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Predictive coding: A contemporary view on the burden of normality and forced normalization in individuals undergoing
Sumayya Mehmood1, Craig Dale2, Monica Parry2
1Krembil Research Institute, Toronto Western Hospital (TWH), Toronto, ON, Canada; Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada.
Abstract:
Following epilepsy surgery, a good psychosocial outcome is not necessarily contingent on a good seizure outcome. Increasingly, it is believed that "successful" surgery is a combination of both an acceptable and expected seizure status as well as the individual's perception of improvements in quality of life (QOL). The factors that create this optimal outcome remain an ongoing area of research in the epilepsy community. That being said, there have been some major breakthroughs in observing and understanding poor outcomes seen in a subset of postoperative patients with epilepsy. Characteristics of burden of normality and forced normalization are two phenomena that have been evident in cases of poor postoperative outcomes. In this review, we provide a summary of research and concepts used to explain these poor QOL outcomes for a seemingly successful surgery and suggest a contemporary view in understanding the mechanism of forced normalization through understanding the brain as a predictive organ. Using such a predictive coding model together with recommendations of other studies, we suggest the crucial need for a preoperative intervention addressing patient predictions and expectations to optimize on the benefits achievable through epilepsy surgery.
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