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Analyzing Various Functions of Prefrontal Cortex (PFC) in Decision Making via Brain Imaging Techniques

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Advances in Cross-Cultural Decision Making (AHFE 2017)

Abstract

With the advent of noninvasive medical imaging techniques, neuro scientists have acquired the ability to examine functional activation of human’s brain in different environments, especially infants and elderly patients, an approach which was difficult until recently with introduction of with non-invasive neuro imaging methods. One innovative new neuro-imaging technique is the functional Near-infrared spectroscopy (fNIRS) which obviously compensate much limitations, and an elucidation of this technology being implemented and gathered attention of modern social and neuro imaging researchers. Most of the Near-infrared spectroscopy (NIRS) research falls into two main categories: Analyzing the brain’s social and biological information in academia, and its clinical applications making neuroimaging particularly advantageous. Moreover, Near-infrared spectroscopy (NIRS) allowed researcher to investigate different cultural and behavioral interaction with human and the behaviors in which these interaction changes effect brain. One of the behavioral interaction is the decision-making process and its study on human brain region known as Prefrontal Cortex Region (PFC). Most decision-making processes takes place in prefrontal cortex region of brain, functional neuro imaging techniques like functional Near-infrared spectroscopy (fNIRS) and functional magnetic resonance imaging (fMRI) and are considered as an optimal medium to investigate these processes. This study also offer further investigation as to how to the use of medical imaging techniques to answer questions of decision making in PFC trigon of human brain.

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Correspondence to Umer Asgher .

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Asgher, U. et al. (2018). Analyzing Various Functions of Prefrontal Cortex (PFC) in Decision Making via Brain Imaging Techniques. In: Hoffman, M. (eds) Advances in Cross-Cultural Decision Making. AHFE 2017. Advances in Intelligent Systems and Computing, vol 610. Springer, Cham. https://doi.org/10.1007/978-3-319-60747-4_23

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  • DOI: https://doi.org/10.1007/978-3-319-60747-4_23

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