About

Hongbo Yu is an Associate Professor in the Psychological & Brain Sciences department at the University of California, Santa Barbara. He received his Ph.D. in psychology in 2016 and his B.S. in physics in 2010 from Peking University, China. His doctoral work with Dr. Xiaolin Zhou investigated the neural bases of social emotions, such as guilt and gratitude, by developing social interactive tasks that can naturally and repeatedly elicit social emotions in laboratory environments. After earning his Ph.D., Dr. Yu joined Dr. Molly Crockett’s lab as a postdoctoral researcher, initially at the University of Oxford where he was awarded a British Academy Newton International Fellowship, and subsequently at Yale University. His postdoctoral research focused on the neurocomputational mechanisms of moral judgment and decision-making. He joined the faculty at UCSB in 2019. His research aims to explain the underlying forces that create emotions, which he describes as 'upheavals of thought,' and how these emotions shape moral lives. His lab studies the neurocognitive mechanisms of social emotions, their moral significance, and how they are influenced by culture. In addition to experimental approaches, his research incorporates text analysis and large language models to explore the universality and variability of emotion and moral concepts across history and cultures. He is also interested in how conceptual knowledge influences perception of objects, such as faces, visual arts, music, and logos, using a combination of LLMs, computer vision models, behavioral experiments, and neuroscience measures.

Research topics

• Psychology
• Social psychology
• Cognitive psychology
• Neuroscience
• Developmental psychology

Selected publications

• A multi-national mega-study of the effects of gratitude practices on subjective well-being

  PsyArXiv (OSF Preprints) · 2026-05-01

  preprintOpen access

  Scholars have observed people from a variety of cultures using a variety of gratitude-related practices to change their emotions, outlooks, and social relationships. Across 34 countries purposefully sampled to cover a broad set of cross-cultural differences (total N = 10,772), we experimentally tested the effects of 6 popular gratitude practices on subjective moods, life outlooks, and social evaluations. Consistent with multiple theoretical accounts, gratitude practices produced immediate (but small) improvements in positive affect (d = 0.36), negative affect (d = -0.22), optimism (d = 0.24), life satisfaction (d = 0.11), indebtedness (d = 0.15), and envy (d = -0.16). Notably, these effects varied across different gratitude practices (0.00 < τpractice < 0.08) and countries (0.10 < τcountry < 0.19). For instance, based on existing evidence, stakeholders can expect gratitude interventions deployed in a randomly-selected country to improve positive affect – but not our other measured outcomes. To guide future inquiry into why this might be the case, we provide exploratory Bayesian estimates of the importance of 12 types of cross-cultural differences.

  Publisher

• Failing Others’ Expectations: Negative Emotions and Behavior Change in Daily Life

  Affective Science · 2026-04-23

  articleOpen accessSenior authorCorresponding

  Social expectations are a ubiquitous part of human experience, yet little is known about the emotions associated with failing to fulfill others’ social expectations. In two studies, we examined the effects of failing to fulfill others’ social expectations on individuals’ emotions, and assessed how situational factors moderate these effects. Study 1 aimed to establish the relationship between social expectation violation and negative affects in ecologically valid everyday contexts using daily diary methods. We found that in both Chinese and American college student samples, negative affects scaled with the degree to which one failed to fulfill a social expectation (i.e., violation). Moreover, the perceived legitimacy and strength of an expectation modulated the relationship between expectation violation and negative affect. Study 2 showed that the participants in Study 1 systematically overestimated the legitimacy and strength of the social expectations they reported relative to independent raters who evaluated the social expectations from a third-person perspective. Importantly, overestimation of the legitimacy of social expectations led to significantly higher self-reported negative affects. Taken together, we demonstrated the critical role of failing to meet social expectations in individuals’ negative social emotions in two cultural contexts and pinpointed important modulating factors of such effects. These results have implications for interventions aiming to alleviate the impacts of social expectations on emotional well-being.

  PublisherOA PDFDOI

• A multi-national mega-study of the effects of gratitude practices on subjective well-being

  PsyArXiv (OSF Preprints) · 2026-04-13

  preprintOpen access

  Scholars have observed people from a variety of cultures using a variety of gratitude-related practices to change their emotions, outlooks, and social relationships. Across 34 countries purposefully sampled to cover a broad set of cross-cultural differences (total N = 10,772), we experimentally tested the effects of 6 popular gratitude practices on subjective moods, life outlooks, and social evaluations. Consistent with multiple theoretical accounts, gratitude practices produced immediate (but small) improvements in positive affect (d = 0.36), negative affect (d = -0.22), optimism (d = 0.24), life satisfaction (d = 0.11), indebtedness (d = 0.15), and envy (d = -0.16). Notably, these effects varied across different gratitude practices (0.00 < τpractice < 0.08) and countries (0.10 < τcountry < 0.19). For instance, based on existing evidence, stakeholders can expect gratitude interventions deployed in a randomly-selected country to improve positive affect – but not our other measured outcomes. To guide future inquiry into why this might be the case, we provide exploratory Bayesian estimates of the importance of 12 types of cross-cultural differences.

