Psychology Models

These models and simulations have been tagged “Psychology”.

The dynamics of antisocial behavior in adolescents coupled with aversive reactions (e.g. punishment, anger,...) by adults
The dynamics of antisocial behavior in adolescents coupled with aversive reactions (e.g. punishment, anger,...) by adults
5 months ago
Bipolar II treatment modeling using Van der Pol-like oscillators.  In this simulation an afflicted individual with Bipolar II disorder is put to treatment after 20 months the calibration of the medicine or treatment he recieves is such that it simulates the natural cycles of a "normal being". You ca
Bipolar II treatment modeling using Van der Pol-like oscillators.

In this simulation an afflicted individual with Bipolar II disorder is put to treatment after 20 months the calibration of the medicine or treatment he recieves is such that it simulates the natural cycles of a "normal being". You can note by manipulating the parameters that sometimes too much treatment disrupts equilibria. Also note that in the state diagrams there are 2 limit cycles, the lower one being the healthiest as there are less changes.
 The simple  graph shows two feedback loops that interact
to make climate change and its consequences worse, leading to   an unexpected
(& inescapable?)   dilemma. Presently, 
there are 413 ppm of CO2 gasses in the atmosphere. Even without any
further emission of greenhouse gasses, this high lev

The simple  graph shows two feedback loops that interact to make climate change and its consequences worse, leading to an unexpected (& inescapable?) dilemma. Presently,  there are 413 ppm of CO2 gasses in the atmosphere. Even without any further emission of greenhouse gasses, this high level of CO2 in the atmosphere will ensure constantly worsening climatic consequences because of delays that operate in the climate system. The dilemma is caused by relentlessly worsening of extreme weather events, droughts, forest fires etc., the need for draconian measures to deal with the situation and the opposition to the measures, described by the feedback loop B2.This opposition is rooted in human nature, the psychological defence mechanisms that cause us to repress or even deny unpalatable truths that threaten our basic assumptions and the way we understand life. Together,  the loops B1 & B2 create a vicious reinforcing loop that describes the escalating and worsening situation created by the dilemma.

Please look at Insight No. 238770 that provides background information and also at the information labels attached to majority of the variables in the model. 

From Brown and Heathcote's 2008  Paper  on the simplest model of Choice ResponseTime , a  Tutorial paper  and a  Workload capacity paper  that estimates drift rate v for individuals with single and multiple targets. With start point variability.
From Brown and Heathcote's 2008 Paper on the simplest model of Choice ResponseTime , a Tutorial paper and a Workload capacity paper that estimates drift rate v for individuals with single and multiple targets. With start point variability.
Based on  1990 SDR Article . Control systems act to make their own input match internal standards or reference signals. Competent control systems create illusions of stimulus response causality. Stimulus-response theory can approximate the relationship between disturbance and action, but it can't pr
Based on 1990 SDR Article. Control systems act to make their own input match internal standards or reference signals. Competent control systems create illusions of stimulus response causality. Stimulus-response theory can approximate the relationship between disturbance and action, but it can't predict the consequences of behavior. These consequences are maintained despite disturbances. See IM-9007 for a double loop version
Based on  1990 SDR Article . Control systems act to make their own input match internal standards or reference signals. Competent control systems create illusions of stimulus response causality. Stimulus-response theory can approximate the relationship between disturbance and action, but it can't pr
Based on 1990 SDR Article. Control systems act to make their own input match internal standards or reference signals. Competent control systems create illusions of stimulus response causality. Stimulus-response theory can approximate the relationship between disturbance and action, but it can't predict the consequences of behavior. These consequences are maintained despite disturbances. See IM-9007 for a double loop version
Three Agent Model of  IM-14058  with Spatial awareness. Unconscious affective dynamics Josh Epstein's Agent Zero Book  webpage   Part II p.89 with spatial ABM
Three Agent Model of IM-14058 with Spatial awareness. Unconscious affective dynamics Josh Epstein's Agent Zero Book webpage  Part II p.89 with spatial ABM

Three Agent Model of  IM-13669 . Unconscious affective dynamics Josh Epstein's Agent Zero Book  webpage  
Three Agent Model of IM-13669. Unconscious affective dynamics Josh Epstein's Agent Zero Book webpage 

The following model models fear expression. The model implements an expectations model of fear expression in the brain.    In this model, four broad brain regions are identified: the sensory/association cortices (SC), the lateral and basal lateral amygdala (FA), the basal medial amygdala (BA), and t
The following model models fear expression. The model implements an expectations model of fear expression in the brain.

In this model, four broad brain regions are identified: the sensory/association cortices (SC), the lateral and basal lateral amygdala (FA), the basal medial amygdala (BA), and the ventromedial prefrontal cortex (PFC).

The sensory/association cortices signal the perception of stimuli to FA and the PFC. The FA and PFC each form an expectation that the subject will (FA) and will not (PFC) experience an intrinsically fearful stimulus (IFS). The PFC inhibits activation of the FA. The amount of inhibition is proportional to the PFCs confidence that the subject will not encounter an intrinsically fearful stimulus. The modulated signal is transmitted to the BA which then stimulates other brain regions that induce the physical changes associated with fear.

Both the FA and PFC adapt their expectations based on experience. This model uses two scaled geometric sum probability estimation models (PEM) to represent the behavior of the expectation circuits within the FA and PFC. In reality, the PFC and FA probably estimate the probability that the subject will encounter an IFS based on the ease of recall of positive (instances in which the observed stimulus predicted the IFS) and negative (instances in which the observed stimulus did not predict the IFS) memories involving the observed and expected stimuli. The memories associated with positive instances are probably more easily recalled as the amygdala sends signals to the hippocampus that strengthen episodic memory formation during stressful events. Accordingly, the PEM associated with the PFC has an additional decay term that weakens the negative expectations over time, modeling memory decay. This decay term, allows us to model spontaneous fear recovery.

