LEARNING IMPULSE CONTROL IN A NOVEL ANIMAL MODEL: SYNAPTIC, CELLULAR, AND PHARMACOLOGICAL SUBSTRATES

Impulse control, an executive process that restrains inappropriate actions, is impaired in numerous psychiatric conditions. This thesis reports three experiments that utilized a novel animal model of impulse control, the response inhibition (RI) task, to examine the substrates that underlie learning this task. In the first experiment, rats were trained to withhold responding on the RI task, and then euthanized for electrophysiological testing. Training in the RI task increased the AMPA/NMDA ratio at the synapses of pyramidal neurons in the prelimbic, but not infralimbic, region of the medial prefrontal cortex. This enhancement paralleled performance as subjects underwent acquisition and extinction of the inhibitory response. AMPA/NMDA was elevated only in neurons that project to the ventral striatum. Thus, this experiment identified a synaptic correlate of impulse control. In the second experiment, a separate group of rats were trained in the RI task prior to electrophysiological testing. Training in the RI task produced a decrease in membrane excitability in prelimbic, but not infralimbic, neurons as measured by maximal spiking evoked in response to increasing current injection. Importantly, this decrease was strongly correlated with successful inhibition in the task. Fortuitously, subjects trained in an operant control condition showed elevated infralimbic, but not prelimbic, excitability, which was produced by learning an anticipatory signal that predicted imminent reward availability. These experiments revealed two cellular correlates of performance, corresponding to learning two different associations under distinct task conditions. In the final experiment, rats were trained on the RI task under three conditions: Short (4-s), long (60-s), or unpredictable (1-s to 60-s) premature phases. These conditions produced distinct errors on the RI task. Interestingly, amphetamine increased premature responding in the short and long conditions, but decreased premature responding in the unpredictable condition. This dissociation may arise from interactions between amphetamine and underlying cognitive processes, such as attention, timing, and conditioned avoidance. In summary, this thesis showed that learning to inhibit a response produces distinct synaptic, cellular, and pharmacological changes. It is hoped that these advances will provide a starting point for future therapeutic interventions of disorders of impulse control.

The Optimality of Decision Making During Motor Learning

In our daily lives, we often must predict how well we are going to perform in the future based on an evaluation of our current performance and an assessment of how much we will improve with practice. Such predictions can be used to decide whether to invest our time and energy in learning and, if we opt to invest, what rewards we may gain. This thesis investigated whether people are capable of tracking their own learning (i.e. current and future motor ability) and exploiting that information to make decisions related to task reward. In experiment one, participants performed a target aiming task under a visuomotor rotation such that they initially missed the target but gradually improved. After briefly practicing the task, they were asked to select rewards for hits and misses applied to subsequent performance in the task, where selecting a higher reward for hits came at a cost of receiving a lower reward for misses. We found that participants made decisions that were in the direction of optimal and therefore demonstrated knowledge of future task performance. In experiment two, participants learned a novel target aiming task in which they were rewarded for target hits. Every five trials, they could choose a target size which varied inversely with reward value. Although participants’ decisions deviated from optimal, a model suggested that they took into account both past performance, and predicted future performance, when making their decisions. Together, these experiments suggest that people are capable of tracking their own learning and using that information to make sensible decisions related to reward maximization.