ArticleJournal of computational neuroscience2015
Estimating characteristic phase and delay from broadband interaural time difference tuning curves.
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.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
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
Identifiers
25278284What OpenQuestion holds
Registered trials
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.