
@article{deepmreye,
	title = {Magnetic resonance-based eye tracking using deep neural networks},
	volume = {24},
	issn = {1097-6256, 1546-1726},
	url = {https://www.nature.com/articles/s41593-021-00947-w},
	doi = {10.1038/s41593-021-00947-w},
	language = {en},
	number = {12},
	urldate = {2022-07-26},
	journal = {Nature Neuroscience},
	author = {Frey, Markus and Nau, Matthias and Doeller, Christian F.},
	month = dec,
	year = {2021},
	pages = {1772--1779},
	file = {Submitted Version:/home/remi/Zotero/storage/I4VSMKCW/Frey et al. - 2021 - Magnetic resonance-based eye tracking using deep n.pdf:application/pdf},
}


@article{alexander_open_2017,
	title = {An open resource for transdiagnostic research in pediatric mental health and learning disorders},
	volume = {4},
	issn = {2052-4463},
	url = {http://www.nature.com/articles/sdata2017181},
	doi = {10.1038/sdata.2017.181},
	language = {en},
	number = {1},
	urldate = {2022-12-16},
	journal = {Scientific Data},
	author = {Alexander, Lindsay M. and Escalera, Jasmine and Ai, Lei and Andreotti, Charissa and Febre, Karina and Mangone, Alexander and Vega-Potler, Natan and Langer, Nicolas and Alexander, Alexis and Kovacs, Meagan and Litke, Shannon and O'Hagan, Bridget and Andersen, Jennifer and Bronstein, Batya and Bui, Anastasia and Bushey, Marijayne and Butler, Henry and Castagna, Victoria and Camacho, Nicolas and Chan, Elisha and Citera, Danielle and Clucas, Jon and Cohen, Samantha and Dufek, Sarah and Eaves, Megan and Fradera, Brian and Gardner, Judith and Grant-Villegas, Natalie and Green, Gabriella and Gregory, Camille and Hart, Emily and Harris, Shana and Horton, Megan and Kahn, Danielle and Kabotyanski, Katherine and Karmel, Bernard and Kelly, Simon P. and Kleinman, Kayla and Koo, Bonhwang and Kramer, Eliza and Lennon, Elizabeth and Lord, Catherine and Mantello, Ginny and Margolis, Amy and Merikangas, Kathleen R. and Milham, Judith and Minniti, Giuseppe and Neuhaus, Rebecca and Levine, Alexandra and Osman, Yael and Parra, Lucas C. and Pugh, Ken R. and Racanello, Amy and Restrepo, Anita and Saltzman, Tian and Septimus, Batya and Tobe, Russell and Waltz, Rachel and Williams, Anna and Yeo, Anna and Castellanos, Francisco X. and Klein, Arno and Paus, Tomas and Leventhal, Bennett L. and Craddock, R. Cameron and Koplewicz, Harold S. and Milham, Michael P.},
	month = dec,
	year = {2017},
	pages = {170181},
	file = {Full Text:/home/remi/Zotero/storage/SMB7U5VH/Alexander et al. - 2017 - An open resource for transdiagnostic research in p.pdf:application/pdf},
}

@article{nau_real-motion_2018,
	title = {Real-motion signals in human early visual cortex},
	volume = {175},
	issn = {10538119},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S1053811918303021},
	doi = {10.1016/j.neuroimage.2018.04.012},
	language = {en},
	urldate = {2022-12-16},
	journal = {NeuroImage},
	author = {Nau, Matthias and Schindler, Andreas and Bartels, Andreas},
	month = jul,
	year = {2018},
	pages = {379--387},
}



@article{polti_rapid_2022,
	title = {Rapid encoding of task regularities in the human hippocampus guides sensorimotor timing},
	volume = {11},
	issn = {2050-084X},
	url = {https://elifesciences.org/articles/79027},
	doi = {10.7554/eLife.79027},
	abstract = {The brain encodes the statistical regularities of the environment in a task-specific yet flexible and generalizable format. Here, we seek to understand this process by bridging two parallel lines of research, one centered on sensorimotor timing, and the other on cognitive mapping in the hippocampal system. By combining functional magnetic resonance imaging (fMRI) with a fast-paced time-to-contact (TTC) estimation task, we found that the hippocampus signaled behavioral feedback received in each trial as well as performance improvements across trials along with reward-processing regions. Critically, it signaled performance improvements independent from the tested intervals, and its activity accounted for the trial-wise regression-to-the-mean biases in TTC estimation. This is in line with the idea that the hippocampus supports the rapid encoding of temporal context even on short time scales in a behavior-dependent manner. Our results emphasize the central role of the hippocampus in statistical learning and position it at the core of a brain-wide network updating sensorimotor representations in real time for flexible behavior.},
	language = {en},
	urldate = {2022-12-16},
	journal = {eLife},
	author = {Polti, Ignacio and Nau, Matthias and Kaplan, Raphael and van Wassenhove, Virginie and Doeller, Christian F},
	month = nov,
	year = {2022},
	pages = {e79027},
	file = {Full Text:/home/remi/Zotero/storage/RNCK2VCY/Polti et al. - 2022 - Rapid encoding of task regularities in the human h.pdf:application/pdf},
}


@article{nau_hexadirectional_2018,
	title = {Hexadirectional coding of visual space in human entorhinal cortex},
	volume = {21},
	issn = {1097-6256, 1546-1726},
	url = {http://www.nature.com/articles/s41593-017-0050-8},
	doi = {10.1038/s41593-017-0050-8},
	language = {en},
	number = {2},
	urldate = {2022-12-16},
	journal = {Nature Neuroscience},
	author = {Nau, Matthias and Navarro Schröder, Tobias and Bellmund, Jacob L. S. and Doeller, Christian F.},
	month = feb,
	year = {2018},
	pages = {188--190},
	file = {Full Text:/home/remi/Zotero/storage/6YLWWVE6/Nau et al. - 2018 - Hexadirectional coding of visual space in human en.pdf:application/pdf},
}

@article{julian_human_2018,
	title = {Human entorhinal cortex represents visual space using a boundary-anchored grid},
	volume = {21},
	issn = {1097-6256, 1546-1726},
	url = {http://www.nature.com/articles/s41593-017-0049-1},
	doi = {10.1038/s41593-017-0049-1},
	language = {en},
	number = {2},
	urldate = {2022-12-16},
	journal = {Nature Neuroscience},
	author = {Julian, Joshua B. and Keinath, Alexandra T. and Frazzetta, Giulia and Epstein, Russell A.},
	month = feb,
	year = {2018},
	pages = {191--194},
	file = {Accepted Version:/home/remi/Zotero/storage/NL6EEHN3/Julian et al. - 2018 - Human entorhinal cortex represents visual space us.pdf:application/pdf},
}

@article{carling_resistant_2000,
	title = {Resistant outlier rules and the non-{Gaussian} case},
	volume = {33},
	issn = {01679473},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S0167947399000572},
	doi = {10.1016/S0167-9473(99)00057-2},
	language = {en},
	number = {3},
	urldate = {2022-12-17},
	journal = {Computational Statistics \& Data Analysis},
	author = {Carling, Kenneth},
	month = may,
	year = {2000},
	pages = {249--258},
	file = {Submitted Version:/home/remi/Zotero/storage/VHQYXF6K/Carling - 2000 - Resistant outlier rules and the non-Gaussian case.pdf:application/pdf},
}
