Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: May 29, 2026

Neurovascular Network Explorer 2.0: A Simple Tool for Exploring and Sharing a Database of Optogenetically-evoked Vasomotion in Mouse Cortex In Vivo
08:32

Neurovascular Network Explorer 2.0: A Simple Tool for Exploring and Sharing a Database of Optogenetically-evoked Vasomotion in Mouse Cortex In Vivo

Published on: May 4, 2018

Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in python.

Krzysztof Gorgolewski1, Christopher D Burns, Cindee Madison

  • 1Neuroinformatics and Computational Neuroscience Doctoral Training Centre, School of Informatics, University of Edinburgh Edinburgh, UK.

Frontiers in Neuroinformatics
|September 8, 2011
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Brain states recur across diverse narrative contexts during longitudinal viewing.

bioRxiv : the preprint server for biology·2026
Same author

ABCD-ReproNim: An educational program for responsible and reproducible analyses of ABCD data.

Developmental cognitive neuroscience·2026
Same author

A layered standards framework for integrating single-cell and spatial omics data into brain cell atlases.

bioRxiv : the preprint server for biology·2026
Same author

Pregistered movie-fMRI analyses reveal altered visual feature encoding in autism in pSTS.

bioRxiv : the preprint server for biology·2026
Same author

Eye-Tracking-BIDS: the Brain Imaging Data Structure extended to gaze position and pupil data.

bioRxiv : the preprint server for biology·2026
Same author

Context modulates brain state dynamics and behavioral responses during narrative comprehension.

Imaging neuroscience (Cambridge, Mass.)·2026
Same journal

Predicting vasovagal syncope during head-up tilt test: three machine learning approaches.

Frontiers in neuroinformatics·2026
Same journal

Decoding basal ganglia motor circuit dysfunction from handwriting: a physics-informed neural signal interpretation framework for Parkinson's disease screening.

Frontiers in neuroinformatics·2026
Same journal

FUSION-AD: interpretable AI framework for risk assessment and subgroup discovery in Alzheimer's disease.

Frontiers in neuroinformatics·2026
Same journal

A 3D-printed phantom to validate subject orientation in 3D imaging and recordings.

Frontiers in neuroinformatics·2026
Same journal

IntegriLAB: a blockchain-enabled electronic lab notebook for reproducible neuroimaging research.

Frontiers in neuroinformatics·2026
Same journal

Long-range correlations in alpha-band of electroencephalogram: a nonlinear embedding and detrended fluctuation analysis.

Frontiers in neuroinformatics·2026
See all related articles

Nipype (Neuroimaging in Python: Pipelines and Interfaces) offers a unified framework for neuroimaging analysis, improving reproducibility and efficiency by integrating diverse software packages through standardized interfaces and workflows.

Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Scientific Software Development

Background:

  • Neuroimaging analysis relies on diverse software packages with varying assumptions, hindering reproducibility and efficient data processing.
  • Challenges include non-uniform access to software, lack of comparative algorithm frameworks, and difficulties in training and methodological continuity.
  • Current methods sections in publications often lack the detail required for replicating neuroimaging results.

Purpose of the Study:

  • To introduce Nipype (Neuroimaging in Python: Pipelines and Interfaces) as an open-source solution to address limitations in current neuroimaging software.
  • To provide a framework for uniform access, comparative algorithm development, and enhanced reproducibility in neuroimaging research.
  • To streamline the use of multiple neuroimaging tools and facilitate efficient data analysis.
Keywords:
Pythondata processingneuroimagingpipelinereproducible researchworkflow

Related Experiment Videos

Last Updated: May 29, 2026

Neurovascular Network Explorer 2.0: A Simple Tool for Exploring and Sharing a Database of Optogenetically-evoked Vasomotion in Mouse Cortex In Vivo
08:32

Neurovascular Network Explorer 2.0: A Simple Tool for Exploring and Sharing a Database of Optogenetically-evoked Vasomotion in Mouse Cortex In Vivo

Published on: May 4, 2018

Main Methods:

  • Nipype provides standardized Interfaces to existing neuroimaging software, enabling uniform usage semantics.
  • It facilitates the creation of Workflows for seamless interaction between different software packages.
  • The library supports local and cluster execution, optimizing computational efficiency without requiring additional scripting.

Main Results:

  • Nipype enables interactive exploration and comparative development of neuroimaging algorithms.
  • It significantly reduces the learning curve associated with using multiple, disparate software packages.
  • The software promotes efficient execution on multi-core machines and clusters.

Conclusions:

  • Nipype enhances the replicability, efficiency, and accessibility of neuroimaging data analysis.
  • Its open-source and community-driven development fosters rapid adaptation to the evolving needs of the neuroimaging community.
  • Nipype is a valuable tool for advancing reproducible research in neuroscience.