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This Science editorial by Kai Simons is worthy of quoting in full (for those of you who cannot get behind the paywall):Research papers from all over the world are published in thousands of Science journals every year. The quality of these papers clearly has to be evaluated, not only to determine their accuracy and contribution to fields of research, but also to help make informed decisions about rewarding scientists with funding and appointments to research positions. One measure often used to determine the quality of a paper is the so-called "impact factor" of the journal in which it was published. This citation-based metric is meant to rank scientific journals, but there have been numerous criticisms over the years of its use as a measure of the quality of individual research papers. Still, this misuse persists. Why?  The annual release of newly calculated impact factors has become a big event. Each year, Thomson Reuters extracts the references from more than 9000 journals and calculates the impact factor for each journal by taking the number of citations to articles published by the journal in the previous 2 years and dividing this by the number of articles published by the journal during those same years. The top-ranked journals in biology, for example, have impact factors of 35 to 40 citations per article. Publishers and editors celebrate any increase, whereas a decrease can send them into a huddle to figure out ways to boost their ranking.  This algorithm is not a simple measure of quality, and a major criticism is that the calculation can be manipulated by journals. For example, review articles are more frequently cited than primary research papers, so reviews increase a journal's impact factor. In many journals, the number of reviews has therefore increased dramatically, and in new trendy areas, the number of reviews sometimes approaches that of primary research papers in the field. Many journals now publish commentary-type articles, which are also counted in the numerator. Amazingly, the calculation also includes citations to retracted papers, not to mention articles containing falsified data (not yet retracted) that continue to be cited. The denominator, on the other hand, includes only primary research papers and reviews.  Why does impact factor matter so much to the scientific community, further inflating its importance? Unfortunately, these numbers are increasingly used to assess individual papers, scientists, and institutions. Thus, governments are using bibliometrics based on journal impact factors to rank universities and research institutions. Hiring, faculty-promoting, and grant-awarding committees can use a journal's impact factor as a convenient shortcut to rate a paper without reading it. Such practices compel scientists to submit their papers to journals at the top of the impact factor ladder, circulating progressively through journals further down the rungs when they are rejected. This not only wastes time for editors and those who peer-review the papers, but it is discouraging for scientists, regardless of the stage of their career.  Fortunately, some new practices are being attempted. The Howard Hughes Medical Institute is now innovating their evaluating practices by considering only a subset of publications chosen by a scientist for the review board to evaluate carefully. More institutions should determine quality in this manner. At the same time, some publishers are exploring new practices. For instance, PLoS One, one of the journals published by the Public Library of Science, evaluates papers only for technical accuracy and not subjectively for their potential impact on a field. The European Molecular Biology Organization is also rethinking its publication activities, with the goal of providing a means to publish peer-reviewed scientific data without the demotivating practices that scientists often encounter today.  There are no numerical shortcuts for evaluating research quality. What counts is the quality of a scientist's work wherever it is published. That quality is ultimately judged by scientists, raising the issue of the process by which scientists review each others' research. However, unless publishers, scientists, and institutions make serious efforts to change how the impact of each individual scientist's work is determined, the scientific community will be doomed to live by the numerically driven motto, "survival by your impact factors."
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The Naked Sientists have published my little article on fruit fly and snail learning: Flies are creatures of habit. This is my first popular science article ever and I love that it is with the Naked Scientists, because I listen to their podcast every week! Thanks, Chris, for this great opportunity!
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The most interesting presentation at the Berlin Open Access Days yesterday was the one from Max Planck geochemist Ulrich Pöschl. He was telling us about the success of his open access journal Atmospheric Chemistry and Physics. Weirdly enough, just as I wanted to look one of Pöschl's publications up, it appeared magically on FriendFeed.
He started out by stating some of the problems facing the scientific community in an age of seemingly ever increasing numbers of scientific publications. He felt that the two major problems were the need to somehow filter this information to only get at the "best" science and the problem that many papers are so sloppily written, that it takes another lab much too long until it can reproduce the already published data. The first problem results in what he aptly called the "dilution of information" whereas the second problem leads to waste and misallocation of rsoures. While I would have offered quite different solutions to these problems than he presented (a single scientific database with a combination of social networking, post-publication review spiced up by a reputation system for the filter problem and JoVE for the second problem), I was neverheless rally impressed and intrigued by what he had to say about the interactive peer-review system he hs establshed in his journal. You can find some older slides whch are fairly similar to his presentation here (PDF), but I'll outline his talk so you get the gist.
