Adam Gopnik on the NeuroX wars in the New Yorker, here. Money quote:
Philosophy may someday dissolve into psychology and psychology into neurology, but since the lesson of neuro is that thoughts change brains as much as brains thoughts, the reduction may not reduce much that matters.
Point counter point on whether neuroscience is good for something. Gary Marcus in The New Yorker, here. The New York Times’ David Brooks here.
Marcus rightly points out that critiquing functional MRI brain scan data analysis is not the same thing as rejecting all of neuroscience–most of neuroscience (the parts not seen so much in the mass media) is knowledge obtained from a huge variety of robust and elegant methods, ranging from optogenetics to electrophysiology.
But it’s a good debate–perhaps it’ll prevent neuroscience from being oversold.
Requarth and Crist’s excellent critique of Jonah Lehrer’s new book Imagine, here. Make sure you read the comment’s for Jonah’s thoughtful reponses.
Over at the Science Progress blog, Justin Masterman takes a stab at explaining the current controversies regarding interpretation of the BOLD signal.
Read the comments also–they’re spot on.
As many of you know, I worry deeply that functional MRI has been oversold. While recent papers have suggested that functional neuronal activity may occur without a concomitant BOLD signal, another critique suggests that the statistical techniques for analyzing fMRI themselves may be suspect:
Money quote from the neuroskeptic blog:
Just in case you need reminding of the story so far: A couple of months ago, MIT grad student Ed Vul and co-authors released a pre-publication manuscript, then titled Voodoo Correlations in Social Neuroscience. This paper reviewed the findings of a number of fMRI studies which reported linear correlations between regional brain activity and some kind of measure of personality. Vul et. al. argued that many (but by no means all) of these correlations were in fact erroneous, with the reported correlations being much higher than the true ones. Vul et. al. alleged that the problem arose due to a flaw in the statistical analysis used, the “non-independence error”. For my non-technical explanation of the issue, see my previous post, or go read the original paper (it really doesn’t require much knowledge of statistics).
Hat Tip to Marginal Revolution