Reward motivation and cognitive flexibility in tau null-mutation mice.

The reduction of tau or hyperphosphorylated tau (p-tau) has been proposed as a therapeutic strategy for Alzheimer's disease (AD) and frontotemporal dementia (FTD). Cognitive decline and sleep-wake dysregulation seen in AD and FTD patients are mimicked in transgenic and null-mutation mouse models of tauopathy. Alterations in the reward system are additional symptoms of AD and FTD. However, the role of tau in reward processes is not well understood. The present study aimed to examine reward and reward-motivated cognitive processes in male and female tau knockout (tau-/-) and wild-type mice using progressive ratio and reversal learning tasks. Tau-/- mice were heavier, ate more in the home cage, and reached criterion in operant lever training faster than wild-type mice. Tau-/- mice had a higher breakpoint in progressive ratio but were unimpaired in reversal learning or reward sensitivity. These data indicate that tau loss of function alters reward processing. This may help to explain aberrant reward-related behaviors in tauopathy patients and highlights a potentially important area for consideration in the development of anti-tau therapies.

Effects of orexin receptor antagonism on human sleep architecture: A systematic review.

Orexin receptor antagonists are a relatively new hypnotic principle. Their influence on human sleep architecture is a point of debate that has not been systematically evaluated. Thus, we performed a systematic review to assess how these compounds effect sleep architecture in healthy and clinical human samples. Relevant articles were identified via searches of PubMed, Embase, the Cochrane central register of controlled trials, and clinicaltrials. gov. From 1147 retrieved records, 18 satisfied inclusion criteria and formed the basis of this review. Of these, fifteen studies administered dual orexin receptor antagonists (DORA) in a healthy control (five studies) or clinical sample (ten studies). By contrast, three studies administered selective orexin receptor-2 antagonists (2-SORA) in either a healthy control (one study) or clinical sample (two studies). Results reveal DORAs increase total sleep time primarily by promoting REM sleep, without affecting, or even decreasing, non-REM sleep, especially in clinical samples. Therefore, the clinical utility of DORAs may depend on the specific sample being treated. For 2-SORAs, limited evidence available precludes firm conclusions about their influence on human sleep architecture and, thus, further investigation of 2-SORAs is required to define their effects and make comparisons on this basis with DORAs.

Separating Probability and Reversal Learning in a Novel Probabilistic Reversal Learning Task for Mice.

The exploration/exploitation tradeoff - pursuing a known reward vs. sampling from lesser known options in the hope of finding a better payoff - is a fundamental aspect of learning and decision making. In humans, this has been studied using multi-armed bandit tasks. The same processes have also been studied using simplified probabilistic reversal learning (PRL) tasks with binary choices. Our investigations suggest that protocols previously used to explore PRL in mice may prove beyond their cognitive capacities, with animals performing at a no-better-than-chance level. We sought a novel probabilistic learning task to improve behavioral responding in mice, whilst allowing the investigation of the exploration/exploitation tradeoff in decision making. To achieve this, we developed a two-lever operant chamber task with levers corresponding to different probabilities (high/low) of receiving a saccharin reward, reversing the reward contingencies associated with levers once animals reached a threshold of 80% responding at the high rewarding lever. We found that, unlike in existing PRL tasks, mice are able to learn and behave near optimally with 80% high/20% low reward probabilities. Altering the reward contingencies towards equality showed that some mice displayed preference for the high rewarding lever with probabilities as close as 60% high/40% low. Additionally, we show that animal choice behavior can be effectively modelled using reinforcement learning (RL) models incorporating learning rates for positive and negative prediction error, a perseveration parameter, and a noise parameter. This new decision task, coupled with RL analyses, advances access to investigate the neuroscience of the exploration/exploitation tradeoff in decision making.