“We literally have a study from a couple of years back showing that you can generate face selectivity in the fusiform face area from other regions, just based on the flows to the face area. So the computation isn't inside. It's probably some, but most of the computation is from other regions.”

Brain Inspired · AI Research & Frontier Labs · November 2026

Context

Near the end, the host asked how a flow-based view differs from how neuroscience has mostly been done. The guest says the usual assumption is that rising activity in a region reflects a process inside it, and gives one of the brain's best-localized functions as his counterexample.

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Transcript

Brain Inspired Around 1:35:43 into the episode

Michael Cole

…brain activity flows and how useful I think that'll be. It would be if we shifted so it's a more generative perspective. It's about adding context to the activity patterns that we're analyzing and the connectivity and combining them to think about how the activity is generated through these flows.

Paul Middlebrooks

And how is that different than the way neuroscience has been done thus far?

Michael Cole

So one kind of unspoken assumption in a lot of cognitive neuroscience has been if you see an activity in a brain region or a neural population go up, say for a given task condition, there's some unknown within region process. Like if it's the fusiform face area, there's face processing going on. But we literally have a study from a few years or a couple years back showing that you can generate face selectivity in the fusiform face area from other regions just based on the flows to the face area. So the computation isn't inside. It's probably some, but most of the computation is from other regions and the selection of the connections and their weights select the features that generate the face selectivity. That's just indicative of like one of the most well-localized functions in the human brain just over two decades of work showing this is actually a distributed process. Right. But it's also a

Paul Middlebrooks

fundamentally different way of looking at it that it's the flow that's doing the processing. The function comes from the flow itself, not from within, not solely from within the area process. Yeah,

Michael Cole

there's some recurrent processing, yeah, but yeah, we didn't even model the recurrent processing and it generated most of the variants on face selectivity. That's cool. And so like there's still a localized function there, but it's it's a distributed process to put it there. And then, you know, the…

Paul Middlebrooks

All right. That's a great place to end it. Congrats again on the book. I enjoyed it. It was my main reading material on those long flights to and from Geneva. So I love reading on planes because you can really sit down and focus, you know, strapping yourself to the mast. Yeah, there's something…

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