Abstract
This paper investigates the neural aspects of obesity, shifting from a focus on isolated brain structures to dynamic neural network interactions. Exploring substance-related and addictive disorders as a foundation, it extends this understanding to alterations in functional integration within reward brain areas, particularly fronto-parietal and temporal regions, in individuals with BMI between 29.6 and 36.6.
Obesity, a global health concern impacting 39% of the population, is associated with diverse brain activity patterns in regions governing intake regulation, satiety, self-control, and impulsivity. Shared neural irregularities between obese individuals and drug addicts suggest common mechanisms fueling reward-seeking behaviors.
Utilizing advanced signal processing technologies, our EEG study involving four participants, explores the interplay of brain function and obesity. Collaborating with a nutritionist underscores the role of dietary considerations in this complex relationship. EEG recordings during fasting and postprandial states proof significant alterations in beta and gamma frequency bands, highlighting FC2, FC4, and F6 as critical electrodes.
This exploration into neural changes during different physiological states provides valuable insights into the intricate relationship between brain function and obesity. The integration of electroencephalographic features offers a nuanced understanding, paving the way for future research and interventions in the intersection of obesity and neuroscience.
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Acknowledgments
This work is part of the OBRAINSITY project - Novel therapeutic approaches to metabolic diseases: modulation of food intake and energy balance through nutraceuticals and neurotechnology, funded by the Department of Innovation, Universities, Science, and Digital Society of the Generalitat Valenciana (PROMETEO/2021/059).
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Elizalde, M. et al. (2024). Analysis of Anxiety Caused by Fasting in Obesity Patients Using EEG Signals. In: Ferrández Vicente, J.M., Val Calvo, M., Adeli, H. (eds) Artificial Intelligence for Neuroscience and Emotional Systems. IWINAC 2024. Lecture Notes in Computer Science, vol 14674. Springer, Cham. https://doi.org/10.1007/978-3-031-61140-7_22
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DOI: https://doi.org/10.1007/978-3-031-61140-7_22
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