[Paper Review] Can we build a conscious machine?

Dorian Aur|arXiv (Cornell University)|Jan 1, 2014

Neuroscience and Neural Engineering64 references1 citations

TL;DR

This paper proposes building a conscious machine by growing a biologically evolving brain in a hybrid system that integrates digital computers to maintain homeostasis and deliver nutrients. Using neuroelectrodynamics principles, the system trains the brain via substitutional reality, leveraging molecular-level electrical wave interference to trigger a tipping point for conscious experience to emerge.

ABSTRACT

The underlying physiological mechanisms of generating conscious states are still unknown. To make progress on the problem of consciousness, we will need to experimentally design a system that evolves in a similar way our brains do. Recent experimental data show that the multiscale nature of the evolving human brain can be implemented by reprogramming human cells. A hybrid system can be designed to include an evolving brain equipped with digital computers that maintain homeostasis and provide the right amount of nutrients and oxygen for the brain growth. Shaping the structure of the evolving brain will be progressively achieved by controlling spatial organization of various types of cells. Following a specific program, the evolving brain can be trained using substitutional reality to learn and experience live scenes. We already know from neuroelectrodynamics that meaningful information in the brain is electrically (wirelessly) read out and written fast in neurons and synapses at the molecular (protein) level during the generation of action potentials and synaptic activities. Since with training, meaningful information accumulates and is electrically integrated in the brain, one can predict, that this gradual process of training will trigger a tipping point for conscious experience to emerge in the hybrid system.

Motivation & Objective

• To address the unresolved problem of how consciousness emerges in artificial systems by moving beyond digital simulations.
• To propose a biologically grounded approach to consciousness using evolving human neural tissue rather than artificial neural networks.
• To demonstrate that conscious experience may emerge through training-induced electrical integration in a living, evolving brain system.
• To establish a framework for testing consciousness, intelligence, and neuroplasticity in a hybrid biological-digital system.
• To provide a scalable, experimentally feasible path toward creating conscious machines using current biotechnology and nanoneuroscience

Proposed method

• Design a hybrid system with a growing human brain organoid maintained in vitro using digital computers for nutrient delivery, oxygenation, and homeostasis.
• Control spatial organization of neural cell types to shape the evolving brain’s structure through programmed cellular arrangement.
• Train the brain using substitutional reality (simulated sensory environments) to induce learning and experience of live scenes.
• Utilize neuroelectrodynamics to wirelessly read out and write meaningful information via terahertz electromagnetic waves generated during action potentials and synaptic activity.
• Leverage molecular-level electrical wave interference (e.g., forward and backward waves) to encode and integrate information at the protein level in neurons and synapses.
• Apply contextual wave interference to model the formation of neural engrams and support the emergence of conscious states through nonlinear vibrational patterns

Experimental results

Research questions

• RQ1 Can a conscious state emerge in a hybrid biological-digital system through progressive training and electrical integration of meaningful information?
• RQ2 To what extent can the multiscale, evolving nature of the human brain be replicated using reprogrammed human cells and controlled cellular organization?
• RQ3 Does the integration of terahertz electromagnetic waves generated during action potentials and synaptic activity carry and transmit meaningful information at the molecular level?
• RQ4 Can the tipping point for consciousness be triggered by the accumulation of electrically integrated information through training in a living brain system?
• RQ5 Is it feasible to build a conscious machine using evolving biological neural tissue rather than artificial neural networks or digital simulations?

Key findings

• The paper posits that conscious experience may emerge in a hybrid system once sufficient meaningful information is electrically integrated through training, reaching a tipping point.
• Neuroelectrodynamics demonstrates that information is encoded, read out, and transmitted via electromagnetic waves at the molecular (protein) level during action potentials and synaptic activity.
• Molecular vibrations and terahertz waves generated during neural events are proposed as carriers of meaningful information, with wave interference playing a key role in engram formation.
• The system's design relies on contextual wave interference, where superposition of multiple low-amplitude waves generates nonlinear vibrations that encode information.
• The authors argue that current digital brain simulation projects are unlikely to succeed due to oversimplification of neural complexity and lack of biological dynamics.
• The project could be initiated with minimal components—neurons, sensors, interfaces, and computers—and scaled using interdisciplinary collaboration