  Publisher

• A framework for studying the conceptual structure of human relationships

  Trends in Cognitive Sciences · 2025-04-07

  reviewSenior author
  PublisherDOI

• Loneliness is associated with unstable and distorted emotion transition predictions

  Communications Psychology · 2025-08-28

  articleOpen access

  Abstract Loneliness is associated with disruptions in socio-cognitive processes, including altered self-other representations and atypical processing of external stimuli. Here, we examine whether loneliness is characterized by altered expectations of emotion transitions for both oneself and others, which may contribute to the observed disruptions in socio-cognitive processes and pose challenges for social connection. Drawing on data from seven studies (total N = 1730; N Study1 = 113; N Study2 = 185; N Study3 = 376; N Study4 = 91; N Study5 = 68; N Study6 = 41; N Study7 = 856) using a validated emotion transition task, we found that lonely individuals hold atypical expectations about both their own and others’ likelihoods to transition between emotions and are less accurate at predicting others’ emotion transitions. While lonely participants relied less on their own emotion transition patterns when predicting others’ emotions, they also showed a response pattern that may reflect reduced confidence, suggesting they use a less stable or altered strategy for predicting others. Furthermore, lonely individuals perceived others as more volatile, expecting them to switch emotion valence states more frequently and be less likely to maintain the same emotion state. At the same time, they viewed themselves as more likely to shift away from positive states. Altogether, these findings suggest that loneliness is associated with unstable, inaccurate expectations of emotion continuity in others and a bias against sustaining positive emotions in the self—patterns that may contribute to challenges in social interactions and reinforce feelings of isolation.

  PublisherOA PDFDOI

• Toward a computational understanding of bribe‐taking behavior

  Annals of the New York Academy of Sciences · 2025-02-12 · 1 citations

  reviewOpen access

  Understanding how corrupt behavior occurs is a critical issue at the intersection of behavioral ethics, social psychology, and other related social sciences, laying the foundation for establishing effective anticorruption policies. Despite a substantial body of studies focused on bribe-taking behavior-a typical form of corruption-and its modulators, its underlying psychological processes remain poorly understood. Drawing inspiration from recent literature on neuroeconomics and moral decision-making, we argue that bribe-taking decision-making involves a value-based computational process that can be characterized by a computational framework. We show how this framework advances our understanding of bribe-taking decision-making by (1) clarifying how the cost-benefit tradeoff determines the decision to accept or reject a bribe and its neural foundations, (2) improving the prediction of bribe-taking behaviors across contexts and individuals, and (3) enhancing our comprehension of individual differences in bribe-taking behaviors. Moreover, we delineate how this framework can benefit future research on bribery by examining the mechanisms through which various modulators impact the bribe-taking behaviors or the computational processes underlying more intricate forms of corrupt behaviors. We also discussed its potential fusion with artificial intelligence techniques in offering insights for understanding cognitive processes underlying bribe-taking behaviors and designing anticorruption strategies.

  PublisherOA PDFDOI

• Failing Others’ Expectations: Negative Emotions and Behavioral Change in Daily Life

  Research Square · 2025-12-19

  preprintOpen accessSenior author
  PublisherOA PDFDOI

• Neural correlates of evidence accumulation in social-affective decision-making under perceptual ambiguity

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-06-26

  preprintOpen accessSenior authorCorresponding

  Abstract Evidence accumulation models have been successfully applied to decision-making in sensory and cognitive domains; however, it remains unclear how this process is regulated when perceptual ambiguity arises from social-affective content. Here, we integrate computational modeling with multimodal neuroscience to characterize how perceptual ambiguity in emotion judgment shapes decision dynamics. Participants viewed perceptually ambiguous stimuli – morphed images of two categories, such as happy and fearful facial expression – and made binary categorization decisions. Using drift diffusion modeling (DDM), we first demonstrate that drift rate, a key index of evidence accumulation, decreases as perceptual ambiguity increases. Scalp electroencephalography (EEG) data reveal that the magnitude of the late positive potential (LPP) tracks the speed of evidence accumulation in both emotional and non-emotional stimulus categories, but only when the ambiguous dimension is relevant to the categorization decision. Similar to LPP magnitude, single-unit recordings from the dorsomedial prefrontal cortex (dmPFC) and amygdala show that neuronal firing rates in both regions also encode drift rate during the emotion categorization task. Moreover, fMRI-based functional connectivity reveals that the strength of connectivity between the amygdala and dmPFC correlates with individual differences in drift rate. To establish the causal role of the dmPFC, we applied anodal transcranial direct current stimulation (tDCS) targeting the dmPFC in patients with schizophrenia and found that stimulation enhanced evidence accumulation speed in emotion categorization under perceptual ambiguity. These findings identify a distributed corticolimbic circuit that dynamically modulates evidence accumulation during social-affective decision-making under perceptual ambiguity. Our results bridge social-affective and perceptual neuroscience, offering a translational framework for understanding emotion recognition and decision-making impairments.

