Nina Lauharatanahirun’s research while affiliated with William Penn University and other places

What is this page?


This page lists works of an author who doesn't have a ResearchGate profile or hasn't added the works to their profile yet. It is automatically generated from public (personal) data to further our legitimate goal of comprehensive and accurate scientific recordkeeping. If you are this author and want this page removed, please let us know.

Publications (17)


(a) Affective image rating task: A typical trial is presented. (b) Effects of image type on ratings: Means and 95% CIs are presented in the bar plot. *Statistically significant (two-tailed, p < 0.05) differences in ratings between image types. Differences between image types were tested in multilevel models as fixed effects (β) of dummy code contrasts on rating measures. See Supplemental Materials for the detailed method and results.
(a) Path coefficients and indirect effects for prototypical behavioral immunity ratings (disgust, sickness appraisals). (b) Indirect effects (a * b) of behavioral immunity ratings by image type. Whiskers indicate two-tailed 95% CIs from a wild bootstrap (10,000 iterations). *Statistically significant (two-tailed, p < 0.05) differences in indirect effects between image types. Differences were tested with a wild bootstrap (10,000 iterations). ns denotes non-significant differences (p > 0.05) in the indirect effects.
(a) Path coefficients and indirect effects for prototypical harm avoidance ratings (fear, harm appraisals). (b) Indirect effects (a * b) of harm avoidance ratings by image type. Whiskers indicate two-tailed 95% CIs from a wild bootstrap (10,000 iterations). *Statistically significant (two-tailed, p < 0.05) differences in indirect effects between image types. Differences were tested with a wild bootstrap (10,000 iterations). ns denotes non-significant differences (p > 0.05) in the indirect effects
The psychological costs of behavioral immunity following COVID-19 diagnosis
  • Article
  • Full-text available

April 2024

·

18 Reads

·

Evaline Y. Li

·

·

[...]

·

Nina Lauharatanahirun

Prior COVID-19 infection may elevate activity of the behavioral immune system—the psychological mechanisms that foster avoidance of infection cues—to protect the individual from contracting the infection in the future. Such “adaptive behavioral immunity” may come with psychological costs, such as exacerbating the global pandemic’s disruption of social and emotional processes (i.e., pandemic disruption). To investigate that idea, we tested a mediational pathway linking prior COVID infection and pandemic disruption through behavioral immunity markers, assessed with subjective emotional ratings. This was tested in a sample of 734 Mechanical Turk workers who completed study procedures online during the global pandemic (September 2021–January 2022). Behavioral immunity markers were estimated with an affective image rating paradigm. Here, participants reported experienced disgust/fear and appraisals of sickness/harm risk to images varying in emotional content. Participants self-reported on their previous COVID-19 diagnosis history and level of pandemic disruption. The findings support the proposed mediational pathway and suggest that a prior COVID-19 infection is associated with broadly elevated threat emotionality, even to neutral stimuli that do not typically elicit threat emotions. This elevated threat emotionality was in turn related to disrupted socioemotional functioning within the pandemic context. These findings inform the psychological mechanisms that might predispose COVID survivors to mental health difficulties.

Download

External and Internal Attribution in Human-Agent Interaction: Insights from Neuroscience and Virtual Reality

January 2024

·

8 Reads

Human-Machine Communication

Agents are designed in the image of humans, both internally and externally. The internal systems of agents imitate the human brain, both at the levels of hardware (i.e., neuromorphic computing) and software (i.e., neural networks). Furthermore, the external appearance and behaviors of agents are designed by people and based on human data. Sometimes, these humanlike qualities of agents are purposely selected to increase their social influence over human users, and sometimes the human factors that influence perceptions of agents are hidden. Inspired by Blascovich’s “threshold of social influence’, a model designed to explain the effects of different methods of anthropomorphizing embodied agents in virtual environments, we propose a novel framework for understanding how humans’ attributions of human qualities to agents affects their social influence in human-agent interaction. The External and Internal Attributions model of social influence (EIA) builds on previous work on agent-avatars in immersive virtual reality and provides a framework to link previous social science theories to neuroscience. EIA connects external and internal attributions of agents to two brain networks related to social influence. the external perception system, and the mentalizing system. Focusing human-agent interaction research along each of the attributional dimensions of the EIA model, or at the functional integration of the two, may lead to a better understanding of the thresholds of social influence necessary for optimal human-agent interaction.


