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So in what order does this happen?
1. 120 fps: orientation;
2. 60 fps: motion;
3. 30 fps: color.

The rest of the research can be done on one's own:
http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1000555

Seriously, did you RTFA where the researcher himself described the algorithm as being based on PageRank

“We first experimented with our own ideas on network algorithms until we realized that what we needed existed already with the PageRank algorithm, so why reinvent the wheel?” Winter recalled.
“Our PageRank-based algorithm singles out proteins in the cancer cells that seem to either promote or suppress disease progression,” Winter said.

How about the abstract of the research paper in question, which specifically mentions Google Page Rank
http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002511

Are you sure it's the journalist who's the retard here?

From the actual scientific article:
In long-term potentiation (LTP), a cellular and molecular model for memory, post-synaptic calcium ion (Ca2+) flux activates the hexagonal Ca2+-calmodulin dependent kinase II (CaMKII), a dodacameric holoenzyme containing 2 hexagonal sets of 6 kinase domains. Each kinase domain can either phosphorylate substrate proteins, or not (i.e. encoding one bit). Thus each set of extended CaMKII kinases can potentially encode synaptic Ca2+ information via phosphorylation as ordered arrays of binary "bits"...
...this suggests sets of six CaMKII kinase domains phosphorylate hexagonal MT lattice neighborhoods collectively, e.g. conveying synaptic information as ordered arrays of six "bits", and thus "bytes", with 64 to 5,281 possible bit states per CaMKII-MT byte...

http://medicalxpress.com/news/2012-03-memories-encoded-brains.html

Q&A with the researcher. Bit more detail than GizMag.

http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002421

The paper (gizmag links to it too)

It's actually in the description: http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000579

Ok, just skimmed the paper. First impressions: it's a good idea. The problem I see is that, after finding a great model, they have absolutely no clue as to why that one works. That is, a functional theory isn't improved by this kind of work; though it is indeed promising and the theory can be improved if someone can understand what the heck that model is doing.

The analogies with computer software were obvious back in the early sixties when the genetic code was first figured out. It turns out they are mostly just vague metaphors, and aren't terribly useful in accounting for any of the details of how biology actually works. Computer science is useful in sorting out how the biology works, and there are thousands of computer scientists working in molecular biology. Statistical models like Hidden Markov Models, Baysean Networks, and Support Vector Machines are where most of the work is being done. Check out PLOS Computational Biology, one of several journals that are devoted to the intersection of computer science to and biology.

As a grad student, for financial reasons I'd given up on the idea of publishing in open-access journals until I get my Ph.D., and hopefully a position at a university that would pay the publication fees. I'm a strong believer in the open-access models, but the fact that traditional subscription journals don't charge authors is a real point in their favor. (NB: I'm also a fiction author, and in the fiction world, you should never ever ever pay a publisher to publish your work. EVER. But academic publishing has always worked by different rules.) However, maybe I wasn't reading the fine print carefully enough; PLoS Comp. Bio. has this to say:

Authors are asked to pay $1500 upon acceptance of their article, to help defray the costs of publication (see the FAQs on publication fees). However, if you have insufficient funds to cover this payment, we allow payment of whatever amount you can afford or waive the charge entirely if necessary. Inability to pay never influences the decision of whether to publish a paper.

That's a good start. Ideally, I'd like to see a formal multi-level pricing structure: some nominal fee for grad students, with progressively higher fees for faculty at various levels, and corporate authors. But it does assuage some of my fears about the open-access publishing model in general.