  PublisherOA PDFDOI

• Peptides alleviate cognitive impairment by inhibiting and disassembling amyloid-β aggregates in Alzheimer’s disease

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-06-01 · 1 citations

  preprintOpen access

  ABSTRACT Alzheimer’s disease (AD) is a devasting neurodegenerative disorder characterized by β-amyloid formation, further exacerbated by RIPK1/RIPK3 necrosome-induced programmed necrosis (necroptosis). We previously showed that the RIPK1/RIPK3 necrosome forms a functional amyloid complex using its RIP homotypic interaction motifs (RHIMs). Here, we discovered that the core RIPK1/RIPK3 necrosome shares strikingly structural similarity to the C-terminal region of β-amyloid (Aβ42), and the RHIM-derived tetrapeptides (IQIG or VQVG) directly inhibit Aβ aggregation, disassemble preformed Aβ fibrils (PFFs), and reduce RIPK1 polymerization. Also, the peptides exhibit effective membrane permeability and could reduce Aβ40 or Aβ42-induced neural death and TNFα-induced necroptosis in SH-SY5Y cells. IQIG and VQVG injected by ICV increase learning and memory abilities by reducing Aβ plaques and hyperphosphorylated tau in the cortex and hippocampus of APP/PS1 double-transgenic mice. Mechanistically, the peptides directly interact with Aβ to block Aβ aggregation and alleviate microglia-mediated neuroinflammation. Strikingly, single-cell RNA sequencing revealed that the peptides-treated AD transgenic mice restored neuronal homeostasis with increased GABAergic neurons and decreased glutamatergic neurons. Furthermore, total cell-cell interaction strength increased while the AD risk gene Apoe expression decreased in the specific oligodendrocyte subtype of peptides-treated AD mice. Thus, our findings revealed that the peptides could improve cognition and memory capabilities and serve as promising structural templates for potential drugs against AD.

  PublisherOA PDFDOI

• Reduced harm aversion relates to antisocial behaviors and orbitofrontal atrophy in dementia patients

  Alzheimer s & Dementia · 2025-09-01 · 3 citations

  articleOpen access

  INTRODUCTION: Antisocial behaviors occur in dementia, but the underlying neurocognitive mechanisms remain underexplored. We administered a decision-making task measuring patients' harm aversion by offering options to shock themselves or another person in exchange for money, hypothesizing that task performance would relate to antisocial behaviors and ventromedial/orbitofrontal cortex (vmPFC/OFC) atrophy. METHODS: Among 43 dementia patients (n = 23 behavioral variant frontotemporal dementia [bvFTD], n = 20 Alzheimer's disease [AD]), we used linear regressions to measure relationships between harm aversion and antisocial behavior, psychopathic personality traits, socioemotional functions, and vmPFC/OFC cortical thickness, controlling for age, sex, and cognitive dysfunction. RESULTS: BvFTD patients demonstrated reduced aversion to harming others and themselves versus AD patients. Reduced aversion to harming others was associated with non-aggressive antisocial behaviors, psychopathic personality traits, impaired empathic concern, impaired perspective taking, and right vmPFC/OFC atrophy. DISCUSSION: Changes to harm aversion are associated with right frontopolar atrophy and rule-breaking criminal behavior in dementia patients. HIGHLIGHTS: Patients with behavioral variant frontotemporal dementia demonstrate reduced aversion to harming others compared to patients with AD. Reduced aversion to harming others was associated with non-aggressive behavioral changes, psychopathic personality traits, impaired empathic concern, and impaired perspective taking. Reduced aversion to harming others was associated with atrophy in the right vmPFC and OFC, specifically in medial Brodmann area 10.

  PublisherOA PDFDOI

Frequent coauthors

• Xiaolin Zhou

  East China Normal University

  130 shared

• Xiaoxue Gao

  East China Normal University

  24 shared

• Molly J. Crockett

  Center for Human Reproduction

  23 shared

• Mriganka Sur

  Massachusetts Institute of Technology

  22 shared

• Anjali Krishnan

  Brooklyn College

  18 shared

• Ania K. Majewska

  University of Rochester Medical Center

  17 shared

• Annayah Miranda Beatrice Prosser

  University of Bath

  17 shared

• Xiaolin Zhou

  Hong Kong Polytechnic University

  15 shared

Labs

• Hongbo Yu Emotion Science LabPI

Education

• PhD, Psychology

  Peking University

  2016

• B.S., Physics

  Peking University

  2010

Awards & honors

• British Academy Newton International Fellowship