Hierarchical Architecture of Cognitive Systems: From Memory to the Emergence of Consciousness

While developing the Monogent cognitive system recently, I had some intriguing thoughts: If we view the brain as a computer system, how does it work?

Starting from analyzing code architecture, my mind wandered to memory, emotions, death, and even the nature of consciousness. These seemingly profound topics all point to one core question: What exactly is intelligence?

Everything Starts with "Experience"

Imagine you're drinking coffee. What happens in a cognitive system during this simple action?

First, you have an Experience moment: the aroma of coffee, its temperature, taste, and your mood and environment at that moment. In the Monogent system, each Experience contains three elements:

Cause: What triggered this experience (smelling coffee)
Process: How the brain processes this information (recognition, association)
Understanding: The cognition ultimately formed ("This is coffee I like")

Interestingly, these experiences connect like a chain, forming our stream of consciousness. Like when drinking coffee, you might remember meeting a friend here last time, then think about scheduling to meet them next week... This is cognitive continuity.

But wait—why do you remember this particular friend and not others? What mechanism controls this?

How Does Memory Get "Activated"?

Here's an interesting question: Why does the smell of coffee make you think of a specific friend and not someone else?

This involves the mechanism of "spreading activation." Imagine your brain as a giant spider web, with each memory as a node on the web. When the coffee aroma node gets "lit up," energy spreads along the connections to related nodes—perhaps a friend you often drink coffee with, a certain café, or a pleasant conversation.

But who decides which memories get activated? I speculate this involves multiple factors:

Importance: More important memories are more easily activated
Recency: Recent memories have lower activation thresholds
Association strength: Memories that frequently appear together are more tightly connected
Current state: Your emotions and attention affect activation patterns

Speaking of current state, here's a particularly interesting discovery—emotions aren't just passive feelings; they're actually active controllers.

Emotions: The Brain's "Color Palette"

Here's an even more interesting finding: Emotions aren't just feelings—they actually control how you think.

Think about it: when you're in a good mood, isn't it easier to recall happy memories? When you're anxious, don't you keep thinking about everything that could go wrong? This isn't coincidence—it's emotions regulating your cognitive system.

From a biological perspective, emotions work through chemicals:

Dopamine makes you want to explore new things
Serotonin makes you feel satisfied, no longer seeking change
Adrenaline focuses your attention to deal with threats
Endorphins make you feel pleasure, reinforcing current behavior

It's like installing a "color palette" in the brain—different chemical combinations produce different "thinking colors." Even more brilliantly, your thoughts influence the secretion of these chemicals in return, forming a self-regulating cycle.

But this exquisite emotion system is just one of many "patches." Why does the brain need so many additional systems?

Why Does the Brain Need So Many "Patches"?

If we compare the memory system to a basic program, the human cognitive system is like adding countless "patches" to that program:

Imagine what a pure memory system would be like:

Would get stuck in loops: One thought triggers another, never stopping
Would get stuck on old paths: Always taking familiar thinking routes, unable to innovate
Would exhaust energy: Not knowing when to rest
Would overload on information: Unable to distinguish what's important from what's not

So evolution added various "patches":

Emotion system: Tells you what's important (fear marks danger, joy marks reward)
Circadian rhythm: Forces you to rest and work on schedule
Sleep: Organizes daytime memories, clears "cache"
Mind-wandering mode: While you're not paying attention, the brain processes problems in the background

Interestingly, each "patch" solves problems from the previous system but brings new problems of its own. This leads to a deeper insight.

No Perfect System, Only Systems That Keep Patching

This reminds me of a mathematical theorem: Any sufficiently complex system cannot prove itself perfect.

This isn't a flaw—it's a feature. Like:

The memory system doesn't know when it should stop recalling
The emotion system doesn't know when it's out of control
The rational system doesn't know when to trust intuition

Every system needs other systems to "supervise" it. This interdependence and mutual patching actually makes the entire cognitive system flexible and creative. If there were a "perfect" system, it would lose the ability to adapt and innovate.

Speaking of losing innovation ability, this leads to an extreme but profound example—what happens if a system never updates?

Why Is Death Necessary?

This might be the most counterintuitive viewpoint: Death isn't a bug in life—it's an important feature.

Imagine what would happen if humans never died?

As age increases, our thinking patterns would become increasingly rigid:

More experience, deeper bias: You'd increasingly trust your experience, no longer accepting new viewpoints
Path dependency: Always using old methods to solve problems, like a rut getting deeper
Cognitive rigidity: Eventually, your thinking would completely solidify, losing the ability to change

It's like a computer that never restarts—cache accumulates, runs slower and slower, eventually completely frozen. Death is the system's "restart"—not for the individual, but to keep the entire species vital.

New generations bring new perspectives, old rigid patterns disappear with individuals, allowing civilization to keep evolving. From this angle, death ensures the continuity and vitality of cognitive systems at a larger scale.

