nipy/nipype: 1.4.2

Estéban, Oscar; Markiewicz, Christopher J.; Johnson, Hans J.; Ziegler, Erik; Manhães-Savio, Alexandre; Jarecka, Dorota; Burns, Christopher; Ellis, David Gage; Hamalainen, Carlo; Notter, Michael; Yvernault, Benjamin C.; Salo, Taylor; Waskom, Michael; Goncalves, Mathias; Jordan, Kesshi; Wong, Jason H.; Dewey, Blake E; Madison, Cindee; Benderoff, Erin; Clark, Daniel J.; Loney, Fred; Clark, Dav; Keshavan, Anisha; Joseph, Michael; Nielson, Dylan; Dayan, Michael; Modat, Marc; Gramfort, Alexandre; Bougacha, Salma; Pinsard, Basile; Berleant, Shoshana L.; Christian, Horea; Rokem, Ariel; Castello, Matteo Visconti di Oleggio; Halchenko, Yaroslav; Kaczmarzyk, Jakub; Varoquaux, Gaël; Ćirić, Rastko; Moloney, Brendan; DuPré, Elizabeth; Koudoro, Serge; Clark, Michael G.; Cipollini, Ben; Wassermann, Demián; Guillon, Jérémy; Markello, Ross; Hanke, Michael; Buchanan, Colin R; Tungaraza, Rosalia; Gillman, Ashley; Pauli, Wolfgang M.; Hollander, Gilles de; Sikka, Sharad; Forbes, Jessica; Mordom, David; Iqbal, Shariq; Mancini, Matteo; Malone, Ian B.; Dubois, Mathieu; Schwartz, Yannick; Frohlich, Caroline; Tabas, Alejandro; Welch, David; Richie-Halford, Adam; Tilley, Steven; Watanabe, Aimi; Nichols, B. Nolan; Huntenburg, Julia M.; Eshaghi, Arman; Ginsburg, Daniel; Schaefer, Alexander; Bottenhorn, Katherine L.; Cumba, Chad; Acland, Benjamin; Heinsfeld, Anibal Sólon; Kastman, Erik; Kent, James D.; Kleesiek, Jens; Ghayoor, Ali; Erickson, Drew; Giavasis, Steven; Vega, Alejandro de la; Liem, Franz; Küttner, René; Perez-Guevara, Martin Felipe; Lee, John A.; Millman, Jarrod; Lai, Jeff; Zhou, Dale; Haselgrove, Christian; Glen, Daniel; Doll, Anna; Renfro, Mandy; Correa, Carlos; Liu, Siqi; Lampe, Leonie; Kong, Xiangzhen; Hallquist, Michael; Kim, Sin; Kahn, Ari E.; Glatard, Tristan; Triplett, William; Chawla, Kshitij; John, Sabu; Pérez-García, Fernando; Ma, Feilong; Park, Anne; Craddock, R. Cameron; Hinds, Oliver; Poldrack, Russell A.; Perkins, L. Nathan; Stojic, Hrvoje; Chetverikov, Andrey; Inati, Souheil; Grignard, Martin; Snoek, Lukas; Sisk, Lucinda M.; Leinweber, Katrin; Wen, Junhao; Urchs, Sebastian; Blair, Ross; Matsubara, Katsumi; Floren, Andrew; Mattfeld, Aaron; Gerhard, Stephan; Stadler, Jörg; Cooper, Gavin; Haehn, Daniel; Broderick, W. R.; Andberg, Sami Kristian; Noel, Maxime; Cieslak, Matthew; Durnez, Joke; Condamine, Eric; Orfanos, Dimitri Papadopoulos; Geisler, Daniel; Meyers, Benjamin S.; Tambini, Arielle; Weinstein, Alejandro; Orozco, Abel A. González; Harms, Robbert; Khanuja, Ranjeet; Sharp, Paul M.; Stanley, Olivia; Lee, Nat; Crusoe, Michael R.; Brett, Matthew; Falkiewicz, Marcel; Weninger, Leon; Podranski, Kornelius; Linkersdörfer, Janosch; Flandin, Guillaume; Lerma-Usabiaga, Garikoitz; Tarbert, Claire; Cheung, Brian; Van, Andrew; Davison, Andrew; Shachnev, Dmitry Alexeevich; Molina-Romero, Miguel; Rothmei, Simon; Bilgel, Murat; Schlamp, Kai; Ort, Eduard; McNamee, Daniel; Arias, Jaime; Bielievtsov, Dmytro; Steele, Christopher J.; Huang, Lijie; González, Iván; Warner, Joshua; Margulies, Daniel S.; Contier, Oliver; Marina, Ana; Saase, Victor; Nickson, Thomas; Varada, Jan; Schwabacher, Isaac; Pellman, John; Pannetier, Nicolas; McDermottroe, Conor; Mihai, Paul Glad; Gorgolewski, Krzysztof J.; Ghosh, Satrajit

doi:10.5281/zenodo.3668316

Cited by 4 publications

(2 citation statements)

