Improving the Interpretability of fMRI Decoding using Deep Neural Networks and Adversarial Robustness.
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| Title: | Improving the Interpretability of fMRI Decoding using Deep Neural Networks and Adversarial Robustness. |
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| Authors: | McClure P; Machine Learning Team, Functional Magnetic Resonance Imaging Facility, National Institute of Mental Health, Bethesda, MD, 20892, USA., Moraczewski D; Data Science and Sharing Team, Functional Magnetic Resonance Imaging Facility, National Institute of Mental Health, Bethesda, MD, 20892, USA., Lam KC; Machine Learning Team, Functional Magnetic Resonance Imaging Facility, National Institute of Mental Health, Bethesda, MD, 20892, USA., Thomas A; Data Science and Sharing Team, Functional Magnetic Resonance Imaging Facility, National Institute of Mental Health, Bethesda, MD, 20892, USA., Pereira F; Machine Learning Team, Functional Magnetic Resonance Imaging Facility, National Institute of Mental Health, Bethesda, MD, 20892, USA. |
| Source: | Aperture neuro [Apert Neuro] 2023; Vol. 3. Date of Electronic Publication: 2023 Aug 07. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Organization for Human Brain Mapping Country of Publication: United States NLM ID: 9918300982606676 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2957-3963 (Electronic) Linking ISSN: 29573963 NLM ISO Abbreviation: Apert Neuro Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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