So far so good. It appears that basically there is little discussion about whether neurons compute things. However, a new conversation between me and @mnxmnkmnd came up as I realized that for him it appears to be close to irrelevant whether you call a neuron a computer or not and you don’t learn more from emulating the computational function of a neuron than from simulating the thing the same way you would from simulating fluid dynamics or a pendulum.
So, here is my new attempt to explain, why I think it is important and meaningful to think of neurons as computing agents rather than simply physical phenomena.
This weekend I happily completed a manuscript describing my recent postdoctoral work. We took the opportunity to try a further step into what hopefully will be the future of publishing. So, next to submitting the manuscript to a well-known, peer-reviewed neuroscience journal, I made a version for bioRxiv. This is a preprint server that is supposed to be a biology version of the aRxiv which is a well-known resource for papers and other material on physics, math and related topics. The bioRxiv is run by the institution I work at, Cold Spring Harbor Laboratory. The idea is to put out your work before it is being peer-reviewed by a journal and instead allow anybody to comment on it. The submission process is simple and it doesn’t cost a dime. It just takes a (short) while for someone to double check that the content you uploaded is actual science. My paper was released not even 24h after I submitted it.
Of course you need to be careful when deciding to put your work out there. If, for example, you are in a highly competitive field and only the peer-reviewed publications in certain journals are accepted by your peers as ‘proper publication’, you might not necessarily want to release your work this way. But I don’t consider my work to be that critical. 😉
Further, if you want to submit the same version of your manuscript to a journal, you might want to first check whether the journal allows it. On their website, bioRxiv links to some resources on this topic. Again, the specific journal I submitted the manuscript to is fine with it.
So, please read and comment on it if you so very much please. I am curious what effect this – for biologists new – way of handling scientific output will have on each of us!
Just recently the last article from my PhD thesis was published by Frontiers in Integrative Neurophysiology! I want to explain to you over the next few posts what my thesis was all about – several posts because I don’t like long posts :P. So, today I start with this brief introduction:
My collaborators and I want to know how small animals can see things during fast flight. Well, it is actually not only about just seeing things. Small animals, especially fast moving ones must be able to quickly realize where all the things around them are and which of those they might collide with if they don’t maneuver around them in time. Imagine you are a little zebra finch, just 12 grams body weight, and you are sitting at the water pond home in Australia minding your own business, taking a sip, washing the dust off your feathers or hopping around looking for grains to eat. And then all of the sudden a warning call! One of your peers has seen a bird of prey approaching! What follows is total chaos – well at least from the perspective of an outsider – everybody, maybe hundreds of fellow zebra finches, rush from the water pond into the bushes and tree tops near by. Flying buddies everywhere, leafs, twigs, branches and you have to be quick! And this is not a made up story, just watch this video!
The question is
Why do zebra finches not crash into each other and into branches?
Maybe it is because of the change in fields and scientific environment, but I increasingly doubt data presented in talks, posters and articles. Mostly because I find myself wondering whether the choice of statistical description of the data makes any sense. I am not speaking of advanced statistics at all, just the simplest descriptive techniques and the choice of the right plot for it.
My doubts are usually raised when I see a bar plot as sketched in figure 1. What looks like a rather okay representation of data actually does not really give you an intuitive idea of how the data are distributed. Continue reading Barplot Madness→
I am planning a blog post on what the Ultimate Goal of Neuroscience is. I would like to make a survey first, to hear from all you neuroscientists out there, what you think, is the big goal of neuroscience. I will present the results in this blog and write a commentary on it.
The question is: “Given unlimited ressources (infinite time – yes immortatlity, people, money, technology, everything), what would be the ultimate goal or ultimate application that would crown your neuroscientific work?”
Please write your brief(!) answer in the comments below, or twitter (don’t forget to adress me: @DennisEckmeier)! Please be creative! ‘Duh, everything.’ does not count! And spread the word!