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The discrimination of interaural level difference sensitivity functions: development of a taxonomic data template for modelling

Overview of attention for article published in BMC Neuroscience, October 2013
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Title
The discrimination of interaural level difference sensitivity functions: development of a taxonomic data template for modelling
Published in
BMC Neuroscience, October 2013
DOI 10.1186/1471-2202-14-114
Pubmed ID
Authors

Balemir Uragun, Ramesh Rajan

Abstract

A major cue for the position of a high-frequency sound source in azimuth is the difference in sound pressure levels in the two ears, Interaural Level Differences (ILDs), as a sound is presented from different positions around the head. This study aims to use data classification techniques to build a descriptive model of electro-physiologically determined neuronal sensitivity functions for ILDs. The ILDs were recorded from neurons in the central nucleus of the Inferior Colliculus (ICc), an obligatory midbrain auditory relay nucleus. The majority of ICc neurons (~ 85%) show sensitivity to ILDs but with a variety of different forms that are often difficult to unambiguously separate into different information-bearing types. Thus, this division is often based on laboratory-specific and relatively subjective criteria. Given the subjectivity and non-uniformity of ILD classification methods in use, we examined if objective data classification techniques for this purpose. Our key objectives were to determine if we could find an analytical method (A) to validate the presence of four typical ILD sensitivity functions as is commonly assumed in the field, and (B) whether this method produced classifications that mapped on to the physiologically observed results.

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 6%
Unknown 17 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 28%
Researcher 3 17%
Student > Bachelor 2 11%
Student > Master 2 11%
Professor 1 6%
Other 3 17%
Unknown 2 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 3 17%
Neuroscience 2 11%
Business, Management and Accounting 2 11%
Computer Science 2 11%
Engineering 2 11%
Other 5 28%
Unknown 2 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 October 2013.
All research outputs
#20,205,224
of 22,725,280 outputs
Outputs from BMC Neuroscience
#1,052
of 1,241 outputs
Outputs of similar age
#182,903
of 209,115 outputs
Outputs of similar age from BMC Neuroscience
#34
of 50 outputs
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