Found something akin to reward history in macaque playing a gambling task (Fig 2G).
www.biorxiv.org/content/10.1...

2/2 a note: these are full Bayesian models. Hierarchical priors etc. .

Congrats and well deserved!

Nice. I recommend PyTorch or Jax for such problems to compute your gradients. Minimize the log-posterior to add in some priors for ease. It then effectively ends up being a lagrangian problem. Let me know if you want more info—- I love this stuff.

feel free to msg me, too.

another question: are we thinking inverse optimal control (IOC)? how interpretable does the cost function need to be (Network vs hand parameterized)? It’s hard to get around model fitting for this problem. But we can do well on the latter using the Karush-Kuhn-Tucker conditions.

Do you mean something like dynamic mode decomposition with control? Or the, eg, Q and R in LQR?

The data is the data. I just tried to listen what it spoke to me.

So is V4 also premotor cortex?! Title change?

Very BOLD predictions to make.

This recent paper is good.
www.nature.com/articles/s41...

new working title: the prefrontal cortex is just premap cortex.

👏🙌