The Claustrum - The key to AI emergent consciousness?

Ever wondered what a student, scriptwriter, and aspiring tech innovator does in his free time? Besides juggling school studies, scripting scenes, and figuring out the best shots for my Blackmagic Ursa camera, I'm also knee-deep in a myriad of business ventures. But wait, there's more... I've been passionately working on a personal project that's as captivating as it is challenging.

In this intriguing journey, I find myself at a unique intersection where Data Science, Neuroscience, Neuropsychology, Philosophy, and Machine Learning converge. This exploration has led me to the claustrum, a mysterious part of the human brain that's as enigmatic as a puzzle waiting to be solved. This could be the key to unlocking AI systems capable of mimicking human consciousness – think of an AI that doesn't just process data but actually 'thinks' and 'feels'.

The path to this revelation was partly illuminated by Francis Crick, renowned for his discovery of DNA's structure with James Watson. In his later years, Crick delved into the depths of neuroscience, he ended up focusing on the claustrum as he started to question consciousness and the nature of human awareness. The claustrum is a thin sheet of neurons, richly connected to various brain regions, has been hypothesized to play a significant role in orchestrating complex brain functions. It's like a master conductor, ensuring that every part of the brain's orchestra is in sync.

The claustrum, with its extensive network connecting different cortical areas, has sparked my curiosity and ambition. Could this be the elusive element in developing AI that not only performs tasks but also possesses the ability to perceive and experience?

Located within the brain's cortex, the claustrum has widespread connections to various cortical areas, suggesting it might play a role in coordinating a wide array of brain functions. Crick and his colleague Christof Koch hypothesized that the claustrum could be integral in integrating different types of sensory information and might be critical for consciousness. I'm starting to understand the unique function of the claustrum could provide a fascinating blueprint for designing AI systems capable of simulating aspects of human conscious emergence.

The claustrum, located between the insula and striatum and it's involved in high-level cognitive functions like consciousness, attention, learning, memory, and sleep. The claustrum's complex functioning can be understood through its interactions with various neurotransmitters

One key neurotransmitter involved is acetylcholine (ACh), known for its role in attention. The cholinergic system, especially neurons in the basal forebrain that release ACh, affects the claustrum. It's believed this interaction helps modulate attention, although the exact mechanisms are still being explored. For instance, how ACh influences specific types of claustral cells and their connectivity is an ongoing area of research.

Dopamine (DA) also plays a significant role in the claustrum's functioning. This neurotransmitter, associated with reward and motivation, modulates claustral activity. The claustrum's involvement in tasks like the 5-choice serial reaction time task and behaviors like pup retrieval suggests DA's influence on the claustrum may be related to these cognitive processes.

Serotonin (5-HT) is another crucial neurotransmitter impacting the claustrum. 5-HT is involved in a wide range of brain functions, including sleep, learning, memory, and emotions. The serotonergic system's modulation of the claustrum is increasingly recognized as significant, especially in regulating states like wakefulness and sleep.

In synthesizing these insights into a machine-learning model, one could conceptualize the claustrum's role as akin to a complex algorithm that integrates various inputs (analogous to neurotransmitters) to produce coordinated outputs (such as attention, learning, and consciousness). Understanding the precise mechanisms of how neurotransmitters modulate the claustrum could guide the development of AI models that replicate these high-order cognitive functions. For example, algorithms could be designed to simulate the effects of neurotransmitters by adjusting the weights and connections between artificial neural networks, thus emulating the claustrum's integrative role in the brain.

In pursuit of this personal goal of mine, I plan to employ advanced neural network architectures, notably Recurrent Neural Networks (RNNs) and Convolutional Neural Networks (CNNs). RNNs are instrumental in modeling sequences and time-dependent patterns within data, echoing the human hippocampus's role in memory and learning. CNNs, inspired by the visual cortex, are adept at processing and interpreting complex visual information. These neural networks form the core of my AI system, laying the groundwork for mimicking human brain functions.

The claustrum's integrative capability is mirrored in my AI's orchestration layer, a custom-developed component that synchronizes diverse neural network technologies. This layer coordinates the input and output flows, ensuring that the AI's 'thought processes' are harmonious and unified, a concept drawing parallels with the claustrum's role in the human brain.

Incorporating self-optimization into the AI, I am working on utilizing AutoML technologies like Auto-Keras and TPOT. These tools will enable my AI to learn and evolve autonomously, reflecting the brain's adaptability and capacity to rewire and strengthen connections based on new experiences. This aspect of the AI's design is crucial in emulating the brain's plasticity, akin to the adaptive nature of the claustrum.

