{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Patterson Gentile C"],"funding":["NEI NIH HHS"],"pagination":["1"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC8024780"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["10(4)"],"pubmed_abstract":["<h4>Purpose</h4>Peak amplitude and peak latency in the pattern reversal visual evoked potential (prVEP) vary with maturation. We considered that principal component analysis (PCA) may be used to describe age-related variation over the entire prVEP time course and provide a means of modeling and removing variation due to developmental age.<h4>Methods</h4>PrVEP was recorded from 155 healthy subjects ages 11 to 19 years at two time points. We created a model of the prVEP by identifying principal components (PCs) that explained >95% of the variance in a \"training\" dataset of 40 subjects. We examined the ability of the PCs to explain variance in an age- and sex-matched \"validation\" dataset (n = 40) and calculated the intrasubject reliability of the PC coefficients between the two time points. W"],"journal":["Translational vision science & technology"],"pubmed_title":["Developmental Effects on Pattern Visual Evoked Potentials Characterized by Principal Component Analysis."],"pmcid":["PMC8024780"],"funding_grant_id":["P30 EY001583"],"pubmed_authors":["Arbogast KB","Master C","Joshi NR","Ciuffreda KJ","Aguirre GK","Patterson Gentile C"],"additional_accession":[]},"is_claimable":false,"name":"Developmental Effects on Pattern Visual Evoked Potentials Characterized by Principal Component Analysis.","description":"<h4>Purpose</h4>Peak amplitude and peak latency in the pattern reversal visual evoked potential (prVEP) vary with maturation. We considered that principal component analysis (PCA) may be used to describe age-related variation over the entire prVEP time course and provide a means of modeling and removing variation due to developmental age.<h4>Methods</h4>PrVEP was recorded from 155 healthy subjects ages 11 to 19 years at two time points. We created a model of the prVEP by identifying principal components (PCs) that explained >95% of the variance in a \"training\" dataset of 40 subjects. We examined the ability of the PCs to explain variance in an age- and sex-matched \"validation\" dataset (n = 40) and calculated the intrasubject reliability of the PC coefficients between the two time points. W","dates":{"release":"2021-01-01T00:00:00Z","publication":"2021 Apr","modification":"2025-04-26T08:20:41.778Z","creation":"2025-04-06T12:38:03.674Z"},"accession":"S-EPMC8024780","cross_references":{"pubmed":["34003980"],"doi":["10.1167/tvst.10.4.1"]}}