Artificial Intelligence

Developing Intelligence

Category archives for Artificial Intelligence

Stimulating the brain with high frequency electrical noise can supersede the beneficial effects observed from transcranial direct current stimulation, either anodal or cathodal (as well as those observed from sham stimulation), in perceptual learning, as newly reported by Fertonani, Pirully & Miniussi in the Journal of Neuroscience. The authors suggest that transcranial random noise stimulation…

Machines Learn How Brains Change

In last week’s Science, Dosenbach et al describe a set of sophisticated machine learning techniques they’ve used to predict age from the way that hemodynamics correlate both within and across various functional networks in the brain. As described over at the BungeLab Blog, and at Neuroskeptic, the classification is amazingly accurate, generalizes easily to two…

Two seemingly contradictory trends characterize brain development during childhood and adolescence: Diffuse to focal: a shift from relatively diffuse recruitment of neural regions to more focal and specific patterns of activity, whether in terms of the number of regions recruited, or the magnitude or spatial extent of that recruitment Local to distributed: a shift in…

“What we’re seeking is not just one algorithm or one cool new trick – we’re seeking a platform technology. In other words, we’re not seeking the entirety of a collection of point solutions, what we’re seeking is a platform technology on which we can build a wide variety of solutions.” Dharmendra Modha, manager of cognitive…

Recent work has leveraged increasingly sophisticated computational models of neural processing as a way of predicting the BOLD response on a trial-by-trial basis. The core idea behind much of this work is that reinforcement learning is a good model for the way the brain learns about its environment; the specific idea is that expectations are…

How can we enhance perception, learning, memory, and cognitive control? Any answer to this question will require a better understanding of the way they are best enhanced: through cognitive change in early development. But we can’t stop there. We also want to know more about the neural substrates that enable and reflect these cognitive transformations…

What if we got the organization of prefrontal cortex all wrong – maybe even backwards? That seems to be a conclusion one might draw from a 2010 Neuroimage paper by Yoshida, Funakoshi, & Ishii. But that would be the wrong conclusion: thanks to an ingenious mistake, Yoshida et al have apparently managed to “reverse” the…

Hierarchical views of prefrontal organization posit that some information processing principle, and not just task difficulty, determines which areas of prefrontal cortex will be recruited in a given task. Virtually all information processing accounts of the prefrontal hierarchy are agreed on this point, though they differ in whether the operative principle is thought to be…

I’ve been busy writing up a new paper, and expect the reviews back on another soon, so … sorry for the lack of posts. But this should be of interest: The Dana Foundation has just posted an interview with Terrence Sejnowki about his recent Science paper, “Foundations for a New Science of Learning” (with coauthors…

Most computational models of working memory do not explicitly specify the role of the parietal cortex, despite an increasing number of observations that the parietal cortex is particularly important for working memory. A new paper in PNAS by Edin et al remedies this state of affairs by developing a spiking neural network model that accounts…