Computational neuroscience & neuroinformatics

In summary, the conversation revolved around a person's interest in pursuing a PhD in computational neuroscience and neuroinformatics at a US university. They mentioned their current research in brain functional connectivity and their willingness to switch to more model-oriented research. Some suggested universities and research groups were mentioned, including UCSD, Indiana University, Brandeis, Yale, Columbia, and MIT/MGH. The conversation also touched upon the challenges of finding a suitable program for both the person and their partner. Finally, the topic of fMRI data analysis and its intersection with computational neuroscience was discussed, with some suggestions for potential labs and researchers to look into.
  • #1
kangaroo
7
0
Hi all,
i'm finishing my master studies this year (physics) and I'm planning to go into grad school next year. Does anybody know which US universities have strong programs & research in computational neuroscience and neuroinformatics? my current theme of research is brain funcional connectivity (mostly large data sets analysis using complex network methods), but i wouldn't mind to switch into more model-oriented research (i'm mainly interested in large scale simulations)

I know UCSD is quite strong overall in neuroscience, but i don't want it to be my only option, so maybe you guys have heard of other good places.

thanks!
 
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  • #2
Not sure what you have in mind for neuroinformatics and connectivity, but maybe: http://www.indiana.edu/~neurosci/sporns.html?

For modelling, perhaps Paul Miller at Brandeis, Xiao-Jing Wang at Yale, Larry Abbott, or Ken Miller, both at Columbia.

Henry Markram is building a blue brain, it's perhaps a little ahead of its time.
 
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  • #3
well, now I'm working with a close sporns collaborator. Trying to find out the relationship between functional and anatomical connectivity based on fmri and dti data seems to be a great deal fun to me.

The thing is - and i haven't said that - i need to search other options because I plan to live with my girlfriend who also is starting grad next year, so just in case that she can't get into indiana or can't find something interesting there i need backup plans. Btw, the whole business of both going together into grad school could have a thread for itself...

anyway, thanks for the info, i'll check out those places (i know some of them, the ones which are actually famous, but i don't want all my options to be at elite university or with elite research groups)
 
  • #4
kangaroo said:
well, now I'm working with a close sporns collaborator. Trying to find out the relationship between functional and anatomical connectivity based on fmri and dti data seems to be a great deal fun to me.

Wow, that must be fun! I like his work.
 
  • #5
If you are interested in functional connectivity AKA fMRI data, most computational neuroscience groups aren't working on that... At least not in the United States. The interest in this kind of thing among computational neuroscientists is generally pretty low. Typically when computational neuroscientists have thought about fMRI at all its been either multi-voxel pattern analysis, biophysical models of the BOLD signal or the associated inverse problems. There is a large and impressive group at MGH in Boston working on some of these statistics problems associated with fMRI data analysis... I don't know if these guys would consider themselves "computational neuroscientists" though...

In general, for this kind of work you may also want to join a cognitive neuroscience group. Many of these are very strongly computational (or at least have accommodated people with computational backgrounds in the past). Here's a couple people off the top of my head...

Nancy Kanwisher
Mike Tarr
John Gabrieli
Jody Culham

and many many more. These groups are where the really exciting work in that area is being done in my opinion.

Another group that you might be particularly interested in is Emery Brown's neuroscience statistics laboratory at MIT / MGH. He's a statistician and an anesthesiologist; he's done a lot of very interesting work on the more statistical side of things and collaborates with many other neuroscience groups. He also does fMRI experiments on patients under general anesthesia (which no one else is doing to my knowledge).
 
  • #6
Yeah, i know computational neuroscientists don't involve themselves too much into neuroimaging issues. But I consider a possible change in my research subject for a ph.d, since I'm already into neuroscience and have some analytical and programming skills, computational neurosciences seems to be a rather fair choice.

i'll check out those labs, thanks again!
 

1. What is computational neuroscience?

Computational neuroscience is an interdisciplinary field that combines the principles of neuroscience, mathematics, and computer science to study how the brain processes and generates information. It uses computer simulations, mathematical models, and data analysis techniques to understand the brain's structure and function.

2. How is computational neuroscience different from traditional neuroscience?

Traditional neuroscience focuses on studying the brain at a cellular and molecular level, while computational neuroscience uses computational tools to study the brain at a systems level. It also allows for the integration of data from different levels and scales, providing a more comprehensive understanding of brain function.

3. What is neuroinformatics?

Neuroinformatics is a branch of computational neuroscience that focuses on developing and applying tools and techniques to collect, store, analyze, and share neuroscience data. It involves the use of databases, software, and other technologies to manage and analyze large amounts of data.

4. What are some real-world applications of computational neuroscience and neuroinformatics?

Computational neuroscience and neuroinformatics have many applications, including brain-computer interfaces, understanding and treating neurological disorders, developing artificial intelligence and machine learning algorithms, and improving our understanding of brain development and aging.

5. What skills are required to work in the field of computational neuroscience and neuroinformatics?

To work in this field, one needs a strong background in neuroscience, mathematics, and computer science. Proficiency in programming languages such as Python and Matlab is essential, as well as knowledge of data analysis and modeling techniques. Good communication skills and the ability to work in a multidisciplinary team are also important.

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