[x] Average speed across days (important for habituation days). Maybe split when the different epochs appear.
[x] Average rewarded trials
[x] Speed in rewarding sites + reward availability. Is there a different between the available reward and the slowing that the animals do? Do they understand that reward is becoming depleted and so they are less unsure about stopping?
[x] Average stopping times vs reward available (important for days of learning when to leave).
[x] Average suboptimal stopping after reward depleted
Single session
[x] Average speed traces for each of the available reward conditions (maybe use percentage to it's independent on the total amount)
[ ] Lick histograms around opening odor valve site + other epochs.
[ ] Stopping histograms around opening odor valve site + other epochs.
[ ] Average speed traces during IPI and ISI (this one split between rewarded and non-rewarded patches). Think about a way to normalizing them because they have different lengths.
[ ] Average speed traces on odor valve offset (split per patches). I think you can anticipate the animal's decisions to leave a patch before they encounter the next site.
[ ] Average stopping times vs reward available vs patch number. Understand dynamics within session, do they shift their preferences depending on how tired they are? Is stopping more costly in the beginning so they want to ensure reward whereas it isn't by the end of the session? Do they learn the environment statistics during the session and so they do better with more encounters?
Future scripts for ongoing analysis of 2nd batch
Prepare a standard scripts that runs core behavior so every session has a summary available. It should depend on the stage (maybe one for habituation and another for training, depending on the final reassessment of the training protocol)
[x] are there difference in behavior for unexpected failures? (pink sites in current visualization)
[x] number of harvests past the last reward (eg. how many reds there are before leaving)
[ ] comparing position effects of failures (order within a patch, and when within a session)
[ ] in general look at within patch and within session effects
[ ] separate patch type for visualization
[ ] what are the small things we can show convincingly -> come up with a draft of interesting observations as next step (eg. statistics of choices, running, sniffing)
[ ] plotting behavioral choice in time + in distance
Across sessions analysis
Single session
Future scripts for ongoing analysis of 2nd batch Prepare a standard scripts that runs core behavior so every session has a summary available. It should depend on the stage (maybe one for habituation and another for training, depending on the final reassessment of the training protocol)