A collaborator's reputation can bias decisions and anxiety under uncertainty
Humans look to others for advice when making decisions under uncertainty. Rational agents, however, do not blindly seek information, but often consider the quality of its source before committing to a course of action. Here, we ask the question of whether a collaborators' reputation can increase social influence and in turn bias perception and anxiety in the context of perceptual uncertainty. We show that when subjects are partnered with collaborators with a high reputation, this leads to increased conformity during uncertain perceptual decision-making and reduces anxiety when joint performance accuracy leads to an electric shock. Furthermore, our results show that information about reputation alters the neural circuits that underlie decision-making and emotion.
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How cognitive and reactive fear circuits optimize escape decisions in humans
Humans, like other animals, have evolved a set of neural circuits whose primary function is survival. In the case of predation, these circuits include “reactive fear” circuits involved in fast escape decisions and “cognitive fear” circuits that are involved in more complex processing associated with slow strategic escape. Using neuroimaging combined with computational modeling, we support this differentiation of fear circuits by showing that fast escape decisions are elicited by the periaqueductal gray and midcingulate cortex, regions involved in reactive flight. Conversely, slower escape decisions rely on the hippocampus, posterior cingulate cortex, and prefrontal cortex, a circuit implicated in behavioral flexibility. These results support a separation of fear into reactive and cognitive circuits.
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Oxytocin's Selective Facilitation of Socially Reinforced Learning
Previous studies have found that given social feedbacks, learners’ procedural learningcan be reinforced accordingly. This study aims to find out whether this reinforcement can be further enhanced or reversely reduced by oxytocin, and which brain areas & neural networks are involved in this process. RALT (Reinforced Association Learning Test) Paradigm :Several 3-digit numbers are randomly assigned to two categories: A or B. Given a random number, subjects are asked to assign the number to a certain category, and will be given a feedback (social, semi-social or non-social) indicating whether they are right. Test for the same number set will be repeated for multiple times, allowing subjects to gradually develop knowledge of the initial categorization through reinforced learning.
--------------------------------------------------------------------------------------------------------------------------------------------------------------------Chinese-English Bilinguals' Lexical Access
How bilinguals’ mental lexicon is represented and retrieved has long been a hot topic in the field of bilingualism research. Large numbers of researches have proven that the bilingual lexicon representation is divided into two dimensions: lexical level and conceptual level. While the two languages’ lexical representations are independent, they share a common conceptual representation. (Zeelenberg & Pecher 2003; De Groot, 2005;Jared & Kroll, 2001; Li Li et al. 2008). However, how’s the two independent lexical representations interact with the common conceptual representation remains controversial.
Long-term Repetition Priming:
The whole experiment is composed of two sections, a encoding section (study section) and a retrieving section (test section). By adjusting the relationship between materials in the two sections, we can observe the influence of “whether the material has been previously learned in the study section” on participants’ responses to the material in the test section.
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Collective Electrotaxis of Epithelial Cell
While migration behavior under electric fields for single cells (Ex. Human immune T cells) has been thoroughly studied, the electrotaxis mechanism for epithelial cells(Ex. MDCK cells) remains largely unknown. The present study seeks to address the issue using a combination of numerical modeling/simulation and electrotaxis experiments.
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Modelling Earth Air Health via Network Dynamics
(ICM 2013 Contest Paper with Honorable Mention)
We construct a directed local temporal network with each node representing a country. Parameters associated with a node describe how air pollution is generated, resolved, and distributed. Links among the nodes represent possible pathways for pollution transfer. We then model a global node with bifurcation dynamic and connect it to the local network. Local forcings’ influence on the global forcing and feedbacks from the global node are simulated by correlating the entropy of the local network and the chaos index in the global bifurcation. We set 2 measures at the local level and global level, reflected by local pollution accumulation and global bifurcation status respectively. The model parameters are estimated via analytical hierarchy process.