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| <full_title>Journal of Open Source Software</full_title> | ||
| <abbrev_title>JOSS</abbrev_title> | ||
| <issn media_type="electronic">2475-9066</issn> | ||
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| <doi>10.21105/joss</doi> | ||
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| <month>11</month> | ||
| <year>2024</year> | ||
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| <title>fMRIStroke: A preprocessing pipeline for fMRI Data from | ||
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| <month>11</month> | ||
| <day>20</day> | ||
| <year>2024</year> | ||
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| <first_page>6636</first_page> | ||
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| <journal_title>Magnetic Resonance Imaging</journal_title> | ||
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| <journal_title>Nature Methods</journal_title> | ||
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| Durnez, J., Poldrack, R. A., & Gorgolewski, K. J. (2019). fMRIPrep: | ||
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| 16(1), 111–116. | ||
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| D. M., & Stout, J. N. (2023). Bbfrederick/rapidtide: Version 2.7.3.3 | ||
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| Metabolism</journal_title> | ||
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| <unstructured_citation>Siegel, J. S., Snyder, A. Z., Ramsey, | ||
| L., Shulman, G. L., & Corbetta, M. (2016). The effects of | ||
| hemodynamic lag on functional connectivity and behavior after stroke. | ||
| Journal of Cerebral Blood Flow & Metabolism, 36(12), 2162–2176. | ||
| https://doi.org/10.1177/0271678X15614846</unstructured_citation> | ||
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| <article_title>Measuring functional connectivity in stroke: | ||
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| <author>Siegel</author> | ||
| <journal_title>Journal of Cerebral Blood Flow & | ||
| Metabolism</journal_title> | ||
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| <unstructured_citation>Siegel, J. S., Shulman, G. L., & | ||
| Corbetta, M. (2017). Measuring functional connectivity in stroke: | ||
| Approaches and considerations. Journal of Cerebral Blood Flow & | ||
| Metabolism, 37(8), 2665–2678. | ||
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| <article_title>Removal of artifacts from resting-state fMRI | ||
| data in stroke</article_title> | ||
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| <journal_title>NeuroImage : Clinical</journal_title> | ||
| <volume>17</volume> | ||
| <doi>10.1016/j.nicl.2017.10.027</doi> | ||
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| <cYear>2017</cYear> | ||
| <unstructured_citation>Yourganov, G., Fridriksson, J., | ||
| Stark, B., & Rorden, C. (2017). Removal of artifacts from | ||
| resting-state fMRI data in stroke. NeuroImage : Clinical, 17, 297–305. | ||
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