Marc Berman

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637 appearances 1 recordings 1 series first heard Jul 2026 last heard 6 Jul

Marc Berman’s voice in public audio — every appearance, attributed to the second.

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Sean Carroll's Mindscape: Science, Society, Philosophy, Culture, Arts, and Ideas · 360 | Marc Berman on the Science of Touching Grass · 6 Jul 2026 podcast

sort of about this, which I actually took in another way.

And I'll explain your figure, then you correct me if I'm wrong.

But the figure that you have, you have in one of your chapters, it's the universe in a cup of coffee, I think is the title of that chapter.

And one thing that's always bothered me a little bit is that

the highest entropy image would be basically white noise, would be the high entropy image.

But as a psychologist, neuroscience, we wouldn't think of that as being a very complex image per se.

It's complex at one level, but it's got,

It's just randomness, right?

Exactly what you mean, yes.

Okay.

So you have a figure in the book where in the beginning, entropy and complexity are very highly correlated, but then at some point they deviate.

Complexity kind of maximizes, and then it starts to decay with increasing entropy, and entropy continues to rise.

So this is a long kind of circuitous route, but I think...

Somehow, I think for an image to be restorative, I think actually it's got to have this kind of right amount of complexity and maybe not too much entropy.

And then I don't know too, there's some relationship here too that I think has to do with ease of processing, which I think later in your chapter you talk about fractalness.

Now, when I think about fractalness, so fractalness is sort of like repeated structure at different kinds of scale.

So natural images tend to have high fractalness because it's built from the same kind of recursive process.

So you can think of a tree.

And the tree structure, if we think of like a maple tree, it's somewhat sort of seen in a maple tree's leaf, the veins of that leaf that also have that same structure.

So we kind of say that looking at the maple tree zoomed in or zoomed out, it's kind of got the same characteristic shape.

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