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GraFT: Graph Filtered Temporal Dictionary Learning for Functional Neural Imaging

View ORCID ProfileAdam S. Charles, Nathan Cermak, Rifqi Affan, Ben Scott, Jackie Schiller, Gal Mishne
doi: https://doi.org/10.1101/2021.05.24.445514
Adam S. Charles
aDepartment of Biomedical Engineering, Kavli Neuroscience Discovery Institute, Center for Imaging Science, and Mathematical Institute for Data Science, Johns Hopkins University, Baltimore, MD 21287 USA
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  • For correspondence: adamsc@jhu.edu
Nathan Cermak
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Rifqi Affan
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Ben Scott
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Jackie Schiller
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Gal Mishne
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Article Information

doi 
https://doi.org/10.1101/2021.05.24.445514
History 
  • May 25, 2021.
Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.

Author Information

  1. Adam S. Charlesa,#,
  2. Nathan Cermakb,
  3. Rifqi Affanc,
  4. Ben Scottc,
  5. Jackie Schillerb and
  6. Gal Mishned
  1. aDepartment of Biomedical Engineering, Kavli Neuroscience Discovery Institute, Center for Imaging Science, and Mathematical Institute for Data Science, Johns Hopkins University, Baltimore, MD 21287 USA
  2. bTechnion – Israel Institute of Technology, Haifa, Israel, 31096
  3. cDepartment of Psychological and Brain Sciences, Boston University, MA 02215 USA
  4. dHalicioğlu Data Science Institute and the Neurosciences Graduate Program, UC San Diego, CA 92093 USA (e-mail: gmishne{at}ucsd.edu)
  1. ↵#Please direct all correspondence to A. S. Charles: e-mail: adamsc{at}jhu.edu
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Posted May 25, 2021.
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GraFT: Graph Filtered Temporal Dictionary Learning for Functional Neural Imaging
Adam S. Charles, Nathan Cermak, Rifqi Affan, Ben Scott, Jackie Schiller, Gal Mishne
bioRxiv 2021.05.24.445514; doi: https://doi.org/10.1101/2021.05.24.445514
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GraFT: Graph Filtered Temporal Dictionary Learning for Functional Neural Imaging
Adam S. Charles, Nathan Cermak, Rifqi Affan, Ben Scott, Jackie Schiller, Gal Mishne
bioRxiv 2021.05.24.445514; doi: https://doi.org/10.1101/2021.05.24.445514

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