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Hsiao PYA, Kim MJ, Chou FCB, Chen PHA. Intersubject representational similarity analysis uncovers the impact of state anxiety on brain activation patterns in the human extrastriate cortex. Brain Imaging Behav 2024; 18:412-420. [PMID: 38324234 DOI: 10.1007/s11682-024-00854-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/16/2024] [Indexed: 02/08/2024]
Abstract
The current study used functional magnetic resonance imaging (fMRI) and showed that state anxiety modulated extrastriate cortex activity in response to emotionally-charged visual images. State anxiety and neuroimaging data from 53 individuals were subjected to an intersubject representational similarity analysis (ISRSA), wherein the geometries between neural and behavioral data were compared. This analysis identified the extrastriate cortex (fusiform gyrus and area MT) to be the sole regions whose activity patterns covaried with state anxiety. Importantly, we show that this brain-behavior association is revealed when treating state anxiety data as a multidimensional response pattern, rather than a single composite score. This suggests that ISRSA using multivariate distances may be more sensitive in identifying the shared geometries between self-report questionnaires and brain imaging data. Overall, our findings demonstrate that a transient state of anxiety may influence how visual information - especially those relevant to the valence dimension - is processed in the extrastriate cortex.
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Affiliation(s)
- Po-Yuan A Hsiao
- Department of Psychology, National Taiwan University, Taipei, Taiwan
| | - M Justin Kim
- Department of Psychology, Sungkyunkwan University, Seoul, South Korea
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, South Korea
| | - Feng-Chun B Chou
- Department of Psychology, National Taiwan University, Taipei, Taiwan
| | - Pin-Hao A Chen
- Department of Psychology, National Taiwan University, Taipei, Taiwan.
- Neurobiology and Cognitive Science Center, National Taiwan University, Taipei, Taiwan.
- Graduate Institute of Brain and Mind Sciences, National Taiwan University, Taipei, Taiwan.
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Zhou Z, Chen YY, Yang B, Qu Y, Lee TH. Family Cohesion Moderates the Relation between Parent-Child Neural Connectivity Pattern Similarity and Youth's Emotional Adjustment. J Neurosci 2023; 43:5936-5943. [PMID: 37400252 PMCID: PMC10436682 DOI: 10.1523/jneurosci.0349-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Revised: 06/05/2023] [Accepted: 06/06/2023] [Indexed: 07/05/2023] Open
Abstract
Despite a recent surge in research examining parent-child neural similarity using fMRI, there remains a need for further investigation into how such similarity may play a role in children's emotional adjustment. Moreover, no prior studies explored the potential contextual factors that may moderate the link between parent-child neural similarity and children's developmental outcomes. In this study, 32 parent-youth dyads (parents: M age = 43.53 years, 72% female; children: M age = 11.69 years, 41% female) watched an emotion-evoking animated film while being scanned using fMRI. We first quantified how similarly emotion network interacts with other brain regions in responding to the emotion-evoking film between parents and their children. We then examined how such parent-child neural similarity is associated with children's emotional adjustment, with attention to the moderating role of family cohesion. Results revealed that higher parent-child similarity in functional connectivity pattern during movie viewing was associated with better emotional adjustment, including less negative affect, lower anxiety, and greater ego resilience in youth. Moreover, such associations were significant only among families with higher cohesion, but not among families with lower cohesion. The findings advance our understanding of the neural mechanisms underlying how children thrive by being in sync and attuned with their parents, and provide novel empirical evidence that the effects of parent-child concordance at the neural level on children's development are contextually dependent.SIGNIFICANCE STATEMENT What neural processes underlie the attunement between children and their parents that helps children thrive? Using a naturalistic movie-watching fMRI paradigm, we find that greater parent-child similarity in how emotion network interacts with other brain regions during movie viewing is associated with youth's better emotional adjustment including less negative affect, lower anxiety, and greater ego resilience. Interestingly, these associations are only significant among families with higher cohesion, but not among those with lower cohesion. Our findings provide novel evidence that parent-child shared neural processes to emotional situations can confer benefits to children, and underscore the importance of considering specific family contexts in which parent-child neural similarity may be beneficial or detrimental to children's development, highlighting a crucial direction for future research.
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Affiliation(s)
- Zexi Zhou
- Department of Human Development and Family Sciences, University of Texas at Austin, Austin, Texas 78712
| | - Ya-Yun Chen
- Department of Psychology, Virginia Tech, Blacksburg, Virginia 24061
| | - Beiming Yang
- School of Education and Social Policy, Northwestern University, Evanston, Illinois 60208
| | - Yang Qu
- School of Education and Social Policy, Northwestern University, Evanston, Illinois 60208
| | - Tae-Ho Lee
- Department of Psychology, Virginia Tech, Blacksburg, Virginia 24061
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Lopez-de-Ipina K, Iradi J, Fernandez E, Calvo PM, Salle D, Poologaindran A, Villaverde I, Daelman P, Sanchez E, Requejo C, Suckling J. HUMANISE: Human-Inspired Smart Management, towards a Healthy and Safe Industrial Collaborative Robotics. SENSORS (BASEL, SWITZERLAND) 2023; 23:1170. [PMID: 36772209 PMCID: PMC9920065 DOI: 10.3390/s23031170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Revised: 01/10/2023] [Accepted: 01/14/2023] [Indexed: 06/18/2023]
Abstract
The workplace is evolving towards scenarios where humans are acquiring a more active and dynamic role alongside increasingly intelligent machines. Moreover, the active population is ageing and consequently emerging risks could appear due to health disorders of workers, which requires intelligent intervention both for production management and workers' support. In this sense, the innovative and smart systems oriented towards monitoring and regulating workers' well-being will become essential. This work presents HUMANISE, a novel proposal of an intelligent system for risk management, oriented to workers suffering from disease conditions. The developed support system is based on Computer Vision, Machine Learning and Intelligent Agents. Results: The system was applied to a two-arm Cobot scenario during a Learning from Demonstration task for collaborative parts transportation, where risk management is critical. In this environment with a worker suffering from a mental disorder, safety is successfully controlled by means of human/robot coordination, and risk levels are managed through the integration of human/robot behaviour models and worker's models based on the workplace model of the World Health Organization. The results show a promising real-time support tool to coordinate and monitoring these scenarios by integrating workers' health information towards a successful risk management strategy for safe industrial Cobot environments.
