Week 4 Instructor Q&A and NDA Presentation
Channel: ABCD-ReproNim Course
Date: 2020-11-10

https://docs.google.com/document/d/12_hGm86jZBFJXIFGSLQPNuzVdr9EGbqvBqSCJ7P2mgw/edit?usp=sharing

Contents:
0:00 - Introduction/Announcements

10:30 - When would you recommend using the minimally processed versus processed rsfMRI data (assuming you are interested in the same output: within and between network connectivity)? When should a researcher download raw fMRI data and do their own preprocessing rather than download the ABCD’s preprocessed data? 

13:55 - Relatedly, are there any downsides to accidentally running it through a step already completed? Would a processing pipeline detect and skip that step or could it distort the data?

15:55 - The Poldrack group recently criticised the stop-signal task design and its usefulness, can you comment on that? 

17:40 - Are the 3 fMRI tasks going to stay the same throughout all the study? If so, are you worried about practice effects influencing performance and the BOLD response? For example, participants are probably going to recognise the face and place stimuli of the n-back task in future sessions.

20:15 - I have not preregistered a study before, what is the minimum and/or typical amount of detail that people preregister?

30:50 - During the lecture about neuroimaging measures, the large effect of motion was discussed. It showed for example an effect of race on motion. First, how does that influence the representability of the sample and generalizability of the results? Second, where can I find the details of these effects? Finally, should we correct for these effects? If so, how?

33:50 - When creating a preregistration, is there turnaround time that will delay when you can actually run analyses, and what is that timeline like?

35:38 - What is your opinion on controversial preprocessing steps such as global signal regression (which seems to be associated with both noise and biological signal)? There are also some people arguing that high frequencies that are typically eliminated by low-pass filters have signals of interest for functional connectivity, what is your take on that? 

38:40 - For fMRI, were there any additional confounds added besides the ones for motion and distortion correction, and if there was any respiratory correction?

42:10 - I understand the importance of running power analyses before running your analysis but I’m not sure how I would do it with the ABCD study. Specifically, my understanding is that power analyses should be run on Pilot data. Has the ABDC study released pilot data for this purpose?

48:30 - What do you think about the idea of replacing our focus to effect sizes rather than p values as a countermeasure to p-hacking and other malpractices? It seems to me that you can hack effect sizes just as easily as p values. 

53:40 - With regard to templates, i am not sure how registration is done in grwoing kids…is the skull used as part of the registration process and how would this change as they get older? is there going to be an age-related ABCD brain template like the MNI standard template for adults?

55:45 - In the slide on Big Data is Hard, it is mentioned that due to nested covariance structure using permutation testing becomes less reliable. What are alternate suggestions, and if we do need to proceed with permutation testing what factors should be paramount?

58:40 - NDA Presentation