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Matlab toolbox to deconvolve BOLD-fMRI data. It produces the underlying spatiotemporal neural and hemodynamic activity

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BrainDynamicsUSYD/BrainPalimpsest

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BrainPalimpsest

What else than a natural and mighty palimpsest is the human brain? -- Thomas De Quincey

This toolbox provides a deconvolution method for BOLD-fMRI data to simultaneously yield
spatiotemporal images of underlying:

  • neural activity,
  • neuroglial drive,
  • cerebral blood flow (CBF),
  • cerebral blood volume (CBV),
  • deoxygenated hemoglobin (dHb) concentration, and
  • response modes W (wave), L (local-oscillating), and D (local-decaying).

Before using the toolbox

Some important aspects you need to do before using the toolbox:

  1. Install Freesurfer from https://surfer.nmr.mgh.harvard.edu/. In case this is not possible, decompress Freesurfer_functions.zip and add the path of the folder to your Matlab directory. The folder contains m files required in the analysis of two-dimensional data.

  2. Build a mex file from inplaceprod.c . This step requires to have a C Matlab-compatible compiler installed.

Citation

If you use our code in your research, please cite us as follows:

J.C. Pang, K.M. Aquino, P.A. Robinson, T.C. Lacy, M.M. Schira, Biophysically based method to deconvolve spatiotemporal neurovascular signals from fMRI data, Journal of Neuroscience Methods, 308, 6-20, 2018.

Other references related to this work

J.C. Pang, P.A. Robinson, K.M. Aquino, N. Vasan, Effects of astrocytic dynamics on spatiotemporal hemodynamics: Modeling and enhanced data analysis, NeuroImage 147, 114-153, 2017.

T.C. Lacy, K.M. Aquino, P.A. Robinson, M.M. Schira, Shock-like haemodynamic responses induced in the primary visual cortex by moving visual stimuli, Journal of the Royal Society Interface, 13(125), 20160576, 2016.

J.C. Pang, P.A. Robinson, K.M. Aquino, Response-mode decomposition of spatio-temporal haemodynamics, Journal of the Royal Society Interface 13(118), 20160253, 2016.

K.M. Aquino, P.A. Robinson, M.M. Schira, M.J. Breakspear, Deconvolution of neural dynamics from fMRI data using a spatiotemporal hemodynamic response function, NeuroImage, 94, 203-215, 2014.

K.M. Aquino, P.A. Robinson, P.M. Drysdale, Spatiotemporal hemodynamic response functions derived from physiology, Journal of Theoretical Biology, 347(1), 118-136, 2014.

K.M. Aquino, M.M. Schira, P.A. Robinson, P.M. Drysdale, M.J. Breakspear, Hemodynamic traveling waves in human visual cortex, PLoS Computational Biology, 8(3), e1002435, 2012.

P.M. Drysdale, J.P. Huber, P.A. Robinson, K.M. Aquino, Spatiotemporal BOLD dynamics from a poroelastic hemodynamic model, Journal of Theoretical Biology, 265(4), 524-534, 2010.

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Matlab toolbox to deconvolve BOLD-fMRI data. It produces the underlying spatiotemporal neural and hemodynamic activity

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