Social Media and the Social Brain

October 2023

·

514 Reads

·

1 Citation

This edited volume examines the ways in which rapidly changing technologies and patterns of media use influence, and are influenced by, our emotional experiences. Following introductory chapters outlining common conceptual frameworks used in the study of emotion and digital media effects, this book is then organized around four general areas highlighting the intersection of technology use and emotional experience: how people experience, and researchers measure, emotions in response to digital media use; potential emotional harms and enrichments resulting from online behaviors; the socio-emotional dynamics of online interaction; and emotion’s role in engagement with online information. Chapters span a wide range of topics, including psychophysiological and neuroscientific responses to new media, virtual reality, social media and well-being, technology addiction, cyberbullying, online hate and empathy, online romantic relationships, self-presentation online, information seeking, message sharing, social support, polarization, misinformation, and more. Through a social scientific lens, contributing authors provide nuanced, interdisciplinary perspectives on contemporary social phenomena, offering cogent reviews and critiques of the literatures and avenues for future research. In essence, this volume highlights the centrality of emotions in understanding how ever-present media technologies influence our lived experiences.


Fig. 1. A) Adolescents made 72 decisions between pairs of risky gambles in an economic lottery choice task (Holt and Laury, 2002). Each gamble consisted of a high and low monetary outcome with an associated probability. Outcomes and probabilities were represented with corresponding colors (pink and blue). The time course of a given trial included a decision phase followed by a jittered fixation interval and an outcome phase, in which participants were shown the results of their choice followed by a jittered inter-trial interval (ITI). B) Distribution of behavioral risk sensitivity scores within each wave, where lower values indicate greater risk aversion. The dotted lines represent the mean. C) Distribution of behavioral reward sensitivity scores within each wave. Higher values indicate greater reward seeking. The dotted lines represent the mean.
Fig. 5. Relation between Wave 1 risk-related brain activation in the right insular cortex and the change in health risk behaviors from Wave 1 to Wave 3.
Risk-related brain activation is linked to longitudinal changes in adolescent health risk behaviors

August 2023

·

18 Reads

·

2 Citations

Developmental Cognitive Neuroscience

Middle adolescence is the period of development during which youth begin to engage in health risk behaviors such as delinquent behavior and substance use. A promising mechanism for guiding adolescents away from risky choices is the extent to which adolescents are sensitive to the likelihood of receiving valued outcomes. Few studies have examined longitudinal change in adolescent risky decision making and its neural correlates. To this end, the present longitudinal three-wave study (Nw1 = 157, Mw1= 13.50 years; Nw2 = 148, Mw2= 14.52 years; Nw3 = 143, Mw3= 15.55 years) investigated the ontogeny of mid-adolescent behavioral and neural risk sensitivity, and their baseline relations to longitudinal self-reported health risk behaviors. Results showed that adolescents became more sensitive to risk both in behavior and the brain during middle adolescence. Across three years, we observed lower risk-taking and greater risk-related activation in the bilateral insular cortex. When examining how baseline levels of risk sensitivity were related to longitudinal changes in real-life health risk behaviors, we found that Wave 1 insular activity was related to increases in self-reported health risk behaviors over the three years. This research highlights the normative maturation of risk-related processes at the behavioral and neural levels during mid-adolescence.



Social perception in Human-AI teams: Warmth and competence predict receptivity to AI teammates

March 2023

·

147 Reads

·

45 Citations

Computers in Human Behavior

Advances in artificial intelligence (AI) promise a future where teams consist of people and intelligent machines, such as robots or virtual agents. In order for human-AI teams (HATs) to succeed, human team members will need to be receptive to their new AI counterparts. In this study, we draw on a tripartite model of human newcomer receptivity, which includes three components: reflection, knowledge utilization, and psychological acceptance. We hypothesize that two aspects of social perception—warmth and competence—are critical predictors of human receptivity to a new AI teammate. Study 1 uses a video vignette design in which participants imagine adding one of eight AI teammates to a referent team. Study 2 leverages a Wizard of Oz methodology in laboratory teams. In addition to testing the effects of perceived warmth and competence on receptivity components, Study 2 also explores the influence of receptivity components on perceived HAT viability. Though both studies find that perceived warmth and competence affect receptivity, we find competence is particularly important for knowledge utilization and psychological acceptance. Further, results of Study 2 show that psychological acceptance is positively related to perceived HAT viability. Implications for future research on social perception of AI teammates are discussed.


