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Overview
Dr. Vargas' research program explores how human experiences influence the representation of information; from distributed neural signatures to associative cognitive maps and collective representations of social groups.
Dr. Vargas' research program explores how human experiences influence the representation of information; from distributed neural signatures to associative cognitive maps and collective representations of social groups.
Roberto's overarching research goal is to explain the computational principles underlying the structure of meaning and experience, identify social and computational mechanisms driving the causal interplay between levels of experience, and develop predictive models of decision making when individuals engage with their world.
Roberto's overarching research goal is to explain the computational principles underlying the structure of meaning and experience, identify social and computational mechanisms driving the causal interplay between levels of experience, and develop predictive models of decision making when individuals engage with their world.
In prep & Under review
In prep & Under review
Indicates current or former +Undergraduate Advisee
Vargas, R. & +Nazzaro, H. (in prep). Identifying Partisan-Biased Language Tokens from Commonly Consumed American News Outlets. https://osf.io/rj6n3/
Vargas, R., +Gelber, A., Verstynen, T. (in prep). Media Consumption and Identity based Concept Geometries Predict Engagement and Beliefs Towards Societal Institutions. https://osf.io/vj7e5/
Vargas, R. & Jarbo, K. (in prep). Attitudes and Actions to Predict Biased Decisions to Punish among White, Black, and Chinese Americans
Vargas, R. +Gelber, A., +Fang, R. (in prep). Racial/Ethnic and Gender Categorization of Names: Toolkit for Evoking Implicit Bias
Eng, C. M., Vargas, R. (under review). Longitudinal Investigation of Executive Function Neural Underpinnings and Resting-State Methodological Validation Using Functional Near Infrared Spectroscopy (fNIRS). https://doi.org/10.17605/OSF.IO/CMTYQ
Peer-reviewed Publications
Peer-reviewed Publications
Vargas, R. & Verstynen, T. (in press). Informational ecosystems partially explain
differences in socioenvironmental conceptual associations between U.S. American racial groups. Nature Communications Psychology. [article link, code]
Vargas, R. & Just, M. (2022) Similarities and Differences in the Neural representations of Abstract Concepts across English and Mandarin: Comparison of Underlying Dimensions of Meaning. Human Brain Mapping. https://doi.org/10.1002/hbm.25844
Vargas, R. & Just, M.A. (2021). The Neural Representation of Concrete and Abstract Concepts. In Barbey, A.K., Karama, S. & Heier, R.J. (Eds.) The Cambridge Handbook of Intelligence and Cognitive Neuroscience.
Vargas, R. & Just, M.A. (2019). Neural representations of Abstract Concepts: Identifying Underlying Neurosemantic Dimensions. Cerebral Cortex. doi.org/10.1093/cercor/bhz229
Wang, J., Cherkassky, V. L., Yang, Y., Chang, K. K., Vargas, R., Diana, N., Just, M.A. (2016) Identifying thematic roles from neural representations measured by functional magnetic resonance imaging. Cognitive Neuropsychology, 1-8. (Special Issue on Conceptual Knowledge Representation)
Price, L.R., Vargas, R., Behroosmand, R., Parkinson, A.L., Larson C.R., Greenlee, J.D.W., & Robin, D.A. (2016) Dynamic Connectivity Mapping of Electrocorticographic Data using Bayesian Differential Structural Equation Modeling. Biometrics and Biostatistics International Journal, 4.
Flagmeier, S.J., Ray, K.L., Parkinson, A.L., Li, K., Vargas, R., Laird, A., Larson, C.R. & Robin, D.A. (2014). The Neural Changes in Connectivity of the Voice Network During Error Detection and Correction. Brain and language, 132, 7-13.
Fernandez, E., Arevalo, I., Torralba, A., & Vargas, R. (2014). Norms for five parameters of anger: How do incarcerated adults differ from the community? International Journal of Forensic Mental Health, 13, 18-24
Fernandez, E., Vargas, R., Mahometa, M., Ramamurthy, S. & Boyle, G.J. (2012). Descriptors of Pain Sensation: A Dual Hierarchical Model of Latent Structure. The Journal of Pain, 13, 532-536.
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