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Learning is an enigmatic process composed of a multitude of cognitive systems that are functionally and neuroanatomically distinct. Nevertheless, two undeniable pillars which underpin learning are attention and memory; to learn, one must attend, and maintain a representation of, an event. Psychological and neuroscientific technologies that permit researchers to “mind-read” have revealed much about the dynamics of these distinct processes that contribute to learning. This investigation first outlines the cognitive pillars which support learning and the technologies that permit such an understanding. It then employs a novel task—the amSMART paradigm—with the goal of building a real-time, closed-loop, electroencephalographic (EEG) neurofeedback paradigm using consumergrade brain-computer interface (BCI) hardware. Data are presented which indicate the current status of consumer-grade BCI for EEG cognition classification and enhancement, and directions are suggested for the developing world of consumer neurofeedback.
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This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Hirschstein, Zall Soren, "Towards Improving Learning with Consumer-Grade, Closed-Loop, Electroencephalographic Neurofeedback" (2018). Senior Projects Spring 2018. 206.