Experimentation suggests that fear extinction does not, principally, involve forgetting fear associations. Rather, it involves learning new associations that suppress previously learned fear associations. Brain imaging experiments suggest that fear expression and suppression are generated by different brain regions; the amygdala (expression) and the ventromedial prefrontal cortex (suppression). The theory that fear extinction does not involve forgetting fear associations was supported by observations of fear recovery, in which it was observed that subjects recover fear faster than they did during fear induction, which suggests that fear associations persist after fear extinction. To model this, we associate two different sensitivity coefficients to the FA PEM and the PFC PEM. This allows us to express the relative stability of fear associations stored within the FA in comparison to those stored within the PFC.

This model uses a simple linear model to represent fear suppression by the PFC. We define a parameter, ki, that defines the maximum proportion of fear generated by the FA that can be suppressed by the PFC. In reality this property corresponds to the strength of the neural projections from the ventromedial prefrontal cortex to the amygdala. The neurons within this pathway are serotonergic, chronic deficiency in serotonin may inhibit the structural development of this pathway contributing to anxiety regulation disorders. Medications such as serotonin reuptake inhibitors (SSRIs) can increase the amount of serotonin available within this region and over time may foster development. Accordingly, we allow ki to evolve over time within the model.

Significantly, our model posits the existence of intrinsically fearful stimuli. It assumes that certain stimuli, such as extreme pain, and fear, are innately anxiogenic. Expectation models, posit that the fear induced by most stimuli however are the result of learned associations. Presented with a non-intrinsically fearful stimlus (NIFS), the amygdala estimates the probability that the NIFS signals an IFS. The fear elicited by the NIFS is proportional to the estimated probability of encountering the IFS.
This model represents an individual as consisting of a brain coupled to an external environment. The brain will be modeled at a resolution of functional brain regions that are thought to be most important for effecting a person's learning in a classroom environment.  This model encodes both hierarch
This model represents an individual as consisting of a brain coupled to an external environment. The brain will be modeled at a resolution of functional brain regions that are thought to be most important for effecting a person's learning in a classroom environment.

This model encodes both hierarchy relationships (brain and senses are part of an individual's body, which is, in turn, part of the environment), as well as causal relationships.

The hierarchy is containment and is represented by nested folders. The environment is modeled as a folder containing all objects of interest, including the individual's body as a whole system. The individual's body is modeled as a folder containing a brain and senses. The individual's body folder is contained inside of the environment folder to represent the idea that the individual's body is contained in, and is a part of, the environment.The brain object and senses objects are contained inside the individual's body folder to represent that the brain and senses together form an object and process that is internal to the individual's body (that is, is contained inside the individual's body and are part of the individual's body).
Unconscious affective dynamics From Epstein, Joshua M. (2014-02-23). Agent_Zero: Toward Neurocognitive Foundations for Generative Social Science (Princeton Studies in Complexity) (p. 37). Princeton University Press. Kindle Edition Publisher  webpage
Unconscious affective dynamics From Epstein, Joshua M. (2014-02-23). Agent_Zero: Toward Neurocognitive Foundations for Generative Social Science (Princeton Studies in Complexity) (p. 37). Princeton University Press. Kindle Edition Publisher webpage
Double loop PCT  IM-9007  extended to show hierarchical PCT and goal conflict psychotherapy. A simulation structure for  IM-233044   See also a Suicide crisis and PCT  IM-173189   simulation structure
Double loop PCT IM-9007 extended to show hierarchical PCT and goal conflict psychotherapy. A simulation structure for IM-233044  See also a Suicide crisis and PCT IM-173189  simulation structure
Based on  1990 SDR Article . Control systems act to make their own input match internal standards or reference signals. Competent control systems create illusions of stimulus response causality. Stimulus-response theory can approximate the relationship between disturbance and action, but it can't pr
Based on 1990 SDR Article. Control systems act to make their own input match internal standards or reference signals. Competent control systems create illusions of stimulus response causality. Stimulus-response theory can approximate the relationship between disturbance and action, but it can't predict the consequences of behavior. These consequences are maintained despite disturbances. See IM-9007 for a double loop version
Based on  1990 SDR Article . Control systems act to make their own input match internal standards or reference signals. Competent control systems create illusions of stimulus response causality. Stimulus-response theory can approximate the relationship between disturbance and action, but it can't pr
Based on 1990 SDR Article. Control systems act to make their own input match internal standards or reference signals. Competent control systems create illusions of stimulus response causality. Stimulus-response theory can approximate the relationship between disturbance and action, but it can't predict the consequences of behavior. These consequences are maintained despite disturbances. See IM-9007 for a double loop version
Fases por las que pasa un individuo cuando experimenta un cambio
Fases por las que pasa un individuo cuando experimenta un cambio
Based on  1990 SDR Article . Control systems act to make their own input match internal standards or reference signals. Competent control systems create illusions of stimulus response causality. Stimulus-response theory can approximate the relationship between disturbance and action, but it can't pr
Based on 1990 SDR Article. Control systems act to make their own input match internal standards or reference signals. Competent control systems create illusions of stimulus response causality. Stimulus-response theory can approximate the relationship between disturbance and action, but it can't predict the consequences of behavior. These consequences are maintained despite disturbances. See IM-9007 for a double loop version