an emotional arousal manipulation shifted these biases across individual differences in interceptive awareness (“IA”); people w/ low IA didn’t show a change across the manipulation whereas those w/ high IA did!

comp. models revealed pre-exp. values & learning rate changes predicted behavior (2/3)

Simulating SRPE integration and URPE segmentation enabled the model to perform associative chaining, which involved reactivating items between two tested probes to assist with sequential retrieval (a la DuBrow and @liladavachi.bsky.social) predicting our previously unaccounted for results (5/7)

We further predict that SRPE integration may increase the contextual similarity of events while URPE segmentation may create a contextual shift, with consequences for temporal order memory, modeled here using a variant of the Context, Maintenance and Retrieval model (3/7)

We argue that signed reward prediction errors (SRPEs) during reward cue (linked to midbrain dopamine) help build a model of the world while large unsigned (U)RPEs at reward outcome (linked to locus coeruleus) can break them (2/7)

I will be recruiting 💫two PhD students💫 for my new lab! (computational learning & memory applied to individual & interactive behavior: rouhanilab.com).

Feel free to e-mail if interested and catch me at SfN!
(poster 06 at 1 PM on Wed 10/09)