P
Peter A. Bandettini
Researcher at National Institutes of Health
Publications - 274
Citations - 40670
Peter A. Bandettini is an academic researcher from National Institutes of Health. The author has contributed to research in topics: Resting state fMRI & Functional magnetic resonance imaging. The author has an hindex of 84, co-authored 261 publications receiving 35902 citations. Previous affiliations of Peter A. Bandettini include Medical College of Wisconsin & Harvard University.
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Representational Similarity Analysis – Connecting the Branches of Systems Neuroscience
TL;DR: A new experimental and data-analytical framework called representational similarity analysis (RSA) is proposed, in which multi-channel measures of neural activity are quantitatively related to each other and to computational theory and behavior by comparing RDMs.
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Dynamic functional connectivity: Promise, issues, and interpretations
R. Matthew Hutchison,Thilo Womelsdorf,Elena A. Allen,Elena A. Allen,Peter A. Bandettini,Vince D. Calhoun,Vince D. Calhoun,Maurizio Corbetta,Maurizio Corbetta,Stefania Della Penna,Jeff H. Duyn,Gary H. Glover,Javier Gonzalez-Castillo,Daniel A. Handwerker,Shella D. Keilholz,Vesa Kiviniemi,David A. Leopold,Francesco de Pasquale,Olaf Sporns,Martin Walter,Martin Walter,Catie Chang +21 more
TL;DR: Emerging evidence suggests that dynamic FC metrics may index changes in macroscopic neural activity patterns underlying critical aspects of cognition and behavior, though limitations with regard to analysis and interpretation remain.
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The impact of global signal regression on resting state correlations: are anti-correlated networks introduced?
TL;DR: It is shown that, after global signal regression, correlation values to a seed voxel must sum to a negative value and that the relative phase of global and local signals can affect connectivity measures and that, experimentally,global signal regression leads to bell-shaped correlation value distributions, centred on zero.
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Information-based functional brain mapping
TL;DR: The development of high-resolution neuroimaging and multielectrode electrophysiological recording provides neuroscientists with huge amounts of multivariate data, but the local averaging standardly applied to this end may obscure the effects of greatest neuroscientific interest.
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Time course EPI of human brain function during task activation.
TL;DR: Using gradient‐echo echo‐planar MRI, a local signal increase is observed in the human brain during task activation, suggesting a local decrease in blood deoxyhemoglobin concentration and an increase in blood oxygenation.