Adults with autism spectrum disorders exhibit decreased sensitivity to reward parameters when making effort-based decisions.

BACKGROUND: Efficient effort expenditure to obtain rewards is critical for optimal goal-directed behavior and learning. Clinical observation suggests that individuals with autism spectrum disorders (ASD) may show dysregulated reward-based effort expenditure, but no behavioral study to date has assessed effort-based decision-making in ASD. METHODS: The current study compared a group of adults with ASD to a group of typically developing adults on the Effort Expenditure for Rewards Task (EEfRT), a behavioral measure of effort-based decision-making. In this task, participants were provided with the probability of receiving a monetary reward on a particular trial and asked to choose between either an "easy task" (less motoric effort) for a small, stable reward or a "hard task" (greater motoric effort) for a variable but consistently larger reward. RESULTS: Participants with ASD chose the hard task more frequently than did the control group, yet were less influenced by differences in reward value and probability than the control group. Additionally, effort-based decision-making was related to repetitive behavior symptoms across both groups. CONCLUSIONS: These results suggest that individuals with ASD may be more willing to expend effort to obtain a monetary reward regardless of the reward contingencies. More broadly, results suggest that behavioral choices may be less influenced by information about reward contingencies in individuals with ASD. This atypical pattern of effort-based decision-making may be relevant for understanding the heightened reward motivation for circumscribed interests in ASD.

Decision-Making in the Primate Brain

Making decisions is fundamental to everything we do, yet it can be impaired in various disorders and conditions. While research into the neural basis of decision-making has flourished in recent years, many questions remain about how decisions are instantiated in the brain. Here we explored how primates make abstract decisions and decisions in social contexts, as well as one way to non-invasively modulate the brain circuits underlying decision-making. We used rhesus macaques as our model organism. First we probed numerical decision-making, a form of abstract decision-making. We demonstrated that monkeys are able to compare discrete ratios, choosing an array with a greater ratio of positive to negative stimuli, even when this array does not have a greater absolute number of positive stimuli. Monkeys’ performance in this task adhered to Weber’s law, indicating that monkeys—like humans—treat proportions as analog magnitudes. Next we showed that monkeys’ ordinal decisions are influenced by spatial associations; when trained to select the fourth stimulus from the bottom in a vertical array, they subsequently selected the fourth stimulus from the left—and not from the right—in a horizontal array. In other words, they begin enumerating from one side of space and not the other, mirroring the human tendency to associate numbers with space. These and other studies confirmed that monkeys’ numerical decision-making follows similar patterns to that of humans, making them a good model for investigations of the neurobiological basis of numerical decision-making.

We sought to develop a system for exploring the neuronal basis of the cognitive and behavioral effects observed following transcranial magnetic stimulation, a relatively new, non-invasive method of brain stimulation that may be used to treat clinical disorders. We completed a set of pilot studies applying offline low-frequency repetitive transcranial magnetic stimulation to the macaque posterior parietal cortex, which has been implicated in numerical processing, while subjects performed a numerical comparison and control color comparison task, and while electrophysiological activity was recorded from the stimulated region of cortex. We found tentative evidence in one paradigm that stimulation did selectively impair performance in the number task, causally implicating the posterior parietal cortex in numerical decisions. In another paradigm, however, we manipulated the subject’s reaching behavior but not her number or color comparison performance. We also found that stimulation produced variable changes in neuronal firing and local field potentials. Together these findings lay the groundwork for detailed investigations into how different parameters of transcranial magnetic stimulation can interact with cortical architecture to produce various cognitive and behavioral changes.

Finally, we explored how monkeys decide how to behave in competitive social interactions. In a zero-sum computer game in which two monkeys played as a shooter or a goalie during a hockey-like “penalty shot” scenario, we found that shooters developed complex movement trajectories so as to conceal their intentions from the goalies. Additionally, we found that neurons in the dorsolateral and dorsomedial prefrontal cortex played a role in generating this “deceptive” behavior. We conclude that these regions of prefrontal cortex form part of a circuit that guides decisions to make an individual less predictable to an opponent.

The Role of Social Cognition and Person Perception in Economic Social Decision-Making

Social decision-making is often complex, requiring the decision-maker to make social inferences about another person in addition to engaging traditional decision-making processes. However, until recently, much research in neuroeconomics and behavioral economics has examined social decision-making while failing to take into account the importance of the social context and social cognitive processes that are engaged when viewing another person. Using social psychological theory to guide our hypotheses, four research studies investigate the role of social cognition and person perception in guiding economic decisions made in social contexts. The first study (Chapter 2) demonstrates that only specific types of social information engage brain regions implicated in social cognition and hinder learning in social contexts. Study 2 (Chapter 3) extends these findings and examines contexts in which this social information is used to generalize across contexts to form predictions about another person’s behavior. Study 3 (Chapter 4) demonstrates that under certain contexts these social cognitive processes may be withheld in order to more effectively complete the task at hand. Last, Study 4 (Chapter 5) examines how this knowledge of social cognitive processing can be used to change behavior in a prosocial group context. Taken together, these studies add to the growing body of literature examining decision-making in social contexts and highlight the importance of social cognitive processing in guiding these decisions. Although social cognitive processing typically facilitates social interactions, these processes may alter economic decision-making in social contexts.

Primary care physician decision making regarding severe obesity treatment and bariatric surgery: a qualitative study.

BACKGROUND: Less than 1% of severely obese US adults undergo bariatric surgery annually. It is critical to understand the factors that contribute to its utilization. OBJECTIVES: To understand how primary care physicians (PCPs) make decisions regarding severe obesity treatment and bariatric surgery referral. SETTING: Focus groups with PCPs practicing in small, medium, and large cities in Wisconsin. METHODS: PCPs were asked to discuss prioritization of treatment for a severely obese patient with multiple co-morbidities and considerations regarding bariatric surgery referral. Focus group sessions were analyzed by using a directed approach to content analysis. A taxonomy of consensus codes was developed. Code summaries were created and representative quotes identified. RESULTS: Sixteen PCPs participated in 3 focus groups. Four treatment prioritization approaches were identified: (1) treat the disease that is easiest to address; (2) treat the disease that is perceived as the most dangerous; (3) let the patient set the agenda; and (4) address obesity first because it is the common denominator underlying other co-morbid conditions. Only the latter approach placed emphasis on obesity treatment. Five factors made PCPs hesitate to refer patients for bariatric surgery: (1) wanting to "do no harm"; (2) questioning the long-term effectiveness of bariatric surgery; (3) limited knowledge about bariatric surgery; (4) not wanting to recommend bariatric surgery too early; and (5) not knowing if insurance would cover bariatric surgery. CONCLUSION: Decision making by PCPs for severely obese patients seems to underprioritize obesity treatment and overestimate bariatric surgery risks. This could be addressed with PCP education and improvements in communication between PCPs and bariatric surgeons.