Project

Design of Adaptive Temporal-Causal Network Models for Handling Extreme Emotions

Goal: In this project, it is addressed by computational modeling how extreme, stressful emotions affect mental processes, and how therapies such as various mindfulness therapies can be used to handle such extreme emotions.

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Seyed Sahand Mohammadi Ziabari
added 2 research items
Stress is often seen as a negative factor which affects every individ-ual's life quality and decision making. To help avoid or deal with extreme emotions caused by an external stressor, a number of practices have been introduced. In the scope of this paper, we take three kinds of therapy into account: mindful-ness, humor, and music therapy. This paper aims to see how various practices help people to cope with stress, using mathematical modelling. We present practical implementations in the form of client-server software, incorporating the computational model which describes therapy effects for overcoming stress based on quantitative neuropsychological research. The underlying network model simulates the elicitation of an extremely stressful emotion due to a strong stress-inducing event as an external stimulus, followed by a therapy practice simulation leading to a reduction of the stress level. Each simulation is based on user input and preferences, integrating a parameter tuning process; it fits a simulation for a particular user. The client-server architecture software which has been designed and developed completely fulfills this objective. It includes server part with embedded MATLAB interaction and API for client communication.
Seyed Sahand Mohammadi Ziabari
added a research item
The influence of acute severe stress or extreme emotion based on a Network-Oriented modeling methodology has been addressed here. Adaptive temporal-causal network modeling is an approach to address the phenomena with a complexity that cannot be or are hard to be explained in a real-world experiment. In the first phase, the suppression of the existing network connections as a consequence of the acute stress modeled and in the second phase relaxing the suppression by giving some time and starting new learning of the decision making in accordance with the presence of stress starts again.
Seyed Sahand Mohammadi Ziabari
added a research item
In this paper a software environment to support Network-Oriented Modeling is presented. The environment has been implemented in Matlab. This code covers the principles of modeling by temporal-causal networks. The software environment has built-in options for network adaptation principles such as the Hebbian Learning principle from Neuroscience and the adaptation principle for bonding based on homophily from Social Science. The implementation is illustrated for an adaptive temporal-causal network model for decision making under acute stress.
Seyed Sahand Mohammadi Ziabari
added a research item
In this paper, an adaptive temporal causal network model based on electroconvulsive therapy to reduce the stress level of post-traumatic stress disorder (PTSD) is presented. The stress reduction is triggered by a cognitive electroconvulsive therapy that uses continuous usage of this therapy. The goal of this therapy is to decrease the strength between certain parts of the brain which are responsible for causing stress. This computational model aims to illustrate the effect of the therapy on different components of the brain. The cognitive model begins with a state of strong and continuous stress within a post-traumatic disorder patient and after following electroconvulsive therapy the stress level starts to decrease over time. The results show that, in the end, the patient will have a declined stress level compared to not using electroconvulsive therapy.
Seyed Sahand Mohammadi Ziabari
added a research item
In this paper the effect of a humor therapy is modeled based on a Network Oriented Modeling approach. Humor therapy is a mindfulness therapy which has been used since many years ago, when Abu Bakr Muhammad ibn Za-kariya al-Razi 1 as a Persian scientist who used humor theory to distinguish one contagious disease from another, to make stressed individuals more relaxed. The presented adaptive temporal-causal network model addresses the computational modeling of humor therapy for a person who in the first step triggers two incon-gruent beliefs in order to get the humor from a humor context to overcome an ongoing stressful event. This happens by showing a comedy movie. As a result, the stress level in the body reduces. Hebbian learning is incorporated to strengthen the effect of the humor therapy.
Seyed Sahand Mohammadi Ziabari
added a research item
In this paper, an adaptive cognitive temporal-causal model using psilocybin for a reduction in extreme emotion is presented. Extreme emotion has an effect on some brain components such as visual cortex, auditory cortex, gustatory cortex, and somatosensory cortex as well as motor cortex such as primary motor cortex, and premotor cortex. Neuroscientific literature reviews show that using psilocybin has a significant effect mostly on two brain components, cerebral cortex, and thalamus. Network-oriented modeling via temporal-causal network-oriented modeling is presented to show the influences of using psilocybin on the cognitive part of the body, the same as the brain components. Hebbian learning used to show the adaptivity and learning section of the presented model.
