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298 results on '"Gu, Xiaosi"'

1. Predicting Depression and Anxiety: A Multi-Layer Perceptron for Analyzing the Mental Health Impact of COVID-19

Author

Fong, David, Chu, Tianshu, Heflin, Matthew, Gu, Xiaosi, and Seneviratne, Oshani

Subjects
Computer Science - Machine Learning, Computer Science - Computers and Society
Abstract

We introduce a multi-layer perceptron (MLP) called the COVID-19 Depression and Anxiety Predictor (CoDAP) to predict mental health trends, particularly anxiety and depression, during the COVID-19 pandemic. Our method utilizes a comprehensive dataset, which tracked mental health symptoms weekly over ten weeks during the initial COVID-19 wave (April to June 2020) in a diverse cohort of U.S. adults. This period, characterized by a surge in mental health symptoms and conditions, offers a critical context for our analysis. Our focus was to extract and analyze patterns of anxiety and depression through a unique lens of qualitative individual attributes using CoDAP. This model not only predicts patterns of anxiety and depression during the pandemic but also unveils key insights into the interplay of demographic factors, behavioral changes, and social determinants of mental health. These findings contribute to a more nuanced understanding of the complexity of mental health issues in times of global health crises, potentially guiding future early interventions.

Published
2024

2. Dopamine and serotonin in human substantia nigra track social context and value signals during economic exchange

Author

Batten, Seth R., Bang, Dan, Kopell, Brian H., Davis, Arianna N., Heflin, Matthew, Fu, Qixiu, Perl, Ofer, Ziafat, Kimia, Hashemi, Alice, Saez, Ignacio, Barbosa, Leonardo S., Twomey, Thomas, Lohrenz, Terry, White, Jason P., Dayan, Peter, Charney, Alexander W., Figee, Martijn, Mayberg, Helen S., Kishida, Kenneth T., Gu, Xiaosi, and Montague, P. Read

Published
2024
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13. Human Substantia Nigra Neurons Encode Reward Expectations

Author

Imtiaz, Zarghona, primary, Kato, Ayaka, additional, Kopell, Brian H, additional, Qasim, Salman E, additional, Davis, Arianna Neal, additional, Martinez, Lizbeth Nunez, additional, Heflin, Matthew, additional, Kulkarni, Kaustubh R, additional, Morsi, Amr, additional, Gu, Xiaosi, additional, and Saez, Ignacio, additional

Published
2024
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29. Revisiting the role of computational neuroimaging in the era of integrative neuroscience

Author

Loosen, Alisa M., Kato, Ayaka, and Gu, Xiaosi

Abstract

Computational models have become integral to human neuroimaging research, providing both mechanistic insights and predictive tools for human cognition and behavior. However, concerns persist regarding the ecological validity of lab-based neuroimaging studies and whether their spatiotemporal resolution is not sufficient for capturing neural dynamics. This review aims to re-examine the utility of computational neuroimaging, particularly in light of the growing prominence of alternative neuroscientific methods and the growing emphasis on more naturalistic behaviors and paradigms. Specifically, we will explore how computational modeling can both enhance the analysis of high-dimensional imaging datasets and, conversely, how neuroimaging, in conjunction with other data modalities, can inform computational models through the lens of neurobiological plausibility. Collectively, this evidence suggests that neuroimaging remains critical for human neuroscience research, and when enhanced by computational models, imaging can serve an important role in bridging levels of analysis and understanding. We conclude by proposing key directions for future research, emphasizing the development of standardized paradigms and the integrative use of computational modeling across neuroimaging techniques.

Published
2024
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44. Testing the Behavioral Interaction and Integration of Attentional Networks

Author

Fan, Jin, Gu, Xiaosi, and Guise, Kevin G.

Abstract

One current conceptualization of attention subdivides it into functions of alerting, orienting, and executive control. Alerting describes the function of tonically maintaining the alert state and phasically responding to a warning signal. Automatic and voluntary orienting are involved in the selection of information among multiple sensory inputs. Executive control describes a set of more complex operations that include detecting and resolving conflicts in order to control thoughts or behaviors. Converging evidence supports this theory of attention by showing that each function appears to be subserved by anatomically distinct networks in the brain and differentially innervated by various neuromodulatory systems. Although much research has been dedicated to understanding the functional separation of these networks in both healthy and disease states, the interaction and integration among these networks still remain unclear. In this study, we aimed to characterize possible behavioral interaction and integration in healthy adult volunteers using a revised attention network test (ANT-R) with cue-target interval and cue validity manipulations. We found that whereas alerting improves overall response speed, it exerts negative influence on executive control under certain conditions. A valid orienting cue enhances but an invalid cue diminishes the ability of executive control to overcome conflict. The results support the hypothesis of functional integration and interaction of these brain networks. (Contains 4 tables and 6 figures.)

Published
2009
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