[UP+ BF]: fixed bibliography entries +

publications.bib

@@ -60,22 +60,6 @@ @article{halchenko_datalad_2021
 	file = {Halchenko et al. - 2021 - DataLad distributed system for joint management o.pdf:/home/alpron/Zotero/storage/JWK96IST/Halchenko et al. - 2021 - DataLad distributed system for joint management o.pdf:application/pdf},
 }
 
-@misc{bollmann_neurodesk_2023,
-	type = {preprint},
-	title = {Neurodesk: {An} accessible, flexible, and portable data analysis environment for reproducible neuroimaging},
-	shorttitle = {Neurodesk},
-	url = {https://www.researchsquare.com/article/rs-2649734/v1},
-	abstract = {Abstract
-          Neuroimaging data analysis often requires purpose-built software, which can be challenging to install and may produce different results across computing environments. Beyond being a roadblock to neuroscientists, these issues of accessibility and portability can hamper the reproducibility of neuroimaging data analysis pipelines. Here, we introduce the Neurodesk platform, which harnesses software containers to support a comprehensive and growing suite of neuroimaging software (https://www.neurodesk.org/). Neurodesk includes a browser-accessible virtual desktop environment and a command line interface, mediating access to containerized neuroimaging software libraries on various computing platforms, including personal and high-performance computers, cloud computing and Jupyter Notebooks. This community-oriented, open-source platform enables a paradigm shift for neuroimaging data analysis, allowing for accessible, flexible, fully reproducible, and portable data analysis pipelines.},
-	urldate = {2024-01-04},
-	publisher = {In Review},
-	author = {Bollmann, Steffen and Renton, Angela and Dao, Thuy and Johnstone, Tom and Civier, Oren and Sullivan, Ryan and White, David and Lyons, Paris and Slade, Benjamin and Abbott, David and Amos, Toluwani and Bollmann, Saskia and Botting, Andy and Campbell, Megan and Chang, Jeryn and Close, Thomas and Eckstein, Korbinian and Egan, Gary and Evas, Stefanie and Flandin, Guillaume and Garner, Kelly and Garrido, Marta and Ghosh, Satrajit and Grignard, Martin and Hannan, Anthony and Huber, Laurentius (Renzo) and Kaczmarzyk, Jakub and Kasper, Lars and Kuhlmann, Levin and Lou, Kexin and Mantilla-Ramos, Yorguin-Jose and Mattingley, Jason and Morris, Jo and Narayanan, Akshaiy and Pestilli, Franco and Puce, Aina and Ribeiro, Fernanda and Rogasch, Nigel and Rorden, Chris and Schira, Mark and Shaw, Thomas and Sowman, Paul and Spitz, Gershon and Stewart, Ashley and Ye, Xincheng and Zhu, Judy and Hughes, Matthew and Narayanan, Aswin},
-	month = mar,
-	year = {2023},
-	doi = {10.21203/rs.3.rs-2649734/v1},
-	file = {Bollmann et al. - 2023 - Neurodesk An accessible, flexible, and portable d.pdf:/home/alpron/Zotero/storage/AQR5KZMM/Bollmann et al. - 2023 - Neurodesk An accessible, flexible, and portable d.pdf:application/pdf},
-}
-
 @article{colliot_reproducibility_2024,
 	title = {Reproducibility in medical image computing: what is it and how is it assessed?},
 	abstract = {Medical image computing (MIC) is devoted to computational methods for analysis of medical imaging data and their assessment through experiments. It is thus an experimental science. Reproducibility is a cornerstone of progress in all experimental sciences. As in many other fields, there are major concerns that reproducibility is unsatisfactory in MIC. However, reproducibility is not a single concept but a spectrum, which is often misunderstood by researchers. Moreover, even though some measures have been put in place to promote reproducibility in the MIC community, it is unclear if they have been effective so far.},
@@ -299,7 +283,31 @@ @misc{noauthor_bids-standardbep028_bidsprov_2024
 	keywords = {BIDS, provenance},
 }
 
