nickledave

I haven't read anything about this besides the Wiki but I would say the RNA monster's not alive because it only reproduces when a scientist adds the right enzyme to the test tube. It can't actually reproduce itself. Viruses on the other hand contain genes in their rna for proteins (both enzymes and the structural proteins that make up their shells) and so they can reproduce by hijacking some cell's protein synthesis pathways.

Exactly. I should know better and I got caught up in the excitement of "neurons editing their DNA". The Hopkins press release department was either clueless or trying to make this paper sexier than necessary. The Tet3 finding is cool; Wonder if that factor does the same thing in other cells besides neurons, or if really just responds to synaptic activity.

I also noticed the lack of a "double dissociation" study. Fwiw there's a ton of studies right now using optogenetics to transiently "lesion" areas where the authors have not done double dissociation type experiments to determine the specificity of their effects. My guess is the authors were in part critiquing that

This paper doesn't describe "traditional" methods. The author test analyses used today. The first simulation specifically tests whether inactivating "cells" (components in the microprocessor) can let us make causal inferences. They conclude that it can't. Whether that's a fair conclusion is up for debate, but they are definitely critiquing the most cutting edge techniques in the field

You have a point. It would be interesting for you to plot the data, or ask the author to plot the data, with rankings of party members, so we could see whether your hypothesis is true. Hypothesis: Politifact gives more "pants-on-fire" ratings to the leadership of one party than another. If true, then there should be a greater number of e.g. Republicans than Democrats that receive the 'pants-on-fire' rating. Of course, there could be other explanations besides bias even if that result turns out to be true. For example, the Politifact site [1] says that they choose which politicians' statements to validate based on how much press a statement gets. You'd have to somehow show that they're not just giving more high-ranking Repubs 'pants-on-fire' ratings because Repubs are getting more press attention overall for things they say. Gee, I can't think of any Republican candidate that keeps saying things mainly to get free publicity in the press. [1] http://www.politifact.com/truth-o-meter/article/2013/nov/01/...

Thank you for posting this. It is a bit mistaken to say "neuroscientists haven't scrutinized their brains" when people like Harvey Karten (one of the authors on the paper at that link) have dedicated their lives to studying the avian brain. Not only do birds have something that looks analogous to neocortex, they also have a bit of actual cortex, and the rest of their brain (below the cortex) is very similar to ours as well. (Here's a review: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2507884/ )We study mainly mouse brains because that's where the genetics worked first, but hopefully new tools like Crispr will change that. By way of analogy, imagine you were an alien race trying to figure out how computers work: would you rather have infinite Windows boxes, or would you rather have some Windows, some Macs, and maybe a TRS-80 and a Commodore?

edit: punctuation, removed crankiness

jacquesm is right, there's no actual scientific breakthrough here. We already know glutaraldehyde does a good job of preserving synaptic structure, that's why we have used it to fix brains for electron microscopy analysis for roughly a century. I guess it's cool that you can freeze a glut-fixed brain and then unfreeze it and that won't have a dramatic effect on the structure. I'd be interested to know how quantitative their analysis was. Absence of evidence (of deformed synapses) is not evidence of absence. But anyways the synaptic ultrastructure probably isn't everything. It's necessary but not sufficient.

Check out the work of Steve Potter's group at Georgia Tech. They culture rat cortical neurons in a dish while recording and stimulating them in a closed loop system. They did some studies with using these hybrid systems to control robots IRL and controlling avatars in a virtual world. If I remember right, the avatars learn... but I've never read the studies closely

She totally does say they're cortical neurons. But it seems the point of the article is that most of the brain is dormant. I'm not sure that most of the brain is dormant.

It would be interesting if active neurons were suppressing memories but I don't know of any evidence in support of that idea.

Most of the articles cited by the author don't deal with neurons that are directly involved in memory. The articles described the activity of neurons in primary sensory areas: the neurons in cortex that receive direct input from the periphery, or at least are the closest to neurons in the periphery in terms of number of connections between them. One exception is the article she cites about the hippocampus, but this area is required only for forming memories--once the memories have formed, they live somewhere else, but probably not in the primary sensory areas. Okay, maybe memories are a distributed network that includes neurons in primary sensory areas...but it would be weird to also have the main sensory area also be the place where memories live.

What this article leaves out is that sparse coding is most common in neocortex (the wrinkly outside part of your brain). In structures underneath there are a lot of brain cells that fire away all the time: the thalamus, the basal ganglia, the dopamine cells in the midbrain that fire like pacemakers. I've recorded from the cerebellum in deeply anesthetized animals; there is still a lot of spiking going on in there. Presumably the same thing is true for humans. So sparse coding is nifty--and people have made some cool algorithms with it, cf. Cris Rozell's work--but it doesn't mean you're not using your whole brain

Worth reading the follow-up post: http://bradfrost.com/blog/post/living-with-bullshit/ He's not against ads. He's against shitty ads that piss off customers.

Anybody know if there actually are any studies that show that these ads (1) help businesses attract clients and (2) do so without alienating more clients than they attract? Or are they all just for businesses that don't care about keeping customers anyways (e.g. weight loss fads)

Just want to point out that there could be a wide range of ability to recognize faces and it's probably realy hard to find a good measure of that. If someone shows you a picture of your wife (to take an example from one comment) and a picture of eg another woman with the same hair color, skin tone, whatever, would you be able to distinguish them? I'll bet you would unless you suffer from prosopagnosia, the loss of the ability to recognize faces that we know can occur after damage to a certain part of visual cortex. Then try to describe how you can tell the pictures apart. Not as easy. Artists (like the one in the article) spend all day thinking about faces (ok, not all artists, but many of them). They probably feel more confident in their ability to recognize faces and in their ability to describe them--because they discuss faces for portraits, with clients, etc. As a skeptical neuroscientist, I'm thinking you should hold off on diagnosing yourself with this condition until we come up with better evidence for it.

Have you ever mistaken "color TV static" for a king penguin? If not, then your built in DNN does a good job of discriminating between them. There are optical illusions that mess with our visual system, of course. You could I guess do something like raise a brain in one environment with statistics different from the natural world and then ask how that affects discrimination. Is that what you're getting are with "a gradient ascent method"? Because AFAIK we also don't have any proof the brain uses a gradient ascent algorithm so I'm not sure why you'd ask an in silico brain to carry one out

There's definitely selective responses in single unit recordings, even upstream of sensory neurons in "higher" areas; look for articles on the "Jennifer Aniston cell" and on so-called mirror neurons. The question is, how come you can fool a DNN into classifying noise as something with high probability (as they explain in the article), but you can't fool the brain?