Learning about reward identities and time.

We discuss three empirical findings that we think any theory attempting to integrate interval timing with associative learning concepts will need to address. These empirical phenomena all come from studies that combine peak timing procedures with reinforcer devaluation or conditional discrimination tasks commonly employed, respectively, in interval timing or associative learning research traditions. The three phenomena we discuss include: (1) the observation that disruptions in reward identity encoding have little to no impact on the encoding of reward time in the peak procedure (Delamateret al., 2018), (2) the findings that organisms tend to average their time estimates when presented with a stimulus compound consisting of separately learned stimuli indicating short or long reward times but that such temporal averaging, itself, is sensitive to post-conditioning selective reward devaluation, and (3) that rats can learn a temporal patterning task in which two stimuli presented independently indicate one time to reward availability while their compound indicates another. We review our prior results and present new findings illustrating these three phenomena and we discuss the special challenges they pose for cascade theories of timing, for multiple-oscillator models, and for any approach that attempts to integrate interval timing and associative models. We close by illustrating some ways in which multi-layer connectionist network models might begin to address some of our key findings. We believe this will require an approach that includes separate mechanisms that code for reward identity and time, but that does so in a way that permits for integration between the two systems.