Evidence map›Paper›PMID 25278284›Full record

ArticleJournal of computational neuroscience2015

Estimating characteristic phase and delay from broadband interaural time difference tuning curves.

Jessica Lehmann, Philipp Tellers, Hermann Wagner, Hartmut Führ

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Article in Journal of computational neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Jessica LehmannLehrstuhl A für Mathematik, RWTH Aachen University, 52056, Aachen, Germany, jessica.lehmann@matha.rwth-aachen.de.
Philipp Tellers
Hermann Wagner
Hartmut Führ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Characteristic delay and characteristic phase are shape parameters of interaural time difference tuning curves. The standard procedure for the estimation of these parameters is based on the measurement of delay curves measured for tonal stimuli with varying frequencies. Common to all procedures is the detection of a linear behavior of the phase spectrum. Hence a reliable estimate can only be expected if sufficiently many relevant frequencies are tested. Thus, the estimation precision depends on the given bandwidth. Based on a linear model, we develop and implement methods for the estimation of characteristic phase and delay from a single broadband tuning curve. We present two different estimation algorithms, one based on a Fourier-analytic interpretation of characteristic delay and phase, and the other based on mean square error minimization. Estimation precision and robustness of the algorithms are tested on artificially generated data with predetermined characteristic delay and phase values, and on sample data from electrophysiological measurements in birds and in mammals. Increasing the signal-to-noise ratio or the bandwidth increases the estimation accuracy of the algorithms. Frequency band location and strong rectification also affect the estimation accuracy. For realistic bandwidths and signal-to-noise ratios, the minimization algorithm reliably and robustly estimates characteristic delay and phase and is superior to the Fourier-analytic method. Bandwidth-dependent significance thresholds allow to assess whether the estimated characteristic delay and phase values are meaningful shape parameters of a measured tuning curve. These thresholds also indicate the sampling rates needed to obtain reliable estimates from interaural time difference tuning curves.

Indexed as

Models, NeurologicalPsychoacousticsAcoustic StimulationAction PotentialsAlgorithmsAnimalsAuditory PathwaysAuditory PerceptionFourier AnalysisHumansNeuronsTime Factors

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.