Topic: reward probability

Animals must continually assess their uncertainty about their environment and future events in order to drive choice behavior and learning. Because uncertainty is a key decision variable for myriad behaviors (e.g. curiosity, attention), neuromodulatory systems, which engage and regulate diverse brain regions and brain states, are ideally suited to subserve uncertainty-guided modulation of local brain computations. Theoretical studies have hypothesized that the neuromodulator acetylcholine is responsible for encoding “expected uncertainty” in the brain (i.e., learned unreliability of predictive

Midbrain dopamine (DA) neurons send teaching signals, reward prediction errors (RPEs), to all regions of the striatum [1]. However, these signals converge with regionally segregated inputs from all levels of the cortical hierarchy [2] that vary in degree of abstraction and temporal extendedness [3]. Recent work highlights how regionally diverse DA RPEs might update parallel estimates of future reward as informed by region-specific inputs[4, 5], yet the behavioral implications of such parallel processing are poorly understood. We used photometry to measure DA release across the striatum in mice

Cognitive flexibility plays a key role in ensuring an individual's survival. The prefrontal cortex and striatum are both essential to cognitive flexibility but competing theories debate which structure among these two leads the role in detecting and representing new circumstances for a change, giving largely opposing predictions on neural activities in the prefrontal cortex and striatum during flexible behavior. We trained head-restrained mice to perform an action-outcome based dynamic foraging task and simultaneously recorded single-neuron activities in the medial prefrontal cortex (mPFC)

Primate amygdala neuron process the value of visual stimuli to guide decision-making and social interactions (Grabenhorst et al., 2019; Grabenhorst et al., 2023). However, it remains unclear whether different amygdala neurons are sensitive to distinct value components, such as reward probability and magnitude, and whether they integrate these components to decision variables, including risk and expected value. To address these questions, we recorded activity of amygdala neurons while monkeys viewed sequentially presented stimuli that provided separate information about the probability, magnitu

We have revealed that there is a causal relationship between activation of dorsal raphe (DR) serotonergic neurons and patience when waiting for future rewards. To explain these behavioral data, we proposed a Bayesian decision model of waiting in which serotonin signals the prior probability of reward delivery. However, there is no direct evidence serotonin neural activity is modulated by reward probability. Five male serotonin neuron-specific GCaMP6-expressing mice were trained to perform a sequential tone-food waiting task that required them to wait for a delayed tone (tone delay: 0.3 s, tone