as small as 0.5%.(cont.) Responses to sinusoidal modulations resembled AN responses to pure tones over a 15-25 dB range of modulation depths. Responses to complex modulations simultaneously represented several spectral components of the modulator in their temporal discharge patterns. However, for modulation depths above 10%, the representation of both sinusoidal and complex modulators was more distorted. These results demonstrate that strategies that incorporate a DPT, and that use low modulation depths to encode sounds, may evoke AN responses that more accurately represent the modulator in their temporal discharge patterns. If the central nervous system can utilize this information, then these strategies may substantially improve performance enjoyed by cochlear implant users.by Leonid Litvak.Ph.D

Short Term Depression Unmasks the Ghost Frequency

Short Term Plasticity (STP) has been shown to exist extensively in synapses throughout the brain. Its function is more or less clear in the sense that it alters the probability of synaptic transmission at short time scales. However, it is still unclear what effect STP has on the dynamics of neural networks. We show, using a novel dynamic STP model, that Short Term Depression (STD) can affect the phase of frequency coded input such that small networks can perform temporal signal summation and determination with high accuracy. We show that this property of STD can readily solve the problem of the ghost frequency, the perceived pitch of a harmonic complex in absence of the base frequency. Additionally, we demonstrate that this property can explain dynamics in larger networks. By means of two models, one of chopper neurons in the Ventral Cochlear Nucleus and one of a cortical microcircuit with inhibitory Martinotti neurons, it is shown that the dynamics in these microcircuits can reliably be reproduced using STP. Our model of STP gives important insights into the potential roles of STP in self-regulation of cortical activity and long-range afferent input in neuronal microcircuits

Short and long-term adaptation in the auditory nerve stimulated with high-rate electrical pulse trains are better described by a power law

Despite the introduction of many new sound-coding strategies speech perception outcomes in cochlear implant listeners have leveled off. Computer models may help speed up the evaluation of new sound-coding strategies, but most existing models of auditory nerve responses to electrical stimulation include limited temporal detail, as the effects of longer stimulation, such as adaptation, are not well-studied. Measured neural responses to stimulation with both short (400 ms) and long (10 min) duration high-rate (5kpps) pulse trains were compared in terms of spike rate and vector strength (VS) with model outcomes obtained with different forms of adaptation. A previously published model combining biophysical and phenomenological approaches was adjusted with adaptation modeled as a single decaying exponent, multiple exponents and a power law. For long duration data, power law adaptation by far outperforms the single exponent model, especially when it is optimized per fiber. For short duration data, all tested models performed comparably well, with slightly better performance of the single exponent model for VS and of the power law model for the spike rates. The power law parameter sets obtained when fitted to the long duration data also yielded adequate predictions for short duration stimulation, and vice versa. The power law function can be approximated with multiple exponents, which is physiologically more viable. The number of required exponents depends on the duration of simulation; the 400 ms data was well-replicated by two exponents (23 and 212 ms), whereas the 10-minute data required at least seven exponents (ranging from 4 ms to 600 s). Adaptation of the auditory nerve to high-rate electrical stimulation can best be described by a power-law or a sum of exponents. This gives an adequate fit for both short and long duration stimuli, such as CI speech segments

Temporal integration in cochlear implants and the effect of high pulse rates

Although cochlear implants (CIs) have proven to be an invaluable help for many people afflicted with severe hearing loss, there are still many hurdles left before a full restoration of hearing. A better understanding of how individual stimuli in a pulse train interact temporally to form a conjoined percept, and what effects the stimulation rate has on the percept of loudness will be beneficial for further improvements in the development of new coding strategies and thus in the quality of life of CI-wearers. Two experiments presented here deal on the topic of temporal integration with CIs, and raise the question of the effects of the high stimulation rates made possible by the broad spread of stimulation. To this effect, curves of equal loudness were measured as a function of pulse train length for different stimulation characteristics. In the first exploratory experiment, threshold and maximum acceptable loudness (MAL) were measured, and the existence and behaviour of the critical duration of integration in cochlear implants is discussed. In the second experiment, the effect of level was further investigated by including MAL measurements at shorter durations, as well as a line of equal loudness at a comfortable level. It is found that the amount of temporal integration (the slope of integration as a function of duration) is greatly decreased in electrical hearing compared to acoustic hearing. The higher stimulation rates seem to have a compensating effect on this, increasing the slope with increasing rate. The highest rates investigated here lead to slopes that are even comparable to those found in persons with normal hearing and hearing impaired. The rate also has an increasing effect on the dynamic range, which is otherwise taken to be a correlate of good performance. The values presented here point towards larger effects of rate on dynamic range than what has been found so far in the literature for more moderate ranges. While rate effects on threshold, dynamic range and integration slope seem to act uniformly for the different test subjects, the critical duration of integration varies strongly but in a non-consistent way, possibly reflecting more central, individual-specific effects. Additionally, measurements on the voltage spread of human CI-wearers are presented which are used to validate a 3D computational model of the human cochlea developed in our group. The theoretical model falls squarely inside of the distribution of measurements. A single, implant dependent voltage-offset seems to adequately explain most of the variability

