Ask Slashdot: DIY Computational Neuroscience? 90
An anonymous reader writes "Over the last couple years, I have taught myself the basic concepts behind Computational Neuroscience, mainly from the book by Abbott and Dayan. I am not currently affiliated with any academic Neuroscience program. I would like to take a DIY approach and work on some real world problems of Computational Neuroscience. My questions: (1) What are some interesting computational neuroscience simulation problems that an individual with a workstation class PC can work on? (2) Is it easy for a non-academic to get the required data? (3) I am familiar with (but not used extensively) simulators like Neuron, Genesis etc. Other than these and Matlab, what other software should I get? (4) Where online or offline, can I network with other DIY Computational Neuroscience enthusiasts? My own interest is in simulation of Epileptogenic neural networks, music cognition networks, and perhaps a bit more ambitiously, to create a simulation on which the various Models of Consciousness can be comparatively tested."
Re:Study and practice this in private. (Score:0, Interesting)
I'm hearing something else. It sounds to me like the professional does enjoy his job, he just doesn't like being dicked around by the shitty, half-assed, unnecessary attempts made by amateurs. A core tenet of professionalism is maintaining extremely high standards, which is something we just don't tend to see from non-professionals, regardless of the field. Being angered by bad work is a very good thing to see from professionals, and in fact it shows that they do care deeply about what they do.
Computational neuro is more than simulations (Score:2, Interesting)
The point of running all the simulations is to aid in the understanding of how neural circuits compute; they aren't all that useful outside a theoretical framework. Computational neuroscience heavily uses concepts from dynamical systems, statistical inference, information theory etc. If you want to figure out new ideas about how neural circuits compute or represent information, then some exposure to these topics is essential. On the other hand, if you simply want to play around with and/or tweak models built by others, good programming/debugging skills should suffice. The network simulators are basically tools that allow you test out theoretical models of computing (which inevitably result from framing the question in the mathematical/physical language).
Playing with these models can be a lot of fun, but don't expect to find some fundamental principle if you don't know what you are looking for -- i.e. w/o a theory.
Re:Study and practice this in private. (Score:4, Interesting)
It's very noble to want to learn and to further educate yourself. But for the sake of the professionals in the field, I do encourage you to engage in your study and practice of this field in private.
I have a better idea. Completely ignore the above, terrible advise. While there is considerable value in doing your own work privately for a time, you need to communicate with others, if you want to improve your game. That means not just dumping code or whatever on the internet, but actually reading and listening to who else is already doing this sort of stuff. Keep in mind that most of your communication should be input - learning from others.
Months or years later, a disaster of some sort happens (a security breach, data loss, and so on), and a professional gets dragged in to try to solve the problems. This wastes the professional's time, which is often very expensive. It also angers them, because it's a problem that would have been unavoidable had the amateurs just kept to themselves.
Sounds like the "pro's" time isn't being wasted, if he's getting paid. And if you or anyone actually are "angry" over something this trivial, maybe you ought to find a different line of work.
So unless you're aiming to become a professional in this field, rather than just an amateur or a hobbyist
The only difference between a professional and an amateur/hobbyist is that the professional gets paid and tends to be a bit more knowledgeable. And that's the source of this friction between professional and amateur. The amateur is doing some of the professional's work for far cheaper. It's screwing with the professional's business model Keep that in mind when you read of professionals complaining about the amateurs.
Re:Study and practice this in private. (Score:4, Interesting)
Not affiliated at all with Coursera, but I noticed this free course [coursera.org] the other day. Starts in January.
Getting better access to information (Score:4, Interesting)
I am not familiar with this particular academic community, but generally it is not easy for an academic to get data. The most useful resource is probably the co-operation of those who have gathered the data, and in order to get that you have to find out who they are. The inclination to be helpful varies immensely across disciplines and people within disciplines, but all you lose by trying to make contact is possible embarassment. Step 2 in the list below will give you a tag to use when introducing yourself, which may make you feel less awkward and therefore may improve co-operation.
I suggest 3 steps, in increasing cost, that are likely to help:
Re:Computational neuro is more than simulations (Score:5, Interesting)
+1
That all being said, going out and playing with some of the established tools, and reimplementing some classic models (or building models off of wet lab papers, or whatever) is going to build you up a great skill set, and make it a lot easier to find a lab position if you want to go that directon (either a paid one or a volunteer one, each has advantages).
I'm personally enough of a biologist to feel compelled to point out that a lot of what has been done in larger networks has diverged from biology in critical ways - some of it might be interesting in its own right, but it's not really neuroscience in any meaningful way.
Get a solid grounding in Neuroscience. (Kandell, Jessel and Schwartz, Principles of Neuronal Science, is the standard text, it's excellent, and highly torrented.) Please, please, please take some time to understand the variety and complexity of single neurons - they are way more complicated than many of the people who model systems with high numbers of neurons let on. Having a system with 100 billion simulated neurons means an awful lot less if the neurons themselves are shit.
Re-implement some classic systems from scratch. Yeah, I mean start with Hodgkin and Huxley, and build up from there. You will learn things from doing that yourself that you'll miss by just diving in with established tools. (And a lot of the established tools have issues.) Itzikevitch, Wilson, and Trautenburg are all favorites of mine off the top of my head. Strogatz is great as an introduction to dynamical systems.
Re:Good start, now.... (Score:2, Interesting)
You'll find that the academic system is not as elitist as you would think
This, in a thread that was started by some academic saying, "There is no way to do interesting computational neuroscience unless you quit your job, convince an admissions board you're worthy of their Institution, and spend 5-6 years as a minimum-wage apprentice/grad student." The GGP is basically saying he won't even talk to people unless they've been properly credentialed, and is absolutely being an elitist snob. The OP doesn't seem to want to do publishable original research, but at least to do something new-ish. He asks about access to data and how to communicate with 'the community.'
Unfortunately, 'the community' has terrible social/professional networking tools. Essentially, it all gets done in person at professional conferences, invited seminars, and during the critical grad school/postdoc. To some extent, professional communication only 'counts' if it appears in written form in one of a few credible journals. This is also part of academic elitism: there's no Neuro-Facebook where you have to wade through mountains of naive crap to find the nugget of real science. The OP wants Neuro-facebook, where he can talk about cool projects with other enthusiasts, and believes he'll be able to sort the good from the bad for himself. I think he's right. He may never find 'professional' neuroscientsts there, if it existed, but enthusiasts are definitely capable of doing novel, cool work.