@inproceedings{5e34992d07244a2ba1329ca9eff24799,
title = "Modulation of Beta Power as a Function of Attachment Style and Feedback Valence",
abstract = "Attachment theory is concerned with the basic level of social connection associated with approach and withdrawal mechanisms. Consistent patterns of attachment may be divided into two major categories: secure and insecure. As secure and insecure attachment style individuals vary in terms of their responses to affective stimuli and negatively valanced cues, the goal of this study was to examine whether there are differences in Beta power activation between secure and insecure individuals to feedback given while performing the arrow flanker task. An interaction emerged between Attachment style (secure or insecure) and Feedback type (success or failure) has shown differences in Beta power as a function of both independent factors. These results corroborate previous findings indicating that secure and insecure individuals differently process affective stimuli.",
keywords = "Attachment theory, Beta band power, EEG, Flanker task",
author = "Dor Mizrahi and Ilan Laufer and Inon Zuckerman",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 16th International Conference on Brain Informatics, BI 2023 ; Conference date: 01-08-2023 Through 03-08-2023",
year = "2023",
doi = "10.1007/978-3-031-43075-6\_2",
language = "אנגלית",
isbn = "9783031430749",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "14--20",
editor = "Feng Liu and Hongjun Wang and Yu Zhang and Hongzhi Kuai and Stephen, \{Emily P.\}",
booktitle = "Brain Informatics - 16th International Conference, BI 2023, Proceedings",
address = "גרמניה",
}