the rise of neuroscience February 5, 2010
Posted by alexholcombe in history, neuroscience, science.1 comment so far
So I knew neuroscience has exploded over the last few decades, but I didn’t know its emergence as a more autonomous discipline is “the biggest structural change in scientific citation patterns over the past decade”. In the authors’ words that follow, they are referring to their figure showing neuroscience emerging as a new citation macro-cluster:
“We also highlight the biggest structural change in scientific citation patterns over the past decade: the transformation of neuroscience from interdisciplinary specialty to a mature and stand-alone discipline, comparable to physics or chemistry, economics or law, molecular biology or medicine. In 2001, 102 neuroscience journals, lead by the Journal of Neuroscience, Neuron, and Nature Neuroscience, are assigned with statistical significance to the field of molecular and cell biology (dark orange, 84 of 102 journals are assigned significantly). Further, Brain, Behavior, and Immunity, Journal of Geriatric Psychiatry and Neurology, Psychophysiology, and 33 other journals appear with statistical insignificance in psychology (green, 6 of 36 journals are assigned significantly) and Neurology, Annals of Neurology, Stroke and 77 other journals appear with statistical significance in neurology (blue, 75 of 80 journals are assigned significantly). In 2003, many of these journals remain in molecular and cell biology, but their assignment to this field is no longer significant (light orange, 5 of 102 journals are assigned significantly). The transformation is underway. In 2005, neuroscience first emerges as an independent discipline (red). The journals from molecular biology split off completely from their former field and have merged with neurology and a subset of psychology into the significantly stand-alone field of neuroscience. (In 2006, shown in Fig. S2, the structure reverts to a pattern similar to 2003.) In their citation behavior, neuroscientists have finally cleaved from their traditional disciplines and united to form what is now the fifth largest field in the sciences (after molecular and cell biology, physics, chemistry, and medicine). Although this interdisciplinary integration has been ongoing since the 1950s [17], only in the last decade has this change come to dominate the citation structure of the field and overwhelm the intellectual ties along traditional departmental lines.”
Rosvall, M., & Bergstrom, C. (2010). Mapping Change in Large Networks PLoS ONE, 5 (1) DOI: 10.1371/journal.pone.0008694
fantastic talk on global energy and the economy January 19, 2010
Posted by alexholcombe in Uncategorized.1 comment so far
Fabulous talk by economist Jeff Rubin on oil supply, oil consumption, and its relation to the global economy. From The Business of Climate Change Conference 2009. Not being my area I can’t comment on his facts but it was delivered with a superbly compelling and accessible style. I learned a lot.
programming for perception job opening [update: position filled] November 25, 2009
Posted by alexholcombe in Python, programming, psychology, science.add a comment
In my lab we’re continuing to program in Python with PsychoPy to create visual experiments, and using R to do data analysis, including to fit psychometric functions.
Unfortunately the one who has been doing most of the real work (as well as having a lot of the best thoughts) is leaving! So, I need a programmer or postdoctoral researcher to help. The role is largely to modify existing code for psychophysical experiments, perform data analysis, and occasionally run experiments. The job would go for a minimum of several months (but probably less than a year) and would be best done on a part-time basis. The psychophysical experiments are written in Python and the data analysis programs are mostly written in R. However, prior knowledge of either is not necessary provided you have significant experience in MATLAB, C, or the like. Experience with psychological, neurological, or perceptual experimentation is a big plus. The projects include investigating the human visual perception of position, audiovisual perceptual interactions, and attentional tracking. If you have experience with psychological experimentation, there is a possibility of developing new experiments in collaboration with us rather than simply working on extensions of in-progress experiments. Most of the work is likely to be working one-on-one with research students to support their programming efforts. See my publications and lab wiki for further info about our research.
If you have a PhD or are an advanced PhD student in visual perception or a related field, there is a further possibility of combining this position with occasional lecturing and teaching coordination employment in our department.
Please contact me (alexh at psych.usyd.edu.au) with your CV. Addendum: Because the job goes for less than a year, if you are not planning on being in Sydney anyway, might be hard to make it work.
UPDATE: This position has been filled
optimizing your coffee consumption September 27, 2009
Posted by alexholcombe in neuroscience, psychology.10 comments
We live in an era where students, shift workers, and scientists increasingly consume drugs that modify brain activity in order to enhance cognition. Ethicists are right to fret about this as the number of addictive substances with some ill effects proliferates (DeJong et al. 2008). People will use these things regardless whether or not some condemn the phenomenon, so it is important that information is out there about how best to use them.
