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Are We Producing Narci-nials? An Adaptive Agent Model for Parental Influence
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Parental influence plays an important role in the mental development of a child. In the early years of childhood, a parent acts as a role model, so most of the children try to mimic their parents. In our work, we address a complex network model of a child who is influenced by a narcissistic parent from his/her childhood to his/her adolescence. This concept of mimicking in childhood is represented by social contagion. Later on, he/she can learn to develop his/her own personality based on experience and learning. This model can be used to predict the influence of a parent over the personality of a child.
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... We tried to explain that when sensing that the parent is happy, a child may internalize and may mimic this parent. We also discussed how social media can play a role in the reflection of such behavior [12]. However, narcissistic parenting has a dark side as well, which needs to be addressed. ...
... Previously, a temporal-causal model was designed for a narcissist, which reflected how the brain of a narcissist may work, and the reaction (s)he may show over some feedback [38]. Moreover, in our previous work, we presented an agent model of a child, who shows a high tendency to become a narcissist like a parent [12] or may also learn to act otherwise. Here, we extend our work [12] by studying the influence of a narcissistic parent, particularly when this parent is not happy. ...
... Moreover, in our previous work, we presented an agent model of a child, who shows a high tendency to become a narcissist like a parent [12] or may also learn to act otherwise. Here, we extend our work [12] by studying the influence of a narcissistic parent, particularly when this parent is not happy. Also, we address how problem-solving skills or self-therapies can help the child to survive. ...
Parents play an important role in the mental development of a child. In our previous work, we addressed how a narcissistic parent influences a child (online/offline) when (s)he is happy and admires the child. Now, we address the influence of a parent who is not so much pleased, and may curse the child for being the reason for his or her unhappiness. An abusive relationship with a parent can also cause trauma and poor mental health of the child. We also address how certain coping behaviors can help the child cope with such a situation. Therefore, the aim of the study is threefold. We present an adaptive agent model of a child, while incorporating the concept of mirroring through social contagion, the avoidance behaviors from a child, and the effects of regulation strategies to cope with stressful situations.
... Agent Model for Parental Influence' (Jabeen et al., 2020) that appeared in the Brain ...
... We tried to explain that when sensing that the parent is happy, a child may internalize and may mimic this parent. We also discussed how social media can play a role in the reflection of such behavior (Jabeen et al., 2020). However, narcissistic parenting has a dark side as well, which needs to be addressed. ...
... Previously, a temporal-causal model was designed for a narcissist, which reflected how the brain of a narcissist may work, and the reaction (s)he may show over some feedback (Jabeen et al., 2019). Moreover, in our previous work, we presented an agent model of a child, who shows a high tendency to become a narcissist like a parent (Jabeen et al., 2020) or may also learn to act otherwise. Here, we extend our work (Jabeen et al., 2020) by studying the influence of a narcissistic parent, particularly when this parent is not happy. ...
Parents play an important role in the mental development of a child. In our previous work, we addressed how a narcissistic parent influences a child (online/offline) when (s)he is happy and admires the child. Now, we address the influence of a parent who is not so much pleased and, may curse the child for being the reason for his or her unhappiness. An abusive relationship with a parent can also cause trauma and poor mental health of the child. We also address how certain coping behaviors can help the child cope with such a situation. Therefore, the aim of the study is three folds. We present an adaptive agent model of a child, while incorporating the concept of mirroring through social contagion, the avoidance behaviors from a child, and the effects of regulation strategies to cope with stressful situations.
Social media like Twitter or Instagram play a role of fertile ground for self-exhibition, which is used by various narcissists to share their frequent updates reflecting their narcissism. Their belief of saving and assisting others, make them vulnerable to the feedback of others, so their rage is as dangerous as their messiah complex. In this paper, we aim to analyse the behaviour of a narcissist when he is admired or receives negative critics. We designed a complex adaptive mental network model of the process of narcissism based on the theories of neuroscience and psychology including a Hebbian learning principle. The model was validated by analyzing Instagram data.
