Resources for new neuroscientists

Analysis can be tricky at times, especially in neuroscience. Our business is one of maths and stats, and it can all be a bit complex, especially for those new to the field. Below is a short list of resources available to neuroscientists that may be useful when trying to make sense of the data:

1. The Q&A forum. There is a new resource in town for those new to neuroscience and stuck on some technical or analysis problem: https://neurostars.org/. It is a discussion forum where you can post your questions and (hopefully) get answers from the community. It has been open since December 2016, and from what I can tell, most questions posed on the forum has received at least one answer. It is not limited to any particular software library and it has a search function that can help you figure out if anyone has asked your question before. Whilst I have not used it myself (yet), it seems like a good resource.

2. The forum for (mostly) FSL. There is also FSL’s JISCmail site which works on the same principle as neurostars. As the name suggests, this is a discussion forum for FMRIB’s Software Library (FSL), but the topics span everything from the highly technical to basic model design, which means it could be useful for those favouring other software. As a FSL user, I’ve found this site immensely helpful whenever I’ve been stuck, and I can vouch for the quality of the answers on the forum. Records go back to 2001, making this a huge resource where you can be almost guaranteed to find the answer you need. However, make sure that the Q&A is not too old, as analysis tools do evolve.

3. The introduction to analysis. Finally, if you don’t really have a specific question, but rather would like an introduction to MRI analysis, I can thoroughly recommend Jeanette Mumford’s youtube channel, mumfordbrainstats. It’s clear and understandable, and it will make sure you understand what goes on under the bonnet of your analysis. She also created this nifty power calculator for fMRI – fmripower – which can give you a better indicator of power in your next experiment beyond “other people have used X subjects, so we’re going to go with that”. While it is not infallible in that it can only calculate power for a limited number of statistical tests, it is still a very useful starting point.

I’m willing to bet that at least one of the above will be able to help should you find that your analysis suddenly doesn’t work the way you expected it to.

loki_notworking

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