This is the very sort of interaction that leads me to be very, <i>very</i> unoptimistic about ever seeing Moore's Law style runaway advancement in biotechnology.<p>Biology, it seems, is deeply <i>unabstractable</i>. Ie, as one moves up the levels of organization, one rarely (never?) reaches a point where a higher level can be fully modeled without also fully modeling each of the lower levels.<p>This is in sharp contrast to computer engineering, where, for example, one can model a processor with all practical accuracy by treating the individual as idealized boolean logic (As we move towards smaller and smaller transistors, this abstraction is threatening to become "leaky", but this has been true thus far throughout the Moore-ian advancement).<p>I suspect that there may be a limit to the degree of complexity humans can "manage", and thus, without the benefit of effective abstraction, there is a limit on the degree of advancement we can achieve in bending biology to our will.<p>(An example that speaks to this, in my mind, is the fact that our attempts to chemically tweak our own biochemistry (viz. drugs) are hilariously crude (flood the system with a handful of chemicals, which hopefully drives the system as a whole in the general direction we want) compared to the regulation that the body carries out on its own.)
If you are interested in making a very stretched analogy, demonstrating dendritic information processing is like realizing that a CPU's transistor is actually itself a little CPU that is itself capable of quite sophisticated computation. In fact, <i>most</i> of a neuron's computation my be carried out by the dendrites. Don't get tied up in the over-simplified model of dendrite=antenna, soma=computer, axon=wires.<p>Active dendritic information processing has, for several decades, been theorized and modeled. The combination of two-photon microscopy and more "classical" electrophysiology techniques (like patch clamping used in this article) is finally opening the theories to experimentation.<p>[Not to be too critical, but this paper is far from the first to experimentally investigate dendritic information processing. I, personally, am glad some segment of HN is interested in neural computation.]
I like this connection between memristors and nuerons: "<i>From an information processing perspective, this tutorial shows that synapses are locally-passive memristors, and that neurons are made of locally-active memristors.</i>"[1]<p>1. <a href="http://iopscience.iop.org/0957-4484/24/38/383001" rel="nofollow">http://iopscience.iop.org/0957-4484/24/38/383001</a>
Amazing to have some evidence of the processing capabilities dendrites could possess. Though this only makes our understanding of the brain <i>that much</i> slimmer.<p>With billions of neurons and dendrites interacting all the time, if each are compartmentalized we're going to have a difficult time coming up with a model to replicate the effects. Which, as I understand it, is our goal in an effort to better understand how the brain works overall.<p>Still, with this insight it's clear we've got some immensely powerful hardware bouncing around between our ears. What a truly brilliant machine.
Novice question:<p>A given dendrite has a voltage raise, presumable because of transmitter from a neighboring neuron. That voltage increase will always be local unless it is adequate (as it spread and dissipates on its way to the cell body) for an action potential.<p>If they showed an action potential starting at the dendrite, then I would expect it to eventually move to the rest of the cell body and then I wouldn't expect the language about 'not seeing the rest of the cell light up'. So, how did they measure/show actual processing? I'm missing that part.
Reminds me of Roger Penrose's assertion in Shadows of the Mind that the microtubules within the neurons might be doing the work - making each Neuron into a metaphorical computer with millions of transistors. This is a different idea but the same conclusion - Neurons aren't the lowest level of computational structure in the brain, which means we have been underestimating the complexity and power of the brain by many orders of magnitude.
It's very interesting research, but I have to say I'd have a hard time being clinically detached with regards to probing a live mouse and working with it, knowing I was going to kill it when my testing was done.
I hope people in the connectome camp take this to heart. I strongly doubt that modeling the connections of neurons will reveal the way the brain works. The mouse and rat brains are very similar in connectivity, but the behavior of the mouse and rat are quite different. One explanation is that the individual neurons are actually processing information differently, and so differences arise out of neuron functionality rather than connectivity. This research bolsters the argument that meaningful information processing occurs within individual neurons, and even at the sub-cellular level.