ArticleThe annals of applied statistics2018
COMPLEX-VALUED TIME SERIES MODELING FOR IMPROVED ACTIVATION DETECTION IN FMRI STUDIES.
Article in The annals of applied statistics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The trial behind it
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Who cites it
9 citing papers in PubMed.
- A single-echo/multi-echo BOLD fMRI test-retest dataset.Data in brief · 2026Article
- Efficient fully Bayesian approach to brain activity mapping with complex-valued fMRI data.Journal of applied statistics · 2025Article
- A fully Bayesian approach for comprehensive mapping of magnitude and phase brain activation in complex-valued fMRI data.Magnetic resonance imaging · 2024Article
- Denoising brain networks using a fixed mathematical phase change in independent component analysis of magnitude-only fMRI data.Human brain mapping · 2023Article
- A practical model-based segmentation approach for improved activation detection in single-subject functional magnetic resonance imaging studies.Human brain mapping · 2023Article
- Enhanced clinical task-based fMRI metrics through locally low-rank denoising of complex-valued data.The neuroradiology journal · 2023Article
- Shift-Invariant Canonical Polyadic Decomposition of Complex-Valued Multi-Subject fMRI Data With a Phase Sparsity Constraint.IEEE transactions on medical imaging · 2020Article
- Spatial source phase: A new feature for identifying spatial differences based on complex-valued resting-state fMRI data.Human brain mapping · 2019Article
- COMPLEX-VALUED TIME SERIES MODELING FOR IMPROVED ACTIVATION DETECTION IN FMRI STUDIES.The annals of applied statistics · 2018Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
A complex-valued data-based model with
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.