For related videos, see the YouTube channel on Self-Modeling Networks here: https://www.youtube.com/channel/UCCO3i4_Fwi22cEqL8M_PgeA. In network models for real-world domains often network adaptation has to be addressed by incorporating certain network adaptation principles. In some cases, also higher-order adaptation occurs: the adaptation principles themselves also change over time. To model such multilevel adaptation processes it is useful to have some generic architecture. Such an architecture should describe and distinguish the dynamics within the network (base level), but also the dynamics of the network itself by certain adaptation principles (first-order adaptation level), and also the adaptation of these adaptation principles (second-order adaptation level), and maybe still more levels of higher-order adaptation. This paper introduces a multilevel network architecture for this, based on the notion network reification. Reification of a network occurs when a base network is extended by adding explicit states representing the characteristics of the structure of the base network. It will be shown how this construction can be used to explicitly represent network adaptation principles within a network. When the reified network is itself also reified, al-so second-order adaptation principles can be explicitly represented. The multilevel network reification construction introduced here is illustrated for an adaptive adaptation principle from Social Science for bonding based on homophily. This first-order adaptation principle describes how connections are changing, whereas this first-order adaptation principle itself changes over time by a second-order adaptation principle. As a second illustration, it is shown how plasticity and metaplasticity from Cognitive Neuroscience can be modeled.
Videos of lectures on several chapters of this book can be found at: https://www.youtube.com/playlist?list=PLtJH8O7BvdydRVu9RXuhdtAo2S2wMPtgp. For more applications, see the Self-Modeling Networks channel at https://www.youtube.com/@self-modelingnetworks4255. This book addresses the challenging topic of modeling (multi-order) adaptive dynamical systems, which often have inherently complex behaviour. This is addressed by using their network representations. Networks by themselves usually can be modeled using a neat, declarative and conceptually transparent Network-Oriented Modeling approach. For adaptive networks changing the network’s structure, it is different; often separate procedural specifications are added for the adaptation process. This leaves you with a less transparent, hybrid specification, part of which often is more at a programming level than at a modeling level. This book presents an overall Network-Oriented Modeling approach by which designing adaptive network models becomes much easier, as also the adaptation processes are modeled in a neat, declarative and conceptually transparent network-oriented manner, like the base network itself. Due to this dedicated overall Network-Oriented Modeling approach, no procedural, algorithmic or programming skills are needed to design complex adaptive network models.
A dedicated software environment is available to run these adaptive network models from their high-level specifications. Moreover, as adaptive networks are described in a network format as well, the approach can simply be applied iteratively, so that higher-order adaptive networks in which network adaptation itself is adaptive too, can be modeled just as easily; for example, this can be applied to model metaplasticity from Cognitive Neuroscience. The usefulness of this approach is illustrated in the book by many examples of complex (higher-order) adaptive network models for a wide variety of biological, mental and social processes.
The book has been written with multidisciplinary Master and Ph.D. students in mind without assuming much prior knowledge, although also some elementary mathematical analysis is not completely avoided. The detailed presentation makes that it can be used as an introduction in Network-Oriented Modelling for adaptive networks. Sometimes overlap between chapters can be found in order to make it easier to read each chapter separately. In each of the chapters, in the Discussion section, specific publications and authors are indicated that relate to the material presented in the chapter. The specific mathematical details concerning difference and differential equations have been concentrated in Chapters 10 to 15 in Part IV and Part V, which easily can be skipped if desired. For a modeler who just wants to use this modeling approach, Chapters 1 to 9 provide a good introduction.
The material in this book is being used in teaching undergraduate and graduate students with a multidisciplinary background or interest. Lecturers can contact me for additional material such as slides, assignments, and software. Videos of lectures for many of the chapters can be found at https://www.youtube.com/watch?v=8Nqp_dEIipU&list=PLF-Ldc28P1zUjk49iRnXYk4R-Jm4lkv2b.
The current study aimed to capture empathy processing in an interpersonal context. Mother-adolescent dyads (N=22) each completed an empathy task during fMRI, in which they imagined the target person in distressing scenes as either themselves or their family (i.e., child for the mother, mother for the child). Using multi-voxel pattern approach, we compared neural pattern similarity for the self and family conditions and found that mothers showed greater perceptual similarity between self and child in the fusiform face area (FFA), representing high self-child overlap, whereas adolescents showed significantly less self-mother overlap. Adolescents' pattern similarity was dependent upon family relationship quality, such that they showed greater self-mother overlap with higher relationship quality, whereas mothers' pattern similarity was independent of relationship quality. Furthermore, adolescents' perceptual similarity in the FFA was associated with increased social brain activation (e.g., TPJ). Mediation analyses indicated that high relationship was associated with greater social brain activation, which was mediated by greater self-mother overlap in the FFA. Our findings suggest adolescents show more distinct neural patterns in perceiving their own versus their mother's distress, and such distinction is sensitive to mother-child relationship quality. In contrast, mothers' perception for their own and child's distress is highly similar and unconditional.
