Review for "A short, robust brain activation control task optimised for pharmacological fMRI studies"

Completed on 21 Mar 2018 by Krzysztof Jacek Gorgolewski .

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Significance

"A short, robust brain activation control task optimised for pharmacological fMRI studies" by Harvey et al. proposes a new standardized task fMRI paradigm optimized for short duration and ease of use. It has a potential for broad adoption in clinical studies.


Comments to author

Comments:

- Line 45: not clear what is the difference between “reliability coefficients for the tasks” and “Voxel-wise reliability metrics”. Maybe more intuitive labels could be used (ROI vs voxel)?

- I really enjoyed the outline of properties of a good pharmacological fMRI task. Maybe it would be good to highlight it in a box or a table. It makes a great guideline for future developments in this area.

- It might be beneficial to accompany the manuscript with video recordings of the visual and auditory stimuli of an example run for the two tasks. Such videos could be a great way to showcase the task to prospective users.

- It is not very clear how the instructions were delivered and if they are standardized. I could not find the instructions in the accompanied code. If this task is supposed to be broadly used in a clinical setting instructions should be explained better or automated.

- The manuscript would benefit from a figure describing the experimental paradigm.

- Why is the buffer time (10s) at the end rather than the beginning? Putting it at the beginning would help with potential non-steady state effects often found in EPI sequences.

- Line 175: missing comma after “31ms”

- Line 182: please specify which template was used

- Line 190: missing citation for ICC (Intraclass Correlations : Uses in Assessing

Rater Reliability Patrick E. Shrout and Joseph L. Fleiss)

- Line 219: referencing figures is usually done with capitalized form (“Figures” vs. “figures”)

- Line 187: It seems that session effects were not modeled explicitly. It might be worth considering a model that removes session mean?

- Figures 1 and 2: I noticed that effects were tested and reported only in one direction (positive). This made me thinking – How would the negative effect look like? It would probably be task-negative network/default mode network. It might be worth looking at “any task vs null” contrast to see if this short protocol can also be used to reliably map that network.

- Figure 3: please consider drawing lines linking corresponding sessions 1 and 2 for each participant. You might also want to reconsider using yellow on white – it has poor contrast. (example: https://www.nature.com/articles/sdata201454/figures/3)

- Big kudos for sharing statistical maps on NeuroVault

- Line 364: It's great that authors share the code, but I don't think figshare is the best place to do it. Uploading the code to GitHub and using zendo for long-term preservation would allow users of this paradigm to submit improvements and bugfixes.

- Source code should specify all of the dependencies with their versions. This could be easily done with "pip list" or "conda list"

- Finally, I strongly encourage the authors to share the raw data from this study. This should be relatively easy on a dedicated platform such as https://OpenNeuro.org