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Literature DB >> 22487186

Decomposing the brain: components and modes, networks and nodes.

Vince D Calhoun¹, Tom Eichele, Tülay Adalı, Elena A Allen.

Abstract

Smith and colleagues recently presented a temporal independent component analysis (tICA) decomposition of resting-state functional MRI data. Compared to the widely used spatial ICA (sICA), tICA better allows for a brain region to engage in multiple, independent interactions with other regions and will potentially offer new insights into brain function.

Entities: Chemical

Mesh：

Year: 2012 PMID： 22487186 PMCID： PMC3773539 DOI： 10.1016/j.tics.2012.03.008

Source DB: PubMed Journal: Trends Cogn Sci ISSN： 1364-6613 Impact factor: 20.229

10 in total

1. Spatial and temporal independent component analysis of functional MRI data containing a pair of task-related waveforms.

Authors: V D Calhoun; T Adali; G D Pearlson; J J Pekar
Journal: Hum Brain Mapp Date: 2001-05 Impact factor: 5.038

2. A method for making group inferences from functional MRI data using independent component analysis.

Authors: V D Calhoun; T Adali; G D Pearlson; J J Pekar
Journal: Hum Brain Mapp Date: 2001-11 Impact factor: 5.038

3. Spatiotemporal pattern of neural processing in the human auditory cortex.

Authors: Erich Seifritz; Fabrizio Esposito; Franciszek Hennel; Henrietta Mustovic; John G Neuhoff; Deniz Bilecen; Gioacchino Tedeschi; Klaus Scheffler; Francesco Di Salle
Journal: Science Date: 2002-09-06 Impact factor: 47.728

4. Temporally-independent functional modes of spontaneous brain activity.

Authors: Stephen M Smith; Karla L Miller; Steen Moeller; Junqian Xu; Edward J Auerbach; Mark W Woolrich; Christian F Beckmann; Mark Jenkinson; Jesper Andersson; Matthew F Glasser; David C Van Essen; David A Feinberg; Essa S Yacoub; Kamil Ugurbil
Journal: Proc Natl Acad Sci U S A Date: 2012-02-07 Impact factor: 11.205

5. Neural network of speech monitoring overlaps with overt speech production and comprehension networks: a sequential spatial and temporal ICA study.

Authors: Vincent van de Ven; Fabrizio Esposito; Ingrid K Christoffels
Journal: Neuroimage Date: 2009-05-27 Impact factor: 6.556

6. Analysis of fMRI data by blind separation into independent spatial components.

Authors: M J McKeown; S Makeig; G G Brown; T P Jung; S S Kindermann; A J Bell; T J Sejnowski
Journal: Hum Brain Mapp Date: 1998 Impact factor: 5.038

7. Modes or models: a critique on independent component analysis for fMRI.

Authors: K J Friston
Journal: Trends Cogn Sci Date: 1998-10-01 Impact factor: 20.229

8. Canonical Correlation Analysis for Data Fusion and Group Inferences: Examining applications of medical imaging data.

Authors: Nicolle M Correa; Tülay Adali; Yi-Ou Li; Vince D Calhoun
Journal: IEEE Signal Process Mag Date: 2010 Impact factor: 12.551

9. Capturing inter-subject variability with group independent component analysis of fMRI data: a simulation study.

Authors: Elena A Allen; Erik B Erhardt; Yonghua Wei; Tom Eichele; Vince D Calhoun
Journal: Neuroimage Date: 2011-10-14 Impact factor: 6.556

10. A method for functional network connectivity among spatially independent resting-state components in schizophrenia.

Authors: Madiha J Jafri; Godfrey D Pearlson; Michael Stevens; Vince D Calhoun
Journal: Neuroimage Date: 2007-11-13 Impact factor: 6.556

10 in total

19 in total

Review 1. A systematic examination of preoperative surgery warm-up routines.

Authors: T W Pike; S Pathak; F Mushtaq; R M Wilkie; M Mon-Williams; J P A Lodge
Journal: Surg Endosc Date: 2016-09-15 Impact factor: 4.584

Review 2. Biomarkers, designs, and interpretations of resting-state fMRI in translational pharmacological research: A review of state-of-the-Art, challenges, and opportunities for studying brain chemistry.

Authors: Najmeh Khalili-Mahani; Serge A R B Rombouts; Matthias J P van Osch; Eugene P Duff; Felix Carbonell; Lisa D Nickerson; Lino Becerra; Albert Dahan; Alan C Evans; Jean-Paul Soucy; Richard Wise; Alex P Zijdenbos; Joop M van Gerven
Journal: Hum Brain Mapp Date: 2017-02-01 Impact factor: 5.038

Decomposing the brain: components and modes, networks and nodes.

1. Spatial and temporal independent component analysis of functional MRI data containing a pair of task-related waveforms.

2. A method for making group inferences from functional MRI data using independent component analysis.

3. Spatiotemporal pattern of neural processing in the human auditory cortex.

4. Temporally-independent functional modes of spontaneous brain activity.

5. Neural network of speech monitoring overlaps with overt speech production and comprehension networks: a sequential spatial and temporal ICA study.

6. Analysis of fMRI data by blind separation into independent spatial components.

7. Modes or models: a critique on independent component analysis for fMRI.

8. Canonical Correlation Analysis for Data Fusion and Group Inferences: Examining applications of medical imaging data.

9. Capturing inter-subject variability with group independent component analysis of fMRI data: a simulation study.

10. A method for functional network connectivity among spatially independent resting-state components in schizophrenia.

Review 1. A systematic examination of preoperative surgery warm-up routines.

Review 2. Biomarkers, designs, and interpretations of resting-state fMRI in translational pharmacological research: A review of state-of-the-Art, challenges, and opportunities for studying brain chemistry.

3. Large-scale sparse functional networks from resting state fMRI.

4. Task-related concurrent but opposite modulations of overlapping functional networks as revealed by spatial ICA.

5. Aberrant Functional Whole-Brain Network Architecture in Patients With Schizophrenia: A Meta-analysis.

6. Time of acquisition and network stability in pediatric resting-state functional magnetic resonance imaging.

7. Topological methods reveal high and low functioning neuro-phenotypes within fragile X syndrome.

Review 8. Methods and Considerations for Dynamic Analysis of Functional MR Imaging Data.

9. Multi-Hypergraph Learning-Based Brain Functional Connectivity Analysis in fMRI Data.

10. Application of Graph Theory to Assess Static and Dynamic Brain Connectivity: Approaches for Building Brain Graphs.