Seyed Sahand Mohammadi Ziabari
added a research item
In this paper, the effect of using sex hormones such as estrogen and producing this hormone in the body using cognitive, biological temporal-causal network model is presented. Reviewing neuroscience pieces of literature about hormone therapy shows the effect of estrogen on some brain components such as basolateral Amygdala, ventromedial Prefrontal Cortex, Hippocampus and resulting in decreasing the extreme emotion. This finding shows that for postnatal depression transdermal estrogen is an effective treatment. Moreover, the presented model integrates the cognitive, biological and effective principle of neuroscience.
Seyed Sahand Mohammadi Ziabari
added a research item
In this paper a computational model of Deep Brain Stimulation (DBS) therapy for post-traumatic stress disorder is presented. The considered therapy has as a goal to decrease the stress level of a stressed individual by using electrode which placed in a specific area in brain. Several areas in brain have been used to decrease the stress level, one of them is Amygdala. The presented temporal-causal network model aims at integrative modeling a Deep Brain Stimulation therapy where the relevant brain areas are modeled in a dynamic manner.
Seyed Sahand Mohammadi Ziabari
added 2 research items
Yoga is a practice that is thousands of years old. This practice is also included in the modern mindfulness-based stress reduction training, and its effects on our cognitive system are supported by extensive literature that comprehend mostly fMRI studies and task-oriented experiments with control groups. In this paper, the problem of testing the effects of mindfulness therapy, with specific regard to the yoga practice, is addressed with a Network-Oriented Modelling approach. The first component of the proposed network simulates the elicitation of an extreme stressful emotion due to a strong stress-inducing event. This was done following the same line of previous papers that proposed simulations of similar processes. A second component represents the role of memory, attention and self-awareness in coping with the stressful event. Finally, the yoga practice, divided into physical movements and breathing, is modelled, to show its influence on memory, attention and self-awareness, leading in this way to a reduction of the stress level.
In this paper a computational model of the effect of caffeine on cortisol and brain activity levels is presented. Using integrative modelling in a temporal-causal network model approach, this paper aims to dynamically model the biological, cognitive and affective processes that are enhanced in the brain while consuming coffee. Firstly, stress stimuli from the individuals’ context conduct an (affective) stressful feeling. Therefore, the individual (cognitive) decides to drink coffee that increases its caffeine levels and makes the individual feel more focused wherefore the individual relaxes. Thirdly, (biologically) it is modeled how caffeine intake by drinking coffee reduces stress levels due to feeling more relaxed.
Seyed Sahand Mohammadi Ziabari
added 2 research items
The brain is the central organ of stress and controls the adaptation to stressors, while it perceives what is potentially threatening and determines the behavioral and physiological responses. Post-traumatic stress disorder (PTSD) is a mental health disease in which an individual has been exposed to a traumatic event that involves actual or imminent death or serious injury, or threatens the physical integrity of the self or others. The effects on the brain caused by stress for people with PTSD are the main subject of this paper. A literature research was conducted to see how stress affects the brain and how regions of the brain are distorted by an excess of myelin, which is formed by oligodendrocytes, in people with PTSD. Network-Oriented Modeling perspective is proposed as an alternative way to address complexity. This perspective takes the concept of network and the interactions within a network as a basis for conceptualization and structuring of any complex processes. It appears myelin, and the oligodendrocytes which produce the myelin can have altering effects in the brain of patients with PTSD. The fear response is increased significantly and the forming and retrieval of memories is also disrupted. As the effect of myelin is decreased in the model, the effects are also decreased. The main purpose of this paper is providing insight into what the effects of myelin excess might be for patients with PTSD, and simulating these effects to make these insights easily accessible.
