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1. Culture and Gender Modulate dlPFC Integration in the Emotional Brain: Evidence from Dynamic Caus-al Modeling

   Pugh, Z.H.; Huang, J.; Leshin, J.; Lindquist, K.A.; Nam, C.S. (February 2023, Cognitive neurodynamics)

   Past research has recognized culture and gender variation in the experience of emotion, yet this has not been examined on a level of effective connectivity. To determine culture and gender differences in effec-tive connectivity during emotional experiences, we applied dynamic causal modeling (DCM) to electro-encephalography (EEG) measures of brain activity obtained from Chinese and American participants while they watched emotion-evoking images. Relative to US participants, Chinese participants favored a model bearing a more integrated dorsolateral prefrontal cortex (dlPFC) during fear v. neutral experiences. Meanwhile, relative to males, females favored a model bearing a less integrated dlPFC during fear v. neutral experiences. A culture-gender interaction for winning models was also observed; only US partici-pants showed an effect of gender, with US females favoring a model bearing a less integrated dlPFC compared to the other groups. These findings suggest that emotion and its neural correlates depend in part on the cultural background and gender of an individual. To our knowledge, this is also the first study to apply both DCM and EEG measures in examining culture-gender interaction and emotion. 

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2. Resilience in Action through Culture: Latinas Successfully Navigating STEM Spaces at an HSI

   https://doi.org/10.3390/educsci14080848  

   Perez, Emma Claudia; Gonzalez, Elsa Maria; Sanchez_Hernandez, Isabella (August 2024, Education Sciences)

   Though research on the perspectives and assets of communities of color in higher education has grown, understanding how underrepresented groups in STEM use those assets to navigate and succeed in STEM fields is still in progress. In this study, Latina students majoring in STEM fields in a Hispanic-Serving Institution (HSI) were interviewed about their college experience and persistence. A Latine resilience model and an HSI servingness framework guided the analysis. Qualitative methodology via case study served to understand this research. Evidence gathered in this study demonstrates how social climate experiences and cultural background influence resilience and success strategies among diverse Latina STEM majors in an HSI. The STEM social climate or culture seemingly clashed with participants’ cultural backgrounds. Perhaps most pertinent to their cultural background and resilience as Latinas were the specific success strategies or assets that participants utilized to navigate the STEM experience. Participants gravitated to diverse spaces, desired more women and ethnic representation in their STEM departments, and practiced prosocial or communal motivations. Understanding STEM culture in conjunction with the assets and strategies that Latinas utilize as ethnic women is important for HSIs as they consider how they truly serve their constituents. 

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3. CULEMO: Cultural Lenses on Emotion--Benchmarking LLMs for Cross-Cultural Emotion Understanding

   Belay, T; Ahmed, A; Grissom_II, A; Ameer, I; Sidorov, G; Kolesnikova, O; Yimam, S (July 2025, Association for Computational Linguistics (ACL))

   NLP research has increasingly focused on subjective tasks such as emotion analysis. However, existing emotion benchmarks suffer from two major shortcomings: (1) they largely rely on keyword-based emotion recognition, overlooking crucial cultural dimensions required for deeper emotion understanding, and (2) many are created by translating English-annotated data into other languages, leading to potentially unreliable evaluation. To address these issues, we introduce Cultural Lenses on Emotion (CuLEmo), the first benchmark designed to evaluate culture-aware emotion prediction across six languages: Amharic, Arabic, English, German, Hindi, and Spanish. CuLEmo comprises 400 crafted questions per language, each requiring nuanced cultural reasoning and understanding. We use this benchmark to evaluate several state-of-the-art LLMs on culture-aware emotion prediction and sentiment analysis tasks. Our findings reveal that (1) emotion conceptualizations vary significantly across languages and cultures, (2) LLMs performance likewise varies by language and cultural context, and (3) prompting in English with explicit country context often outperforms in-language prompts for culture-aware emotion and sentiment understanding. The dataset and evaluation code are publicly available. 

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4. Pipeline for Cultural Context Grounding of Conversations

   Pujari, Rajkumar; Goldwasser, Dan (May 2025, Association for Computational Linguistics)

   Conversations often adhere to well-understood social norms that vary across cultures. For example, while addressing work superiors by their first name is commonplace in the Western culture, it is rare in Asian cultures. Adherence or violation of such norms often dictates the tenor of conversations. Humans are able to navigate social situations requiring cultural awareness quite adeptly. However, it is a hard task for NLP models. In this paper, we tackle this problem by introducing a Cultural Context Schema for conversations. It comprises (1) conversational information such as emotions, dialogue acts, etc., and (2) cultural information such as social norms, violations, etc. We generate ∼110k social norm and violation descriptions for ∼23k conversations from Chinese culture using LLMs. We refine them using automated verification strategies which are evaluated against culturally aware human judgements. We organize these descriptions into meaningful structures we call Norm Concepts, using an interactive human-in-the-loop framework. We ground the norm concepts and the descriptions in conversations using symbolic annotation. Finally, we use the obtained dataset for downstream tasks such as emotion, sentiment, and dialogue act detection. We show that it significantly improves the empirical performance. 

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5. The Influence of Social Information on Speech Intelligibility within the Spanish Heritage Community

   https://doi.org/10.3390/languages7030231  

   Staggs, Cecelia; Baese-Berk, Melissa; Nagle, Charlie (September 2022, Languages)

   Previous research in speech perception has shown that perception is influenced by social factors that can result in behavioral consequences such as reduced intelligibility (i.e., a listeners’ ability to transcribe the speech they hear). However, little is known about these effects regarding Spanish speakers’ perception of heritage Spanish, Spanish spoken by individuals who have an ancestral and cultural connection to the Spanish language. Given that ideologies within the U.S. Latino community often equate Latino identity to speaking Spanish “correctly” and proficiently, there is a clear need to understand the potential influence these ideologies have on speech perception. Using a matched-guised methodology, we analyzed the influence of speaker social background information and listener social background information on speech perception. Participants completed a transcription task in which four different Spanish heritage speakers were paired with different social guises to determine if the speakers were perceived as equally intelligible under each guise condition. The results showed that social guise and listener social variables did not significantly predict intelligibility scores. We argue that the unique socio-political culture within the U.S. Latino community may lead to different effects of language ideology and social expectation on speech perception than what has been documented in previous work. 

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