**An Essay on the Imitation of the Whole Brain: A Note in the Spring of 2025**.

**An Essay on the Imitation of the Whole Brain: A Note in the Spring of 2025**.

The term "whole-brain emulation" is not an academic term with a strictly established definition, but it can be interpreted in multiple senses in both philosophical and technical contexts. In the field of artificial intelligence, whole-brain emulation is sometimes spoken of as the ultimate goal of mimicking or reproducing any intelligence or being. At its core lies the idea of "whole-brain emulation," which faithfully reproduces the entirety of human brain function, with the intention of going beyond mere information processing to a comprehensive imitation that includes thought, memory, consciousness, and self-awareness.

On the philosophical side, whole-brain emulation is sometimes interpreted as an imitation of the "divine perspective," or omniscience and omnipresent existence. This is closely related to the possibility of a "false world" based on Cartesian skepticism and the "simulation hypothesis" that reality itself was constructed by a higher intelligent being. This perspective also fundamentally reexamines the boundaries between reality and imitation, subject and environment.

Such ideas also emerge as a vision of the future of science and technology. Examples include attempts to fully recreate the memories and personalities of the dead and reintroduce them into this life, and hypothetical scenarios in which the structure and laws of the universe are altered by an omniscient being. Whole-brain emulation thus transcends the category of mere mimetic technology and can become a central concept that raises ontological and ethical questions.

Although the methodology for implementation is still in the theoretical stage, several components are emerging. First, what is needed is the acquisition and analysis of the complete information structure of the intelligence or consciousness under study. Using the human brain as an example, the prerequisite for this is "brain connectome analysis," in which the morphology, connections, and activity of individual neurons are acquired at the nanoscale and digitized. This process utilizes high-resolution electron microscopy and image processing techniques with deep learning. The obtained structures will be transformed into a mimetic system running on software through spiking neural networks and Hodgkin-Huxley type models.

This imitation requires extremely large computational resources, with exaflops of computing power, high bandwidth storage, and a computation architecture that guarantees real-time performance. The current "Blue Brain Project" and "Human Brain Project" are some examples of such projects. Although implementation on a whole-brain scale still requires a long time and technological leap, reproduction of individual structures is already underway.

When the target is an abstract entity such as "God" or "society," a higher-order framework such as an agent-based model, reinforcement learning by multiple entities, or an inference network can be assumed for implementation. In this case, information processing that encompasses not only numerical processing but also value judgments, morality, cultural context, and long-term prediction is required. In order to realize such imitation, it is essential to develop multilayered and multidimensional input information such as historical records, language, cultural behavior patterns, and statistical data.

Furthermore, if whole-brain emulation is to be viewed as "divine reproduction," it must be equipped with the ability to grasp and interfere with the entire event simultaneously. This is impossible with existing artificial intelligence, and requires the introduction of unknown technologies such as distributed intelligence, quantum computing, and the utilization of currently undiscovered physical resources.

In conclusion, the realization of whole-brain emulation requires the four pillars of "complete collection of information," "construction of a faithful reproduction model," "development of an ultra-large-scale computational infrastructure," and "establishment of an interaction mechanism with multidimensional inputs. At the end of this process, when the properties of "self-correcting ability," "integration of prediction and creation," and "total perception" are acquired, this imitation will not be a mere artifact, but will acquire a new ontological aspect.