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Affiliation(s)
- Karmele Lopez-de-Ipina
- Department of Psychiatry, University of Cambridge, Cambridge CB2 3PT, UK
- EleKin Lab, Systems Engineering and Automation, Computers’ Architecture and Technology, and Enterprise Management Departments, University of the Basque Country UPV/EHU, 20018 Donostia-San Sebastian, Spain
| | - Jon Iradi
- EleKin Lab, Systems Engineering and Automation, Computers’ Architecture and Technology, and Enterprise Management Departments, University of the Basque Country UPV/EHU, 20018 Donostia-San Sebastian, Spain
| | - Elsa Fernandez
- EleKin Lab, Systems Engineering and Automation, Computers’ Architecture and Technology, and Enterprise Management Departments, University of the Basque Country UPV/EHU, 20018 Donostia-San Sebastian, Spain
| | - Pilar M. Calvo
- EleKin Lab, Systems Engineering and Automation, Computers’ Architecture and Technology, and Enterprise Management Departments, University of the Basque Country UPV/EHU, 20018 Donostia-San Sebastian, Spain
| | - Damien Salle
- Tecnalia Research Centre, Tecnalia Industry and Transport Division, 20009 Donostia-San Sebastia, Spain
| | - Anujan Poologaindran
- Department of Psychiatry, University of Cambridge, Cambridge CB2 3PT, UK
- The Alan Turing Institute, British Library, London NW1 2DB, UK
| | - Ivan Villaverde
- Tecnalia Research Centre, Tecnalia Industry and Transport Division, 20009 Donostia-San Sebastia, Spain
| | - Paul Daelman
- Tecnalia Research Centre, Tecnalia Industry and Transport Division, 20009 Donostia-San Sebastia, Spain
| | - Emilio Sanchez
- Department of Mechanical Engineering and Materials, Engineering School, University of Navarra, TECNUN, 20018 Donostia-San Sebastian, Spain
- CEIT, Manufacturing Division, 20018 Donostia-San Sebastian, Spain
| | - Catalina Requejo
- Cajal Institute, Consejo Superior de Investigaciones Científicas (CSIC), 28002 Madrid, Spain
| | - John Suckling
- Department of Psychiatry, University of Cambridge, Cambridge CB2 3PT, UK
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Xu HQ, Chung CC, Yu C. Visualizing Research Trends on Culture Neuroscience (2008–2021): A Bibliometric Analysis. Front Psychol 2022; 13:884929. [PMID: 35602732 PMCID: PMC9121129 DOI: 10.3389/fpsyg.2022.884929] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Accepted: 04/19/2022] [Indexed: 11/25/2022] Open
Abstract
Recently, cultural neuroscience has gained attention as a new, important, and interdisciplinary topic in the field of neuroscience. It helps us understand the interaction of cultural and biological factors over the course of life. This study aims to provide a comprehensive overview of the field to readers and potential researchers engaged in cultural neuroscience research. A bibliometric analysis was performed on 113 articles in the field of cultural neuroscience from 2008 to 2021 using data from the core collection of Web of Science. Network visualization software VOSviewer and ITGInsight were used for performance analysis and science mapping. Specifically, the performance analysis included countries, institutions, authors, papers, and journals, while science mapping analyzed the collaboration network, keyword network, bibliographic coupling network, and time series evolution. The results showed that the United States was the most productive country, Northwestern University was the most influential research institution, Chiao Jy was the most influential scholar, and “Social Cognitive and Affective Neuroscience” made the greatest contribution to publishing in the field of cultural neuroscience. Furthermore, collaboration is expected to be the development trend in the future. The key research topics in the field of cultural neuroscience included neuroimaging and psychiatric diseases, theoretical methods, interdisciplinary research, cultural differences (collectivism and individualism), and brain functions. Finally, future research will focus on cultural neuroscience, culture, and self, while adolescence will be the emerging research frontier.
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Affiliation(s)
- Han Qing Xu
- College of Science and Technology, Ningbo University, Ningbo, China
- *Correspondence: Han Qing Xu,
| | - Chih-Chao Chung
- General Research Service Center, National Pingtung University of Science and Technology, Neipu, Taiwan
- Chih-Chao Chung,
| | - Cheng Yu
- College of Science and Technology, Ningbo University, Ningbo, China
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