It is generally agreed that the human brain is responsive to environmental influences, and that the male brain may be particularly sensitive to early adversity. However, this is largely based on retrospective studies of older children and adolescents exposed to extreme envi- ronments in childhood. Less is understood about how nor- mative variations in parent–child interactions are associated with the development of the infant brain in typical settings. To address this, we used magnetic resonance imaging to investigate the relationship between observational measures of mother–infant interactions and regional brain volumes in a community sample of 3- to 6-month-old infants (N = 39). In addition, we examined whether this relationship differed in male and female infants. We found that lower maternal sensitivity was correlated with smaller subcortical grey matter volumes in the whole sample, and that this was similar in both sexes. However, male infants who showed greater levels of positive communication and engagement during early interactions had smaller cerebellar volumes. These preliminary findings suggest that variations in mother–infant interaction dimensions are associated with differences in infant brain development. Although the study is cross-sectional and causation cannot be inferred, the findings reveal a dynamic interaction between brain and environment that may be important when considering interventions to optimize infant outcomes.
This chapter is a discussion in which some of the main issues addressed in the book are briefly reviewed. In particular, Network-Oriented Modeling based on adaptive temporal-causal networks is discussed and how generic and applicable it is as a modeling approach and as a computational paradigm.
To address complexity of modeling the world’s processes, over the years in different scientific disciplines separation assumptions have been made to isolate parts of processes, and in some disciplines they have turned out quite useful. It can be questioned whether such assumptions are adequate to address complexity of integrated human mental and social processes and their interactions. In this paper it is discussed that a Network-Oriented Modeling perspective can be considered an alternative way to address complexity for modeling human and social processes.
Narcissism is a personality trait characterized by a sense of superiority and a desire for respect and admiration from others. A common belief, both in psychology and in popular culture, is that narcissism represents a form of excessive self-esteem. Psychologists, including ourselves, have labeled narcissism as “an exaggerated form of high self-esteem,” “inflated self-esteem,” and “defensive high self-esteem.” We review research that challenges this belief by showing that narcissism differs markedly from self-esteem in its phenotype, its consequences, its development, and its origins. Drawing on emerging developmental-psychological evidence, we propose a distinction between narcissism and self-esteem that is based on the divergent socialization experiences that give rise to them. This proposal clarifies previous findings, stimulates theory development, and creates opportunities for intervention to concurrently raise self-esteem and curtail narcissism from an early age.
‘The biological birth of the human infant and the psychological birth of the individual are not coincident in time. The former is a dramatic, observable, and well-circumscribed event; the latter a slowly unfolding intra psychic process.‘Thus begins this highly acclaimed book in which the author and her collaborators break new ground in developmental psychology and present the first complete theoretical statement of the author’s observations on the normal separation-individuation process. Separation and individuation are presented in this major work as two complementary developments. Separation is described as the child’s emergence from a symbiotic fusion with the mother, while individuation consists of those achievements making the child’s assumption of his own individual characteristics. Each of the sub-phases of separation-individuation is described in detail, supported by a wealth of clinical observations which trace the tasks confronting the infant and his mother as he progresses towards achieving his own individuality.
Western parents often give children overly positive, inflated praise. One perspective holds that inflated praise sets unattainable standards for children, eventually lowering children's self-esteem (self-deflation hypothesis). Another perspective holds that children internalize inflated praise to form narcissistic self-views (self-inflation hypothesis). These perspectives were tested in an observational-longitudinal study (120 parent–child dyads from the Netherlands) in late childhood (ages 7–11), when narcissism and self-esteem first emerge. Supporting the self-deflation hypothesis, parents’ inflated praise predicted lower self-esteem in children. Partly supporting the self-inflation hypothesis, parents’ inflated praise predicted higher narcissism—but only in children with high self-esteem. Noninflated praise predicted neither self-esteem nor narcissism. Thus, inflated praise may foster the self-views it seeks to prevent.