+@misc{noauthor_bids_nodate,
+	title = {{BIDS} {Extension} {Proposal} ({BEP028}): {Provenance}},
+	shorttitle = {{BIDS} {Extension} {Proposal} ({BEP028})},
+	url = {https://docs.google.com/document/d/1vw3VNDof5cecv2PkFp7Lw_pNUTUo8-m8V4SIdtGJVKs/edit?usp=sharing&usp=embed_facebook},
+	language = {fr},
+	urldate = {2024-02-29},
+	journal = {Google Docs},
+	keywords = {BIDS, provenance},
+	file = {Snapshot:/home/alpron/Zotero/storage/84FRG2PA/edit.html:text/html},
+}
 
+@misc{noauthor_computational_nodate,
+	title = {Computational basis and {ReproIn}/{DataLad}: {A} complete portable and reproducible {fMRI} study from scratch},
+	url = {http://www.repronim.org/ohbm2018-training/03-01-reproin/},
+	urldate = {2024-02-29},
+	keywords = {datalad},
+	file = {Computational basis and ReproIn/DataLad\: ReproIn/DataLad\: A complete portable and reproducible fMRI study from scratch:/home/alpron/Zotero/storage/C7QV89WR/03-01-reproin.html:text/html},
+}
+
+@article{maumet_best_nodate,
+	title = {The best of both worlds: using semantic web with {JSON}-{LD}. {An} example with {NIDM}-{Results} \& {Datalad}},
+	language = {en},
+	author = {Maumet, Camille and Ghosh, Satrajit and Halchenko, Yaroslav O and Jarecka, Dorota and Nichols, Nolan B and Poline, Jean-Baptiste and Hanke, Michael},
+	file = {Maumet et al. - The best of both worlds using semantic web with J.pdf:/home/alpron/Zotero/storage/MW5U3VID/Maumet et al. - The best of both worlds using semantic web with J.pdf:application/pdf},
+}
 
 @article{nichols_best_2017,
 	title = {Best practices in data analysis and sharing in neuroimaging using {MRI}},
@@ -312,7 +320,12 @@ @article{nichols_best_2017
 	file = {Nichols et al. - 2017 - Best practices in data analysis and sharing in neu.pdf:/home/alpron/Zotero/storage/H88I739N/Nichols et al. - 2017 - Best practices in data analysis and sharing in neu.pdf:application/pdf},
 }
 
-
+@misc{noauthor_datalad_nodate,
+	title = {{DataLad} extension module for neuroimaging studies — {Datalad} for {Hirnis} 0.0.8 documentation},
+	url = {http://docs.datalad.org/projects/hirni/en/latest/index.html},
+	urldate = {2024-03-19},
+	keywords = {datalad},
+	file = {DataLad extension module for neuroimaging studies — Datalad for Hirnis 0.0.8 documentation:/home/alpron/Zotero/storage/Z3HMSFLD/index.html:text/html},
 }
 
 @misc{halchenko_nipyheudiconv_2023,
@@ -382,7 +395,20 @@ @unpublished{vila_impact_2024
 	file = {HAL PDF Full Text:/home/alpron/Zotero/storage/HQPFHLFC/Vila et al. - 2024 - The Impact of Hardware Variability on Applications.pdf:application/pdf},
 }
 
+@misc{maumet_towards_nodate,
+	title = {Towards reusable derived data in neuroimaging},
+	language = {en},
+	author = {Maumet, Camille},
+	file = {Maumet - Towards reusable derived data in neuroimaging.pdf:/home/alpron/Zotero/storage/SPIMSHT9/Maumet - Towards reusable derived data in neuroimaging.pdf:application/pdf},
+}
 
+@phdthesis{maumet_towards_nodate-1,
+	title = {Towards reproducible neuroimaging: {Solutions} for sharing and re-using brain imaging data},
+	language = {en},
+	author = {Maumet, Camille},
+	keywords = {Important},
+	file = {Maumet - Towards reproducible neuroimaging Solutions for s.pdf:/home/alpron/Zotero/storage/S7YM9AUP/Maumet - Towards reproducible neuroimaging Solutions for s.pdf:application/pdf},
+}
 