Obviously, editors and referees have only limited capacity for review and as such more submissions inevitably means slower publication times, i.e. papers get stuck publication traffic. Often, very important, critical reviews in closed review systems never see the light of day (beyond authors and editors, that is), further slowing down progress. Traditional commenting on published articles used to catch some of these critical points, but it has dropped from about 1/20 in 1978 (comments/paper) to only about 1/100 in 1998. The conflict is clear: science needs rapid publication but must not give up on thorough peer review. How can this be acomplished? I've taken the liberty of copying one of his graphs from his presentation to explain the system he has established (click to enlarge):
First, the initially submitted mansucript is handled by an editor who picks the reviewers. The manuscript gets published as a "discussion paper" and both the reviewers and any reader can comment on it, either anonymously or openly. This review period lasts about 8 weeks and can of course be repeated for several iterations until the editor finds all concerns addressed. Once the editor accepts the discussion paper for publication, it gets published in its final form in a different journal, at the moment without the possibility of any further commenting directly on the paper (traditional commenting, of course, is still possible).
This transparent form of interactive review provides a huge incentive foreveryone for a constructive discussion: author don't want to embarrass themselves publicly and thus are very careful in drafting their manuscripts. Reviewers and readers still have influence on the final version of the paper and don't want to risk this influence by using personal attacks or unwarranted criticisms in public. This system works great in preventing many drawbacks of traditional peer-review such as hidden obstruction and plagiarism, and at the same time provides authors with the means of rapidly publishing their research results. All critical comments on the research are kept and public. I agree with Pöschl hat widesprad adoption of this system would also help reduce the flood of papers by deterring careless, useless and false papers.
ACP manages to publish about 400 papers/year with ~70 editors and a total cost of each paper for the authors of about 1000€ (~1400US$). They have about 10.000 comments so far and had only to delete two of them for being inappropriate. This makes about 5 comments per discussion paper where ~3-4 are from authors and reviewers. Pöschl told me afterwards that he thinks the reason why their commenting system works so well is because the potential of having an impact on the form of the final paper is a strong motivating factor in the whole commenting game. I thought this was a very convincing argument. They managed to reach the top impact factor of their field with a rejection rate of only about 10-20%. The total time from initial submission to final paper is 3-6 months with only about 1 month to initial publication as discussion paper. I don't remembr if he showed the final slide of the PDF file I linked above, but I think I would've because all his points are right down my alley  : Promote open access publishing- prescribe open accessto publicly funded research results
- transfer fundsfrom subscription to open access publications:
convert subscription budgets (e.g. 10-30 % per year) into OA publishing funds (e.g., 2000 EUR per year & scientist, plus project-specific funds)
Emphasize quality assurance & interactivity- foster open access publishing & collaborative peer review:
implement discussion forums in new & existing journals
- mere access is not enough(repositories & self-archiving)
Improve scientific evaluation & rating methods- evaluate individual papers not just journal impact factors
- refine statistical parameters for citation, download, and usage;
interactive commenting & rating
IMHO, this is really something the folks at PLoS One should look at to try and see if there's anything they can take home from this system to implement in PLoS One. I thought this all made a lot of sense.
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Yesterday, I particpated in the Open Acces Days here in Berlin. It was a very inspiring conference with over 250 participants, up sharply from around 70 last year (in Konstanz). Before the whole thing started, we printed one of the new JoVE posters and placed it on what we thought was a prominent spot. To our great amusement, as you can see in the second picture below, the exhibitions accompanying the conference were opened right in front of it so that everybody had to see it 
 
At the conference itself, we learned a lot about the open access movement here in Germany starting from how the German copyright laws concern open access, to successful high-quality open access publishing.
The day was concluded with a panel discussion. There were some interesting points raised with regards to publshers, funders and scientist. I was not surprised that none of the panelists really had anything sensible to say to my suggestion to get rid of all journals and just publish in a single database (or at least have a top level entry point for a complete set of fully cross-referenced set of scientific publications). The highlight of the discussion was a comment by the head of our very own library here (in the picture below, it's the third guy from the right who looks exactly like a retired army general), Ulrich Naumann, in which he urged all scientists to unite and declare open war on the Impact Factor! Imagine the cheers and applaud that broke loose 
Unfortunately, by the time I registered for the conference, the workshops were alrady filled up and I couldn't attend any of them today, so I only have yesterday to report about.
