LIPSIA 3.1.1: fMRI analysis tools

Lipsia is a collection of tools for the analysis of functional magnetic resonance imaging (fMRI) data. Its primary focus lies in implementing novel algorithms, including laminar-specific fMRI analysis (cylarim), statistical inference (LISA), and Eigenvector centrality mapping (ECM). Lipsia is designed with a focus on compactness and ease of installation, making it readily accessible for researchers to incorporate these advanced analysis methods into their workflows.

The code is available on GitHub: GitHub. If you like lipsia, please go to the repository and star it!

Star

Installation and first steps:

Installation and Getting started

Layer-specific fMRI analysis:

Cylarim

Statistical inference:

LISA

Semi-blind machine learning:

SML

Task-related edge density (TED):

TED

Network tools:

• ECM

• CCM

• BCM

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Credits

If you use Lipsia in your research, please cite the relevant publications:

Lohmann et al (2023) “Improving the reliability of fMRI-based predictions of intelligence via semi-blind machine learning”, bioRxiv

@article{Lohmann2023,
  title = {Improving the reliability of fMRI-based predictions of intelligence via semi-blind machine learning},
  url = {http://dx.doi.org/10.1101/2023.11.03.565485},
  DOI = {10.1101/2023.11.03.565485},
  publisher = {Cold Spring Harbor Laboratory},
  author = {Lohmann,  Gabriele and Heczko,  Samuel and Mahler,  Lucas and Wang,  Qi and Steiglechner,  Julius and Kumar,  Vinod J. and Roost,  Michelle and Jost,  J\"{u}rgen and Scheffler,  Klaus},
  year = {2023},
  month = nov
}

Lohmann et al (2018) “LISA improves statistical analysis for fMRI”, Nature Comm

@article{Lohmann2018,
  title = {LISA improves statistical analysis for fMRI},
  volume = {9},
  ISSN = {2041-1723},
  url = {http://dx.doi.org/10.1038/s41467-018-06304-z},
  DOI = {10.1038/s41467-018-06304-z},
  number = {1},
  journal = {Nature Communications},
  publisher = {Springer Science and Business Media LLC},
  author = {Lohmann,  Gabriele and Stelzer,  Johannes and Lacosse,  Eric and Kumar,  Vinod J. and Mueller,  Karsten and Kuehn,  Esther and Grodd,  Wolfgang and Scheffler,  Klaus},
  year = {2018},
  month = oct
}

Lohmann, G. et al (2018), Eigenvector centrality mapping for ultrahigh resolution fMRI data of the human brain. bioRxiv

@article{Lohmann2018,
  title = {Eigenvector centrality mapping for ultrahigh resolution fMRI data of the human brain},
  url = {http://dx.doi.org/10.1101/494732},
  DOI = {10.1101/494732},
  publisher = {Cold Spring Harbor Laboratory},
  author = {Lohmann,  Gabriele and Loktyushin,  Alexander and Stelzer,  Johannes and Scheffler,  Klaus},
  year = {2018},
  month = dec
}

Lohmann et al (2012), “Connectivity Concordance Mapping: A New Tool for Model-Free Analysis of fMRI Data of the Human Brain.” Frontiers in Systems Neuroscience. 2012;6:13.

@article{Lohmann2012,
  title = {Connectivity Concordance Mapping: A New Tool for Model-Free Analysis of fMRI Data of the Human Brain},
  volume = {6},
  ISSN = {1662-5137},
  url = {http://dx.doi.org/10.3389/fnsys.2012.00013},
  DOI = {10.3389/fnsys.2012.00013},
  journal = {Frontiers in Systems Neuroscience},
  publisher = {Frontiers Media SA},
  author = {Lohmann,  Gabriele and Ovadia-Caro,  Smadar and Jungeh\"{u}lsing,  Gerhard Jan and Margulies,  Daniel S. and Villringer,  Arno and Turner,  Robert},
  year = {2012}
}

Lohmann, G. et al (2010), Eigenvector centrality mapping for analyzing connectivity patterns in fMRI data of the human brain. PLoS ONE 5(4)

@article{Lohmann2010,
  title = {Eigenvector Centrality Mapping for Analyzing Connectivity Patterns in fMRI Data of the Human Brain},
  volume = {5},
  ISSN = {1932-6203},
  url = {http://dx.doi.org/10.1371/journal.pone.0010232},
  DOI = {10.1371/journal.pone.0010232},
  number = {4},
  journal = {PLoS ONE},
  publisher = {Public Library of Science (PLoS)},
  author = {Lohmann,  Gabriele and Margulies,  Daniel S. and Horstmann,  Annette and Pleger,  Burkhard and Lepsien,  Joeran and Goldhahn,  Dirk and Schloegl,  Haiko and Stumvoll,  Michael and Villringer,  Arno and Turner,  Robert},
  editor = {Sporns,  Olaf},
  year = {2010},
  month = apr,
  pages = {e10232}
}