Abstract
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, same as the brain components. Hebbian learning used to show the adaptivity and learning section of the presented model.
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Mohammadi Ziabari, S.S., Treur, J. (2019). An Adaptive Cognitive Temporal-Causal Model for Extreme Emotion Extinction Using Psilocybin. In: Silhavy, R., Silhavy, P., Prokopova, Z. (eds) Computational Statistics and Mathematical Modeling Methods in Intelligent Systems. CoMeSySo 2019 2019. Advances in Intelligent Systems and Computing, vol 1047. Springer, Cham. https://doi.org/10.1007/978-3-030-31362-3_18
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DOI: https://doi.org/10.1007/978-3-030-31362-3_18
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