We are interested in social behavior, and in particular, strategic decision-making in humans. We seek to understand the mechanisms by which the brain anticipates actions or consequences of others with value-based goals to produce choices within interpersonal interactions.
To this end, we combine game-theoretic models of behavior with neuroscience techniques to examine functional circuits that translate external information presented in games (e.g. payoffs, rules, and feedback) into internal cognitive states (e.g. beliefs, valuation, and attention) and external choice behaviors (e.g. competition, cooperation, coordination, communication, etc.). This approach helps us to draw formal inferences about the underlying choice processes that span multiple levels of analysis (e.g. behavior, cognition, brain, and genetics), and provide objective metrics with potential diagnostic and assessment utility.
Our research can be divided into several research foci, each of which explores the neurobehavioral substrates of decision-making under specific motivational or interpersonal context.
Social and Strategic Learning
Decision-making in the presence of other competitive intelligent agents is fundamental for social behavior. Such decisions require agents to behave strategically, where in addition to learning about the rewards and punishments available in the environment, they also need to anticipate and respond to actions or consequences of others competing for the same rewards. Whereas strategic learning has been extensively investigated at both behavioral and algorithmic levels in the fields of game theory and artificial intelligence, neurocognitive mechanisms underlying strategic behavior remain to be explored.
Research in our lab aims at developing mechanistic understanding about brain regions that facilitate such decision-making in either simple interpersonal settings or complex social environments where the brain uses simple heuristics to guide behavior. For example, based on an economic game called “patent race”, in which individuals compete for the same monetary reward during repeated interactions, we identified separable learning signals encoded in partially overlapping but distinct brain regions. Prediction errors arising from trial and error for learning the available rewards and punishments
(reinforcement learning) are processed in the ventral striatum; whereas error signals arising from predicting, interpreting, and responding to actions of social opponents (belief learning) are encoded in both the ventral striatum and rostral anterior cingulate. These results suggest that decisions made within competitive environments are guided by inputs from parallel neural processes––one that is common to adaptive behaviors across a wide range of non-social settings and one that is specific to social interactions. We further tested whether these neural regions were necessary for strategic learning by examining the performance of patients with focal lesions in the regions identified in our fMRI study. We found preserved capacity to learn in economic games following the basal ganglia damage, which suggests a model where higher-order learning processes are dissociable from trial-and-error learning and can be preserved despite basal ganglia damage. Ongoing research projects in our lab aim at exploring the interplay between strategic learning and social structures.
L Zhu*, Y Jiang, D Scabini, RT. Knight, M Hsu*, Nature Communications. 2019.
L Zhu, K Mathewson, M Hsu*. Proceedings of the National Academy of Sciences, 2012.
Communication as Goal-Directed Decision-Making
Social communication is pervasive in nature, ranging from basic animal behaviors such as birds singing for courtship, to complicated human actions such as lying, begging, and apologizing. To date, many neuroscience studies on communication have focused on the cognitive and neural functions involved in the low-level processing of communicative signals such as narratives and facial expressions, whereas behavioral studies in ethology and economics are rooted in a very different tradition. These studies often seek to understand how organisms survive and thrive by sharing and responding to social information concerning the opportunities and challenges encountered in the daily environment. While these studies have produced rich theoretical and empirical findings at the behavioral level, the characterization of their neural underpinnings has been remarkably unexplored.
We seek to understand neurocomputational mechanisms of communicative behavior, taking a unique perspective by investigating inferences and choices in intentional information transmission as goal-directed, strategic decision-making, and by drawing from recent developments in decision neuroscience, computational pragmatics, and the large body of work in signaling games. Collaborating with developmental psychologists, we also seek to leverage our findings to further elucidate when and how humans acquire the ability to interpret communicative signals and what neural developments underlie this process.
Q Mi, C Wang, C F. Camerer, L Zhu*. Science Advances. 2021
L Zhu, AC Jenkins, E Set, D Scabini, R Knight, P Chiu, B King-Casas, and Ming Hsu*. Nature Neuroscience, 2014.