Simulating electrical modulation detection thresholds using a biophysical model of the auditory nerve.

Modulation detection thresholds (MDTs) assess listeners' sensitivity to changes in the temporal envelope of a signal and have been shown to strongly correlate with speech perception in cochlear implant users. MDTs are simulated with a stochastic model of a population of auditory nerve fibers that has been verified to accurately simulate a number of physiologically important temporal response properties. The procedure to estimate detection thresholds has previously been applied to stimulus discrimination tasks. The population model simulates the MDT-stimulus intensity relationship measured in cochlear implant users. The model also recreates the shape of the modulation transfer function and the relationship between MDTs and carrier rate. Discrimination based on fluctuations in synchronous firing activity predicts better performance at low carrier rates, but quantitative measures of modulation coding predict better neural representation of high carrier rate stimuli. Manipulating the number of fibers and a temporal integration parameter, the width of a sliding temporal integration window, varies properties of the MDTs, such as cutoff frequency and peak threshold. These results demonstrate the importance of using a multi-diameter fiber population in modeling the MDTs and demonstrate a wider applicability of this model to simulating behavioral performance in cochlear implant listeners.

Improved perception of speech in noise and Mandarin tones with acoustic simulations of harmonic coding for cochlear implants.

Harmonic and temporal fine structure (TFS) information are important cues for speech perception in noise and music perception. However, due to the inherently coarse spectral and temporal resolution in electric hearing, the question of how to deliver harmonic and TFS information to cochlear implant (CI) users remains unresolved. A harmonic-single-sideband-encoder [(HSSE); Nie et al. (2008). Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing; Lie et al., (2010). Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing] strategy has been proposed that explicitly tracks the harmonics in speech and transforms them into modulators conveying both amplitude modulation and fundamental frequency information. For unvoiced speech, HSSE transforms the TFS into a slowly varying yet still noise-like signal. To investigate its potential, four- and eight-channel vocoder simulations of HSSE and the continuous-interleaved-sampling (CIS) strategy were implemented, respectively. Using these vocoders, five normal-hearing subjects' speech recognition performance was evaluated under different masking conditions; another five normal-hearing subjects' Mandarin tone identification performance was also evaluated. Additionally, the neural discharge patterns evoked by HSSE- and CIS-encoded Mandarin tone stimuli were simulated using an auditory nerve model. All subjects scored significantly higher with HSSE than with CIS vocoders. The modeling analysis demonstrated that HSSE can convey temporal pitch cues better than CIS. Overall, the results suggest that HSSE is a promising strategy to enhance speech perception with CIs.

Prediction for human motion tracking failures.

We propose a new and effective method of predicting tracking failures and apply it to the robust analysis of gait and human motion. We define a tracking failure as an event and describe its temporal characteristics using a hidden Markov model (HMM). We represent the human body using a three-dimensional, multicomponent structural model, where each component is designed to independently allow the extraction of certain gait variables. To enable a fault-tolerant tracking and feature extraction system, we introduce a single HMM for each element of the structural model, trained on previous examples of tracking failures. The algorithm derives vector observations for each Markov model using the time-varying noise covariance matrices of the structural model parameters. When transformed with a logarithmic function, the conditional output probability of each HMM is shown to have a causal relationship with imminent tracking failures. We demonstrate the effectiveness of the proposed approach on a variety of multiview video sequences of complex human motion.

Detection of acoustic temporal fine structure by cochlear implant listeners: behavioral results and computational modeling.

A test of within-channel detection of acoustic temporal fine structure (aTFS) cues is presented. Eight cochlear implant listeners (CI) were asked to discriminate between two Schroeder-phase (SP) complexes using a two-alternative, forced-choice task. Because differences between the acoustic stimuli are primarily constrained to their aTFS, successful discrimination reflects a combination of the subjects' perception of and the strategy's ability to deliver aTFS cues. Subjects were mapped with single-channel Continuous Interleaved Sampling (CIS) and Simultaneous Analog Stimulation (SAS) strategies. To compare within- and across- channel delivery of aTFS cues, a 16-channel clinical HiRes strategy was also fitted. Throughout testing, SAS consistently outperformed the CIS strategy (p ≤ 0.002). For SP stimuli with F0 = 50 Hz, the highest discrimination scores were achieved with the HiRes encoding, followed by scores with the SAS and the CIS strategies, respectively. At 200 Hz, single-channel SAS performed better than HiRes (p = 0.022), demonstrating that under a more challenging testing condition, discrimination performance with a single-channel analog encoding can exceed that of a 16-channel pulsatile strategy. To better understand the intermediate steps of discrimination, a biophysical model was used to examine the neural discharges evoked by the SP stimuli. Discrimination estimates calculated from simulated neural responses successfully tracked the behavioral performance trends of single-channel CI listeners.

