MBCT Seminar: Huan Wang and Effie Li

Event Details:

Monday, December 2, 2024
Time
4:00pm to 5:00pm PST
Contacts
neuroscience@stanford.edu
Event Sponsor
Wu Tsai Neurosciences Institute
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Split image of two individuals standing outdoors, showcasing promotional material for "MBCT Seminar Series 2024-2025" by the Wu Tsai Neurosciences Institute.

Continue the conversation: Join the speaker for a complimentary dinner in the Theory Center (second floor of the neurosciences building) after the seminar

This seminar event will feature two talks presented by Stanford PhD students Huan Wang and Effie Li.

 


 

Different cultural norms and neuroaffective mechanisms promote trust in Eastern and Western cultures

Abstract 

Why do individuals differ on their levels of trust towards strangers between the East and West? Across three studies, we examined interpersonal trust across cultures, individuals, and reputational contexts. We found that trust norms as well as cultural values of social cooperation explained cross-cultural differences in trust. These cultural differences further influenced individuals’ neural responses to trusting cooperative or competitive strangers. Together, these findings indicate that trust plays a critical role in promoting exchange between strangers, but cultural tendencies and motivations to trust may differ across cultures.

 

Huan Wang

Stanford University

Huan is a 5th year student in Psychology interested in understanding how interpersonal trust varies across individuals and cultures, as well as exploring the underlying reasons for such variation and its supporting neural mechanisms.

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Emergent task decomposition and subgoal choices in transformers

Abstract 

Recent years have witnessed wide success from transformers trained on diverse data, giving rise to powerful language and multimodal models. Transformers excel at nuanced context sensitivity across high-dimensional inputs, but it remains unclear whether they can achieve structured, algorithmic computation that may seed higher-level cognitive abilities such as goal-directed behavior. In this talk, I will discuss our recent work training small-scale transformers to solve simple algorithmic tasks and reverse-engineering the internal dynamics that supported their behavior. We find that multi-layer self-attention can develop structured solutions to these tasks and even develop signs of task decomposition. When trained on graph-traversal experiences, simple transformers can learn human-like subgoal choices and motivate hypotheses about human subgoal discovery. These studies offer concrete insights into why structured experiences, simple learning objectives, and general architectures have not only been a successful recipe, but have fundamental links to higher-level cognition.

 

Effie Li

Stanford University

Yuxuan (Effie) Li is a final year PhD student in the Department of Psychology at Stanford University. Her research focuses on machine and human cognition, exploring how higher-level cognitive abilities such as goal-directed behavior and task decomposition can emerge in a learning system. She also spent time understanding multimodal large models and embodied agents at Meta and AI2, and researched neural mechanisms of human memory at the University of Pennsylvania.

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About the Mind, Brain, Computation, and Technology (MBCT) Seminar Series

The Stanford Center for Mind, Brain, Computation and Technology (MBCT) Seminars explore ways in which computational and technical approaches are being used to advance the frontiers of neuroscience. 

The series features speakers from other institutions, Stanford faculty, and senior training program trainees. Seminars occur about every other week, and are held at 4:00 pm on Mondays at the Cynthia Fry Gunn Rotunda - Stanford Neurosciences E-241. 

Questions? Contact neuroscience@stanford.edu

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