The more examples, courses, tutorials, and manuals together link here (http://www.pymvpa.org/docoverview.html).

10. Deep learning 

As mentioned before, with the development of supercomputer and machine learning, more and more data is produced from society.  In the neuroscience research field,  the traditional data analysis approaches face a big challenge and bottleneck when the big data fade into it, so that's why deep learning make very popular in the neuroscience research area that specific for fMRI data analysis, through deep learning model that we can train enough data to dig more medical information or cognitive mechanism. When we back to see the published paper in the recent year,  the research topic related to deep learning already become a hot topic. So what kind of tools that we can use to neuroscience data analysis, in the next section, I will introduce some famous, classical and friendly model or library that we can use in our research.

10.1 Tensorflow - Very popular open source deep learning model framework

Tensorflow is an open source software library for numerical computation using data flow graphs. The graph nodes represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) that flow between them. It provides stable Python API and C APIs as well as without API backwards compatibility guarantee like C++, Go, Java, JavaScript and Swift.
Tensorflow is fully supporting CPU and GPU, it also supports friendly interface with Python, you can through easy install or drive CPU and GPU works \cite{Pattanayak_2017,Gad_2018,Pattanayak_2017a}.