[clickok]

Hey Will-- congratulations on the publication. It's very cool to see an algorithm reflected in the brain, and the turnaround (from idea to implementation to experiment) in... what, three years? is astonishingly fast.

On a more technical note, I was curious about whether the distribution is being approximated "properly" (in the sense of probabilities summing to one, no negative probabilities) via expectile regression. Does that hold here? I'm less than an expert on neurology so I am unsure if that would be necessary in vivo (since it's clearly not needed for good performance in silico).

[wdabney]

Thanks! It felt like a very long time, but yes for neuroscience it is extremely fast and was only possible because Naoshige Uchida and his lab had already done the rodent experiments around probabilistic reward delivery.

There are a lot of open questions here, so anything I could say about the brain itself would be more of a guess. That said, for our proposed model no negative probabilities are needed, as the distribution is represented by a population of estimators for different predictors of value (in the general sense).

Hope that makes sense and helps clarify.