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SP Arun

@sparuniisc.bsky.social

530 followers 220 following 67 posts

Neuroscientist at IISc Bangalore studying visual perception using 🐒🚶🏽‍♀️💻 https://sites.google.com/site/visionlabiisc/

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SP Arun @sparuniisc.bsky.social · Apr 18

In a study now out in @eLife, @GeorginJacob @PramodRT9 and I have some exciting results: a novel computation that helps the brain solve disparate visual tasks, a novel brain region that performs this computation....what's not to like?! Read on.... 1/n
elifesciences.org/articles/93033

Visual homogeneity computations in the brain enable solving property-based visual tasks

Seemingly disparate property-based tasks (oddball search, same-different and symmetry) are solved by computing a novel image property, visual homogeneity, which is localized to the object selective co...

elifesciences.org

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SP Arun @sparuniisc.bsky.social · Jun 14

Come join us for this exciting event next week. You can't possibly have anything better to do next Saturday 🙃

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SP Arun @sparuniisc.bsky.social · Apr 30

Maybe so, if all edges are detected nicely. Computer vision based edge detection doesn't look like this.

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SP Arun @sparuniisc.bsky.social · Apr 18

We are grateful to the (late) Carl Olson, @nancykanwisher.bsky.social and many others for their critical and constructive inputs, to the awesome India Alliance for the blue-sky funding and to CNS & IISc for continuing to be an awesome place to work! And we're done! Thanks for making it this far! n/n

SP Arun @sparuniisc.bsky.social · Apr 18

(started in Aug 2022, got reviewed by several high profile journals, got kicked out each time due to 1 of 3 dissenting reviewers who gave single-paragraph reviews, etc., and finally ended up with eLife where the reviewers still gave us a hard time but we are done) 29/n

SP Arun @sparuniisc.bsky.social · Apr 18

For now we are content with showing a really cool set of results, on which we have worked hard over several years, and shepherded through an unusually long review process 28/n

SP Arun @sparuniisc.bsky.social · Apr 18

We think this computation could predict all kinds of visual behaviours – such as visual search asymmetry, aesthetic appeal, perceived complexity and image memorability. All this needs to be investigated thoroughly before we know what this all means. 27/n

SP Arun @sparuniisc.bsky.social · Apr 18

To sum up, we think we’ve found experimental evidence that there’s a novel computation called visual homogeneity, being performed in a localized region in the brain, which is being used to solve property-based visual tasks. 26/n

SP Arun @sparuniisc.bsky.social · Apr 18

If visual homogeneity is a really universal computation, then it should also work for a symmetry task. Here too, we obtained exactly similar results - the visual homogeneity computation predicted symmetry responses, and the same region showed proportional activations!! 25/n

SP Arun @sparuniisc.bsky.social · Apr 18

This region is just anterior to the lateral occipital complex, where neural dissimilarity between images matched perceived dissimilarity 24/n

SP Arun @sparuniisc.bsky.social · Apr 18

In the brain, we found a localized region whose brain activity is directly proportional to visual homogeneity. 23/n

SP Arun @sparuniisc.bsky.social · Apr 18

So armed with these predictions, we collected and analyzed our data.....and lo and behold! We found that indeed, exactly as we predicted, we can find a center in perceptual space relative to which distance computations do predict oddball present/absent search 22/n

SP Arun @sparuniisc.bsky.social · Apr 18

By contrast, regions that encode task difficulty will not show this pattern, because task difficulty is largest in the middle range of VH and not the extremes 21/n

SP Arun @sparuniisc.bsky.social · Apr 18

In brain activity, if there's a single brain region (region VH) that encodes this quantity, the response in this region should be directly proportional to visual homogeneity. 20/n

SP Arun @sparuniisc.bsky.social · Apr 18

If such a computation was actually being used by the brain, what do we expect? Well, first of all, it should act like a decision variable, which means that any stimulus close to the decision boundary will be hard to decide, and will have long response times. 19/n

SP Arun @sparuniisc.bsky.social · Apr 18

Because this is a very specific computation that involves calculating the distance of each visual stimulus to some hypothetical center in neural space, we called this quantity/computation as "visual homogeneity". 18/n

SP Arun @sparuniisc.bsky.social · Apr 18

The same idea would work for symmetry tasks: because the symmetric object has the same visual features repeated, it will "stand apart" compared to asymmetric or visually heterogeneous arrays. Thus we could "solve" a symmetry task by computing the distance to some center 17/n

SP Arun @sparuniisc.bsky.social · Apr 18

What this means is that visually homogeneous arrays would automatically create a neural response that "stands apart" compared to visually heterogeneous arrays. Thus we could "solve" the oddball search task by simply computing the distance of each image to some center 16/n

SP Arun @sparuniisc.bsky.social · Apr 18

So, when you see an array containing identical items the neural response is equal to the single item response (well, almost, to an approximation). But when you see an array containing an oddball, its representation is somewhere between the neural response to the two items. 15/n

SP Arun @sparuniisc.bsky.social · Apr 18

Well to test it, first of all, we need to explain how we get the response to a multi-item array from the response to a single item. Luckily, we know the answer: the neural response is the average of the single item responses, as shown by us and others 14/n

SP Arun @sparuniisc.bsky.social · Apr 18

Well in science, just having a cool idea isn't enough, you got to show that it works. And as Feynman says, if it doesn't work, it doesn't matter how famous or rich you are, its just wrong. Its a heartbreaking but beautiful aspect of doing science. 13/n
www.youtube.com/watch?v=p2xh...

Feynman: It doesn't matter how beautiful your theory is, it doesn't matter how smart you are..

YouTube video by Nick Stöpler

www.youtube.com

SP Arun @sparuniisc.bsky.social · Apr 18

We thought maybe we use the same underlying computation to solve all these three tasks, despite the fact that our verbal description for them is entirely different! Cool no? 12/n

SP Arun @sparuniisc.bsky.social · Apr 18

In a same-different task, the "same" display is visually homogeneous. In an oddball search task, the "target-absent" array is visually homogeneous. In a symmetry task, the symmetric object is visually homogeneous. 11/n

SP Arun @sparuniisc.bsky.social · Apr 18

We realized that the common property that across all these property-based tasks (same-different, oddball search and symmetry) is that you are trying to discriminate a visually homogeneous image from a visually heterogeneous image 10/n

SP Arun @sparuniisc.bsky.social · Apr 18

Our key insight was based on our earlier work where we showed that symmetric objects become special due to simple computations in neurons, and that perceiving symmetry does not require "symmetry detectors" as many have proposed 9/n

SP Arun @sparuniisc.bsky.social · Apr 18

What's the feature space used by the brain to solve these tasks? What's the decision variable? You cannot solve these tasks by looking for any particular feature in feature space, because an object can have any set of features and be symmetric or asymmetric. 8/n