Time elapsed between choices in a probabilistic task correlates with repeating the same decision

Non-motor symptoms associated with progressive loss of dopaminergic neurons in a mouse model of Parkinson's disease

Parkinson's disease (PD) is characterized by three main motor symptoms: bradykinesia, rigidity and tremor. PD is also associated with diverse non-motor symptoms that may develop in parallel or precede motor dysfunctions, ranging from autonomic system dysfunctions and impaired sensory perception to cognitive deficits and depression. Here, we examine the role of the progressive loss of dopaminergic transmission in behaviors related to the non-motor symptoms of PD in a mouse model of the disease (the TIF-IADATCreERT2 strain). We found that in the period from 5 to 12 weeks after the induction of a gradual loss of dopaminergic neurons, mild motor symptoms became detectable, including changes in the distance between paws while standing as well as the swing speed and step sequence. Male mutant mice showed no apparent changes in olfactory acuity, no anhedonia-like behaviors, and normal learning in an instrumental task; however, a pronounced increase in the number of operant responses performed was noted. Similarly, female mice with progressive dopaminergic neuron degeneration showed normal learning in the probabilistic reversal learning task and no loss of sweet-taste preference, but again, a robustly higher number of choices were performed in the task. In both males and females, the higher number of instrumental responses did not affect the accuracy or the fraction of rewarded responses. Taken together, these data reveal discrete, dopamine-dependent non-motor symptoms that emerge in the early stages of dopaminergic neuron degeneration.

Time elapsed between choices in a probabilistic task correlates with repeating the same decision

Reinforcement learning causes an action that yields a positive outcome more likely to be taken in the future. Here, we investigate how the time elapsed from an action affects subsequent decisions. Groups of C57BL6/J mice were housed in IntelliCages with access to water and chow ad libitum; they also had access to bottles with a reward: saccharin solution, alcohol, or a mixture of the two. The probability of receiving a reward in two of the cage corners changed between 0.9 and 0.3 every 48 hr over a period of ~33 days. As expected, in most animals, the odds of repeating a corner choice were increased if that choice was previously rewarded. Interestingly, the time elapsed from the previous choice also influenced the probability of repeating the choice, and this effect was independent of previous outcome. Behavioral data were fitted to a series of reinforcement learning models. Best fits were achieved when the reward prediction update was coupled with separate learning rates from positive and negative outcomes and additionally a “fictitious” update of the expected value of the nonselected choice. Additional inclusion of a time‐dependent decay of the expected values improved the fit marginally in some cases.