TY - GEN
T1 - The Effect of Feedback on Electrophysiological Signal Complexity as a Function of Attachment Style
AU - Mizrahi, Dor
AU - Laufer, Ilan
AU - Zuckerman, Inon
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024
Y1 - 2024
N2 - Attachment theory has been applied to various domains, including developmental, clinical, and social psychology. It has been instrumental in understanding the mechanisms underlying interpersonal relationships, mental health, and well-being. The attachment profiles can be divided into several styles, but the most basic set comprises two basic attachment styles, secure and insecure. Today, the current practice of measuring attachment typically involves using self-report questionnaires or interviews. However, the self-report data may be influenced by social desirability or other factors that may conceal or distort the respondents true feelings or opinions. Therefore, in this study, we will try to rely on an objective assessment of the attachment style by analyzing scalp EEG brain recordings. Specifically, we sought to investigate whether signal complexity, derived by using the method of Lempel Ziv Complexity (LZC), could differentiate between insecure and secure attachment styles based on a success or failure feedback given in the context of a flanker task. A significant interaction between attachment style and feedback type was found due to the change in complexity level between success and failure as a function of attachment type. Secure players were associated with an increase in complexity level between success and failure, whereas for insecure players no change was observed between these conditions. These results may be explained by different mechanisms of emotional regulation that are employed by secure and insecure participants. Possibilities for future research were also discussed.
AB - Attachment theory has been applied to various domains, including developmental, clinical, and social psychology. It has been instrumental in understanding the mechanisms underlying interpersonal relationships, mental health, and well-being. The attachment profiles can be divided into several styles, but the most basic set comprises two basic attachment styles, secure and insecure. Today, the current practice of measuring attachment typically involves using self-report questionnaires or interviews. However, the self-report data may be influenced by social desirability or other factors that may conceal or distort the respondents true feelings or opinions. Therefore, in this study, we will try to rely on an objective assessment of the attachment style by analyzing scalp EEG brain recordings. Specifically, we sought to investigate whether signal complexity, derived by using the method of Lempel Ziv Complexity (LZC), could differentiate between insecure and secure attachment styles based on a success or failure feedback given in the context of a flanker task. A significant interaction between attachment style and feedback type was found due to the change in complexity level between success and failure as a function of attachment type. Secure players were associated with an increase in complexity level between success and failure, whereas for insecure players no change was observed between these conditions. These results may be explained by different mechanisms of emotional regulation that are employed by secure and insecure participants. Possibilities for future research were also discussed.
KW - Attachment theory
KW - Data analysis
KW - EEG
KW - Lempel–Ziv complexity
KW - NeuroIS
UR - http://www.scopus.com/inward/record.url?scp=85200771567&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-58396-4_23
DO - 10.1007/978-3-031-58396-4_23
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AN - SCOPUS:85200771567
SN - 9783031583957
T3 - Lecture Notes in Information Systems and Organisation
SP - 263
EP - 270
BT - Information Systems and Neuroscience - NeuroIS Retreat 2023
A2 - Davis, Fred D.
A2 - Riedl, René
A2 - Riedl, René
A2 - Brocke, Jan vom
A2 - Léger, Pierre-Majorique
A2 - Randolph, Adriane B.
A2 - Müller-Putz, Gernot R.
PB - Springer Science and Business Media Deutschland GmbH
T2 - 15th Annual NeuroIS Retreat, NeuroIS 2023
Y2 - 30 May 2023 through 1 June 2023
ER -