Seyed Sahand Mohammadi Ziabari
added 3 research items
Yoga is a practice that is thousands of years old. This practice is also included in the modern mindfulness-based stress reduction training, and its effects on our cognitive system are supported by extensive literature that comprehend mostly fMRI studies and task-oriented experiments with control groups. In this paper, the problem of testing the effects of mindfulness therapy, with specific regard to the yoga practice, is addressed with a Network-Oriented Modelling approach. The first component of the proposed network simulates the elicitation of an extreme stressful emotion due to a strong stress-inducing event. This was done following the same line of previous papers that proposed simulations of similar processes. A second component represents the role of memory, attention and self-awareness in coping with the stressful event. Finally, the yoga practice, divided into physical movements and breathing, is modelled, to show its influence on memory, attention and self-awareness, leading in this way to a reduction of the stress level.
In this paper a computational model of the effect of caffeine on cortisol and brain activity levels is presented. Using integrative modelling in a temporal-causal network model approach, this paper aims to dynamically model the biological , cognitive and affective processes that are enhanced in the brain while consuming coffee. Firstly, stress stimuli from the individuals' context conduct an (affective) stressful feeling. Therefore, the individual (cognitive) decides to drink coffee that increases its caffeine levels and makes the individual feel more fo-cused wherefore the individual relaxes. Thirdly, (biologically) it is modeled how caffeine intake by drinking coffee reduces stress levels due to feeling more relaxed .
Seyed Sahand Mohammadi Ziabari
added a research item
The brain is the central organ of stress and controls the adaptation to stressors, while it perceives what is potentially threatening and determines the behav-ioral and physiological responses. Post-traumatic stress disorder (PTSD) is a mental health disease in which an individual has been exposed to a traumatic event that involves actual or imminent death or serious injury, or threatens the physical integrity of the self or others. The effects on the brain caused by stress for people with PTSD are the main subject of this paper. A literature research was conducted to see how stress affects the brain and how regions of the brain are distorted by an excess of myelin, which are formed by oligodendrocytes, in persons with PTSD. The interruptions in connections in the brain are displayed in a dynamic model designed using network-oriented modeling. The Network-Oriented Modeling perspective is proposed as a way to address complexity. This perspective takes the concept of network and the interactions within a network as a basis for conceptualization and structuring of any complex processes. It appears myelin, and the oligodendrocytes which produce the myelin can have altering effects in the brain of patients with PTSD. The fear response is increased significantly and the forming and retrieval of memories is also disrupted. The main purpose of this paper is providing insight in what the effects of myelin excess might be for patients with PTSD, and simulating these effects to make these insights easily accessible.
Seyed Sahand Mohammadi Ziabari
added a research item
In this paper, an adaptive temporal causal network model based on drug therapy named fluoxetine to decrease the stress level of post-traumatic stress disorder is presented. The stress extinction is activated by a cognitive drug therapy (here fluoxetine) that uses continuous usage of medicine. The aim of this therapy is to reduce the connectivity between some components inside the brain which are responsible for causing stress. This computational model aspires to realistically demonstrate the activation of different portions of brain when the therapy is applied. The cognitive model starts with a situation of strong and continuous stress in an individual and after using fluoxetine the stress level begins to decrease over time. As a result, the patient will have a reduced stress level compared to not using drug.
Seyed Sahand Mohammadi Ziabari
added a research item
This paper presents the connection between exam or test anxiety and the illicit use of Ritalin (methylphenidate). Ritalin is used by students as a cog-nitive enhancer and thus to increase their learning and memory abilities. However , a side effect of Ritalin is altered fear reactions to stimuli. Thus, this paper aims to gain insight in the mechanisms of Ritalin on the anxiety system. The created network visualises the overlapping systems of Ritalin and anxiety and possible outcomes of the use of Ritalin around exam weeks. First, the exam is noticed, with the induced (normal) stress response on having this exam. The wish to increase learning abilities during exam weeks surfaces and Ritalin is administered as a result of cognitive decision making. Finally, the model shows how Ri-talin can decrease test anxiety.
