One method of computing is to require that all numbers be real values between 0 and 1, and then instead of encoding these numbers into bit streams using binary, represent them with a long stream of random bits which are 1 with probability x, where x is the number being encoded. An advantage is that computations which require many logic gates to implement can implemented more simply (assuming that the randomness in the input bit streams are uncorrelated); eg x*y can be implemented by ANDing the bit streams together, and (x+y)/2 can be implemented by evenly sampling both of the inputs (select about half the bits from x, and the other half of the bits from y, and concatenate all of the selected bits (in any order) to produce the output). Another advantage is that this method is naturally tolerant to noise.
If the circuit is tolerant to noise, power can be saved because circuit elements can be designed to consume less power at the cost of producing noisy results.
A disadvantage is that the numbers of bits needed to represent each number scales exponentially with required precision, as opposed to radix encodings such as binary which scale linearly (eg to represent one of 256 values, you need 8 bits in binary but 256 bits using stochastic computing).
Obviously, this sort of thing is a candidate neural code.
The journal, Frontiers in Neuroscience, edited by Idan Segev, has made it Volume 3, issue 1. Launching last year at the Society for Neuroscience conference, its probably the newest Neuroscience-related journal.
I’m a fan of it because it is an open-access journal featuring a “tiered system” and more. From their website:
The Frontiers Journal Series is not just another journal. It is a new approach to scientific publishing. As service to scientists, it is driven by researchers for researchers but it also serves the interests of the general public. Frontiers disseminates research in a tiered system that begins with original articles submitted to Specialty Journals. It evaluates research truly democratically and objectively based on the reading activity of the scientific communities and the public. And it drives the most outstanding and relevant research up to the next tier journals, the Field Journals.
Cryonics never really delivered. But can we now develop the technology to preserve neural structures? Ken Hayworth thinks we can and advocates a brain preservation technology prize. It’s nice to see such big ideas.
I came across this fantastic review of tools for the Genetic Dissection of Neural Circuits in Neuron a few days ago. It’s by Liqun Luo, Ed Callaway, and Karel Svoboda. I highly recommend it, as it spans the gamut from genetic targeting (recombination, binary logic, viral delivery) to circuit reconstruction (super resolution LM, EM, brainbow) to activity modulation and functional mapping (uncaging, artificial GPCRs, light-gated channels, MIST). I don’t think I’ve ever seen quite a review of so many cutting edge neurotechnologies in one place. I can’t recommend this piece enough really. For me, with my lack of molecular expertise, the first sections on combinatorial gene targeting/expression techniques were great, pulling together Gal4, Cre/Flp, and Tet systems into a unified framework, along with more general concepts like site-directed integration, enhancer-trap, and repressor trap (eg. Thy1 mice).
Over the last week, it seems like everyone has sent me this NYT piece on PKM-zeta (about work in Todd Sacktor’s lab). I’m not sure why this work is being featured in the Times right now, since it’s a few years old. But it was news to me and I think it is of interest to anyone trying to understand structure-function relationships in the brain. In the original Science paper (from 2007), a pseudosubstrate inhibitor of PKM-zeta caused irreversible loss of a conditioned taste aversion memory (news and views here). I was unfamiliar with PKM-zeta, which appears to be a constitutively active form of PKC-zeta (a kinase that some might be more familiar with) and that lacks the autoinhibitory regulatory domain of PKC. The amazing phenomena is that, after treatment with ZIP (the pseudosubstrate that ties up PKM-zeta), the memory is permanently erased and doesn’t seem to return.
What’s going on? One tantalizing possibility is that the enzyme itself is directly related to the memory trace. This contradicts the (unproven) assumption of modern neuroscience that memories are stored solely in the synaptic strengths (ie. membrane-bound receptors) of a neuron. The other suggestion is that PKM-zeta is actively maintaining synapses and that enzymatic inhibition disrupts the precise maintenance of receptors or synaptic machinery. The effects happen quite fast (within 2 hours after drug injection), which seems short for receptor recycling but perhaps long enough for structural change to occur. I’m no expert on receptor movement: Is 2 hours long enough to add/remove a significant number of receptors?
