Wave digital filter model of the entire auditory periphery

A model of the auditory periphery assembled from analog network submodels of all the relevant anatomical structures is described. There is bidirectional coupling between networks representing the outer ear, middle ear and cochlea. A simple voltage source representation of the outer hair cells provides level-dependent basilar membrane curves. The networks are translated into efficient computational modules by means of wave digital filtering. A feedback unit regulates the average firing rate at the output of an inner hair cell module via a simplified modelling of the dynamics of the descending paths to the peripheral ear. This leads to a digital model of the entire auditory periphery with applications to both speech and hearing research.

Dentin phosphoprotein frameshift mutations in hereditary dentin disorders and their variation patterns in normal human population

Background: Dentin phosphoprotein ( DPP) is the most abundant non-collagenous protein in dentin, which is highly phosphorylated and plays key roles in dentin biomineralisation. The aetiology of isolated hereditary dentin disorders in most affected familie

Differential amplitude modulation of auditory evoked cortical potentials associated with brain state in the freely moving rhesus monkey

We simultaneously recorded auditory evoked potentials (AEP) from the temporal cortex (TCx), the dorsolateral prefrontal cortex (dPFCx) and the parietal cortex (PCx) in the freely moving rhesus monkey to investigate state-dependent changes of the AEP. AEPs obtained during passive wakefulness, active wakefulness (AW), slow wave sleep and rapid-eye-movement sleep (REM) were compared. Results showed that AEP from all three cerebral areas were modulated by brain states. However, the amplitude of AEP from dPFCx and PCx significantly appeared greater attenuation than that from the TCx during AW and REM. These results indicate that the modulation of brain state on AEP from all three cerebral areas investigated is not uniform, which suggests that different cerebral areas have differential functional contributions during sleep-wake cycle. (C) 2002 Elsevier Science Ireland Ltd.. All rights reserved.

Assessing functioning of the prefrontal cortical subregions with auditory evoked potentials in sleep-wake cycle

Our previously observations showed that the amplitude of cortical evoked potentials to irrelevant auditory stimulus (probe) recorded from several different cerebral areas was differentially modulated by brain states. At present study, we simultaneously re

Chronic morphine selectively impairs cued fear extinction in rats: Implications for anxiety disorders associated with opiate use

Previous studies have shown that opioid transmission plays an important role in learning and memory. However, little is known about the course of opiate-associated learning and memory deficits after cessation of chronic opiate use in a behavioral animal m

Perceptual learning, roving and the unsupervised bias

Perceptual learning improves perception through training. Perceptual learning improves with most stimulus types but fails when . certain stimulus types are mixed during training (roving). This result is surprising because classical supervised and unsupervised neural network models can cope easily with roving conditions. What makes humans so inferior compared to these models? As experimental and conceptual work has shown, human perceptual learning is neither supervised nor unsupervised but reward-based learning. Reward-based learning suffers from the so-called unsupervised bias, i.e., to prevent synaptic " drift" , the . average reward has to be exactly estimated. However, this is impossible when two or more stimulus types with different rewards are presented during training (and the reward is estimated by a running average). For this reason, we propose no learning occurs in roving conditions. However, roving hinders perceptual learning only for combinations of similar stimulus types but not for dissimilar ones. In this latter case, we propose that a critic can estimate the reward for each stimulus type separately. One implication of our analysis is that the critic cannot be located in the visual system. © 2011 Elsevier Ltd.

Perceptual thresholds for acoustical guitar models

Synthesised acoustic guitar sounds based on a detailed physical model are used to provide input for psychoacoustical testing. Thresholds of perception are found for changes in the main parameters of the model. Using a three-alternative forced-choice procedure, just-noticeable differences are presented for changes in frequency and damping of the modes of the guitar body, and also for changes in the tension, bending stiffness and damping parameters of the strings. These are compared with measured data on the range of variation of these parameters in a selection of guitars. © S. Hirzel Verlag © EAA.

MCBoost: Multiple classifier boosting for perceptual co-clustering of images and visual features

We present a new co-clustering problem of images and visual features. The problem involves a set of non-object images in addition to a set of object images and features to be co-clustered. Co-clustering is performed in a way that maximises discrimination of object images from non-object images, thus emphasizing discriminative features. This provides a way of obtaining perceptual joint-clusters of object images and features. We tackle the problem by simultaneously boosting multiple strong classifiers which compete for images by their expertise. Each boosting classifier is an aggregation of weak-learners, i.e. simple visual features. The obtained classifiers are useful for object detection tasks which exhibit multimodalities, e.g. multi-category and multi-view object detection tasks. Experiments on a set of pedestrian images and a face data set demonstrate that the method yields intuitive image clusters with associated features and is much superior to conventional boosting classifiers in object detection tasks.