Caffeine is probably the most widely-used drug for enhancing cognition and productivity. However despite its long history, I have not been able to find a good manual or user’s guide! By a manual, I just mean a description of on what kind of schedule it is best used, given caffeine’s tolerance profile, acute effects, withdrawal symptoms, etc. Here I’ll report a few things I found in the scientific literature, in relation to my own experience.
When I first drank coffee, the effects were perhaps too strong to help me much, because I got some ‘jitters’ and had trouble focussing. But as I gained a bit of tolerance to caffeine’s effects, the jitters faded and the arousal effect became milder but more conducive to productivity. This tendency has in fact been reported in the scientific literature, as a rapid tolerance selective to some negative effects even while positive effects can continue (Evans & Griffiths 1992; Schuh & Griffiths 1997). However after many months of judicious usage during which an afternoon coffee was effective in heightening and prolonging my workday productivity, I gradually became a daily user. After approximately a year of this, my tolerance to the arousal effects became great enough that I needed a daily coffee simply to feel normal. It still provided a boost, but only to what a year ago I would have considered baseline. In contrast to this important slow rise in tolerance, the academic literature focuses on the very rapid increase in tolerance during the first several days of caffeine consumption. Usually this is measured by decrease in effect of caffeine on blood pressure elevation. Not very useful for understanding how to best enhance cognition.
My situation, in which caffeine no longer had its productivity-boosting effects, must be a very common problem. To solve it, one might either increase one’s dosage, or try to regain the original effects by going off caffeine for a while. I decided to try the latter.
Arvind says that science indicates one can restore complete sensitivity to caffeine after only 5 days of abstinence (or 10 days of gradual abstinence), however I haven’t been able to find a study that documents this. A blood pressure study estimates that only 20 hours of abstinence (Shi et al. 1993) will restore total sensitivity to caffeine on the blood pressure response. But the subjective withdrawal effects don’t peak until nearly 48 hours of absence! Apparently, for different caffeine effects, different amounts of time are required to restore sensitivity. So what about the positive subjective and arousal effects the average person is most interested in?
I decided to go nearly cold turkey for 7 days, with only one or two decafs in that interval to blunt my withdrawal-effect blues. Fortunately, I had only mild headaches, but did have significant lethargy and loss of mental focus. After seven days, I think I have regained most of my caffeine sensitivity. But I’m only on day one of using again, so not certain how close I am to the sensitivity I had 6 months or a year ago. I hope to share Arvind’s experience of increased productivity for a long period before needing to abstain again to restore sensitivity.
Are there any scientific papers on the topic, or lacking that, further personal reports to certify that this works? I worry about chronic tolerance effects that might not dissipate even after prolonged abstinence, but haven’t seen a shred of relevant science. To bring us closer to having a real user’s manual for both caffeine and other cognitive enhancers, those already using should report the results of their self-experimentation!
DEJONGH, R., BOLT, I., SCHERMER, M., & OLIVIER, B. (2008). Botox for the brain: enhancement of cognition, mood and pro-social behavior and blunting of unwanted memories Neuroscience & Biobehavioral Reviews, 32 (4), 760-776 DOI: 10.1016/j.neubiorev.2007.12.001
Shi J, Benowitz NL, Denaro CP, & Sheiner LB (1993). Pharmacokinetic-pharmacodynamic modeling of caffeine: tolerance to pressor effects. Clinical pharmacology and therapeutics, 53 (1), 6-14 PMID: 8422743
Update: this post provides related info in the same spirit.
moving beyond journal impact factor September 17, 2009
Posted by alexholcombe in Uncategorized.add a comment
Good news from PLoS, they’re posting more metrics indicating the usage and popularity of individual articles.
Vestibulo-neck-ular reflex and stumbling baby August 23, 2009
Posted by alexholcombe in neuroscience, psychology, science.Tags: vestibular physiology
1 comment so far
After several students requested copies, I posted two movies on youtube, one of how visual input to balance can make a baby fall when visual stimulation is perverse. The other shows how the owl’s vestibular system allows its neck to quickly counterrotate to compensate for the body’s movement.
Both videos make people laugh. Both demonstrate aspects of animal proprioceptive systems that allow us to keep our balance and keep our eyes on an object of interest. We humans have a reflex (the vestibulo-ocular reflex) like the owl’s which causes our eyes to compensate for our head and body movement. Probably because the owls can’t move their eyes much, they move their head instead to compensate for body movement (Money & Correia 1972), which you might call a vestibulo-neck-ular reflex. I haven’t been able to determine the origin of this video, but it was apparently created by K.E. Money who did much of the associated physiological work.