Seyed Sahand Mohammadi Ziabari
added 3 research items
In this paper, the effect of a mindfulness therapy based on a Network-Oriented Modeling approach is addressed. The considered therapy is Autogenic Training that can be used when under stress; it has as two main goals to achieve feeling heavy and warm body parts (limbs). Mantras have been used in therapies since long ago to make stressed individuals more relaxed, and they are also used in Autogenic Training. The presented cognitive temporal-causal network model addresses the modeling of Autogenic Training asking this into account. In the first phase a strong stress-inducing stimulus causes the individual to develop an extreme stressful emotion. In the second phase, the therapy with the two goals is shown to make the stressed individual relaxed. Hebbian learning is used to increase the influence of the therapy.
In this paper the effect of a music therapy is modeled based on a Net-work-Oriented Modeling approach. Music therapy is a mindfulness therapy used since many years ago. The presented adaptive temporal-causal network model addresses music therapy for a person who in a first phase develops an extreme stressful emotion due to an ongoing stressful event. In a second phase, music therapy is considered to reduce the stress. This happens by playing memorable music first and then singing on that music. The music and the singing have a direct relaxing effect on the body. Hebbian learning is incorporated to increase the effect of the therapy.
In this paper a computational analysis is presented of differences between men and women in coping with extreme emotions. This analysis is based on an adaptive temporal-causal network model. It takes into account the suppression of connections between preparation states and sensory representations of action effects due to an extreme stressful emotion. It is shown how this model can be used to represent the difference between males and females facing an extreme emotion, thereby performing their own methods in coping with the extreme emotion, for males fight or flight and for females tend-and-befriend.
Seyed Sahand Mohammadi Ziabari
added a research item
In this paper the effect of a mindfulness therapy is addressed based on a Network-Oriented Modeling approach. The considered therapy is Autogenic Training, that can be used when under stress; it has as two main goals to achieve feeling heavy and warm body parts (limbs). Mantra's have been used in therapies since long ago to make stressed individuals more relaxed, and they are also used in Autogenic Training. The presented cognitive temporal-causal network model addresses the modeling of Autogenic Training taking this into account. In the first phase a strong stress-inducing stimulus causes the individual to develop an extreme stressful emotion. In the second phase, the therapy with the two goals is shown to make the stressed individual relaxed. Hebbian learning is used to increase the influence of the therapy. This paper received the Best Paper Award at the conference.
Seyed Sahand Mohammadi Ziabari
added a research item
In this paper a computational analysis is presented of differences between men and women in coping with extreme emotions. This analysis is based on an adaptive temporal-causal network model. It takes into account the suppression of connections between preparation states and sensory representations of action effects due to an extreme stressful emotion. It is shown how this model can be used to represent the difference between males and females facing an extreme emotion, thereby performing their own methods in coping with the extreme emotion , for males fight or flight and for females tend-and-befriend. 1 Introduction When facing an extreme stressful emotion, generally speaking men and women have different strategies. More specifically, men more often use a fight or flight strategy and women a tend and befriend strategy. Moreover, it has been reported that women show a longer duration of rumination before a decision is made. In this paper these phenomena are analysed based on an adaptive temporal causal network model that allows to display such gender differences. The model takes into account suppression of connections between preparation states and sensory representations of action effects due to an extreme stressful emotion, as described in [27]. Differences in gender in addressing stress and fear seem to start at an age as early as 9-12 year-old [4]. Up to one third of these differences are estimated to go back to the genetic factors [5]. It is reported that females subscribe a more massive violence to fear than males [7]. Epidemiological research implies that females are much more likely to get anxiety disorders than males [8]. The neurological perspective in [3] shows that females have a weaker Hypothalamic-pituitary-adrenal axis (HPAA) and autonomic reactivity than males. In [10] it has been shown that the common characterization of coping with fear and anxiety for most animals and humans is not tailored well to the hormonal and physiological responses of females; females have their 'tend-and-befriend' pattern and it stands for protecting offspring (tending) and searching for the social company to defend together (befriending). In [10] it was found out that when females get stressed, the level
Seyed Sahand Mohammadi Ziabari
added a research item
In this paper a computational analysis is presented of differences between men and women in coping with extreme emotions. This analysis is based on an adaptive temporal-causal network model. It takes into account the suppression of connections between preparation states and sensory representations of action effects due to an extreme stressful emotion. It is shown how this model can be used to represent the difference between males and females facing an extreme emotion, thereby performing their own methods in coping with the extreme emotion, for males fight or flight and for females tend-and-befriend. 1 Introduction When facing an extreme stressful emotion, generally speaking men and women have different strategies. More specifically, men more often use a fight or flight strategy and women a tend and befriend strategy. Moreover, it has been reported that women show a longer duration of rumination before a decision is made. In this paper these phenomena are analysed based on an adaptive temporal causal network model that allows to display such gender differences. The model takes into account suppression of connections between preparation states and sensory representations of action effects due to an extreme stressful emotion, as described in [27]. Differences in gender in addressing stress and fear seem to start at an age as early as 9-12 year-old [4]. Up to one third of these differences are estimated to go back to the genetic factors [5]. It is reported that females subscribe a more massive violence to fear than males [7].
