Dataset Information

A Bayesian perspective on tinnitus pitch matching.

ABSTRACT: New tinnitus therapies are being developed and marketed that target the patient's tinnitus frequency. This frequency is estimated clinically by pitch matching, which has the patient identify the pure tone that is closest to the perceived tinnitus frequency. Though widely used, pitch matching is heavily criticized as unreliable, and the degree of reliability varies among patients. At the very least, it is recommended that multiple pitch matches be used to identify the patient's tinnitus frequency. Even so, it is not clear how many pitch matches to collect, how they should be combined, or how doing so will enhance the audiologist's certainty about the true tinnitus frequency. In this article, we describe a simple Bayesian method of sequentially combining pitch matches until acceptable precision is achieved and illustrate the method in 10 patients with chronic tinnitus.Subjects were recruited from previous study participants and support group attendees at the National Center for Rehabilitative Auditory Research. Thirty tinnitus pitch matches were elicited from 10 patients with chronic, monotonal tinnitus.A Bayesian sequential analysis yielded estimated tinnitus frequencies for 7 patients that were within one-quarter octave of their true value with 90% certainty. Between four and twenty pitch matches were required to achieve acceptable results in these seven patients.Despite criticism, pitch matching is widely used to estimate tinnitus frequency. We address reliability concerns with a Bayesian sequential analysis to jointly estimate tinnitus frequency and reliability. The method is easily applied.

SUBMITTER: McMillan GP

PROVIDER: S-EPMC4782933 | biostudies-literature | 2014 Nov-Dec

REPOSITORIES: biostudies-literature

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A Bayesian perspective on tinnitus pitch matching.

McMillan Garnett P GP Thielman Emily J EJ Wypych Krystyn K Henry James A JA

Ear and hearing 20141101 6

<h4>Objectives</h4>New tinnitus therapies are being developed and marketed that target the patient's tinnitus frequency. This frequency is estimated clinically by pitch matching, which has the patient identify the pure tone that is closest to the perceived tinnitus frequency. Though widely used, pitch matching is heavily criticized as unreliable, and the degree of reliability varies among patients. At the very least, it is recommended that multiple pitch matches be used to identify the patient's ...[more]

PMID: 25166630

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Project description:BackgroundMatching functional sites is a key problem for the understanding of protein function and evolution. The commonly used graph theoretic approach, and other related approaches, require adjustment of a matching distance threshold a priori according to the noise in atomic positions. This is difficult to pre-determine when matching sites related by varying evolutionary distances and crystallographic precision. Furthermore, sometimes the graph method is unable to identify alternative but important solutions in the neighbourhood of the distance based solution because of strict distance constraints. We consider the Bayesian approach to improve graph based solutions. In principle this approach applies to other methods with strict distance matching constraints. The Bayesian method can flexibly incorporate all types of prior information on specific binding sites (e.g. amino acid types) in contrast to combinatorial formulations.ResultsWe present a new meta-algorithm for matching protein functional sites (active sites and ligand binding sites) based on an initial graph matching followed by refinement using a Markov chain Monte Carlo (MCMC) procedure. This procedure is an innovative extension to our recent work. The method accounts for the 3-dimensional structure of the site as well as the physico-chemical properties of the constituent amino acids. The MCMC procedure can lead to a significant increase in the number of significant matches compared to the graph method as measured independently by rigorously derived p-values.ConclusionMCMC refinement step is able to significantly improve graph based matches. We apply the method to matching NAD(P)(H) binding sites within single Rossmann fold families, between different families in the same superfamily, and in different folds. Within families sites are often well conserved, but there are examples where significant shape based matches do not retain similar amino acid chemistry, indicating that even within families the same ligand may be bound using substantially different physico-chemistry. We also show that the procedure finds significant matches between binding sites for the same co-factor in different families and different folds.

Dataset Information

A Bayesian perspective on tinnitus pitch matching.

Publications

A Bayesian perspective on tinnitus pitch matching.

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