Introduction tutorials: Editing process

http://neuroimage.usc.edu/brainstorm/Tutorials

Redactors:

• Francois Tadel: Montreal Neurological Institute

• Elizabeth Bock: Montreal Neurological Institute

Reviewers [current reviewing status]

• Sylvain Baillet: Montreal Neurological Institute [overview 1-14, no proofreading]

• Richard Leahy: University of Southern California [validated 1-19]

• John Mosher: Cleveland Clinic [not started]

• Dimitrios Pantazis: Massachusetts Institute of Technology [validated 1-15]

Expected timeline (2016)

• March: Tutorials #1-#21 (interface and pre-processing)

• April: Tutorials #22-#24 (source estimation and time-frequency)

• May-June: Tutorials #25-#28 (statistics and workflows)

• July-Sept: Cross-validation of the pipeline and the results with MNE, FieldTrip and SPM

• October: Presentation during a satellite meeting at the Biomag 2016 conference

• Nov-Dec: Connectivity tutorial

Tutorial 10: Power spectrum and frequency filters

[CODE]

• Richard, John, Sylvain: Finish the evaluation of the band-pass filters used in Brainstorm
• Francois: Mark with an extended event the time segments that we cannot trust (edge effect)
• Francois: Add warning if recordings are not long enough

[ONLINE DOC]

• Richard, John, Sylvain: Section What filters to apply?

• Richard, John, Sylvain: Section Filters specifications

Tutorial 12: Artifact detection

[ONLINE DOC]

• Beth: Adding examples of the different detection processes. Section Other detection processes

Tutorial 13: Artifact cleaning with SSP

[CODE]

• Francois: Check the length needed to filter the recordings (after finishing #10)
  Section SSP Algorithm

Tutorial 15: Import epochs

[ONLINE DOC]

• Richard, Sylvain, John, Francois: Define recommendations for epoch lengths (after finishing #10)
  Section Epoch length

Tutorial 20: Head modelling

[ONLINE DOC]

• John, Richard, Sylvain: In-depth review of this sensitive tutorial

• John, Richard, Sylvain: Section References

Tutorial 22: Source estimation

[CODE]

• John: Inverse code: sLORETA
• John: Inverse code: NAI
• John: Inverse code: Mixed head models

• John, Richard, Sylvain: How to deal with unconstrained sources ?

  • For the Z-score normalization?

  • For the connectivity analysis? http://neuroimage.usc.edu/forums/showthread.php?2401

  • For the statistics?
  • Projection on a dominant orientation?
• Francois: Remove the warning messages in the interface

• Francois: Call FieldTrip headmodels and beamformers

[ONLINE DOC]

• John, Richard, Sylvain: Section Source estimation options

• John, Richard, Sylvain: Section Advanced options

• John, Richard, Sylvain: Section Equations

• John, Richard, Sylvain: Section References

• John, Richard, Sylvain: Why are dSPM values 2x lower than Z-score ?
• John, Richard, Sylvain: In-depth review of this sensitive tutorial

Tutorial 24: Time-frequency

[CODE]

• Francois: Enable option "Hide edge effects" for Hilbert (after finishing #10)

[ONLINE DOC]

• Francois: Hilbert: Link back to the filters tutorial (after finishing #10)

Tutorial 25: Difference

[ONLINE DOC]

• Validate order of the processes: Difference sources => Zscore => Low-pass filter
  Section: Difference deviant-standard

Tutorial 26: Statistics

[CODE]

• Francois: Implementation of Brainstorm-only permutation tests
• Francois: Keep edge effects map (TFmask) for the stats on time-frequency maps

[ONLINE DOC]

• Francois: Add a section about unconstrained sources (after finishing #27)

Tutorial 27: Workflows

• Update everything after: http://neuroimage.usc.edu/brainstorm/Tutorials/Workflows#Constrained_cortical_sources

• Update: http://neuroimage.usc.edu/brainstorm/Tutorials/WorkflowGuide

• Update number of pages

Tutorial 28: Scripting

• Not evaluated yet
• Update number of pages

Final steps

• Francois: Check that the script tutorial_introduction.m produces the same output as tutorials
• Francois: Check all the links in all the pages

• Francois: Reference on ResearchGate, Academia and Google Scholar
  http://neuroimage.usc.edu/brainstorm/Tutorials/AllIntroduction

[Additional important stuff]

Other analysis scenarios

• Francois: Update all the tutorials (100+ pages)
• Francois: Remove useless images from all tutorials
• Francois: Add number of pages in the tutorials
• Francois: Split list in columns

Connectivity

• Not documented at all
• Richard, Sylvain: Define example dataset and precise results to obtain from them
• Richard: How to assess significance from connectivity matrices
• Francois: Preparation of a tutorial

Parametric experiments

• A = B: Parametric t-test for constrained sources.

  1. Sources: Compute source maps for each trial (constrained, no normalization)

  2. First-level statistic: Compute a t-statistic for the source maps of all the trials A vs B.

     • Process2 "Test > Compute t-statistic": no absolute values, independant, equal variance.

     • With a high number of trials (n>30), t-values follow approximately a N(0,1) distribution.

  3. Low-pass filter your evoked responses (optional). [NO! SHOULD BE DONE BEFORE, BUT WHEN ? => SPLIT ANALYSIS IN TWO: ERP OR FREQUENCY/RS]

  4. Rectify the individual t-statistic (we're giving up the sign across subjects).

  5. Project the individual t-statistic on a template (only when using the individual brains).

  6. Smooth spatially the t-statistic maps.

  7. Second-level statistic: Compute a one-sampled chi-square test based on the t-statistics.

     • Process1: "Test > Parametric test against zero": One-sampled Chi-square test

     • This tests for |A-B|=0 using a Chi-square test: X = sum(|t_i|^2) ~ Chi2(N_subj)

     • Indicates when and where there is a significant effect (but not in which direction).

  8. After identifying the significant effects, you may want to know which condition is stronger:
     Compute and plot power maps at the time points of interest: average(Ai²) - average(Bi²)