neurodudes

Researchers at the University of Nevada, Reno have an interesting and ambitious set-up for doing research in AI that the describe in a recent paper.

From the paper:

We define virtual neurorobotics as follows: a computer-facilitated behavioral loop wherein a human interacts with a projected robot that meets five criteria: (1) the robot is sufficiently embodied for the human to tentatively accept the robot as a social partner, (2) the loop operates in real time, with no pre-specified parcellation into receptive and responsive time windows, (3) the cognitive control is a neuromorphic brain emulation incorporating realistic neuronal dynamics whose time constants reflect synaptic activation and learning, membrane and circuitry properties, and (4) the neuromorphic architecture is expandable to progressively larger scale and complexity to track brain development, (5) the neuromorphic architecture can potentially provide circuitry underlying intrinsic motivation and intentionality, which physiologically is best described as “emotional” rather than rule-based drive.

What’s interesting to me about this is the combination of a embodied robot in a virtual world with a neurally inspired controller for that robot. While there are pros and cons of embodiment in virtual world (some of which have been touched on here before), I think that if your priority is closing the loop from embodiment to research on neural systems, the importance of this kind of approach cannot be ignored.

Neurons come in many shapes and sizes. Frequently, the shape of a neuron is characteristic to its type. Several theoretical papers have demonstrated that the shape of a neuron can crucially determine its pattern of activity, independently of other factors (Mainen & Sejnowski, 1996, for example). Several resources on the web such as neuromorpho.org and the Cell Centered Database are dedicated to maintaining repositories of different neuronal shapes (also known as morphologies).

Any computer scientist worth their salt, noticing this trend, is tempted to say: if neuronal shape is so important, maybe we ought to have good data standards to describe it. That’s just what a paper last year did. It surveyed the popular data standards for modeling, primarily in the NEURON and Genesis simulation packages. The result is a data standard called MorphML, which is part of a larger effort called NeuroML.

Neuronal shape is a weird data type for the computer science world, but I think an incredibly important and fundamental one for deeply coping with the complexity of real brain tissue. It seems to me that many areas of neuroscience research could benefit from the construction of more explicit models of the circuits they study.

A friend recently alerted me to The Journal of Visualized Experiments, a revolutionary way to present science by showing the actual experimental procedures. Poking around the site I already picked up tips for my own research just by watching others perform procedures that I do myself in the lab (eg. use Sparkle glass cleaner not just for objectives but also for sample coverglass, how to properly interpret the OD ratio on the spectrophotometer for RNA purity, etc.)

Click more to see some of my favorite videos on the site.

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This new technique from Cori Bargmann’s lab is one of the neatest that I’ve seen in a while. The authors split GFP into two pieces, expressing one piece presynaptically and the other postsynaptically. This creates functional (ie. fluorescing) GFP only at sites of synaptic contact where the protein can reconstitute. They call the technique GFP Reconstitution Across Synaptic Partners (GRASP). Check out an example labeling here:

The neurons are expressing mCherry in the cytoplasm but GFP is expressed only at the site of synaptic contacts where the split GFP peptides can be reconstituted into a complete GFP fluorophore.

The Encyclopedia of Life, No Bookshelf Required – New York Times

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 few model organisms that have large scientific followings but this kind of wikipedia of all organisms is long overdue. Here’s a link to the EOL website.

We’ve certainly come a long way. (And I never knew about Music Portal behind that thing.)

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.

Anyone know if the consumer version will require gel for the scalp electrodes? Hmmm… if gamers are the target audience, I think I have a good idea for a cross-promotional opportunity here.

Video-Rate Far-Field Optical Nanoscopy Dissects Synaptic Vesicle Movement

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:

And, for those of you with ~$1.25M lying around, you can now purchase a STED setup directly from Leica!

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.

http://sand.stat.cmu.edu