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词条 List of functional connectivity software
释义

  1. See also

  2. References

Functional connectivity software is used to study functional properties of the connectome using functional Magnetic Resonance Imaging (fMRI) data in the resting state and during tasks. To access many of these software applications visit the NIH funded Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) site.

Name Description Programming language Is part of / requires Developer/Organization
Brain Connectivity Toolbox[1] Graph-theoretical analyses of functional connectivity Matlab Department of Psychological and Brain Sciences, Indiana University
Brain Modulyzer [2]Explore Hierarchical Processes of the functional brain networksPython U.S. Dept. of Energy, Lawrence Berkeley National Laboratory
BrainNet viewer[3] Brain network visualization tool Matlab National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Brainwaver[4] Brain connectivity extraction and analysis R waveslim Centre National de la Recherche Scientifique, {{ill>GIPSA-lab|fr|Grenoble images parole signal automatique}}, University of Cambridge
C-PAC[5] Functional connectivity analysis pipeline Python Child Mind Institute; Nathan Kline Institute; NYU Langone Medical Center
CONN[6] Functional connectivity analysis and display tool Matlab SPM McGovern Institute for Brain Research, Massachusetts Institute of Technology: MIT
Connectome workbench Visualization and discovery tool Python Child Mind Institute, Nathan Kline Institute, NYU Langone Medical Center
cPPI[7] Task-related functional connectivity analysis Matlab SPM Monash Clinical and Imaging Neuroscience
DCM[8] Dynamic Causal Modelling analysis Matlab SPM Wellcome Trust Centre for Neuroimaging, University College London
FATCAT[9] Functional and tractographic connectivity analysis C AFNI Scientific and Statistical Computing Core, National Institute of Mental Health: NIMH
FSFC[10] Seed-based functional connectivity analysis Shell FreeSurfer Martinos Center for Biomedical Imaging
Fubraconnex[11] Tool for visual analysis of functional connectivity C Delft University of Technology
GIFT[12] Independent component analysis Matlab Medical Image Analysis Lab, The Mind Research Network
gPPI[13] Task-related functional connectivity analysis Matlab SPM University of Wisconsin Madison
Graph Theoretic GLM Toolbox[14]Graph theory analysis and fMRI preprocessing pipelineMatlab Boston University School of Medicine, VA Boston Healthcare System
Graphvar[15] Graph-theoretical analysis tool Matlab Division of Mind and Brain Research, Charité Universitätsmedizin
MELODIC[16] Independent component analysis C FSL Functional Magnetic Resonance Imaging of the Brain Analysis Group, Oxford University
NIAK[17] Neuroimaging analysis library Matlab, Octave Research Centre of the Montreal Geriatric Institute, University of Montreal
nilearn[18] Machine learning for Neuro-Imaging in Python Python INRIA Parietal Project Team, Neurospin, CEA Institute
REST[19] Resting-state functional connectivity analysis tool Matlab State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University