 @article{martone_past_2024,
 	title = {The past, present and future of neuroscience data sharing: a perspective on the state of practices and infrastructure for {FAIR}},
@@ -403,6 +429,12 @@ @article{martone_past_2024
 	file = {Martone - 2024 - The past, present and future of neuroscience data .pdf:/home/alpron/Zotero/storage/JSZZGSIN/Martone - 2024 - The past, present and future of neuroscience data .pdf:application/pdf},
 }
 
+@article{sanz-robinson_open-source_nodate,
+	title = {Open-source tools and platforms to investigate analytical variability in neuroimaging},
+	author = {Sanz-Robinson, Jacob and Wang, Michelle and McPherson, Brent and Glatard, Tristan and Poline, Jean-Baptiste},
+	note = {Publisher: OSF},
+	file = {Sanz-Robinson et al. - Open-source tools and platforms to investigate ana.pdf:/home/alpron/Zotero/storage/ZCERUVV7/Sanz-Robinson et al. - Open-source tools and platforms to investigate ana.pdf:application/pdf},
+}
 
 @article{luppi_systematic_2024,
 	title = {Systematic evaluation of {fMRI} data-processing pipelines for consistent functional connectomics},
@@ -518,26 +550,6 @@ @article{jadavji_editorial_2023
 	file = {Jadavji et al. - 2023 - Editorial Reproducibility in neuroscience.pdf:/home/alpron/Zotero/storage/G7DDIIRI/Jadavji et al. - 2023 - Editorial Reproducibility in neuroscience.pdf:application/pdf},
 }
 
