255 research outputs found
Frequency selectivity of the human cochlea:Suppression tuning of spontaneous otoacoustic emissions
AbstractFrequency selectivity is a key functional property of the inner ear and since hearing research began, the frequency resolution of the human ear has been a central question. In contrast to animal studies, which permit invasive recording of neural activity, human studies must rely on indirect methods to determine hearing selectivity. Psychophysical studies, which used masking of a tone by other sounds, indicate a modest frequency selectivity in humans. By contrast, estimates using the phase delays of stimulus-frequency otoacoustic emissions (SFOAE) predict a remarkably high selectivity, unique among mammals. An alternative measure of cochlear frequency selectivity are suppression tuning curves of spontaneous otoacoustic emissions (SOAE). Several animal studies show that these measures are in excellent agreement with neural frequency selectivity. Here we contribute a large data set from normal-hearing young humans on suppression tuning curves (STC) of spontaneous otoacoustic emissions (SOAE). The frequency selectivities of human STC measured near threshold levels agree with the earlier, much lower, psychophysical estimates. They differ, however, from the typical patterns seen in animal auditory nerve data in that the selectivity is remarkably independent of frequency. In addition, SOAE are suppressed by higher-level tones in narrow frequency bands clearly above the main suppression frequencies. These narrow suppression bands suggest interactions between the suppressor tone and a cochlear standing wave corresponding to the SOAE frequency being suppressed. The data show that the relationship between pre-neural mechanical processing in the cochlea and neural coding at the hair-cell/auditory nerve synapse needs to be reconsidered
Modeling the characteristics of spontaneous otoacoustic emissions in lizards
Lizard auditory papillae have proven to be an attractive object for modelling the production of spontaneous otoacoustic emissions (SOAE). Here we use an established model (Vilfan and Duke, 2008) and extend it by exploring the effect of varying the number of oscillating elements, the strength of the parameters that describe the coupling between oscillators, the strength of the oscillators, and additive noise. The most remarkable result is that the actual number of oscillating elements hardly influences the spectral pattern, explaining why spectra from very different papillar dimensions are similar. Furthermore, the spacing between spectral peaks primarily depends on the reactive coupling between the oscillator elements. This is consistent with observed differences between lizard species with respect to tectorial covering of hair cells and SOAE peak spacings. Thus, the model provides a basic understanding of the variation in SOAE properties across lizard species. (C) 2019 Elsevier B.V. All rights reserved
Inner-ear abnormalities and their functional consequences in Belgian Waterslager canaries (Serinus canarius)
Recent reports of elevated auditory thresholds in canaries of the Belgian Waterslager strain have shown that this strain has an inherited auditory deficit in which absolute auditory thresholds at high frequencies (i.e. above 2.0 kHz) are as much as 40 dB less sensitive than the thresholds of mixed-breed canaries and those of other strains. The measurement of CAP audiograms showed that the hearing deficit is already present at the level of the auditory nerve (Gleich and Dooling, 1992). Here we show gross abnormalities in the anatomy of the basilar papilla of Belgian Waterslager canaries at the level of the hair cell. The extent of these abnormalities was correlated with the amount of hearing deficit as measured behaviorally
A Neural Map of Interaural Intensity Differences in the Brain Stem of the Barn Owl
The nucleus ventralis lemnisci lateralis pars posterior (VLVp) is the first binaural station in the intensity-processing pathway of the barn owl. Contralateral stimulation excites and ipsilateral stimulation inhibits VLVp cells. The strength of the inhibition declines systematically from dorsal to ventral within the nucleus. Cells selective for different intensity disparities occur in an orderly sequence from dorsal to ventral within each isofrequency lamina. Cells at intermediate depths in the nucleus are selective for a particular narrow range of interaural intensity differences independently of the absolute sound-pressure level. A simple model of the interaction between inhibition and excitation can explain most of the response properties of VLVp neurons. The map of selectivity for intensity disparity is mainly based on the gradient of inhibition
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The LONI QC System: A Semi-Automated, Web-Based and Freely-Available Environment for the Comprehensive Quality Control of Neuroimaging Data.
Quantifying, controlling, and monitoring image quality is an essential prerequisite for ensuring the validity and reproducibility of many types of neuroimaging data analyses. Implementation of quality control (QC) procedures is the key to ensuring that neuroimaging data are of high-quality and their validity in the subsequent analyses. We introduce the QC system of the Laboratory of Neuro Imaging (LONI): a web-based system featuring a workflow for the assessment of various modality and contrast brain imaging data. The design allows users to anonymously upload imaging data to the LONI-QC system. It then computes an exhaustive set of QC metrics which aids users to perform a standardized QC by generating a range of scalar and vector statistics. These procedures are performed in parallel using a large compute cluster. Finally, the system offers an automated QC procedure for structural MRI, which can flag each QC metric as being 'good' or 'bad.' Validation using various sets of data acquired from a single scanner and from multiple sites demonstrated the reproducibility of our QC metrics, and the sensitivity and specificity of the proposed Auto QC to 'bad' quality images in comparison to visual inspection. To the best of our knowledge, LONI-QC is the first online QC system that uniquely supports the variety of functionality where we compute numerous QC metrics and perform visual/automated image QC of multi-contrast and multi-modal brain imaging data. The LONI-QC system has been used to assess the quality of large neuroimaging datasets acquired as part of various multi-site studies such as the Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) Study and the Alzheimer's Disease Neuroimaging Initiative (ADNI). LONI-QC's functionality is freely available to users worldwide and its adoption by imaging researchers is likely to contribute substantially to upholding high standards of brain image data quality and to implementing these standards across the neuroimaging community
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