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The English language service of Deutsche Welle Spectrum has just broadcast a short report on our study on the first operant learning gene. You can get the whole program at this link, or just the short clip on our research. I'm really excited about this exposure as this is broadcast all over the entire world both in old fashioned radio and online.
See this video for some visuals with the audio:
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I met Columbia neurologist John Krakauer (who has a very interesting brother at the Santa Fe Institute, by the way) at the 2006 SfN meeting in Atlanta after his PLoS Biology paper on how motor learning transfers differently from easy to difficult tasks and vice versa. He's a very smart guy with an interesting background. John has now written a short article for Scientific American entitled: "Why do we like to dance--And move to the beat?". He could be onto something, but I think he's not taking the idea far enough: Many things stimulate our brains' reward centers, among them, coordinated movements. Consider the thrill some get from watching choreographed fight or car chase scenes in action movies. What about the enjoyment spectators get when watching sports or actually riding on a roller coaster or in a fast car?
Scientists aren't sure why we like movement so much, but there's certainly a lot of anecdotal evidence to suggest we get a pretty big kick out of it. When I read this I was a little confused as to what is actually stimulating our reward centers, moving ourselves or watching movements of others, but he clarfiied this later in the article with a reference to mirror neurons (which is not what I'm going to discuss now).
Anyway, not only we get a kick out of moving. Controlling one's own movements in space can be shown to be inherently rewarding in many animals, including insects. For instance, the fruit fly Drosophila prefers to fly in flight directions where there is no artifically added "wobble" of its visual environment. This preference is so strong, that we can use it as reward in a conditioning experiment. Visual patterns (say, upright and inverted Ts) denote different flight directions in a cylindrical environment where the fly has been fixed in the center (see video). Whenever the fly is flying towards, for instance, the upright T, the computer makes the environment oscillate around the flight path such that the fly can still see the target and is able to steer away from it. If it flies towards the other, inverted T, no such oscillations occur. After a few minutes of such training, the flies will show a preference for the inverted T, even if there are no more oscillations. Thus, having full behavioral control over its movements in the environment is a strong reward for the fly, rivalling that of primary rewards such as food and water. The tranmitter involved in processing reward in insects is octopamine. Octopamine is also involved in behavior initiation and control. For example, firing octopaminergic neurons in locusts triggers flight behavior. Interestingly, the neurons triggering flight in locusts are homologous to the neurons thought to be involved in reward in honeybees.
Thus, at least on the surface, there is a tight connection between behavioral initiation and control and reward in insects.
In mammals, the transmitter involved in processing reward is dopamine. John writes in his article: "some reward-related areas in the brain are connected with motor areas". He is talking about the striatum which is involved in action selection as well as operant learning in mammals. The dopaminergic neurons are the ones degenerating in Parkinson's disease. Parkinon's patients show the typical tremors and inabilities to initiate and control movements and also have impairments in operant learning. Music also stimulates the striatum, John writes in the article. Thus, also in mammals, the transmitter system involved in movement initiation and control is the same as (and morphologically related to) the system processing rewards.
Is this all coincidence? Superficial similarities, like human faces in clouds found by human brains looking for patterns? Or is there an underlying evolutionary reason, maybe that one of the first control system early ambulatory animals needed was one for behavioral control? The solution to controlling behavior was to invent a teaching signal which was derived from continuously monitoring the animal's output and compared it with its sensory input. Such a comparison yields a difference signal between stimuli generated externally and stimuli generated by self-mtion. If minimizing externally generated stimulation were rewarding, animals would always strive to control their behavior. Reinforcement learning and optimal control theory provide the theoretical background for such simple systems. Could it be that all other reward systems stem from this initial reward system? Or why is motor control so tightly coupled with reward?
Now, in the postgenomic age, I wonder if one could look at what is known about the genes involved in setting up the reward centers in mammals and insects. Maybe there is a simple master gene (or gene cassette) which organizes the system with dopamine in one variant and with octopamine in one variant. Any bioinformaticians out there who'd like to study this?