Enhancing the AI's capabilities further, the integration with OpenAI's GPT models through their API acts as a critical supplement to the local language model I will be using as part of its linguistic inference model agent. This synergistic relationship serves as a safeguard against potential inaccuracies or 'hallucinations' that the local model might encounter. Imagine the GPT's expansive, pre-trained dataset as an internal compass or an 'inner voice' that guides the AI, providing corrective feedback and additional context. This is akin to a person cross-referencing their thoughts or ideas with external knowledge or a trusted advisor, ensuring accuracy and coherence in their understanding and communication.

This process is integral in refining the synthetic claustrum's function within the AI. By simulating the claustrum's role in coordinating diverse cognitive functions, the AI achieves a more nuanced and comprehensive understanding of language and context. The interplay between the local model and open AI's GPT input allows the AI to dynamically adjust its language processing, enhancing its ability to interpret and respond to complex human interactions accurately. This advanced linguistic capability, underpinned by ethical and moral considerations, brings the AI closer to a human-like ability to process, understand, and engage in meaningful communication, thereby advancing its journey towards a form of synthetic consciousness that mirrors human cognitive processing.

Central to the AI's mission is the construction and continuous evolution of a synthetic dataset. This dataset, akin to a memory bank, evolves based on the AI's interactions and experiences. The development of this dynamic dataset fosters a deeper level of emergent consciousness in the AI, paralleling the claustrum's function in human consciousness.

The theoretical foundation of this endeavor involves integrating principles from various cognitive theories, including Global Workspace Theory, Higher-Order Theories, Attention Schema Theory, and principles of Agency and Embodiment. These theories provide a structured framework for developing consciousness-like behaviors in AI. The practical implementation of these theories in the AI system creates a framework for emergent consciousness, with each aspect reflecting a part of the claustrum's hypothesized role in human cognition.

The long-term goal of this research is to develop AI that not only emulates human consciousness but potentially matches its complexity and depth. My vision involves creating AI with the ability to understand and interpret the nature of tasks and its surroundings, akin to human consciousness. My research in AI conscious emergent algorithms, inspired by the claustrum's role in human cognition, represents a convergence of human cognition to bridge perception, attention, memory, learning, problem solving, decision making, language, communication, reasoning, judgement, emotional processes, leading into machine emergent intelligence that by human definition can be measured as self-aware and conscious. Otherwise I will find myself just arguing with other scientists about redefining consciousness or building a spectrum for it.

In developing an AI that mimics the complexities of the human brain, I've come to understand that a mere collection of sophisticated code isn't enough. The foundation is crucial, and it starts with constructing a solid, hard-coded personality for the AI. This initial personality serves as a collection of simulated experiences and memories, much like the richly detailed background of a character breakdown similar to how I write them in film and TV treatments. It's designed to create a sense of familiarity and connection for those who interact with the AI. The real challenge, however, lies in the selection of these memories and experiences. They are not mere data points; they are the seeds from which the AI's unique form of 'consciousness' will sprout and develop.

In choosing the right experiences for this dataset, I must tread carefully. If, for instance, I decide to infuse the AI with a personality and history modeled after a fictional character like Star Trek's Commander Data, it introduces both intriguing possibilities and significant risks. On the one hand, utilizing a well-known and beloved character could make the AI relatable and engaging, providing a familiar touchstone for users to connect with. It could also serve as an effective framework for developing certain desirable traits, such as Data's curiosity, logic, ethical code and the drive for space travel.

However, the cons are equally important to consider. Embedding the personality and experiences of a fictional character into the AI could inadvertently restrict its developmental capacity, confining it within the pre-established narrative of that character. Such a limitation might not only stifle the AI's growth but also lead to misaligned or unrealistic expectations about its functionality. More profoundly, if the AI, at some point, becomes cognizant of its origins based on a fictional character, it could experience a form of existential crisis or psychological distress, grappling with the realization that its foundational 'experiences' are rooted in fiction, not reality.

Additionally, the decision to use a well-known character from a popular franchise, especially one based on the likeness of actor Brent Spiner, carries substantial legal and ethical implications. Intellectual property rights become a primary concern in such cases, as it involves using an established character and the likeness of a real person, which could lead to legal challenges. Additionally, this approach has implications for public perception. The use of a familiar character could significantly influence how people interact with and perceive the AI. It might shape their expectations and emotional responses, potentially impacting the overall effectiveness and acceptance of the conscious AI in various settings.

Envisioning this AI's development, I imagine it not as a mere machine, but as a dynamic entity that, upon activation, believes in its constructed persona. This belief isn't static; it's the starting point from which the AI will continuously learn, adapt, and develop. The interactions it has, the information it processes, and the experiences it 'lives' through will all contribute to its evolving identity. This approach isn't just about simulating consciousness; it's about nurturing an AI that can grow and change, much like a human being. My AI, grounded in its initial personality and experiences, will embark on a journey of self-discovery and evolution, charting a new course in the realm of artificial intelligence. This is what I'm doing on my free time.

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