MENTAL-ONE: Cross-Exploration of Neuroscience and AGI — From Orch-OR to Integrated Information Theory

MENTAL-ONE is a research project exploring the intersection of neuroscience, psychiatry, and Artificial General Intelligence (AGI). It attempts to combine the Orch-OR theory and Integrated Information Theory (IIT) to understand the essence of consciousness. Maintained by yoonalimsuwan, the project was released on GitHub on June 10, 2026 (link: https://github.com/yoonalimsuwan/MENTAL-ONE). Its core goal is to provide a new perspective for consciousness research and AGI development.

Questions such as the nature of consciousness, how the brain generates subjective experiences, and whether machines can have consciousness have moved from philosophy to the realm of scientific research. In the name MENTAL-ONE, 'MENTAL' refers to mind and consciousness, while 'ONE' implies the pursuit of a unified theory. The project aims to connect neuroscience, psychiatry, and AGI to explore the possible realization of consciousness in artificial systems.

Orch-OR Theory

Proposed by Penrose and Hameroff, its core idea is that consciousness arises from quantum coherence and computation in neuronal microtubules, with objective reduction (critical collapse of quantum superposition states) and biological processes coordinating this process. Controversy: Whether the brain environment supports quantum coherence.

Integrated Information Theory (IIT)

Proposed by Tononi, its core is that consciousness corresponds to the amount of integrated information in a system (Φ value), requiring both integration and differentiation, based on five axioms, and has panpsychist tendencies. It is applied to the study of consciousness levels such as sleep and anesthesia. Controversy: The computational complexity and falsifiability of Φ.

Research Objectives

1. Physical basis of consciousness: Relationship between quantum coherence and Φ value, quantum entanglement explaining the unity of consciousness;
2. Psychiatry framework: Using Orch-OR/IIT to understand mental illnesses and develop diagnostic and therapeutic methods;
3. AGI path: Replicating the physical basis of consciousness and exploring the necessary path for AGI.

Technical Directions

1. Neural computation modeling: Combining classical neural dynamics with quantum effects;
2. Integrated information computation: Approximation algorithms for Φ value;
3. Consciousness detection tools: Assessing consciousness signs in comatose patients and artificial systems;
4. AGI architecture: Integrated information maximization networks, quantum neural computation, etc.

Scientific Significance

• Neuroscience: A unified theoretical framework to guide experiments and provide a basis for brain-computer interfaces;
• Psychiatry: Redefining mental illnesses as disorders of consciousness integration or quantum coherence, and developing new treatments;
• AI: Revealing key elements missing in current AI, guiding next-generation architectures, and sparking ethical discussions.

Philosophical Implications

It touches on profound issues such as the mind-body problem, free will (quantum randomness), artificial consciousness, and panpsychism (IIT implies the widespread existence of consciousness).

Scientific Challenges

Maintenance of quantum coherence (noisy brain environment), computational complexity of Φ value, difficulty in connecting theory and experiments;

Philosophical Challenges

Insufficient falsifiability of the theory, explanatory gap (whether confirming theoretical predictions truly explains consciousness);

Technical Challenges

Computational complexity (quantum neural computation and integrated information computation), lack of consciousness-related neural data.

Related Research

Quantum biology (biological quantum effects), consciousness neuroscience (searching for NCC), computational psychiatry (mathematical models to understand diseases), AI ethics (discussions related to consciousness);

Outlook

The interdisciplinary exploration of the project is valuable; consciousness research requires multidisciplinary collaboration. Current AI is still far from true AGI, and consciousness research may provide key insights; bold exploration may lead to breakthroughs in the field of consciousness.