Relationship between neural network structure and temperament/personality traits in healthy subjects
Introduction Cloninger divides personality into temperament and character, proposing that temperament is innate and character is shaped by environment. With the development of noninvasive methods for measuring central nervous system activity, there have been many attempts to test personality theori...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Cambridge University Press
2023-03-01
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| Series: | European Psychiatry |
| Online Access: | https://www.cambridge.org/core/product/identifier/S0924933823011641/type/journal_article |
| _version_ | 1797617470723325952 |
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| author | Y. Kawasaki Y. Koide A. Ohata T. Senoh Y. Kataoka T. Shimada T. Nagasawa T. Uehara |
| author_facet | Y. Kawasaki Y. Koide A. Ohata T. Senoh Y. Kataoka T. Shimada T. Nagasawa T. Uehara |
| author_sort | Y. Kawasaki |
| collection | DOAJ |
| description |
Introduction
Cloninger divides personality into temperament and character, proposing that temperament is innate and character is shaped by environment. With the development of noninvasive methods for measuring central nervous system activity, there have been many attempts to test personality theories using neuroscientific research methods. Thus, the use of neuroscience to examine existing theories of personality will enable a review of these theories and may lead to the formulation of new theories of personality.
Objectives
The purpose of this study was to investigate the biological factors underlying temperament and personality development in healthy adults by analyzing neural networks in the brain using resting-state functional magnetic resonance imaging.
Methods
The study was conducted after obtaining prior approval from the Ethics Committee of Kanazawa Medical University. Eighty-one healthy subjects who consented to the study after explaining the purpose and methods were imaged with a 3T MRI scanner in the resting state, and statistical image analysis was performed using the CONN toolbox. Personality and temperament were assessed using the temperament personality test based on Cloninger’s 7-dimensional model of personality.
Results
Five types of neural networks were extracted by independent component analysis, including Salience, Default mode, and Language. Regression analysis revealed a significant relationship between the functional connectivity of the networks and temperament/personality traits.
Conclusions
We were able to observe the functional connectivity of representative neural networks from the data of healthy subjects, suggesting that individual differences in the degree of functional connectivity of neural networks may be related to the individual characteristics of temperament and personality of the subjects.
Disclosure of Interest
None Declared |
| first_indexed | 2024-03-11T07:56:32Z |
| format | Article |
| id | doaj.art-2c9e15b806694eb0a28092a7102a8ef5 |
| institution | Directory Open Access Journal |
| issn | 0924-9338 1778-3585 |
| language | English |
| last_indexed | 2024-03-11T07:56:32Z |
| publishDate | 2023-03-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | European Psychiatry |
| spelling | doaj.art-2c9e15b806694eb0a28092a7102a8ef52023-11-17T05:05:29ZengCambridge University PressEuropean Psychiatry0924-93381778-35852023-03-0166S552S55210.1192/j.eurpsy.2023.1164Relationship between neural network structure and temperament/personality traits in healthy subjectsY. Kawasaki0Y. Koide1A. Ohata2T. Senoh3Y. Kataoka4T. Shimada5T. Nagasawa6T. Uehara7Neuropsychiatry, Kanazawa Medical UNiversity, Uchinada, Ishikawa, JapanNeuropsychiatry, Kanazawa Medical UNiversity, Uchinada, Ishikawa, JapanNeuropsychiatry, Kanazawa Medical UNiversity, Uchinada, Ishikawa, JapanNeuropsychiatry, Kanazawa Medical UNiversity, Uchinada, Ishikawa, JapanNeuropsychiatry, Kanazawa Medical UNiversity, Uchinada, Ishikawa, JapanNeuropsychiatry, Kanazawa Medical UNiversity, Uchinada, Ishikawa, JapanNeuropsychiatry, Kanazawa Medical UNiversity, Uchinada, Ishikawa, JapanNeuropsychiatry, Kanazawa Medical UNiversity, Uchinada, Ishikawa, Japan Introduction Cloninger divides personality into temperament and character, proposing that temperament is innate and character is shaped by environment. With the development of noninvasive methods for measuring central nervous system activity, there have been many attempts to test personality theories using neuroscientific research methods. Thus, the use of neuroscience to examine existing theories of personality will enable a review of these theories and may lead to the formulation of new theories of personality. Objectives The purpose of this study was to investigate the biological factors underlying temperament and personality development in healthy adults by analyzing neural networks in the brain using resting-state functional magnetic resonance imaging. Methods The study was conducted after obtaining prior approval from the Ethics Committee of Kanazawa Medical University. Eighty-one healthy subjects who consented to the study after explaining the purpose and methods were imaged with a 3T MRI scanner in the resting state, and statistical image analysis was performed using the CONN toolbox. Personality and temperament were assessed using the temperament personality test based on Cloninger’s 7-dimensional model of personality. Results Five types of neural networks were extracted by independent component analysis, including Salience, Default mode, and Language. Regression analysis revealed a significant relationship between the functional connectivity of the networks and temperament/personality traits. Conclusions We were able to observe the functional connectivity of representative neural networks from the data of healthy subjects, suggesting that individual differences in the degree of functional connectivity of neural networks may be related to the individual characteristics of temperament and personality of the subjects. Disclosure of Interest None Declaredhttps://www.cambridge.org/core/product/identifier/S0924933823011641/type/journal_article |
| spellingShingle | Y. Kawasaki Y. Koide A. Ohata T. Senoh Y. Kataoka T. Shimada T. Nagasawa T. Uehara Relationship between neural network structure and temperament/personality traits in healthy subjects European Psychiatry |
| title | Relationship between neural network structure and temperament/personality traits in healthy subjects |
| title_full | Relationship between neural network structure and temperament/personality traits in healthy subjects |
| title_fullStr | Relationship between neural network structure and temperament/personality traits in healthy subjects |
| title_full_unstemmed | Relationship between neural network structure and temperament/personality traits in healthy subjects |
| title_short | Relationship between neural network structure and temperament/personality traits in healthy subjects |
| title_sort | relationship between neural network structure and temperament personality traits in healthy subjects |
| url | https://www.cambridge.org/core/product/identifier/S0924933823011641/type/journal_article |
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