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“…fMRI preprocessing. Preprocessing of the anatomical and functional data was performed using the fmriprep pipeline, version 1.1.2 (Esteban et al, 2019; RRID: SCR_016216), a Nipype-based tool (Esteban, Markiewicz, Johnson, et al, 2020;Gorgolewski et al, 2011;RRID: SCR_002502). Pipeline details can be found at https://fmriprep.org/en/1.1.2/workflows.html.…”

Section: Methodsmentioning

confidence: 99%

Distinct spatial patterns of neural and physiology-related activity in the human periaqueductal grey during anticipatory social stress

Theriault

Fischbach

Kragel

et al. 2022

Preprint

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Periaqueductal gray (PAG) columns mediate affective experience, physiological regulation, and survival-related behavior; yet, only 7T imaging can resolve these small structures in humans. In a social stress task, participants prepared a speech, and we observed (a) bilateral ventrolateral PAG activity, relative to baseline, and (b) distinct spatial patterns of correlation between PAG activity and physiological response (i.e., cardiac interbeat interval, reparation rate, and tonic electrodermal activity).

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Section: Methodsmentioning

confidence: 99%

Distinct spatial patterns of neural and physiology-related activity in the human periaqueductal grey during anticipatory social stress

Theriault

Fischbach

Kragel

et al. 2022

Preprint

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show abstract

“…sh script in the code/ directory). FMRIPrep is a containerized, automated tool based on Nipype 1.4.2 137,138 (RRID:SCR_002502) that adaptively adjusts to idiosyncrasies of the dataset (as captured by the metadata) to apply the best-in-breed preprocessing workflow. Many internal operations of fMRIPrep functional processing (2021) 8:250 | https://doi.org/10.1038/s41597-021-01033-3 www.nature.com/scientificdata www.nature.com/scientificdata/ workflow use Nilearn 0.6.2 139 (RRID:SCR_001362).…”

Section: Mri Preprocessingmentioning

confidence: 99%

The “Narratives” fMRI dataset for evaluating models of naturalistic language comprehension

et al. 2021

Self Cite

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The “Narratives” collection aggregates a variety of functional MRI datasets collected while human subjects listened to naturalistic spoken stories. The current release includes 345 subjects, 891 functional scans, and 27 diverse stories of varying duration totaling ~4.6 hours of unique stimuli (~43,000 words). This data collection is well-suited for naturalistic neuroimaging analysis, and is intended to serve as a benchmark for models of language and narrative comprehension. We provide standardized MRI data accompanied by rich metadata, preprocessed versions of the data ready for immediate use, and the spoken story stimuli with time-stamped phoneme- and word-level transcripts. All code and data are publicly available with full provenance in keeping with current best practices in transparent and reproducible neuroimaging.

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Rapid Rule-Based Reward Reversal and the Lateral Orbitofrontal Cortex

Rolls

Vatansever

et al. 2020

Cerebral Cortex Communications

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Humans and other primates can reverse their choice of stimuli in one trial when the rewards delivered by the stimuli change or reverse. Rapidly changing our behavior when the rewards change is important for many types of behavior, including emotional and social behavior. It is shown in a one-trial rule-based Go-NoGo deterministic visual discrimination reversal task to obtain points, that the human right lateral orbitofrontal cortex and adjoining inferior frontal gyrus is activated on reversal trials, when an expected reward is not obtained, and the non-reward allows the human to switch choices based on a rule. This reward reversal goes beyond model-free reinforcement learning. This functionality of the right lateral orbitofrontal cortex shown here in very rapid, one-trial, rule-based changes in human behavior when a reward is not received is related to the emotional and social changes that follow orbitofrontal cortex damage, and to depression in which this non-reward system is oversensitive and over-connected.

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nipy/nipype: 1.4.2

Cited by 4 publications

References 0 publications

Distinct spatial patterns of neural and physiology-related activity in the human periaqueductal grey during anticipatory social stress

Distinct spatial patterns of neural and physiology-related activity in the human periaqueductal grey during anticipatory social stress

The “Narratives” fMRI dataset for evaluating models of naturalistic language comprehension

Rapid Rule-Based Reward Reversal and the Lateral Orbitofrontal Cortex

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