UPDATE: John has replied via email and said "I agree with you more than you realize: I am attaching a paper we published in J.Neurosci last year which argues very much for your idea." Here's the reference and link to the paper: The Journal of Neuroscience, July 4, 2007 • 27(27):7105–7116: Why Don’t We Move Faster? Parkinson’s Disease, Movement Vigor, and Implicit Motivation. Pietro Mazzoni, Anna Hristova, and John W. Krakauer.
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 The most well-known molecular mechanism of learning involves coincidence detection. In post-synaptic LTP, the NMDA receptor only opens fully if a postsynaptic depolarization has removed the magnesium block by the time glutamate arrives at the receptor. In pre-synaptic facilitation, adenylyl cycase only generates large amounts of cAMP when stimulated both by transmitter and by coincident Ca2+ influx. Thus, in both cases, you need neural activity (i.e., action potentials or spikes) to coincide onto the synapse in question. Insect learning, specifically clasical olfactory conditioning, has been instrumental in developing this model of "spike timing-dependent plasticity" (STDP). For delay conditioning in which the conditioned stimulus (CS) overlaps with the unconditioned stimulus (US), this is not a problem: the spikes of the CS are still arriving at the convergence point when the spikes from the US start to come in. However, in trace conditioning, when there is a delay between the end of the CS and the onset of th US (of up to 24h in the case of conditioned taste aversion), it is difficult to imagine how the well-known mechanisms of STDP could occur. What happens during the interval between CS offset and US onset for trace conditioning to occur?
To say it right away, we just discussed the new paper in Nature Neuroscience from the lab of Mark Stopfer (NNeuro preview) in our journal club and it doesn't answer this question either. What it does show is that in the paradigm which was so instrumental in develping STDP (classical olfactory learning in insects), STDP appears not to be able to explain trace conditioning either. The authors recorded from projection neurons (projecting from the antennal lobes to the mushroom bodies) and from Kenyon cells (intrinsic mushroom-body neurons) in moths (Manduca sexta). They showed that after odor alone presentations (no conditioning) no more spikes are fired in the Kenyon cells at a time point where they had demonstrated a US presentation to lead to maximum learning behaviorally. This is remarkable, because the Kenyon cells are considered to be the site where the associative memory is stored in this paradigm. The really new aspect of this work was that electrophysiological recordings (albeit not during conditioning) were combined with a behavioral approach analyzing optimal inter-stimulus intervals for classical conditioning. What the authors found was basically a negative result: STDP in the Kenyon cells cannot account for the learning exhibited by the insects. This is reminiscent of trace and delay conditioning in mammals: "In delay eyeblink conditioning, the CS overlaps with the US and only a brainstem-cerebellar circuit is necessary for learning. In trace eyeblink conditioning, the CS ends before the US is delivered and several forebrain structures, including the hippocampus, are required for learning, in addition to a brainstem-cerebellar circuit." (source).
Maybe also in insect trace conditioning, both Kenyon cells and some other structure are required? Maybe this other structure works as a buffer to store the eligibility trace of the CS until the US arrives? Another option could be residual calcium (or some second-messenger) lingering for a few seconds until the US spikes arrive in the Kenyon cells. Only Kenyon cell recordings during conditioning can show the behavior of the Kenyon cells when the US arrives (to fully rule out STDP). I also think a trace conditioning paradigm for Drosophila needs to be developed in order to harness the genetic power also for this type of learning (this would address the calcium or second messenger hypothesis). This paper didn't really answer any questions, but it was so thoroughly done and well-designed that it threw up a lot of interesting ones which will hopefully lead to a completely new line of learning research in insects.
Citation:
Iori Ito, Rose Chik-ying Ong, Baranidharan Raman, Mark Stopfer (2008). Sparse odor representation and olfactory learning Nature Neuroscience, 11 (10), 1177-1184 DOI: 10.1038/nn.2192
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Dave Munger over at Cognitive Daily has a great post on how zoos use operant conditioning for the welfare of their animals. They use operant conditioning on basically all mammals, maybe even most vertebrates there, for everything from teeth brushing to herding of animals in case of an emergency: Conditioning, Jayne told us, was a much safer and effective way to care for the animals than older methods like shooting the animals with tranquilizer darts. Even dangerous animals like grizzly bears can be trained to rear up onto a special apparatus, placing their claws and snouts in designated spots, and exposing their razor-sharp teeth for brushing. "The animals love to be trained," she said. The sea lions used to get so excited in anticipation of a training session that their behavior became unnatural for several hours each day, so trainers had to vary the training schedule in order to avoid this problem.
