As a non-academic but doing scientific exploration on the side, I'm wondering what analytical toolkits the computational neuroscience community uses for its data analysis.
Which language, which framework?
Are standard algorithms rewritten for each project?
Does each lab have its own implementation of these algorithms?
Please be specific about which analysis packages are used.
I want to know this so that my outside-of-academia doings are as similar to what is really done in the field as possible.
There are a wide variety of statistical packages out there available and even more statistical methods that may or may NOT be appropriate for your data. Many people these days are moving towards using "R". R is a programing language based software that is free/open source, with a wide variety of analysis libraries that can be added for enhanced graphing, molecular analysis, multivariate analysis, bayesian methods, and much much more. There is a bit of a learning curve, but it is well worth it.
It would do yourself great wonders to take a couple of online workshops on introduction to R and proper data analysis. Running software is one thing, but interpreting the results correctly is nearly whole other discipline.
Generally R, python and Matlab seem to be the most popular options these days. All have pros and cons (I use R myself) and many people use more than one of these tools for different purposes.
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