NEUROQUANTUM: The Brain as a Computational System

Abstract. This paper introduces the evolution of Neuroquantum from a computational perspective in neuroscience, beginning with classical models that conceptualize the brain as an information-processing machine driven by symbol manipulation, hierarchical encoding, and stimulus–response transformations.

These traditional frameworks focus on how neurons fire, how signals pass between connections, and how information is coded in the brain as the main ways the nervous system handles, saves, and uses information. Based on this, the paper has a new neuroscience perspective based on cognitive artificial intelligence and new theories that use neural networks and learning methods inspired by biology, such as how connections between neurons change, how information is spread across many parts of the brain, and how complex behaviors can arise from simple interactions—similar to how modern artificial intelligence works. The new Neuroquantum science faces several problems and limitations in explaining more complex phenomena such as consciousness, purpose, sudden insights, and human creativity. These limitations necessitate new approaches that integrate personal experience and cognitive reasoning with well-established computing ideas. This paper outlines multiple open research directions to bridge the gap among research on traditional computing, brain activity, and quantum processes, thereby fully understanding human thought and its application in real-life situations.