Improved perception of music with a harmonic based algorithm for cochlear implants.

The lack of fine structure information in conventional cochlear implant (CI) encoding strategies presumably contributes to the generally poor music perception with CIs. To improve CI users' music perception, a harmonic-single-sideband-encoder (HSSE) strategy was developed , which explicitly tracks the harmonics of a single musical source and transforms them into modulators conveying both amplitude and temporal fine structure cues to electrodes. To investigate its effectiveness, vocoder simulations of HSSE and the conventional continuous-interleaved-sampling (CIS) strategy were implemented. Using these vocoders, five normal-hearing subjects' melody and timbre recognition performance were evaluated: a significant benefit of HSSE to both melody (p < 0.002) and timbre (p < 0.026) recognition was found. Additionally, HSSE was acutely tested in eight CI subjects. On timbre recognition, a significant advantage of HSSE over the subjects' clinical strategy was demonstrated: the largest improvement was 35% and the mean 17% (p < 0.013). On melody recognition, two subjects showed 20% improvement with HSSE; however, the mean improvement of 7% across subjects was not significant (p > 0.090). To quantify the temporal cues delivered to the auditory nerve, the neural spike patterns evoked by HSSE and CIS for one melody stimulus were simulated using an auditory nerve model. Quantitative analysis demonstrated that HSSE can convey temporal pitch cues better than CIS. The results suggest that HSSE is a promising strategy to enhance music perception with CIs.

Stochastic differential equation models for ion channel noise in Hodgkin-Huxley neurons.

The random transitions of ion channels between conducting and nonconducting states generate a source of internal fluctuations in a neuron, known as channel noise. The standard method for modeling the states of ion channels nonlinearly couples continuous-time Markov chains to a differential equation for voltage. Beginning with the work of R. F. Fox and Y.-N. Lu [Phys. Rev. E 49, 3421 (1994)], there have been attempts to generate simpler models that use stochastic differential equation (SDEs) to approximate the stochastic spiking activity produced by Markov chain models. Recent numerical investigations, however, have raised doubts that SDE models can capture the stochastic dynamics of Markov chain models.We analyze three SDE models that have been proposed as approximations to the Markov chain model: one that describes the states of the ion channels and two that describe the states of the ion channel subunits. We show that the former channel-based approach can capture the distribution of channel noise and its effects on spiking in a Hodgkin-Huxley neuron model to a degree not previously demonstrated, but the latter two subunit-based approaches cannot. Our analysis provides intuitive and mathematical explanations for why this is the case. The temporal correlation in the channel noise is determined by the combinatorics of bundling subunits into channels, but the subunit-based approaches do not correctly account for this structure. Our study confirms and elucidates the findings of previous numerical investigations of subunit-based SDE models. Moreover, it presents evidence that Markov chain models of the nonlinear, stochastic dynamics of neural membranes can be accurately approximated by SDEs. This finding opens a door to future modeling work using SDE techniques to further illuminate the effects of ion channel fluctuations on electrically active cells.

Stochastic population model for electrical stimulation of the auditory nerve.

We have developed a biophysical model of a population of electrically stimulated auditory nerve fibers. It can be used to interpret results from physiological and behavioral experiments with cochlear implants and propose novel stimulation strategies. Our model consists of myelinated internodes described by a passive resistor-capacitor network, membrane capacitance, and leakage current at the nodes of Ranvier, as well as stochastic representations of nodal voltage-dependent channels. To approximate physiological properties measured in the auditory nerve (AN) of an acutely deafened cat, electrical parameters of the model fiber were chosen based on literature-reported values. Using our model, we have replicated the following properties within 10 % of the reported feline single-fiber measurements: relative spread (5.8 %), spike latency (630 micros), jitter (93 micros), chronaxie (238 micros), relative refractory period (4.6 ms), and conduction velocity (14 m/s). Moreover, we have successfully matched response characteristics of a population of fibers with the same number of diameter-distributed model fibers, enabling us to simulate responses of the entire AN. To demonstrate the performance of our model, we compare responses of a population of ANs stimulated with two speech encoding strategies, Continuous Interleaved Sampling and Compressed Analog.

Geographic origin of human mitochondrial DNA: accommodating phylogenetic uncertainty and model comparison.

Many biogeographic problems are tested on phylogenetic trees. Typically, the uncertainty in the phylogeny is not accommodated when investigating the biogeography of the organisms. Here we present a method that accommodates uncertainty in the phylogenetic trees. Moreover, we describe a simple method for examining the support for competing biogeographic scenarios. We illustrate the method using mitochondrial DNA sequences sampled from modern humans. The geographic origin of modern human mtDNA is inferred to be in Africa, although support for this hypothesis was ambiguous for data from an early paper.