-@article{soskic_garden_2024,
-	title = {Garden of forking paths in {\textless}span style="font-variant:small-caps;"{\textgreater}{ERP}{\textless}/span{\textgreater} research – {Effects} of varying pre‐processing and analysis steps in an {\textless}span style="font-variant:small-caps;"{\textgreater}{N400}{\textless}/span{\textgreater} experiment},
-	issn = {0048-5772, 1469-8986},
-	shorttitle = {Garden of forking paths in {\textless}span style="font-variant},
-	url = {https://onlinelibrary.wiley.com/doi/10.1111/psyp.14628},
-	doi = {10.1111/psyp.14628},
-	abstract = {Abstract
-            This study tackles the Garden of Forking Paths, as a challenge for replicability and reproducibility of ERP studies. Here, we applied a multiverse analysis to a sample ERP N400 dataset, donated by an independent research team. We analyzed this dataset using 14 pipelines selected to showcase the full range of methodological variability found in the N400 literature using systematic review approach. The selected pipelines were compared in depth by looking into statistical test outcomes, descriptive statistics, effect size, data quality, and statistical power. In this way we provide a worked example of how analytic flexibility can impact results in research fields with high dimensionality such as ERP, when analyzed using standard null‐hypothesis significance testing. Out of the methodological decisions that were varied, high‐pass filter cut‐off, artifact removal method, baseline duration, reference, measurement latency and locations, and amplitude measure (peak vs. mean) were all shown to affect at least some of the study outcome measures. Low‐pass filtering was the only step which did not notably influence any of these measures. This study shows that even some of the seemingly minor procedural deviations can influence the conclusions of an ERP study. We demonstrate the power of multiverse analysis in both identifying the most reliable effects in a given study, and for providing insights into consequences of methodological decisions.
-          , 
-            This study shows that most ERP preprocessing and analysis steps can affect study outcomes, and that even some of the seemingly minor procedural deviations can influence conclusions of an ERP study, and it demonstrates the power of the multiverse analysis approach in both identifying the most reliable effects and providing concrete insights into consequences of a given methodological decision.},
-	language = {en},
-	urldate = {2024-07-22},
-	journal = {Psychophysiology},
-	author = {Šoškić, Anđela and Styles, Suzy J. and Kappenman, Emily S. and Ković, Vanja},
-	month = jul,
-	year = {2024},
-	keywords = {to read, to\_add\_github},
-	pages = {e14628},
-}
-
 @article{weigard_flexible_2024,
 	title = {Flexible adaptation of task-positive brain networks predicts efficiency of evidence accumulation},
 	volume = {7},
@@ -585,3 +597,34 @@ @misc{demidenko_impact_2024
 	keywords = {to read, to\_add\_github},
 	file = {Demidenko et al. - 2024 - Impact of analytic decisions on test-retest reliab.pdf:/home/alpron/Zotero/storage/JDL4YPK4/Demidenko et al. - 2024 - Impact of analytic decisions on test-retest reliab.pdf:application/pdf},
 }
+
+@article{soskic_garden_nodate,
+	title = {Garden of forking paths in {ERP} research – {Effects} of varying pre-processing and analysis steps in an {N400} experiment},
+	volume = {n/a},
+	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/psyp.14628},
+	doi = {https://doi.org/10.1111/psyp.14628},
+	abstract = {Abstract This study tackles the Garden of Forking Paths, as a challenge for replicability and reproducibility of ERP studies. Here, we applied a multiverse analysis to a sample ERP N400 dataset, donated by an independent research team. We analyzed this dataset using 14 pipelines selected to showcase the full range of methodological variability found in the N400 literature using systematic review approach. The selected pipelines were compared in depth by looking into statistical test outcomes, descriptive statistics, effect size, data quality, and statistical power. In this way we provide a worked example of how analytic flexibility can impact results in research fields with high dimensionality such as ERP, when analyzed using standard null-hypothesis significance testing. Out of the methodological decisions that were varied, high-pass filter cut-off, artifact removal method, baseline duration, reference, measurement latency and locations, and amplitude measure (peak vs. mean) were all shown to affect at least some of the study outcome measures. Low-pass filtering was the only step which did not notably influence any of these measures. This study shows that even some of the seemingly minor procedural deviations can influence the conclusions of an ERP study. We demonstrate the power of multiverse analysis in both identifying the most reliable effects in a given study, and for providing insights into consequences of methodological decisions.},
+	number = {n/a},
+	journal = {Psychophysiology},
+	author = {Šoškić, Anđela and Styles, Suzy J. and Kappenman, Emily S. and Ković, Vanja},
+	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/psyp.14628},
+	keywords = {to read},
+	pages = {e14628},
+}
+
+@article{renton_neurodesk_2024,
+	title = {Neurodesk: an accessible, flexible and portable data analysis environment for reproducible neuroimaging},
+	volume = {21},
+	issn = {1548-7091, 1548-7105},
+	shorttitle = {Neurodesk},
+	url = {https://www.nature.com/articles/s41592-023-02145-x},
+	doi = {10.1038/s41592-023-02145-x},
+	language = {en},
+	number = {5},
+	urldate = {2024-07-23},
+	journal = {Nature Methods},
+	author = {Renton, Angela I. and Dao, Thuy T. and Johnstone, Tom and Civier, Oren and Sullivan, Ryan P. and White, David J. and Lyons, Paris and Slade, Benjamin M. and Abbott, David F. and Amos, Toluwani J. and Bollmann, Saskia and Botting, Andy and Campbell, Megan E. J. and Chang, Jeryn and Close, Thomas G. and Dörig, Monika and Eckstein, Korbinian and Egan, Gary F. and Evas, Stefanie and Flandin, Guillaume and Garner, Kelly G. and Garrido, Marta I. and Ghosh, Satrajit S. and Grignard, Martin and Halchenko, Yaroslav O. and Hannan, Anthony J. and Heinsfeld, Anibal S. and Huber, Laurentius and Hughes, Matthew E. and Kaczmarzyk, Jakub R. and Kasper, Lars and Kuhlmann, Levin and Lou, Kexin and Mantilla-Ramos, Yorguin-Jose and Mattingley, Jason B. and Meier, Michael L. and Morris, Jo and Narayanan, Akshaiy and Pestilli, Franco and Puce, Aina and Ribeiro, Fernanda L. and Rogasch, Nigel C. and Rorden, Chris and Schira, Mark M. and Shaw, Thomas B. and Sowman, Paul F. and Spitz, Gershon and Stewart, Ashley W. and Ye, Xincheng and Zhu, Judy D. and Narayanan, Aswin and Bollmann, Steffen},
+	month = may,
+	year = {2024},
+	pages = {804--808},
+}