Temporal integration in cochlear implants and the effect of high pulse rates

Although cochlear implants (CIs) have proven to be an invaluable help for many people afflicted with severe hearing loss, there are still many hurdles left before a full restoration of hearing. A better understanding of how individual stimuli in a pulse train interact temporally to form a conjoined percept, and what effects the stimulation rate has on the percept of loudness will be beneficial for further improvements in the development of new coding strategies and thus in the quality of life of CI-wearers. Two experiments presented here deal on the topic of temporal integration with CIs, and raise the question of the effects of the high stimulation rates made possible by the broad spread of stimulation. To this effect, curves of equal loudness were measured as a function of pulse train length for different stimulation characteristics. In the first exploratory experiment, threshold and maximum acceptable loudness (MAL) were measured, and the existence and behaviour of the critical duration of integration in cochlear implants is discussed. In the second experiment, the effect of level was further investigated by including MAL measurements at shorter durations, as well as a line of equal loudness at a comfortable level. It is found that the amount of temporal integration (the slope of integration as a function of duration) is greatly decreased in electrical hearing compared to acoustic hearing. The higher stimulation rates seem to have a compensating effect on this, increasing the slope with increasing rate. The highest rates investigated here lead to slopes that are even comparable to those found in persons with normal hearing and hearing impaired. The rate also has an increasing effect on the dynamic range, which is otherwise taken to be a correlate of good performance. The values presented here point towards larger effects of rate on dynamic range than what has been found so far in the literature for more moderate ranges. While rate effects on threshold, dynamic range and integration slope seem to act uniformly for the different test subjects, the critical duration of integration varies strongly but in a non-consistent way, possibly reflecting more central, individual-specific effects. Additionally, measurements on the voltage spread of human CI-wearers are presented which are used to validate a 3D computational model of the human cochlea developed in our group. The theoretical model falls squarely inside of the distribution of measurements. A single, implant dependent voltage-offset seems to adequately explain most of the variability

Accurate and Fast Simulation of Channel Noise in Conductance-Based Model Neurons by Diffusion Approximation

Stochastic channel gating is the major source of intrinsic neuronal noise whose functional consequences at the microcircuit- and network-levels have been only partly explored. A systematic study of this channel noise in large ensembles of biophysically detailed model neurons calls for the availability of fast numerical methods. In fact, exact techniques employ the microscopic simulation of the random opening and closing of individual ion channels, usually based on Markov models, whose computational loads are prohibitive for next generation massive computer models of the brain. In this work, we operatively define a procedure for translating any Markov model describing voltage- or ligand-gated membrane ion-conductances into an effective stochastic version, whose computer simulation is efficient, without compromising accuracy. Our approximation is based on an improved Langevin-like approach, which employs stochastic differential equations and no Montecarlo methods. As opposed to an earlier proposal recently debated in the literature, our approximation reproduces accurately the statistical properties of the exact microscopic simulations, under a variety of conditions, from spontaneous to evoked response features. In addition, our method is not restricted to the Hodgkin-Huxley sodium and potassium currents and is general for a variety of voltage- and ligand-gated ion currents. As a by-product, the analysis of the properties emerging in exact Markov schemes by standard probability calculus enables us for the first time to analytically identify the sources of inaccuracy of the previous proposal, while providing solid ground for its modification and improvement we present here