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38	38	== What can I find here? ==
39	39
40	40	* an IPython notebook that describes how to
41		-** use the TVB processing pipeline on one of the associated supercomputers using PyUnicore
42		-** upload MRI data to the supercomputer
	41	+** use the TVB pipeline on one of the associated supercomputers using PyUnicore
	42	+** upload model data to the supercomputer
43	43	** set up and run the pipeline
44	44	** download processing results
45	45
46		-== What does the TVB processing pipeline do? ==
47		-
48		-After uploading MRI data to the supercomputer, the pipeline runs the three containers
49		-
50		-* [[bids/mrtrix3_connectome>>https://hub.docker.com/r/bids/mrtrix3_connectome||rel=" noopener noreferrer" target="_blank"]]
51		-* [[poldracklab/fmriprep>>https://hub.docker.com/r/poldracklab/fmriprep||rel=" noopener noreferrer" target="_blank"]], and
52		-* [[thevirtualbrain/tvb_converter>>https://hub.docker.com/r/thevirtualbrain/tvb_converter||rel=" noopener noreferrer" target="_blank"]]
53		-
54		-The TVB Processing Pipeline takes multimodal MRI data sets (anatomical, functional and diffusion-weighted MRI) as input and generates SCs, region-average fMRI time series, FCs, brain surfaces, electrode positions, lead field matrices, and atlas parcellations as output. The pipeline performs preprocessing and distortion-correction on MRI data as well as white matter fiber bundle tractography on diffusion data. Outputs are formatted according to two data standards: a TVB-ready data set that can be directly used to simulate brain network models and the same output in BIDS format.
55		-
56	56	== How do I use it? ==
57	57
58	58	* the pipeline is implemented by three Docker containers (mrtrix3_connectome, fmriprep and tvb_converter)