Learning and decision-making are driven by expectations of future reward. Two key parameters determining the valuation of future rewards are 1) ?how much? reward to expect, and 2) ?when? to expect it (ie, Reward Prediction). However, how reward prediction is generated by the brain in response to predictive cues is poorly understood. Exemplifying the when of reward-prediction is so-called ?reward timing? activity in the primary visual cortex (V1), which emerges in V1 when visual stimuli are behaviorally conditioned with delayed water reward. Previously, we have demonstrated that this timing activity is generated within V1 itself, requires basal forebrain cholinergic innervation to be formed, and informs on the timing of visually-cued actions. More recently we have conceived, computationally, how the harder problem of reward prediction signaling could be learned within a network by the action of a reinforcement signal. Together, these observations make V1 a powerful system to address how reward prediction can be learned and reported neurally. Combined with our theory of intertemporal decision-making, these observations well motivate our research into how V1 circuitry produces reward prediction signals, how cholinergic innervation teaches that circuitry to learn reward prediction, and whether reward prediction signaling in V1 informs decision-making. Whether behavioral conditioning leads to V1 learning to produce reward prediction signals in V1 is unknown, though pilot data indicates it is (Aim1a). Testing predictions from our formal model, reward prediction responses will be mapped onto opto-identified inhibitory cell types (Aim1b). Optogenetic perturbation of inhibitory subtypes will specifically test predictions on the expression of reward prediction (Aim1c). Pilot Ca2+ imaging of cholinergic fibers within V1 indicates that reward is indeed reported to V1 by this input as predicted (Aim2a). Therefore, the degree of cholinergic activation within V1 (as controlled optogenetically) may serve to teach V1 to express reward prediction signaling (Aim2b). This ability to optogenetically mimic reward signaling affords a means to test whether learned reward prediction signaling in V1 informs decision-making: By instilling fictive reward expectancies atop behaviorally conditioned reward expectancies of otherwise equal value, reward prediction signaling in V1 can be shown to impact future decision making (Aim3a&b). Observations made here will advance an understanding of the mechanisms? impaired in many cognitive diseases?of how the behavioral meaning of sensory information is learned in order to remember past experiences and inform decision making.
Learning and decision making are driven by expectations of future rewards, yet how reward prediction is generated by the brain to inform behavior is poorly understood. We propose to investigate this issue by using a model system for the study of reinforcement-based learning in the cortex that affords control over inputs predictive of future reward, as well as inputs conveying the acquisition of reward. The goals of the work are to: 1) characterize cortical signaling of reward prediction and the circuitry producing it, 2) measure cholinergic signaling of reward acquisition and establish how it teaches cortical circuitry to report reward prediction, and 3) demonstrate that this reward prediction signal causally informs decision making.
