Most of you have probably already seen this (NS), but I figured I’d pass it on anyways. As usual, the media has gone over the top with the “robots are going to take over the world” theme. I think the basic idea, which does deserve some attention, is that hypothesis generation in the face of complex biology can be overwhelming. I don’t think this kind of inductive AI is that innovative nor is it necessarily the best solution in all cases of hypothesis generation, but the example is interesting.
The best part of this research, though, is the “experimental comparison” to graduate students. You can guess who won. I’m sure those students just love being in that lab now.
Article in Nature. Here’s a more entertaining article that includes a diss by Pat Langley!
Welcome to both old and new Neurodudes!
Bayle and I have decided to try moving Neurodudes to a more open, blog-based format. The idea here is to encourage more contributions from more people. If you’d like to post something, just follow the directions on the left. If you find yourself posting often, we’ll hook you up with you own account.
I hope that we can revive the Neurodudes discussion and make it even more lively in its new home on the web!
Bayesian integration in sensorimotor learning, Konrad Kording & Daniel Wolpert
This recent (Jan 15) Nature article is some really well done computational neuroscience. Shows that humans are actually doing an accurate Bayesian computation in motor skill learning instead of some simple heuristic estimations. I’m curious as to what CNS circuitry must underlie these abilities.
In the pop sci version, the NYT reports “Subconsciously, Athletes May Play Like Statisticians.”
In PLoS, Sidarta Ribeiro, Damien Gervasoni , Ernesto S. Soares, Yi Zhou , Shih-Chieh Lin , Janaina Pantoja , Michael Lavine , Miguel A. L. Nicolelis report that after rats explored novel objects, patterns similar to the neural patterns evoked by those objects repeated in diverse areas of the brain for two days after exposure, especially during slow-wave sleep.
Plants use distributed computation to decide how to open and close their stomata in order to take in as much CO2 as possible while losing the least amount of water.
Subjects actively tried not to think about something that they had learned while being while being reminded of it. This suppression was effective at degrading memory. fMRI scanns showed that active suppression “was associated with increased dorsolateral prefrontal activation, reduced hippocampal activation, and impaired retention of those memories. Both prefrontal cortical and right hippocampal activations predicted the magnitude of forgetting.”