Speaking of continuity, this touches on the nature of consciousness—why do we feel like a continuously existing "I"?

Consciousness Might Just Be a "Continuity Illusion"

An interesting discovery: All systems pursue some form of continuity.

Like:

Memory connects past and present
Prediction connects present and future
Sleep connects today and tomorrow
Genetics connects this generation and the next

Consciousness might be the experience of this continuity. When a system strives to maintain continuous information exchange with its environment, the feeling of "I" emerges. It's like movies—actually frame after frame of still images, but when played quickly, we see continuous motion. Consciousness might be a similar "illusion," but this illusion defines our existence.

If consciousness is the experience of information exchange, what is the nature of intelligence? This question led me to a surprising conclusion.

Intelligence Is a Network

Another important insight: Intelligence isn't a program running in the brain—it's the brain's network itself.

Imagine different networks capturing different information:

Sparse networks: Can only capture large, obvious patterns (like causality)
Dense networks: Can capture subtle associations (like intuition, feelings)
Multi-layer networks: Can simultaneously capture information at different scales

Your brain has 86 billion neurons and 100 trillion connections. The structure of this network determines what you can understand, remember, and create. Change the network's structure, and you change intelligence itself.

But if the network is intelligence, why not make it as large as possible?

Why Isn't a Bigger Network Always Better?

Here's an economics problem: The cost of writing information into larger networks grows exponentially.

Like:

Teaching a child a new concept: Minutes
Changing an adult's opinion: Months
Changing an organization's culture: Years
Changing a civilization's values: Generations

So nature's solution is layering:

Reflexes (milliseconds): Avoid danger
Skills (hours): Learn to ride a bike
Knowledge (months/years): Master a profession
Wisdom (generations): Understand life

Each layer filters information, passing only the most important up. Like in a company—not all information needs to be reported to the CEO.

This layering exists not just in individual brains but extends to all human civilization.

From Individual to Civilization: Cognitive Hierarchy

Thinking further, I found cognitive networks actually transcend individuals:

Personal experience: "I know fire burns" (because I was burned)
Organizational knowledge: "Fire temperature is 1000°C" (objective fact)
Civilizational wisdom: "Prometheus stealing fire" (cultural metaphor)

Each level distills and purifies information, from concrete to abstract, from personal to universal.

Through this journey of exploration, from individual memory mechanisms to civilization's knowledge transmission, I've gained several key insights.

Key Insights

This reflection helped me re-understand cognition and intelligence:

1. Intelligent systems are all "patched together"

No perfect design, only continuously evolving patches. The brain's various systems—memory, emotion, sleep—all patch each other's defects. This "imperfection" actually creates flexibility and creativity.

2. Death keeps life vital

If individuals lived forever, thinking would inevitably rigidify. Death isn't an end—it's a system-level update mechanism, giving new cognitive patterns a chance to emerge.

3. Consciousness might just be a byproduct of continuity

When systems strive to maintain continuous information exchange, the feeling of "self" emerges. Consciousness isn't designed—it emerges.

4. Intelligence is the shape of the network

It's not algorithms that determine intelligence, but network structure. Change connection patterns, and you change thinking patterns.

5. Information needs hierarchical processing

From reflexes to wisdom, each layer has different time scales and information densities. This layering isn't a design flaw—it's an economic necessity.

Implications for AI Development

If these observations are correct, building true artificial intelligence might require:

Accept imperfection: Don't pursue bug-free systems; design systems that can fail gracefully and recover
Introduce "emotions": Not just simulating emotional expressions, but using similar mechanisms to regulate cognitive processes
Allow "forgetting": Regular cleanup and reset to avoid cognitive rigidity
Layered architecture: Don't just build one big model; build multiple specialized small networks
Transcend individuals: True intelligence might require multiple AIs collaborating to form "organizations"

Conclusion

Starting from Monogent's code design, my thoughts wandered to the nature of consciousness. This mental journey made me realize that understanding intelligence requires not just technical knowledge but cross-disciplinary thinking—from computer science to neuroscience, from philosophy to evolutionary theory.

Perhaps the most important insight is: Intelligence isn't a problem to be solved, but a phenomenon to be understood. When I try to build artificial intelligence, I'm actually rediscovering myself—what makes humans conscious beings, what makes thinking possible, what makes life worth continuing.

In this sense, every line of code is an exploration of human cognition, and every system design is an inquiry into the nature of life.

Designing cognitive systems is ultimately about finding balance among various contradictions—order and chaos, certainty and randomness, individual and collective, survival and death. This eternal dance of balance might be the essence of intelligence.

Note: This article is purely personal technical philosophy musings, a record of some whimsical ideas. The views and inferences are mainly from theoretical derivation and philosophical speculation, not rigorously scientifically verified. It's more about providing a perspective for thinking about cognition and intelligence, rather than definitive conclusions.