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New preprint! Does V4’s tuning to hue on artificial stimuli tell us about its tuning to hue on natural images? Not really. (Twitterified in the thread below) https://www.biorxiv.org/content/10.1101/780478v1 … with @desipoika, @jugoguj, Matthew Smith, and @KordingLabpic.twitter.com/c7Bu8JFHsm
So, a classic way to ask "what does neural activity mean?" in the visual cortex is to vary stimuli in a systematic, parameterized way while recording responses. But do those results tell you what activity 'means' in other contexts, like while viewing natural scenes?
In V1 there’s a rich literature asking this question by estimating tuning from natural scene responses. But what about in higher areas, like V4? We can’t use the same methods, since responses are so nonlinear.
It took a few years to get it right, but we managed to estimate tuning of macaque V4 neurons from natural scenes. We looked at hue tuning, since there's a already big literature about color responses in V4.
We tried reverse-correlation approaches and also a new method: we fit a nonlinear V4 model (based on ImageNet-trained DNNs, Yamins/DiCarlo style) and characterized how tiny perturbations to hue affected the model’s response.
We then compared these tuning curves to hue tuning curves estimated using artificial stimuli. Were they similar? Not really. Stated cleanly: in different visual contexts, the immediate effect of varying hue upon the response was different.
This is obviously about how we understand V4’s activity. But we also think this is a cautionary tale for the vary-stimuli-in-a-parameterized-way approach. When does this approach tell you about a neuron's response on other stimuli & the neuron's general role?
It’s a hard question that we’ve thought carefully about. There’s an empirical and a theoretical side. Our thoughts are in the Discussion, but please, tell us your thoughts!
Ah Matt I couldn't find your handle! Everyone should follow @SmithLabNeuro
Enjoyed the poster version too 
Let's check my understanding: tuning ≠ sensitivity. "Tuning" ought to imply invariance. eg V1 is "tuned to orientation", invariant to frequency, contrast, etc. V4 cells don't pass the invariance test for hue.
A fair Twitter-length summary?
I'd say 'tuning' is used to imply separability: varying other features don't change the way neurons respond to X (e.g. orientation). It's a weaker condition than invariance to Y&Z, which says neurons also don't respond to variations in other things
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