Vero: An accessible method for studying human-AI teamwork

December 2022

·

140 Reads

·

14 Citations

Computers in Human Behavior

Despite the recognized need to prepare for a future of human-AI collaboration, the technical skills necessary to develop and deploy AI systems are considerable, making such research difficult to perform without specialized knowledge. To make human-AI collaboration research more accessible, we developed a novel experimental method that combines a standard video conferencing platform, a set of animations, and Wizard of Oz methods to simulate a group interaction with an AI teammate. Through a case study, we demonstrate the flexibility and ease of deployment of this approach. We also provide evidence that the method creates a highly believable experience of interacting with an AI agent. By detailing this method, we hope that researchers regardless of background can replicate it to more easily answer questions that will inform the design and development of future human-AI collaboration technologies.


Schematic of experimental procedure.
Effect of advice source on acceptance of advice. (A) Percentage of observations where individuals changed their answer after being provided with advice. The overall rate encompasses all 2772 observations. Each subsequent comparison filters the data by advice format, question difficulty, or advice quality. All differences are statistically significant using Tukey multiple comparison tests at the 95% confidence level. (B) Specification chart illustrating estimates of the coefficient for the effect of algorithmic advice on whether participants changed answers. Each model has a varying number of control variables. The boxes below the chart indicate which controls are included (filled box) or excluded (empty box). The main result is highlighted in purple and contains all controls. All estimates are produced by mixed effects logistic regression models with random slopes for the participants. Intervals are 95% and 99% confidence intervals for the estimates; the grey band is one standard deviation above and below the main estimate.
Effect of advice source on rate of identifying correct answer. (A) Percentage of observations where individuals identified the correct answer after being provided with advice. The overall rate encompasses all 2772 observations. Each subsequent comparison filters the data by advice format, question difficulty, or advice quality. All differences are statistically significant using Tukey multiple comparison tests at the 95% confidence level. (B) Specification chart illustrating estimates of the coefficient for the effect of algorithmic advice on whether participants identified the correct answer. Each model has a varying number of control variables. The boxes below the chart indicate which controls are included (filled box) or excluded (empty box). The main result is highlighted in purple and contains all controls. All estimates are produced by mixed effects logistic regression models with random slopes for the participants. Intervals are 95% and 99% confidence intervals for the estimates; the grey band is one standard deviation above and below the main estimate.
Relationship between advice source, quality of advice, and confidence. (A) The relationship between participants’ Initial Confidence and Final Confidence, broken down by advice source and quality. Purple lines indicate algorithmic advice, and solid lines indicate high quality advice. All lines are linear best fits with 95% confidence bands. (B) The estimated marginal mean Final Confidence, accounting for initial confidence. Error bars represent one standard deviation. All pairwise differences between marginal means are statistically significant at p<0.01\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$p<0.01$$\end{document} using Tukey’s multiple comparison criterion.
Human preferences toward algorithmic advice in a word association task

August 2022

·

106 Reads

·

11 Citations

Algorithms provide recommendations to human decision makers across a variety of task domains. For many problems, humans will rely on algorithmic advice to make their choices and at times will even show complacency. In other cases, humans are mistrustful of algorithmic advice, or will hold algorithms to higher standards of performance. Given the increasing use of algorithms to support creative work such as text generation and brainstorming, it is important to understand how humans will respond to algorithms in those scenarios—will they show appreciation or aversion? This study tests the effects of algorithmic advice for a word association task, the remote associates test (RAT). The RAT task is an established instrument for testing critical and creative thinking with respect to multiple word association. We conducted a preregistered online experiment (154 participants, 2772 observations) to investigate whether humans had stronger reactions to algorithmic or crowd advice when completing multiple instances of the RAT. We used an experimental format in which subjects see a question, answer the question, then receive advice and answer the question a second time. Advice was provided in multiple formats, with advice varying in quality and questions varying in difficulty. We found that individuals receiving algorithmic advice changed their responses 13% more frequently (χ2=59.06, p<0.001) and reported greater confidence in their final solutions. However, individuals receiving algorithmic advice also were 13% less likely to identify the correct solution (χ2=58.79, p<0.001). This study highlights both the promises and pitfalls of leveraging algorithms to support creative work.


