| Форма представления | Тезисы и материалы конференций в российских журналах и сборниках |
| Год публикации | 2024 |
| Язык | английский |
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Граница Александр Станиславович, автор
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Муртазин Альберт Инзирович, автор
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| Библиографическое описание на языке оригинала |
Murtazin A., Granitsa A. Integration of cognitive model and predictive coding models/EABCT 2024 ~ New Age of CBT – Challenges and Perspectives. Book of abstracts.-Belgrade,Serbia-September 4-7, 2024,p.401 |
| Аннотация |
ABCT 2024 ~ New Age of CBT – Challenges and Perspectives. Book of abstracts.-Belgrade,Serbia-September 4-7, 2024 |
| Ключевые слова |
cognitive model, predictive model, Bayesian brain hypothesis, generative models, integration |
| Название журнала |
ABCT 2024 ~ New Age of CBT – Challenges and Perspectives. Book of abstracts.-Belgrade,Serbia-September 4-7, 2024
|
| Пожалуйста, используйте этот идентификатор, чтобы цитировать или ссылаться на эту карточку |
https://repository.kpfu.ru/?p_id=303775 |
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| Поле DC |
Значение |
Язык |
| dc.contributor.author |
Граница Александр Станиславович |
ru_RU |
| dc.contributor.author |
Муртазин Альберт Инзирович |
ru_RU |
| dc.date.accessioned |
2024-01-01T00:00:00Z |
ru_RU |
| dc.date.available |
2024-01-01T00:00:00Z |
ru_RU |
| dc.date.issued |
2024 |
ru_RU |
| dc.identifier.citation |
Murtazin A., Granitsa A. Integration of cognitive model and predictive coding models/EABCT 2024 ~ New Age of CBT – Challenges and Perspectives. Book of abstracts.-Belgrade,Serbia-September 4-7, 2024,p.401 |
ru_RU |
| dc.identifier.uri |
https://repository.kpfu.ru/?p_id=303775 |
ru_RU |
| dc.description.abstract |
ABCT 2024 ~ New Age of CBT – Challenges and Perspectives. Book of abstracts.-Belgrade,Serbia-September 4-7, 2024 |
ru_RU |
| dc.description.abstract |
Cognitive-behavioural therapy (CBT) is a practical, goal-focused approach that helps understand the relationship be
tween thoughts, feelings and behaviours. The aim is to identify the dysfunctional and distorted cognitions associated
with their psychological problems and to create more functional and balanced cognitive patterns that create less
emotional distress and more helpful behaviours.
Beck's cognitive model has provided an evidence-based way to conceptualize and treat psychological disorders. CBT
theoretical models and mechanisms of change have been the most researched and are in line with the current main
stream paradigms of human mind and behavior (e.g., information processing). When information processing provides
faulty information, other systems (e.g., affective, motivational, behavioral) no longer function in an adaptive way. Er
rors can result in other cognitive biases (e.g., interpretation, attention, memory), excessive or inappropriate affect, and
maladaptive behavior. A negative bias will assure reactions to true danger; however, at the cost of many false alarms.
Consequently, individuals are likely to experience unwarranted anxiety in many seemingly dangerous but innocuous
situations. Similarly, a positive bias exaggerates the probability or degree of positive outcomes and consequently
increases or maintains motivation to engage in a task (Beck, Hugh, 2015). An erroneous or exaggerated interpretation
of threat, for example, will result in inappropriate or excessive anxiety and avoidance (Clark & Beck, 2011).
A biased information-processing system reflects predictive coding models. Predictive coding models of brain process
ing propose that top-down cortical signals promote efficient neural signaling by carrying predictions about incoming
sensory information (Gilbert et al, 2022). The framework is rooted in Bayesian probability theory and the so-called
Bayesian brain hypothesis [Knill and Pouget, 2004] that conceptualizes perception as a constructive process that uses
internal or generative models to encode prior beliefs about sensory inputs and their causes. Generative models help
an individual formulate predictions about incoming sensory information that are tested against incoming sensory
inputs and produce prediction errors. Prediction errors, in turn, are used by the brain to revise its model of the world
by updating predictions in order to minimize prediction errors [Friston, 2010]
These ideas are actually used in cognitive conceptualizations of clinical cases. Distant antecedents as childhood
events can be viewed as incoming perceptual signals that may run counter to the predictive model of well-being.
And this discrepancy, accompanied by frustration of needs, forms a generalized conclusion about the causes of these
discrepancies as a basic belief. Thus, basic beliefs and cognitive schemas are part of a universal predictive model and
relate to a fairly wide range of particular situations.
Although numerou |
ru_RU |
| dc.language.iso |
ru |
ru_RU |
| dc.subject |
cognitive model |
ru_RU |
| dc.subject |
predictive model |
ru_RU |
| dc.subject |
Bayesian brain hypothesis |
ru_RU |
| dc.subject |
generative models |
ru_RU |
| dc.subject |
integration |
ru_RU |
| dc.title |
Integration of cognitive model and predictive coding models |
ru_RU |
| dc.type |
Тезисы и материалы конференций в российских журналах и сборниках |
ru_RU |
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