FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2110185148> ?p ?o ?g. }

• W2110185148 endingPage "311" @default.
• W2110185148 startingPage "298" @default.
• W2110185148 abstract "Decoding models based on pattern recognition (PR) are becoming increasingly important tools for neuroimaging data analysis. In contrast to alternative (mass-univariate) encoding approaches that use hierarchical models to capture inter-subject variability, inter-subject differences are not typically handled efficiently in PR. In this work, we propose to overcome this problem by recasting the decoding problem in a multi-task learning (MTL) framework. In MTL, a single PR model is used to learn different but related tasks simultaneously. The primary advantage of MTL is that it makes more efficient use of the data available and leads to more accurate models by making use of the relationships between tasks. In this work, we construct MTL models where each subject is modelled by a separate task. We use a flexible covariance structure to model the relationships between tasks and induce coupling between them using Gaussian process priors. We present an MTL method for classification problems and demonstrate a novel mapping method suitable for PR models. We apply these MTL approaches to classifying many different contrasts in a publicly available fMRI dataset and show that the proposed MTL methods produce higher decoding accuracy and more consistent discriminative activity patterns than currently used techniques. Our results demonstrate that MTL provides a promising method for multi-subject decoding studies by focusing on the commonalities between a group of subjects rather than the idiosyncratic properties of different subjects." @default.
• W2110185148 created "2016-06-24" @default.
• W2110185148 creator A5043557856 @default.
• W2110185148 creator A5045174960 @default.
• W2110185148 creator A5064274203 @default.
• W2110185148 creator A5089543470 @default.
• W2110185148 date "2014-05-01" @default.
• W2110185148 modified "2023-09-24" @default.
• W2110185148 title "Bayesian multi-task learning for decoding multi-subject neuroimaging data" @default.
• W2110185148 cites W1908808553 @default.
• W2110185148 cites W1969959732 @default.
• W2110185148 cites W1971600338 @default.
• W2110185148 cites W1979289529 @default.
• W2110185148 cites W1993120888 @default.
• W2110185148 cites W1998078060 @default.
• W2110185148 cites W2000292092 @default.
• W2110185148 cites W2003400098 @default.
• W2110185148 cites W2007804187 @default.
• W2110185148 cites W2014157362 @default.
• W2110185148 cites W2018102971 @default.
• W2110185148 cites W2019428019 @default.
• W2110185148 cites W2021515139 @default.
• W2110185148 cites W2022561739 @default.
• W2110185148 cites W2030936242 @default.
• W2110185148 cites W2031967811 @default.
• W2110185148 cites W2037272682 @default.
• W2110185148 cites W2042116371 @default.
• W2110185148 cites W2048513666 @default.
• W2110185148 cites W2056392803 @default.
• W2110185148 cites W2060144980 @default.
• W2110185148 cites W2063951486 @default.
• W2110185148 cites W2068403333 @default.
• W2110185148 cites W2080908547 @default.
• W2110185148 cites W2082906925 @default.
• W2110185148 cites W2087859320 @default.
• W2110185148 cites W2089322632 @default.
• W2110185148 cites W2105259239 @default.
• W2110185148 cites W2121148108 @default.
• W2110185148 cites W2123923307 @default.
• W2110185148 cites W2138790588 @default.
• W2110185148 cites W2139376466 @default.
• W2110185148 cites W2143228953 @default.
• W2110185148 cites W2149726258 @default.
• W2110185148 cites W2158485497 @default.
• W2110185148 cites W2163203678 @default.
• W2110185148 cites W2165698076 @default.
• W2110185148 cites W2171831801 @default.
• W2110185148 cites W2496675188 @default.
• W2110185148 cites W2889622349 @default.
• W2110185148 cites W2913340405 @default.
• W2110185148 cites W3100067206 @default.
• W2110185148 doi "https://doi.org/10.1016/j.neuroimage.2014.02.008" @default.
• W2110185148 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/4010954" @default.
• W2110185148 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/24531053" @default.
• W2110185148 hasPublicationYear "2014" @default.
• W2110185148 type Work @default.
• W2110185148 sameAs 2110185148 @default.
• W2110185148 citedByCount "52" @default.
• W2110185148 countsByYear W21101851482014 @default.
• W2110185148 countsByYear W21101851482015 @default.
• W2110185148 countsByYear W21101851482016 @default.
• W2110185148 countsByYear W21101851482017 @default.
• W2110185148 countsByYear W21101851482018 @default.
• W2110185148 countsByYear W21101851482019 @default.
• W2110185148 countsByYear W21101851482020 @default.
• W2110185148 countsByYear W21101851482021 @default.
• W2110185148 countsByYear W21101851482022 @default.
• W2110185148 countsByYear W21101851482023 @default.
• W2110185148 crossrefType "journal-article" @default.
• W2110185148 hasAuthorship W2110185148A5043557856 @default.
• W2110185148 hasAuthorship W2110185148A5045174960 @default.
• W2110185148 hasAuthorship W2110185148A5064274203 @default.
• W2110185148 hasAuthorship W2110185148A5089543470 @default.
• W2110185148 hasBestOaLocation W21101851481 @default.
• W2110185148 hasConcept C107673813 @default.
• W2110185148 hasConcept C11413529 @default.
• W2110185148 hasConcept C118552586 @default.
• W2110185148 hasConcept C119857082 @default.
• W2110185148 hasConcept C121332964 @default.
• W2110185148 hasConcept C153180895 @default.
• W2110185148 hasConcept C154945302 @default.
• W2110185148 hasConcept C15744967 @default.
• W2110185148 hasConcept C162324750 @default.
• W2110185148 hasConcept C163716315 @default.
• W2110185148 hasConcept C177769412 @default.
• W2110185148 hasConcept C187736073 @default.
• W2110185148 hasConcept C2780451532 @default.
• W2110185148 hasConcept C41008148 @default.
• W2110185148 hasConcept C57273362 @default.
• W2110185148 hasConcept C58693492 @default.
• W2110185148 hasConcept C61326573 @default.
• W2110185148 hasConcept C62520636 @default.
• W2110185148 hasConcept C97931131 @default.
• W2110185148 hasConceptScore W2110185148C107673813 @default.
• W2110185148 hasConceptScore W2110185148C11413529 @default.
• W2110185148 hasConceptScore W2110185148C118552586 @default.
• W2110185148 hasConceptScore W2110185148C119857082 @default.
• W2110185148 hasConceptScore W2110185148C121332964 @default.

• next