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Muslim creationist and author of "Atlas of Creation" Harun Yahya (yes, the guy who uses fishing lures to argue his creationism) has been interviewed by the eminent German weekly DER SPIEGEL. The title is the same as the one in this post: "All terrorists are Darwinists". In the interview, Yahya claims that there are 100 million fossils that show that they have been created (in the really short interview he never goes into how all these species had room at the same time or why the are so clearly ordered geological in strata). He gos on to say that Satan has misled legions of scientists and interested laymen for 150 years and that his book will finally open their eyes and convince everyone that Allah has created everything. Asked about whether he was inspired by christian fundamentalists in the US, he derides intelligent design as dishonest: "the people should just come out and say that god did it!". Asked about Dawkin's "God delusion" now appearing in Turkey and apparently quickly becoming a best-seller, he emphasizes that he thinks all evil (Hitler, Stalin, Mussolini and today's islamic terrorists) stems from Darwinism. Asked by the interviewer if he honestly thinks islamic terrorists are closet Darwinists, he says that nobody who prays every day could ever carry out a terroristic act and that all terrorists are only foreign-educated Darwinists who just afterwards use the cloke of Islam (he never says why they would be doing that). Asked how he funds his campaign, he says that he doesn't earn any money from the sales of his book and since it's such a great success, he can afford all the free copies he sends around.
This guy clearly needs new advisors. Interviews like these can only backfire. It's so clear that this dude is a total nutcase, the interviewer didn't even have to go after him, lol
UPDATE: there's now also an English version from the SPIEGEL.
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 The economist has a nice, short article out featuring two science sites: researchblogging.org and Nature Networks. The author finds that Although Web 2.0, with its emphasis on user-generated content, has been derided as a commercial cul-de-sac, it may prove to be a path to speedier scientific advancement. There can be no doubt that the scientific community is starting to use the socal web tool more and more and that it is accelerating science. That media outside of science are noticing this is evidence of these developments. Along with the incorporation of these social tools will come publishing reform, i.e. the move away from pre-publication editor-based assessment towards post-publication peer-based assessment. The article didn't really go into the intricacies of this movement and actually got a few things slightly wrong (or at least ambiguous) about blogs and traditional, peer-reviewed publications. But even still, the developments have gone so far by now, that even outsiders a beginning to take note of a change in how we do science.
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This story has so many connotations on so many levels, I don't even know where to start. Of course, we all know about the history of the fish and the Christians and the bumper sicker wars. In July surfaced the first stories about the connections beween radical Islam and Christian creationists. Now the guy involved in the islamic creationism movement, Harun Yahya (Adnan Oktar) has actually succeeded in getting a court order to block Turkey’s access to the web site of Richard Dawkins. This story (and the thread on RichardDawkins.net) also featured this picture from Yahya's book:
 Apparently, the book uses this picture to make the claim that these caddisflies haven't changed for a few million years, so no animals have ever changed (great logic, isn't it?). If you look closely (as PZ has done already in January), you'll see that it actually depicts a fishing lure! It's a dummy only mimicking a caddis to lure fish to bite. Obviously, the flies made by Graham Owen are good enough to lure not only fish, but also creationists! 
This whole thing is just too good to be true! And yet, despite so many incidents like this, stupidity rules and creationism is still not dead after 150 years of evolutionary theory. There must be something strangely attractive to pseudo- or non-science.
Thursday 18 September 2008 - 04:42:47
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 comments: 0
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I've just converted the old chatbox to a new experiment: microblogging. You can see the result on the right. In order for this to work the way I want, I need to hook the feed up to my Friendfeed feed (many feeds in there, lol). I tried to do this and it sort of worked: the posts appeared but with "no title" displayed, instead of the post body as a message (duh, not that I couldn't have figured that ou before trying!). So I tried to delete the feed again. However, in FF, there is only one URL for both feeds, so I had a 50% chance of deleting the wrong one. Guess which feed got deleted? Of course the one of this blog and not the one from the other feed. So now all my old posts and their comments and likes are probably gone forever. Anybody know how to get them back?
I also need to find out how I can register my MicroBlog posts such that they appear with the posts as messages. Any ideas, tips, hints??
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