Fascinating work but the method is blunt, wiping all experimentally-induced memories (and probably others too). Last month, another group reported (also in Science) selective erasure of a fear-conditioned memory using an interesting new genetic tool. Here, neurons in the amgydala that overexpressed CREB were found to be preferentially recruited into a fear memory trace (as shown in a previous Science paper). Incorporation into the memory trace was assayed by expression of the immediate-early gene (ie. activity-dependent) Arc. In the present study, they combine overexpression of CREB in a subset of neurons with cell death (via Diphtheria toxin in a transgenic mouse vulnerable to diphtheria). Apparently, normal mice lack the receptor (here a simian version is used) that confers pathogenicity for diphtheria. Thus, the viral construct both overexpresses CREB in a subset of neurons and selectively makes the same subset vulnerable to diphtheria. Ablation of just these neurons causes a permanent loss of the memory. Subsequent similar learning proceeds just fine (using the remaining neurons).
Can we say that the race is officially on to ablate just the synapses involved in the memory? I think so. Extra points if the ablation is reversible too!
The First International Conference on Neuroprosthetic Devices will take place at National Chiao Tung University, Hsinchu, Taiwan on March 19th and 20th, 2009. The mission of this newly founded conference is to foster West-East interaction and collaboration in the rapidly advancing clinical use of neuroprosthetics. The specific aim of the first conference is to expose unique technological and neurological research opportunities in Taiwan. National Chaio Tung University is one of the best universities in Taiwan and is located right next to the world-famous HsinChu Science Park hosting hundreds of biotechnology, semiconductor, and electronics companies.
The conference sessions will cover several key areas in the neuroprosthetic development, such as deep brain stimulation for treatment of Parkinson’s disease and epilepsy, devices for restoring hearing and overcoming muscle paralysis, microelectrode biocompatibility, and novel microelectrode technologies. For detailed conference program and registration information, please visit http://www.bsrc.nctu.edu.tw/ICND/.
Bi-stable neural state switches : Article : Nature Neuroscience
Another channelrhodopsin breakthrough from Deisseroth’s lab. This time light is not required to keep the channel open. Light merely triggers opening and closing behavior. Blue-shifted light opens channels and red-shifted light closes them. This looks like another potentially powerful neurotechnology for interrogating circuits and systems.
NSF’s Emerging Frontiers in Research and Innovation (EFRI) office funded 4 very futuristic neuroengineering grants.
- Deep learning in mammalian cortex
- Studying neural networks in vitro with an innovative patch clamp array
- Determining how the brain controls the hand for robotics
- In vitro power grid simulation using real neurons
Disclaimer: I was involved with the second proposal on this page.
Findings: Tapping Into What a Deer Sees, and Doesn’t
Not being a hunter, I’m not sure how much I support this, but I must admit this is at least a very interesting application of psychophysics data. Using deer as subjects in a standard battery of visual psychophysics tests, researchers have engineered a new material/pattern (“Gore Optifade”) that is superior to standard camo for evading detection by deer. Looks like deer are red-green colorblind but have higher acuity in the blue end of spectrum than humans.
Once they had assessed the deer’s visual strengths and weaknesses, Dr. Neitz and Dr. O’Neill worked out colors, textures and shapes with Guy Cramer of HyperStealth Biotechnology, a company that designs military camouflage. Mr. Cramer’s computer algorithms create fractal patterns that exploit a couple of ancient tricks used by animal predators.
The first and most obvious trick is to fade into the background, as a leopard’s spots enable it to do while it’s patiently waiting to ambush a prey. The spots aren’t shaped like leaves or branches, but they form an overall “micropattern” matching the colors and overall texture of the woodland background.
That trick, though, won’t work for a predator on the move, which is why a tiger doesn’t have spots. It has a “macropattern” of stripes that break up the shape of its body as it’s stalking or running.
There is a nice demonstration image with the article showing the same scene viewed with human vs. deer vision.