Relationship between parental education and inhibitory performance. Note: Scatterplot showing the relationship between parental education and individual differences in inhibitory performance (i.e., efficiency scores). Robustness checks also verified that the relationship between parental education and inhibitory performance remained nonsignificant when removing potential outliers beyond 3 SD ((β = − 0.00, t(66) = − 0.02, p = 0.986, r² = 0.00, CI = [− 0.24, 0.24]), suggesting the lack of a relationship is not driven by an outlier (see scatterplot in supplemental materials). Scatterplot was created using ggplot2 in the ggplot2 (version 3.3.5) package (https://ggplot2.tidyverse.org).
Relationship between parental education and activity in classic frontal-subcortical response inhibition pathway. Note: Scatterplot showing the relationship between parental education and activity in the rIFG, rSTN, and rGP during successful no-go > successful go trials. Robustness checks verified that the relationship between parental education and activity in the rIFG + rSTN + rGP remained significant when excluding potential outliers beyond 3 SD ((β = 0.04, t(67) = 3.13, p = 0.003, r² = 0.06, CI = [0.12, 0.53]), suggesting the relationship is not driven by an outlier (see scatterplot in supplemental materials). Scatterplot was created using ggplot2 in the ggplot2 (version 3.3.5) package (https://ggplot2.tidyverse.org).
Response inhibition task. Note: Response inhibition was measured using the go/no-go task. We focus on the contrast (correct no-go trials > correct go trials).
Regions of interest. Note: Our primary regions of interest included the right inferior frontal gyrus (rIFG), right subthalamic nucleus (rSTN), and right globus pallidus (rGP), which comprises the classic “frontal-subcortical pathway” to response inhibition⁴⁸. ROI image was created using MRIcroGL (version 17; https://ggplot2.tidyverse.org).
Parental education is associated with differential engagement of neural pathways during inhibitory control

January 2022

·

99 Reads

·

10 Citations

Response inhibition and socioeconomic status (SES) are critical predictors of many important outcomes, including educational attainment and health. The current study extends our understanding of SES and cognition by examining brain activity associated with response inhibition, during the key developmental period of adolescence. Adolescent males ( N = 81), aged 16–17, completed a response inhibition task while undergoing fMRI brain imaging and reported on their parents’ education, one component of socioeconomic status. A region of interest analysis showed that parental education was associated with brain activation differences in the classic response inhibition network (right inferior frontal gyrus + subthalamic nucleus + globus pallidus) despite the absence of consistent parental education-performance effects. Further, although activity in our main regions of interest was not associated with performance differences, several regions that were associated with better inhibitory performance (ventromedial prefrontal cortex, middle frontal gyrus, middle temporal gyrus, amygdala/hippocampus) also differed in their levels of activation according to parental education. Taken together, these results suggest that individuals from households with higher versus lower parental education engage key brain regions involved in response inhibition to differing degrees, though these differences may not translate into performance differences.


Trust and Risk: Neuroeconomic Foundations of Trust Based on Social Risk

November 2021

·

26 Reads

·

2 Citations

Trust is essential for establishing and maintaining cooperative behaviors between individuals and institutions in a wide variety of social, economic, and political contexts. This book explores trust through the lens of neurobiology, focusing on empirical, methodological, and theoretical aspects. Written by a distinguished group of researchers from economics, psychology, human factors, neuroscience, and psychiatry, the chapters shed light on the neurobiological underpinnings of trust as applied in a variety of domains. Researchers and students will discover a refined understanding of trust by delving into the essential topics in this area of study outlined by leading experts.


Citations (12)


... That type of alcohol drinking has short and long-term problems for the adolescent, like intoxication, depression [8], social rejection [9], and other neuronal alterations, like reduction in the volume of the grey matter and decrease in white matter integrity [10]. During childhood and adolescence, the brain undergoes several maturation processes that require neurotransmission changes and synaptic plasticity related to structural modifications in different brain regions [11][12][13][14]. Some studies reported smaller hippocampal decision making [45,46], we believe that mPFC function and decision making could be impaired by binge-like alcohol administration through the impaired interplay between Hp, Ht, and mPFC. ...

Reference:

Binge-like Alcohol Administration Alters Decision Making in an Adolescent Rat Model: Role of N-Methyl-D-Aspartate Receptor Signaling
Risk-related brain activation is linked to longitudinal changes in adolescent health risk behaviors

Developmental Cognitive Neuroscience

... In contemporary society, social media has become a necessity. It is used by individuals of all ages, nationalities, and religions for diverse purposes such as information, entertainment, and communication [2]. However, the pace of this maturation process is not always in line with the rapid advancement of information technology in social media as stated in abc research that social media addiction is emotionally immature [3]. ...

