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PyHRF: A Python Library for the Analysis of fMRI Data Based on Local Estimation of Hemodynamic Response Function

PyHRF: A Python Library for the Analysis of fMRI Data Based on Local Estimation of Hemodynamic Response Function

Jaime Arias Almeida

December 07, 2017
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  1. A Python Library for the Analysis
    of fMRI Data Based on Local
    Estimation of Hemodynamic
    Response Function
    J. Arias, P. Ciuciu, M. Dojat, F. Forbes, A. Frau-Pascual,
    T. Perret, J. M. Warnking

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  2. 1.
    Introduction
    “Begin at the beginning”, the King said, very gravely,
    “and go on till you come to the end; then stop.”
    -- Lewis Carroll, Alice in Wonderland
    2

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  3. × The current fMRI methods (e.g., SPM) estimates
    the neural activity using a canonical HRF for the
    whole brain.
    × There are local variations of the HRF in brain
    regions of patients with anomalies (e.g., Stenosis).
    Conjecture: Local variations of the HRF in patients
    with anomalies cause a wrong estimation of the neural
    activity.
    3
    Motivation

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  4. × Separate estimation of the response function
    (HRF)
    × A Bayesian framework allows to account for prior
    knowledge
    × A parcellation is used to deal with the HRF
    estimation regionally.
    JDE is solved with Variational Expectation
    Maximization (VEM).
    4
    Joint Detection-Estimation
    (JDE)

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  5. “Never send a human to do a machine’s job”
    -- Agent Smith, The Matrix
    5
    2.
    PyHRF

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  6. 6
    PyHRF
    × Open source software
    × Pythonic
    × Robust scientific libraries
    × e.g., scipy, numpy, scikit-learn, nilearn, nipype ...
    × Implementation of several models
    × MCMC-BOLD, JDE-BOLD, JDE-ASL …
    × Parallel computation
    × Documentation, Notebooks, Docker image
    http://www.pyhrf.org https://github.com/pyhrf

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  7. 7
    PyHRF

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  8. 8
    PyHRF
    http://www.neurovault.org/images/307
    Posterior Probability Map (PPM)
    Z-Scores
    Right Hand
    Gorgolewski, K. J., Storkey, A., Bastin, M. E., Whittle, I. R., Wardlaw, J. M., & Pernet, C. R. (2013). A test-retest fMRI dataset for
    motor, language and spatial attention functions. GigaScience, 2(1), 6. https://doi.org/10.1186/2047-217X-2-6

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  9. × Improvement of the PyHRF API for further
    developments
    × Bring PyHRF to clinicians (GUI, CLI).
    × Pythonic framework from acquisition to
    visualization
    × Interaction SPM PyHRF
    Show the variations of the HRF response in brain
    regions of patients with anomalies (e.g., Stenosis).
    9
    Semavi Project

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  10. Semavi Project
    Stimuli &
    Acquisition
    Pre-
    processing
    Analysis
    10
    PyHRF

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  11. 11
    Semavi Project

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  12. Semavi Project
    12
    I
    f

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  13. Alice: “How long is forever?”
    White Rabbit: “Sometimes, just one second.
    -- Lewis Carroll, Alice in Wonderland
    13
    3.
    Concluding
    Remarks
    15 minutes

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  14. × PyHRF allows to estimate the HRF locally
    × Open source software
    × Multiplatform (Conda, Docker)
    × Extensible framework for the fMRI workflow
    Now we have a powerful tool for non-experts that
    will allow to test our hypothesis and new ideas.
    14
    Summary

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  15. × Continue to improve PyHRF
    × Internships
    × Use of PyHRF for the analysis of small animals
    × rats
    × Calibration of some parameters of the model to be
    able to compare our results with SPM
    × ROC analysis
    Show the variations of the HRF response in brain
    regions of patients with anomalies (e.g., Stenosis).
    15
    Future Work

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  16. Thanks!
    Any questions?

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