CS and Neuroscience
These days software is used for:
Simulation models are also coming up, which are difficult to pull of, but are gaining traction.
How brain stores information
I tried a developmental rodent lab (Dr. Jamie Olavarria at University of Washington), an fMRI / sign language lab (Dr. David Corina at University of Washington), an EEG / attention lab (Dr. Lourdes Anllo-Vento at UC San Diego), and an MEG lab (Dr. Eric Halgren at UC San Diego). These were all great labs; I learned a lot in each, got great recommendations, and sharpened my research focus along the way.
With that said, there are a number of potential ways to go:
Contribute to open-source projects. There are some good neural network simulators that are open source (for example, Brian, Nengo, and others) that you could contribute to. When you're contributing to a project, people are usually much more open to offering their expertise in return :) Participate in experiments at your local university! I wanted to be a graduate student at UC San Diego; I drove there with nowhere to stay and no way to make money. I wound up participating in 3-4 experiments per week--some to get money, all to get a "lay of the land" as to what kinds of research people were doing. In fact, I got my first research job that way--asking questions about the experiment, expressing interest in the topics! Join a lab as a volunteer (or even as a research assistant). There are all sorts of opportunities for this--as a volunteer if you want to explore something completely new, or as a poorly paid employee if you want to contribute through your programming skills. I learned about brain development, fMRI and sign language, and ADHD / attention this way. Join some of the online research communities! There are a few ways to contribute from the outside (e.g. http://EyeWire.org)
List of Useful Softwares:
MATLAB, Python, open source libraries, SciPy
SPM via Matlab, FSL, FreeSurfer, Afni, BrainVoyager
The open-ephys system is an open-source program to record and analyze electrophysiological data, which permits scientists to understand activity in the brain.
electrophysiology experiment, EEG, fMRI
Capture Millions of data points
data must be run through rigorous large-scale data analysis algorithms to “find the signal.”
2 kinds of data:
MRI, which is the bread and butter of non-invasive brain research on humans
Understand how data is collected, will give better grasp what the numbers mean biologically across different kinds of images.
two kinds of people that do research in neuroscience:
those with burning biological questions(neuropsychotic disorder)
and those that can’t get enough of the data, methods, and tools.
Brain Scanning Technology: