Understanding Affective Cognition: Frontiers in modeling reasoning about others’ emotions

Understanding Affective Cognition: Frontiers in modeling reasoning about others’ emotions Desmond C. Ong (dco@stanford.edu) Jamil Zaki (jzaki@stanford.edu) Noah D. Goodman (ngoodman@stanford.edu) Department of Psychology, Stanford University, Stanford CA, USA implications and future directions, will be led and moderated by Noah Goodman. Affective cognition is a key topic that is growing increas- ingly relevant to the cognitive science community in the past few years, and it is the perfect time to bring together leaders in the field of affective cognition to discuss the exciting state of the art of this field, moving forward. In addition to gain- ing deeper understanding of the core computations that un- derlie such reasoning, there are many promising applications of this work. In particular, this symposium and its applica- tions resonate well with the theme of this year’s conference, Cognitive Science Meets Artificial Intelligence: Human and Artificial Agents in Interactive Contexts. First, having a better understand about basic human affective cognition will enable us to make progress in building interactive artificial agents that can reason about human emotions (Picard, 2000). Sec- ond, having models of working and dysfunctional affective cognition would enable us to build computational algorithms and agents to assist with diagnosing and treating clinical dis- orders (Montague, Dolan, Friston, & Dayan, 2012). Such ap- plications of affective cognition are becoming more ubiqui- tous each year, and this dialogue between leaders in the cog- nitive science community will, we hope, spur future research in both the basic and applied disciplines. Keywords: Affective cognition; Social cognition; Neu- roscience; Computational Modeling; Developmental Ap- proaches Motivation Social life constantly requires us to decipher information about others into inferences about their emotional states: for example, we have to reason about what makes our romantic partners happy (a surprise gift?) or angry (not doing one’s chores?), and what they would do in those emotional states, in order to plan our upcoming interactions. Such affective cognition, or our ability to reason about others’ emotions, scaffolds everything from cooperation to the maintenance of social relationships. Affective cognition lies in the intersec- tion of two foundational social cognitive topics, Theory of Mind (ToM; the ability to reason about others’ mental states) and Empathy (the ability to feel and understand others’ emo- tions). Although the past decade has seen much progress in understanding ToM and empathy using neuroscience (Koster- Hale & Saxe, 2013; Zaki & Ochsner, 2012), developmental (Meltzoff, 2011), and computational (Baker, Saxe, & Tenen- baum, 2009; Goodman & Stuhlmuller, 2013) approaches, somewhat less attention has been paid specifically to affective cognition and some of its foundational cognitive questions. How do we represent (cognitively and neurally) others’ emo- tional states? How do we reason with those representations? How do we make predictions and inferences about others’ fu- ture actions or desires based on their emotions? Finally, how does affective cognition shift across development? The aim of the symposium is to answer these, and other relevant ques- tions, at the forefront of this field. In this symposium, we will discuss recent work in affective cognition done by some of the above-cited researchers and their labs who approach the topic from different disciplines and backgrounds. There will be ample time set aside at the end of the symposium for the speakers and the audience to discuss future research directions. Amy Skerry will kick off the symposium by discussing recent work on neural represen- tations of others’ emotional states. Desmond Ong will then present a computational model of emotion attribution to other agents. Yang Wu will continue the discussion with a model of inference over an agent’s desires and beliefs from observed emotions, in both adults and children. Our final speaker, An- drew Meltzoff will describe and discuss recent developmen- tal work on how children learn and make inferences about others’ emotional traits, and regulate their own behavior in response. Finally, open discussion, especially with regards to A common neural code for perceived and inferred emotions Amy Skerry (Harvard University) & Rebecca Saxe (Massachusetts Institute of Technology) Attributing emotional states to others is crucial for predict- ing and explaining action, identifying intentions and attitudes, and successfully navigating social interactions. While the emotions of other people can often be perceived from overt reactions (e.g. facial or vocal expressions), they can also be inferred from situational information in the absence of ob- servable expressions. How does the human brain make use of these diverse forms of evidence to generate a common rep- resentation of a target’s emotional state? In the present re- search, we identify neural patterns that correspond to emo- tions attributed based on context, and find that these patterns generalize across different cues from which an emotion can be inferred. Specifically, we use fMRI to measure neural responses to dynamic facial expressions with positive and negative valence, and to short animations in which the va- lence of a character’s emotion could be identified only from the situation. Using multi-voxel pattern analysis (MPVA),