Siyana Hristova has been awarded an Undergraduate Research Apprentice Program (URAP) summer award. She will be working on neuroimaging investigations of the interaction of memory and valuation processes in decision-making.

Samira Maboudian has been awarded the SRNDNA Summer Undergraduate Research Award. She will be studying novel ways to quantify memory deficits due to neurodegeneration and how these deficits affect economic decision-making.

Our paper on dissociating BG and OFC functioning in social decision-making, in collaboration with lab alum Lusha Zhu and the Knight lab, is now out at Nature Communication.

Zhu, Lusha, Yaomin Jiang, Donatella Scabini, Robert T. Knight, and Ming Hsu. 2019. “Patients with Basal Ganglia Damage Show Preserved Learning in an Economic Game.” Nature Communications. [Link]

Now you play the gambling task from our paper Encoding of multiple reward-related computations in transient and sustained high-frequency activity in human OFC! Just click below to get started or go here if the game is not showing in your browser.

Zhihao Zhang received a Career Transition Award from Scientific Research Network on Decision Neuroscience and Aging. This award will go toward his studies of how semantic memory influences and constrains value-based decision-making, and how changes in memory over the lifespan and in neurodegenerative diseases affect decision-making.

Anna Jenkins paper accepted at PNAS!

Jenkins AC, Karashchuk P, Zhu L & Hsu M. Predicting human behavior toward members of different social groups. Proceedings of the National Academy of Sciences. 2018.

Abstract:

Disparities in outcomes across social groups pervade human societies and are of central interest to the social sciences. How people treat others is known to depend on a multitude of factors—e.g., others’ gender, ethnicity, or appearance—even when these should be irrelevant. However, despite substantial progress, much remains unknown regarding (i) the set of mechanisms shaping people’s behavior toward members of different social groups and (ii) the extent to which these mechanisms can explain the structure of existing societal disparities. Here we show in a set of experiments the important interplay between social perception and social valuation processes in explaining how people treat members of different social groups. Building on the idea that stereotypes can be organized onto basic, underlying dimensions, we first found using laboratory economic games that quantitative variation in stereotypes about different groups’ warmth and competence translated meaningfully into resource allocation behavior toward those groups. Computational modeling further revealed that these effects operated via the interaction of social perception and social valuation processes, with warmth and competence exerting diverging effects on participants’ preferences for equitable distributions of resources. This framework successfully predicted behavior toward members of a diverse set of social groups across samples and successfully generalized to predict societal disparities documented in labor and education settings with substantial precision and accuracy. Together, these results highlight a common set of mechanisms linking social group information to social treatment and show how pre-existing, societally shared assumptions about different social groups can produce and reinforce societal disparities.

Last week I had a very interesting conversation with Michelle Quinn from Voice of America on the struggle of tech companies to curtail offensive speech. Here is the article and the accompanying video. My primary contribution is in highlighting the challenge with real-world operationalizations of concepts like "bias" and "discrimination".

On the one hand, the bias against certain groups is so obvious as to be common sense. On the other hand, get outside of these "common sensical" categories and things get really controversial, really fast. Are rural Americans biases against? What about working class? Is there pervasive bias against caucasians?

I think most of us have heard these and similar claims. So the question I would like to pose is, can we validate these claims in some way? Even if we find some of these claims offensive, and the people making these claims odious, can we nevertheless test these claims rigorously, and either validate or falsify them in a fact-based, data-driven manner?

Since our forthcoming paper on the topic is still under embargo, I will leave things a bit vague here, and just say that I think we are beginning to develop tools that may finally answer these difficult questions. So, as lame as it might sound, stay tuned...

Cross posted on faculty page.

I will be recruiting for my lab in Fall 2018. Depending on the specific interests, students can apply through PhD programs in Haas School of Business, Helen Wills Neuroscience Institute, or Department of Psychology. Those who are interested should contact me with their current cv and a short description of research interests.