It sounds surreal, and yet scientists are writing the Book of All Species. Or to be more precise, they are building a Web site called the Encyclopedia of Life (www.eol.org). On Thursday its authors, an international team of scientists, will introduce the first 30,000 pages, and within a decade, they predict, they will have the other 1.77 million.
Definitely the most impressive thing here is the automated populating of the pages using existing databases. What a fantastic idea. Right now, it’s easy to find information for a fewmodelorganisms that have large scientific followings but this kind of wikipedia of all organisms is long overdue. Here’s a link to the EOL website.
Download MP3It’s hard to judge the merits of this particular interface but I’m sure this is just the first of many such devices that we’re about to see (demo starts 2:00):
This is an Emotiv headset. More than the gaming application, I like the idea of using it for IM emoticons.
Just the optical engineering alone here deserves mention: 28 frames per second at 62nm resolution (well below the diffraction limit of 260nm for light of the wavelength used)! STED (or stimulated emission depletion, developed in Stefan Hell’s group) is ideal for visualizing synaptic vesicles, whose small size (~50nm) has typically confined them to the domain of electron microscopists. The ability to get high-speed STED allowed the researchers to track individual vesicles and their path dynamics. They conclude that vesicle movement has both motor-driven and diffusive components (ie. a biased random walk). I’m sure with more time and more analysis there will be a lot of interesting applications for this kind of real-time vesicle tracking. Perhaps in the near future we will have single vesicle “minis” monitored at multiple sites through microscopy instead of just one or two sites electrophysiologically…
Here’s the resolution difference between STED and confocal for a single vesicle:
CFA: Workshop on Statistical Analysis of Neuronal Data
Abstracts for the Fourth International Workshop on Statistical Analysis of Neuronal Data (SAND4) are due Saturday, March 1. The meeting will take place May 29-31 in Pittsburgh, PA. Contact Lisa Bopp at lbopp (domain pitt.edu) for further information.
Haim Sompolinsky has written an excellent book chapter on the scientific view of free will and choice, pulling in good ideas from physics and neuroscience along with contemporary philosophical commentary.
I think this chapter might be helpful for neuroscientists outside of the lab. Often a dinner table discussion has moved to the idea of “quantum consciousness” or “quantum free will”. Often, someone will mention Roger Penrose, who has become something of a poster boy for this idea that quantum indeterminacy (eg. Heisenberg’s uncertainty principle) is one possible way that free will is really free. And then, people look around and say, “Well, you’re a neuroscientist. Do we have free will?” (And that’s when I take another big drink or bite while I figure out something semi-coherent to say.)
Sompolinsky does a nice job of evaluating such claims (in the end, he says we cannot rule out the possibility that the brain is an indeterministic system but it seems unlikely) and provides nice scientific insight. In his view, it is far more likely that the brain’s apparent randomness (eg. individual cell spike rasters vary across repeated presentations of the same stimulus) is more simply explained by thermal noise (think of varying channel gating properties) and chaotic brain dynamics. (Recall, a chaotic system is still deterministic; it simply exhibits aperiodic behavior due to exquisite sensitivity to initial conditions. It is difficult to predict the long-term behavior of chaotic systems. The more we know the initial conditions in detail, the better our prediction.) On the other hand, he argues that the relevant length and time scales for neurons (micrometers and milliseconds) are far larger by many orders of magnitude than those of quantum noise. Chaos might amplify such quantum events, but this is far from being the simplest, most parsimonious explanation. Given the current level of neuroscience understanding, this is almost idle speculation. Regardless of the (in)determinacy of the world, Sompolinsky effectively argues against any non-physical, purely mental (ie. dualistic) agent of causation.
Thus, in sum, the world and our brains might not be determined but, even given that, there’s no reason to believe we have any causative ability to change things in the sense of traditional free will. These observations seem right on the mark to me. I hope they bring some insight for others. Or at least a way to fend off the dinner-table-free-will-conversation barrage of questions.
Jonathon Keats (no, not that one) has written a scorching review of neuro grad student Jonah Lehrer’s new book, Proust was a Neuroscientist.
I saw this somewhat more favorable review a few weeks in the NYT and was intrigued by the book. As an undergrad, I majored in cognitive science and English and, naturally, was fascinated by the cultural differences of academics in these disparate fields.
As in the Salon article, I also think attempts to unify the “two cultures” (ie. arts and sciences) are misguided. A work like Lehrer’s book (which I have not read) will need to work hard to “prove” its thesis and likely sound very forced. What can we really say about arts vs. sciences? For that matter, is it important to make value judgments on this topic? I’d say, no. We seem to have a natural urge to categorize our activities and then try to order them. Science is more worthwhile. Art is a more creative endeavor. Are these blanket generalizations productive?
But there is overlap between the two cultures and those regions seem more and more important to me. And I think neuroscience in particular has a lot to say here, too. If we know what makes good art good (in a scientific way), will we stop appreciating it or enjoying it? (This is similar to the idea that if someone told you free will was simply an illusion would the illusion be any less powerful than it is right now?) Often, the surprise of creative thought underlies the best science and the best art. Okay, there’s my attempt at a unification!
On a separate note, there certainly seems to be a hunger amongst the reading public for neuroscience books, despite our incomplete picture of how the brain works. For those frustrated with slow progress in research, maybe we should just go write a book.
The relatively recently discovered cannabinoid receptors has me wondering how many other neuroreceptors may be left to discover. One way to estimate the number of these is to screen the genome and look for sequences that look like receptors. This paper says that people have done that for the special case of G protein-coupled receptors (GPCRs), and that the result is that, excluding receptors involved in “chemosensory responses such as taste and olfaction”, there are “367 receptors (1), of which some 200 have been shown to bind known transmitters (3). This leaves about 160 orphan GPCRs that are not activated by any known transmitters and thus are genes with unknown function.”
I didn’t notice this before, but in a study of about 4000 subjects, people who took Rimonabant (marketed as Acomplia), a selective antagonist of the cannabinoid type 1 receptor (CB1), apparently had a 3.2% incidence of depressive disorders where placebo-takers apparently had a 1.6% incidence. Also, irritability went from .6% to 1.9%, parasomnia from .2% to 1.5%, nervousness from .2% to 1.2%, sleep disorders from .4% to 1.0%, memory loss from .9% to 1.6%, hypoesthesia from .6% to 1.6%, and sciatica from .4% to 1.0%. Psychiatric adverse events were dose-dependent.
Determining research trends from Neuroscience abstracts
In this paper at arXiv, Yin et al. report on an analysis of the abstracts from the SfN meetings from 2001 to 2006. It sounds like their analysis uncovered several interesting trends: Two they mention in their abstract are that 60% of authors appear in only one year’s abstracts over the studied period, and that systems neuroscience seems to be on the rise relative to cellular and molecular neuroscience.
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