Money KE, & Correia MJ (1972). The vestibular system of the owl. Comparative biochemistry and physiology. A, Comparative physiology, 42 (2), 353-8 PMID: 4404369
scientific journal articles: Too much is left out June 1, 2009
Posted by alexholcombe in open access, science, science 2.0.add a comment
The current system of publishing scientific papers hampers scientific advancement in particular ways. I’d like to diagnose the problems so that new publishing efforts (like PLoS ONE) can be shaped to remedy them.
I believe that a major flaw in the modern journal system is that it discourages complete treatments of the literature. A few factors work together to cause this:
- Most prestigious papers nowadays are very short- e.g. high impact, multidisciplinary journals mostly contain very short papers.
- To get their paper in, authors often are better off not mentioning problematic aspects of one’s paper or its relationship to the literature. After all they can always work on them if the reviewers force them to, but why undermine one’s own argument and raise red flags for the reviewers and reader if they don’t have to?
- Even in long papers, most authors avoid direct criticism of papers if the issue is not critical to their thesis.
These problems combine to create a large “back story” of information to every paper to which most readers will be forever oblivious. And there is even more that I won’t discuss now- we all know papers are largely a fairy tale, one more digestible than would be an accurate record of the twists and turns that really happened in the lab.
To factor 2, one might respond that in practically all writing of any kind, the authors have an incentive to sweep their problems under the rug. Perhaps there is little hope of remedying the problem. But the problem is worse than it need be. For one thing, knowledge of the problems with an article is available, but suppressed. During the review process, journals ask experts in the area to evaluate the science of a manuscript in depth. Reviewers make very extensive comments including links to other literature and concerns about the methods. Unfortunately, very few journals actually publish these comments (there are reasons for this, but they could be published more often). The authors incorporate many of the comments into their manuscript revisions but many are left out. Even those concerns that result in the manuscript being modified are usually hard to detect by all but the most expert of readers of the final manuscript.
Besides the reviewers, many readers immediately recognize problems with a new article and unmentioned links to other scientific results. Traditionally publishing these concerns is pretty difficult. Now that some journals allow anyone to post comments on an article, there is no real obstacle. Nevertheless the average scientist does not post comments, probably because he believes he is more likely to be punished for doing so (by the authors responding in kind with criticism) than rewarded (he cannot put the comments on his all-important academic CV). Many people (e.g. Cameron) have thought about how to reform the system to reward these comments, and I’ll set that aside for now.
Regarding point 3 above, in some instances of “selective citation”, the authors have omitted citing a paper because they have a reason not to believe its conclusion. They may have spotted a logical or technical methodological problem, or made an unreported attempt at replication that failed. I have done this many times myself.
Do you agree that these are major problems? How can we address them?
I’ll describe some ideas for partial remedies in subsequent posts.
Isfahan, Iran May 28, 2009
Posted by alexholcombe in history.1 comment so far
Isfahan, Iran has one of the most beautiful plazas in the world. A gorgeous book about that city has been redone and includes a full-page version of this photograph I took of its Friday Mosque. I hope the book, Isfahan: Pearl of Persia gets the readers it deserves. I also highly recommend visiting Iran yourself.
More photos
scientific computing with Python webinar May 22, 2009
Posted by alexholcombe in Python, programming, science.add a comment
https://www1.gotomeeting.com/register/422340144
Fri, May 22, 2009 3:00 PM – 3:30 PM CDT
description: http://blog.enthought.com/?p=116
They will try to record it for later playback.
UPDATE: The recording and announcement of future broadcasts is at the Enthought site
ggplot2 quickly makes beautiful plots in R May 18, 2009
Posted by alexholcombe in programming, science.1 comment so far
Earlier I wrote about the open-source free tools I use to plot and analyze my data—Python and R. One of the most time-consuming and fiddly parts of making graphs for our papers is the need to:
- plot multiple subsets of the data (different experimental conditions), sometimes with double axes
- make a whole array of plots, one for each of the experimental participants’ data
I’ve been doing this in python with scipy by coding an outer loop iterating over the different participants’ data and the inner loop iterating through the experimental conditions. I also write code to label all the conditions and participants, put the horizontal axes only on the bottom-most plots, the vertical axis only on the left-most plots, and sometimes code to offset the different conditions’ data points slightly so they don’t completely occlude each other. This can be a huge pain.
Recently Dani has discovered a much better way. There is a library of R code called ggplot2 that does all these things for you and more to yield really beautiful and clean arrays of plots. Dani has posted an example of the few lines of code needed and the resulting plot. Ideally I would like to do all this in Python without having to use R but the ggplot2 R library is wonderful and I haven’t seen anything remotely like it (yet) for Python.
