Unsupervised Thinking
a podcast about neuroscience, artificial intelligence and science more broadly

Wednesday, May 24, 2017

Episode 21: Understanding fMRI

To much of the world, the face of neuroscience is an image of a brain with small colored blobs on it. Those images come from functional magnetic resonance imaging (fMRI), a technology that's made a big splash in its relatively short tenure. For this episode, we delve into fMRI and what scientists do with the data it produces. To start, we review the technology behind MRI and fMRI. We get into the thorny issue of relating the BOLD signal recorded from fMRI with actual neural activity, and what's been learned from animal studies that have looked at both simultaneously. After that we talk stats: particularly the trouble with traditional "voxel"-wise comparison methods and putting all your eggs in one basket (or in separate, but similar, baskets?). Approaches to fMRI analysis are quickly evolving however, and so we discuss multi-voxel pattern analysis, comparing across individual brains, real time-analysis, mind reading, and lie detecting. Finally, we turn a little more philosophical and ask "What does it mean to measure information in the brain?". Is what an experimenter can see in these colored patterns even relevant to the brain itself?? We give examples of when it's not.

We read:
Interpreting the BOLD Signal
Computational Approaches to fMRI Analysis
Is Neuroimaging Measuring Information in the Brain?

And mentioned:
Our episode on Neural Oscillations (wherein we try to understand what the local field potential/"LFP" is)
A mind-reading-style paper on movie reconstruction by Jack Gallant
Stefano Fusi's paper on decoding information that the animal doesn't use

To listen to (or download) this episode, (right) click here

As always, our jazzy theme music "Quirky Dog" is courtesy of Kevin MacLeod (incompetech.com) 

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