Functional modelling of interaural time difference discrimination in acoustical and electrical hearing

A comparative study of eight human auditory models of monaural processing

A number of auditory models have been developed using diverging approaches, either physiological or perceptual, but they share comparable stages of signal processing, as they are inspired by the same constitutive parts of the auditory system. We compare eight monaural models that are openly accessible in the Auditory Modelling Toolbox. We discuss the considerations required to make the model outputs comparable to each other, as well as the results for the following model processing stages or their equivalents: Outer and middle ear, cochlear filter bank, inner hair cell, auditory nerve synapse, cochlear nucleus, and inferior colliculus. The discussion includes a list of recommendations for future applications of auditory models.

Artificial Neuron and Synapse Realized in an Antiferromagnet/Ferromagnet Heterostructure Using Dynamics of Spin-Orbit Torque Switching

Efficient information processing in the human brain is achieved by dynamics of neurons and synapses, motivating effective implementation of artificial spiking neural networks. Here, the dynamics of spin-orbit torque switching in antiferromagnet/ferromagnet heterostructures is studied to show the capability of the material system to form artificial neurons and synapses for asynchronous spiking neural networks. The magnetization switching, driven by a single current pulse or trains of pulses, is examined as a function of the pulse width (1 s to 1 ns), amplitude, number, and pulse-to-pulse interval. Based on this dynamics and the unique ability of the system to exhibit binary or analog behavior depending on the device size, key functionalities of a synapse (spike-timing-dependent plasticity) and a neuron (leaky integrate-and-fire) are reproduced in the same material and on the basis of the same working principle. These results open a way toward spintronics-based neuromorphic hardware that executes cognitive tasks with the efficiency of the human brain.

Functional rate-code models of the auditory brainstem for predicting lateralization and discrimination data of human binaural perception

This paper presents a rate-code model of binaural interaction inspired by recent neurophysiological findings. The model consists of a peripheral part and a binaural part. The binaural part is composed of models of the medial superior olive (MSO) and the lateral superior olive (LSO), which are parts of the auditory brainstem. The MSO and LSO model outputs are preprocessed in the interaural time difference (ITD) and interaural level difference (ILD) central stages, respectively, which give absolute values of the predicted lateralization at their outputs, allowing a direct comparison with psychophysical data. The predictions obtained with the MSO and LSO models are compared with subjective data on the lateralization of pure tones and narrowband noises, discrimination of the ITD and ILD, and discrimination of the phase warp. The lateralization and discrimination experiments show good agreement with the subjective data. In the case of the phase-warp experiment, the models agree qualitatively with the subjective data. The results demonstrate that rate-code models of MSO and LSO can be used to explain psychophysical data considering lateralization and discrimination based on binaural cues.

A framework for computational modelling of interaural time difference discrimination of normal and hearing-impaired listeners

Different computational models have been developed to study the interaural time difference (ITD) perception. However, only few have used a physiologically inspired architecture to study ITD discrimination. Furthermore, they do not include aspects of hearing impairment. In this work, a framework was developed to predict ITD thresholds in listeners with normal and impaired hearing. It combines the physiologically inspired model of the auditory periphery proposed by Zilany, Bruce, Nelson, and Carney [(2009). J. Acoust. Soc. Am. 126(5), 2390-2412] as a front end with a coincidence detection stage and a neurometric decision device as a back end. It was validated by comparing its predictions against behavioral data for narrowband stimuli from literature. The framework is able to model ITD discrimination of normal-hearing and hearing-impaired listeners at a group level. Additionally, it was used to explore the effect of different proportions of outer- and inner-hair cell impairment on ITD discrimination.