Seyed Sahand Mohammadi Ziabari
added a research item
In this paper a computational model of a therapy for post-traumatic stress disorder by medicines is presented. The considered therapy has as a goal to decrease the stress level of a stressed individual by injections. Several medicines have been used to decrease the stress level. The presented temporal-causal network model aims at integrative modeling a medicine-based therapy where the relevant biological, cognitive and affective factors are modeled in a dynamic manner. In the first phase a strong stress-inducing stimulus causes the individual to develop an (affective) extreme stressful emotion. In the second phase, the individual makes the (cognitive) decision to apply an injection as a medicine with a goal shown to make the stressed individual relaxed. The third phase (biologically) models how the injection reduces the stress level.
Seyed Sahand Mohammadi Ziabari
added 3 research items
In recent literature from Neuroscience the adaptive role of the effects of stress on decision making is highlighted. The problem addressed in this paper is how that can be modelled computationally. The presented adaptive temporal-causal network model addresses the suppression of the existing network connections in a first phase as a result of the acute stress, and then as a second phase relaxing the suppression after some time and give room to start new learning of the decision making in the context of the stress again.
In this paper the effect of a music therapy is modeled based on a Network Oriented Modeling approach. Music therapy is a mindfulness therapy used since many years ago. The presented adaptive temporal-causal network model addresses music therapy for a person who in a first phase develops an extreme stressful emotion due to an ongoing stressful event. In a second phase, music therapy is considered to reduce the stress. This happens by playing memorable music first and then singing on that music. The music and the singing have a direct relaxing effect on the body. Hebbian learning is incorporated to increase the effect of the therapy.
Seyed Sahand Mohammadi Ziabari
added a research item
In recent literature from Neuroscience the adaptive role of the effects of stress on decision making is highlighted. The problem addressed in this paper is how that can be modelled computationally. The adaptive effect of acute severe stress on decision making is addressed based on a Network-Oriented Modeling approach. The presented adaptive temporal-causal network model addresses the suppression of the existing network connections in a first phase as a result of the acute stress, and then as a second phase relaxing the suppression after some time and give room to start new learning of the decision making in the context of the stress again.
Jan Treur
added 5 project references
Jan Treur
added a research item
In this paper the effect of a mindfulness therapy is addressed based on a Network-Oriented Modeling approach. The considered therapy is Autogenic Training, that can be used when under stress; it has as two main goals to achieve feeling heavy and warm body parts (limbs). Mantra's have been used in therapies since long ago to make stressed individuals more relaxed, and they are also used in Autogenic Training. The presented cognitive temporal-causal network model addresses the modeling of Autogenic Training taking this into account. In the first phase a strong stress-inducing stimulus causes the individual to develop an extreme stressful emotion. In the second phase, the therapy with the two goals is shown to make the stressed individual relaxed. Hebbian learning is used to increase the influence of the therapy. This paper received the Best Paper Award at the conference.
Seyed Sahand Mohammadi Ziabari
added a project reference
Seyed Sahand Mohammadi Ziabari
added a project reference
Seyed Sahand Mohammadi Ziabari
added a project reference
Seyed Sahand Mohammadi Ziabari
added a project goal
In this project, it is addressed by computational modeling how extreme, stressful emotions affect mental processes, and how therapies such as various mindfulness therapies can be used to handle such extreme emotions.