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Contact

For software support contact us at opennft@gmail.com.

References

  • For open-source OpenNFT code and applied real-time data processing and software features, cite Koush et al., 2017, Neuroimage 157:489-503
  • For real-time fMRI data, cite Koush et al., 2017, Data in Brief 14:344-347
  • For SPM features, cite SPM12 http://fil.ion.ucl.ac.uk/spm/
  • For DCM features, cite used SPM/DCM release.
  • For incremental GLM, cite Bagarinao et. al. 2003, NeuroImage
  • For connectivity-based feedback using DCM, cite Koush et al. 2013, NeuroImage; Koush et al. 2015, Cerebral Cortex.
  • For real-time signal processing using Kalman filter, cite Koush et al. 2012, NeuroImage
  • For SVM-based feedback, cite LaConte et al. 2007, HBM; LaConte 2011, NeuroImage
  • For sigmoidal function, cite deBettencourt et al. 2015, NatNeuroscience
  • For feedback display based on PTB-3 functions, cite psychtoolbox.org
  • For Matlab, cite MathWorks, Natick, Massachusetts, United States.
  • For Python, cite https://www.python.org/

Citations

  1. Koush Y., Ashburner J., Prilepin E., Sladky R., Zeidman P., Bibikov S., Frank Scharnowski F., Nikonorov A., Van De Ville D. (2017). OpenNFT: An open-source Python/Matlab framework for real-time fMRI neurofeedback training based on activity, connectivity and multivariate pattern analysis. Neuroimage 157:489-503)
  2. Koush Y., Ashburner J., Prilepin E., Sladky R., Zeidman P., Bibikov S., Frank Scharnowski F., Nikonorov A., Van De Ville D. (2017). Real-time fMRI data for testing OpenNFT functionality. Data in Brief 14:344-347