Matches in SemOpenAlex for { <https://semopenalex.org/work/W2948702906> ?p ?o ?g. }
- W2948702906 abstract "The application of deep learning (DL) models to neuroimaging data poses several challenges, due to the high dimensionality, low sample size and complex temporo-spatial dependency structure of these datasets. Even further, DL models act as as black-box models, impeding insight into the association of cognitive state and brain activity. To approach these challenges, we introduce the DeepLight framework, which utilizes long short-term memory (LSTM) based DL models to analyze whole-brain functional Magnetic Resonance Imaging (fMRI) data. To decode a cognitive state (e.g., seeing the image of a house), DeepLight separates the fMRI volume into a sequence of axial brain slices, which is then sequentially processed by an LSTM. To maintain interpretability, DeepLight adapts the layer-wise relevance propagation (LRP) technique. Thereby, decomposing its decoding decision into the contributions of the single input voxels to this decision. Importantly, the decomposition is performed on the level of single fMRI volumes, enabling DeepLight to study the associations between cognitive state and brain activity on several levels of data granularity, from the level of the group down to the level of single time points. To demonstrate the versatility of DeepLight, we apply it to a large fMRI dataset of the Human Connectome Project. We show that DeepLight outperforms conventional approaches of uni- and multivariate fMRI analysis in decoding the cognitive states and in identifying the physiologically appropriate brain regions associated with these states. We further demonstrate DeepLight's ability to study the fine-grained temporo-spatial variability of brain activity over sequences of single fMRI samples." @default.
- W2948702906 created "2019-06-14" @default.
- W2948702906 creator A5026451495 @default.
- W2948702906 creator A5047729967 @default.
- W2948702906 creator A5070255304 @default.
- W2948702906 creator A5072994165 @default.
- W2948702906 date "2018-10-23" @default.
- W2948702906 modified "2023-10-02" @default.
- W2948702906 title "Analyzing Neuroimaging Data Through Recurrent Deep Learning Models" @default.
- W2948702906 cites W1498436455 @default.
- W2948702906 cites W1533861849 @default.
- W2948702906 cites W1538131130 @default.
- W2948702906 cites W1560724230 @default.
- W2948702906 cites W1584308190 @default.
- W2948702906 cites W1787224781 @default.
- W2948702906 cites W1815076433 @default.
- W2948702906 cites W1947481528 @default.
- W2948702906 cites W1972498024 @default.
- W2948702906 cites W1977220343 @default.
- W2948702906 cites W1983208069 @default.
- W2948702906 cites W1993053013 @default.
- W2948702906 cites W2009797711 @default.
- W2948702906 cites W2024729467 @default.
- W2948702906 cites W2042116371 @default.
- W2948702906 cites W2045185094 @default.
- W2948702906 cites W2048631316 @default.
- W2948702906 cites W2059473123 @default.
- W2948702906 cites W2063951486 @default.
- W2948702906 cites W2064675550 @default.
- W2948702906 cites W2071608556 @default.
- W2948702906 cites W2081186010 @default.
- W2948702906 cites W2089632738 @default.
- W2948702906 cites W2095705004 @default.
- W2948702906 cites W2107187638 @default.
- W2948702906 cites W2108995755 @default.
- W2948702906 cites W2113619522 @default.
- W2948702906 cites W2115082678 @default.
- W2948702906 cites W2116649573 @default.
- W2948702906 cites W2120698894 @default.
- W2948702906 cites W2124757386 @default.
- W2948702906 cites W2126598020 @default.
- W2948702906 cites W2145680887 @default.
- W2948702906 cites W2151591509 @default.
- W2948702906 cites W2151969869 @default.
- W2948702906 cites W2154384688 @default.
- W2948702906 cites W2159580216 @default.
- W2948702906 cites W2171512898 @default.
- W2948702906 cites W2195388612 @default.
- W2948702906 cites W2316116400 @default.
- W2948702906 cites W2325276834 @default.
- W2948702906 cites W2402144811 @default.
- W2948702906 cites W2463071499 @default.
- W2948702906 cites W2522716651 @default.
- W2948702906 cites W2525157777 @default.
- W2948702906 cites W2588849466 @default.
- W2948702906 cites W2657631929 @default.
- W2948702906 cites W2802082113 @default.
- W2948702906 cites W2892239517 @default.
- W2948702906 cites W2902687238 @default.
- W2948702906 cites W2962981726 @default.
- W2948702906 cites W2963287333 @default.
- W2948702906 cites W2963527806 @default.
- W2948702906 cites W2964045325 @default.
- W2948702906 cites W2971788173 @default.
- W2948702906 cites W788946302 @default.
- W2948702906 cites W2162619305 @default.
- W2948702906 hasPublicationYear "2018" @default.
- W2948702906 type Work @default.
- W2948702906 sameAs 2948702906 @default.
- W2948702906 citedByCount "3" @default.
- W2948702906 countsByYear W29487029062019 @default.
- W2948702906 crossrefType "posted-content" @default.
- W2948702906 hasAuthorship W2948702906A5026451495 @default.
- W2948702906 hasAuthorship W2948702906A5047729967 @default.
- W2948702906 hasAuthorship W2948702906A5070255304 @default.
- W2948702906 hasAuthorship W2948702906A5072994165 @default.
- W2948702906 hasConcept C108583219 @default.
- W2948702906 hasConcept C119857082 @default.
- W2948702906 hasConcept C120843803 @default.
- W2948702906 hasConcept C153180895 @default.
- W2948702906 hasConcept C154945302 @default.
- W2948702906 hasConcept C15744967 @default.
- W2948702906 hasConcept C169760540 @default.
- W2948702906 hasConcept C169900460 @default.
- W2948702906 hasConcept C2779226451 @default.
- W2948702906 hasConcept C2781067378 @default.
- W2948702906 hasConcept C3018011982 @default.
- W2948702906 hasConcept C41008148 @default.
- W2948702906 hasConcept C522805319 @default.
- W2948702906 hasConcept C54170458 @default.
- W2948702906 hasConcept C58693492 @default.
- W2948702906 hasConcept C66324658 @default.
- W2948702906 hasConcept C70518039 @default.
- W2948702906 hasConcept C97820695 @default.
- W2948702906 hasConceptScore W2948702906C108583219 @default.
- W2948702906 hasConceptScore W2948702906C119857082 @default.
- W2948702906 hasConceptScore W2948702906C120843803 @default.
- W2948702906 hasConceptScore W2948702906C153180895 @default.
- W2948702906 hasConceptScore W2948702906C154945302 @default.
- W2948702906 hasConceptScore W2948702906C15744967 @default.