Introduction to self-attachment and its neural basis
File(s)self-attachment.pdf (476.23 KB)
Accepted version
Author(s)
Edalat, A
Type
Conference Paper
Abstract
We introduce the notion of self-attachment which, based on an interdisciplinary set of concepts, proposes a new psychotherapeutic technique. The underlying ideas include findings and paradigms in developmental psychology and neuroscience, neuroplasticity and long term term potentiation, fMRI studies on human bond making, ethology and psychology of religion and experiments in energy based artificial neural networks. The proposed self-attachment therapeutic technique is distinguished by its intervention to create an internal and passionate affectional bond within the individual between the “adult self”, representing the logical and cognitive faculty, and the “inner child”, representing the unregulated and undeveloped emotional circuits. The aim is to create more optimal circuits for emotional regulation. The proposed self-attachment protocols internally emulate within the individual the interactions of a good enough primary care-giver and child in order to moderate the child’s arousal level, minimise its negative affects and maximize its positive affects. These interactions are assumed, in developmental neuroscience and in developmental psychology, to be the basis of secure attachment of children with their parents, which leads to an optimal regulation of neurotransmitters, hormones, and the emotional dynamics of the individual. We report on several case studies of this technique in recent years. Finally, we propose a simple mathematical model to capture the impact of self-attachment protocols using the notion of strong patterns in energy based neural networks and employ a recently developed mathematical model to examine the impact of self-attachment using emotional and ognitive neural pathways for decision making.
Date Issued
2015-07-12
Date Acceptance
2015-03-27
Citation
The 2015 International Joint Conference on Neural Networks (IJCNN), 2015, pp.1-8
Publisher
IEEE
Start Page
1
End Page
8
Journal / Book Title
The 2015 International Joint Conference on Neural Networks (IJCNN)
Copyright Statement
© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Source
The 2015 International Joint Conference on Neural Networks (IJCNN)
Publication Status
Published
Start Date
2015-07-12
Finish Date
2015-07-17
Coverage Spatial
Killarney, Ireland