Benefits of functional PCA in the analysis of single-trial auditory evoked potentials

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F19%3A00107161" target="_blank" >RIV/00216224:14310/19:00107161 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/article/10.1007%2Fs00180-018-0819-6" target="_blank" >https://link.springer.com/article/10.1007%2Fs00180-018-0819-6</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s00180-018-0819-6" target="_blank" >10.1007/s00180-018-0819-6</a>

Result language
angličtina
Original language name
Benefits of functional PCA in the analysis of single-trial auditory evoked potentials
Original language description
Evoked potentials reflect neural processing and are widely used to studying sensory perception. Here we applied a functional approach to studying single-trial auditory evoked potentials in the rat model of tinnitus, in which overdoses of salicylate are known to alter sound perception characteristically. Single-trial evoked potential integrals were generated with sound stimuli (tones and clicks) presented systematically over an intensity range and further assessed using the functional principal component analysis. Comparisons between the single-trial responses for each sound type and each treatment were done by inspecting the scores corresponding to the first two principal components. An analogous analysis was performed on the first derivative of the response functions. We conclude that the functional principal component analysis is capable of differentiating between the controls and salicylate treatments for each type of sound. It also well separates the response function for tones and clicks. The results of linear discriminant analysis show, that scores of the first two principal components are effective cluster predictors. However, the distinction is less pronounced in case the first derivative of the response.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10103 - Statistics and probability

Project
<a href="/en/project/GA15-06991S" target="_blank" >GA15-06991S: Functional data analysis and related topics</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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