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Sliding windows analysis can undo the effects of preprocessing when applied to fMRI data

bioRxiv (Cold Spring Harbor Laboratory)(2023)10.1101/2023.10.06.561221Source: DataRank Database

Sliding windows analysis can undo the effects of preprocessing when applied to fMRI data is a research paper published in bioRxiv (Cold Spring Harbor Laboratory) (2023). On theSindex it has a DataRank of 0. It has been cited 2 times.

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (3 grants)OA: greenTopics (17)IDs (PubMed, OpenAlex)

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Authors (1)

Martin A. Lindquist ORCID

Live enrichment

PubMed:37873165 OpenAlex:https://openalex.org/W4387499645

Wellcome Trust

Grant: unidentified

unidentified

National Institutes of Health

Grant: 5R01MH129397-02

Personalized spatiotemporal hemodynamic response models for functional magnetic resonance imaging

National Institutes of Health

Grant: 5R01EB026549-03

Individualized spatial topology in functional neuroimaging

greenLicense: cc-by-nc

repositoryhttps://www.biorxiv.org/content/biorxiv/early/2023/10/09/2023.10.06.561221.full.pdf

publisherhttps://syndication.highwire.org/content/doi/10.1101/2023.10.06.561221

repositoryhttps://doi.org/10.1101/2023.10.06.561221

repositoryhttps://pubmed.ncbi.nlm.nih.gov/37873165

Fields of Study

Functional Brain Connectivity StudiesAdvanced MRI Techniques and ApplicationsAdvanced Neuroimaging Techniques and Applications05 social sciences0501 psychology and cognitive sciences

Keywords

PreprocessorComputer scienceSliding window protocolResting state fMRISIGNAL (programming language)Pattern recognition (psychology)UndoArtificial intelligenceNeuroscienceWindow (computing)PsychologyArticle