Social Media and the Social Brain
  • Citing Chapter
  • October 2023

... Positive evaluation of functionality such as perceived usefulness and competence facilitates one's acceptance of AI as well as other related work outcomes (e.g., Harris-Watson et al., 2023;Park et al., 2024). ...

Social perception in Human-AI teams: Warmth and competence predict receptivity to AI teammates
  • Citing Article
  • March 2023

Computers in Human Behavior

... This is as yet unknown, but it leads to a second question of whether we can tell the difference between a human and an AI. In a recent study of 'emotional attachment' to AI as team members [89], most participants could tell the difference between an AI and a human based on their interactions with both. Another study [90] examined human trust in AIs as a function of the perception of the AI's identity. ...

Vero: An accessible method for studying human-AI teamwork
  • Citing Article
  • December 2022

Computers in Human Behavior

... (algorithmic appreciation 15 ). This tendency is particularly evident in tasks with measurable outcomes that require logical problem-solving or in judgments under uncertainty 16 . The underlying mechanisms leading to either algorithmic aversion or appreciation are not yet fully understood, with several advice characteristics proposed as potentially relevant, including the quality of advice. ...

Human preferences toward algorithmic advice in a word association task

... While not the primary focus, other covariates (i.e., caregiver education levels, age, sex at birth) were independent predictors of BOLD signaling. Higher parental education attainment was related to greater BOLD signaling in the IFG, ACC, pre-SMA, and dlPFC, which is consistent with research demonstrating a positive relationship between parental education and activation in inhibitory control regions (Cascio et al., 2022). Reported sex differences in activation patterns are consistent with findings in the adult literature where males show greater BOLD response during successful inhibition (Weafer, 2020). ...

Parental education is associated with differential engagement of neural pathways during inhibitory control

... This result is in line with a meta-analysis in adults, which examined the gender differences in baseline trust behavior [33], and with some studies of adolescents [17,49]. Trusting others has been suggested to involve risk-taking as one does not know whether their trust will be reciprocated; hence, there is a chance of betrayal of trust [50]. The increased risk-taking tendencies seen in men compared to women may explain the gender differences in initial trust behavior [33,51]. ...

Trust and Risk: Neuroeconomic Foundations of Trust Based on Social Risk
  • Citing Chapter
  • November 2021

... Literature suggests that decisions undertaken by ethnic minorities on code switching and how to linguistically represent themselves may be motivated by a desire both to conform to perceived norms and to avoid stereotypes and discrimination (DeJordy, 2008;Newheiser & Barreto, 2014). Code switching requires additional cognitive effort and often causes stress and other negative psychological consequences for the individual (Johnson et al., 2021). The students suggested that offering more resources might be advantageous for new minority ethnic students. ...

Social-Cognitive and Affective Antecedents of Code Switching and the Consequences of Linguistic Racism for Black People and People of Color
  • Citing Article
  • September 2021

Affective Science

... In this manuscript, we operationally defined a neuronal avalanche, as an event that begins when the amplitude of at least one region deviates from its baseline and ends when all regions restore their typical amplitude. Previous studies analysed the high-amplitude burst activity of the brain through the neuronal avalanche approach in resting state conditions, demonstrating power-law probability distributions of the size and duration of the avalanche and showing a balance between ongoing and future neuronal activity [17][18][19] . An avalanche pattern is the set of all the brain areas that were recruited during an avalanche, and the functional repertoire is the set of the unique avalanche patterns (for a full explanation see Table 1). ...

Scale-specific dynamics of high-amplitude bursts in EEG capture behaviorally meaningful variability
  • Citing Article
  • July 2021

NeuroImage

... Une équipe humain-autonomie y est définie comme un collectif interdépendant dans l'activité et le résultat, impliquant un ou plusieurs humains et un ou plusieurs agents artificiels, dans lequel chacun est considéré comme un membre à part entière et occupe un rôle distinct, et dont tous les membres s'efforcent d'atteindre un objectif commun [14]. Pour Sciara et al., afin qu'un agent artificiel puisse interagir à la manière d'un coéquipier, lui et ses partenaires humains devront être capables d'anticiper et de s'adapter à l'état des autres [17]. Afin d'être véritablement au service du décideur et de lui apporter une valeur ajoutée, les outils de recommandation ergonomique se doivent d'intégrer les limites cognitives, émotionnelles et sociales qui structurent la prise de décision humaine [8]. ...

Adaptation in Human-Autonomy Teamwork
  • Citing Conference Paper
  • September 2020