Effects of stimulus timing on the acquisition of an olfactory working memory task in head-fixed mice.

Acquisition of a behavioural task is influenced by many factors. The relative timing of stimuli is such a factor and is especially relevant for tasks relying on short-term memory, like working memory paradigms, due to the constant evolution and decay of neuronal activity evoked by stimuli. Here we assess two aspects of stimulus timing on the acquisition of an olfactory delayed non-match-to-sample (DNMS) task. We demonstrate that head-fixed male mice learn to perform the task more quickly when the initial training uses a shorter sample-test odour delay without detectable loss of generalisability. Unexpectedly, we observed a faster task acquisition when the odour-reward interval was longer. The effect of early reward timing was accompanied by a shortening of reaction times and more frequent sporadic licking. Analysis of this result using a drift-diffusion model indicated that a primary consequence of early reward delivery is a lowered threshold to act, or lower decision bound. Since an accurate performance with a lower decision bound requires greater discriminability in the sensory representations, this may underlie the slower learning rate with early reward arrival. Together, our results reflect the possible effects of stimulus timing on stimulus encoding and its consequence on the acquisition of a complex task. SIGNIFICANCE STATEMENT: This study describes how head-fixed mice acquire a working memory task (olfactory delayed non-match-to-sample task). We simplified and optimised the stimulus timing, allowing robust and efficient training of head-fixed mice.Unexpectedly, we found that early reward timing leads to slower learning. Analysis of this data using a computational model (drift-diffusion model) revealed that the reward timing affects the behavioural threshold, or how quickly animals respond to a stimulus. But, in order to still be accurate with early reaction times, the sensory representation needs to become even more refined. This may explain the slower learning rate with early reward timing.