See also

  • List of neuroimaging software
  • Functional connectivity
  • Neuroimaging

References

1. ^{{cite journal | last1 = Rubinov | first1 = M. | last2 = Sporns | first2 = O. | year = 2010 | title = Complex network measures of brain connectivity: uses and interpretations | url = | journal = NeuroImage | volume = 52 | issue = 3| pages = 1059–1069 | doi=10.1016/j.neuroimage.2009.10.003| pmid = 19819337 }}
2. ^{{Cite journal|last=Murugesan|first=S.|last2=Bouchard|first2=K.|last3=Brown|first3=J. A.|last4=Hamann|first4=B.|last5=Seeley|first5=W. W.|last6=Trujillo|first6=A.|last7=Weber|first7=G. H.|date=2016-01-01|title=Brain Modulyzer: Interactive Visual Analysis of Functional Brain Connectivity|journal=IEEE/ACM Transactions on Computational Biology and Bioinformatics|volume=PP|issue=99|pages=805–818|doi=10.1109/TCBB.2016.2564970|pmid=28113724|issn=1545-5963}}
3. ^{{cite journal | last1 = Xia | first1 = M. | last2 = Wang | first2 = J. | last3 = He | first3 = Y. | year = 2013 | title = BrainNet Viewer: a network visualization tool for human brain connectomics | url = | journal = PLoS ONE | volume = 8 | issue = 7| page = e68910 | doi=10.1371/journal.pone.0068910}}
4. ^{{cite journal | last1 = Achard | first1 = S. | last2 = Salvador | first2 = R. | last3 = Whitcher | first3 = B. | last4 = Suckling | first4 = J. | last5 = Bullmore | first5 = Ed | year = 2006 | title = Brainwaver: Basic wavelet analysis of multivariate time series with a visualisation and parametrisation using graph theory | url = | journal = J. Neurosci. | volume = 26 | issue = 1 | pages = 63–72 | doi=10.1523/JNEUROSCI.3874-05.2006 | pmid = 16399673 }}
5. ^{{cite journal | last1 = Di Martino | first1 = A. |display-authors=etal | year = 2014 | title = The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecturein autism | url = | journal = Mol. Psychiatry | volume = 19 | issue = 6| pages = 659–667 | doi=10.1038/mp.2013.78| pmid = 23774715 | pmc = 4162310 }}
6. ^{{cite journal | last1 = Whitfield-Gabrieli | first1 = S. | last2 = Nieto-Castanon | first2 = A. | year = 2012 | title = Conn: a functional connectivity toolbox for correlated and anticorrelated brainnetworks | url = | journal = Brain Connect | volume = 2 | issue = 3| pages = 125–141 | doi=10.1089/brain.2012.0073| pmid = 22642651 }}
7. ^{{cite journal | last1 = Fornito | first1 = A. | last2 = Harrison | first2 = B. J. | last3 = Zalesky | first3 = A. | last4 = Simons | first4 = J.S. | year = 2012 | title = Competitive and cooperative dynamics of large-scale brain functional networks supporting recollection | journal = PNAS | volume = 109 | issue = 31| pages = 12788–12793 | doi=10.1073/pnas.1204185109 | pmid=22807481 | pmc=3412011}}
8. ^{{cite journal | last1 = Friston | first1 = K. J. | last2 = Kahan | first2 = J. | last3 = Biswal | first3 = B. | last4 = Razi | first4 = A. | year = 2014 | title = A DCM for resting state fMRI | url = | journal = NeuroImage | volume = 94 | issue = | pages = 396–407 | doi=10.1016/j.neuroimage.2013.12.009| pmid = 24345387 | pmc = 4073651 }}
9. ^{{cite journal | last1 = Taylor | first1 = P. A. | last2 = Saad | first2 = Z. S. | year = 2013 | title = FATCAT: (an efficient) Functional and Tractographic Connectivity Analysis Toolbox | url = | journal = Brain Connect | volume = 3 | issue = 5| pages = 523–535 | doi=10.1089/brain.2013.0154| pmid = 23980912 | pmc = 3796333 }}
10. ^{{cite journal | last1 = Fischl | first1 = B. FreeSurfer | year = 2012 | title = FreeSurfer| doi = 10.1016/j.neuroimage.2012.01.021 | pmid = 22248573 | journal = NeuroImage | volume = 62 | issue = 2| pages = 774–781 | pmc = 3685476 }}
11. ^van Dixhoorn, A.F., Vissers, B., Ferrarini, L., Milles, J., and Botha, C.P. (2010). Visual analysis of integrated resting state functional brain connectivity and anatomy, Eurographics Workshop on Visual Computing for Biology and Medicine
12. ^Calhoun, V. D., Adali, T., Pearlson, G. D. & Pekar, J. J. (2001). A method for making group inferences from functional MRI data using independent component analysis. Hum. Brain Mapp. 14, 140–151
13. ^McLaren, D.G., Ries, M.L., Xu, G., Johnson, S.C. (2012). A generalized form of context-dependent psychophysiological interactions (gPPI): A comparison to standard approaches, NeuroImage, 61(4), 1277-1286
14. ^{{Cite journal|title = Brain Network Disturbance Related to Posttraumatic Stress and Traumatic Brain Injury in Veterans|journal = Biological Psychiatry|pages = 210–216|volume = 78|issue = 3|doi = 10.1016/j.biopsych.2015.02.013|first = Jeffrey M.|last = Spielberg|first2 = Regina E.|last2 = McGlinchey|first3 = William P.|last3 = Milberg|first4 = David H.|last4 = Salat|pmid=25818631|year = 2015}}
15. ^{{cite journal | last1 = Kruschwitz | first1 = J. D. | last2 = List | first2 = D. | last3 = Waller | first3 = L. | last4 = Rubinov | first4 = M. | last5 = Walter | first5 = H. | year = 2015 | title = GraphVar: A user-friendly toolbox for comprehensive graph analyses of functional brain connectivity | url = | journal = Journal of Neuroscience Methods | volume = 245 | issue = | pages = 107–115 | doi=10.1016/j.jneumeth.2015.02.021| pmid = 25725332 }}
16. ^{{cite journal | last1 = Beckmann | first1 = C. F. | last2 = DeLuca | first2 = M. | last3 = Devlin | first3 = J. T. | last4 = Smith | first4 = S. M. | year = 2005 | title = Investigations into resting-state connectivity using independentcomponent analysis | url = | journal = Philos. Trans. R. Soc. Lond. B Biol. Sci.| volume = 360 | issue = 1457| pages = 1001–1013 | doi=10.1098/rstb.2005.1634| pmid = 16087444 | pmc = 1854918 }}
17. ^{{cite journal | last1 = Bellec | first1 = P. |display-authors=etal | year = 2012 | title = The pipeline system for Octave and Matlab (PSOM): a lightweight scripting framework and execution engine forscientific workflows | url = | journal = Front. Neuroinformatics | volume = 6 | issue = | page = 7 | doi=10.3389/fninf.2012.00007| pmid = 22493575 | pmc = 3318188 }}
18. ^Abraham, A., Pedregosa, F., Eickenberg, M., Gervais, P., Mueller, A., Kossaifi, J., ... & Varoquaux, G. (2014). Machine learning for neuroimaging with scikit-learn. Frontiers in neuroinformatics, 8
19. ^{{cite journal | last1 = Song | first1 = X. W. |display-authors=etal | year = 2011 | title = REST: a toolkit for resting-state functional magnetic resonance imaging data processing | url = | journal = PLoS ONE | volume = 6 | issue = 9| page = e25031 | doi=10.1371/journal.pone.0025031| pmid = 21949842 }}
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