Cognitive Architecture
Theory

I Introduction: An Information-Theoretic Reconstruction of the Dual System
인지 이중 시스템의 정보이론적 재구성

The dual-system theory proposed by Daniel Kahneman in Thinking, Fast and Slow divided human cognition into System 1 (fast, intuitive, automatic) and System 2 (slow, deliberate, effortful). This classification has served as the dominant paradigm of cognitive science for the past two decades. However, the “fast and slow” description remains at the operational level — it tells us about differences in processing speed and resource consumption between the two systems, yet fails to address a more fundamental question: what do these two systems do to information?

This paper proposes an entirely new definition. The core function of System 2 is not “slow thinking,” but rather abstraction — classifying, ordering, analogizing, distilling received information, and invoking existing knowledge for alignment and internalization. This is a process of information dimensionality ascension: converting low-order sensory input into high-order conceptual structures. The core function of System 1 is not “fast intuition,” but rather concretization — converting abstract structures processed by System 2, or directly received information, into cognitive units that humans can immediately invoke. This is a process of information dimensionality reduction: compressing high-dimensional concepts into multimodal concrete representations — visual images (the most common and highest-bandwidth modality), auditory patterns (inner sounds and melodies), somatosensory-motor memory (procedural actions involving the cerebellum, such as cycling and piano playing), and visceral-somatic sensations (the bodily substrate of “gut feelings”). Image-formation is the most readily invoked concrete modality for humans, but it is not the only one.

This redefinition is not a purely conceptual exercise. It yields a critical analytical advantage: it allows us to describe cognitive processes in the language of information theory, thereby introducing precise tools such as channels, bandwidth, noise, and signal-to-noise ratio. And it is precisely these tools that will reveal a series of structural problems overlooked by traditional cognitive science.

Empirical neuroscience research supports this redefinition. The hippocampus and prefrontal cortex achieve abstract representations through dimensionality reduction processes — compressing high-dimensional sensory input into low-dimensional formats to support generalization. The ventromedial prefrontal cortex exhibits goal-directed dimensionality compression during concept learning, and the degree of compression predicts individual selective attention ability. Episodic memory relies on two opposing processes of reduction and ascension: reduction compresses sensory input into storable simplified encoding, while ascension reconstructs vivid details during retrieval. These findings confirm that the brain is indeed performing systematic information dimensionality transformation operations, rather than simple “fast/slow” switching.

II The Four-Layer Cognitive Architecture
4층 인지 아키텍처

The traditional dual-system model omits two critical lower-level systems. This paper proposes that the complete human information processing architecture consists not of two layers, but four. From bottom to top:

  ┌─────────────────────────────────────────────────────────┐
  │  Layer 4: System 1 · Concretization Engine · Dim. Red.  │
  │  Compresses abstract structures into multimodal          │
  │  concrete cognitive units for output                     │
  ├──────────────── ↕ Bidirectional Feedback ────────────────┤
  │  Layer 3: System 2 · Abstraction Engine · Dim. Ascension │
  │  Classification, ordering, analogy, distillation,        │
  │  alignment, internalization                              │
  ├──────────────── ↕ Bidirectional Feedback ────────────────┤
  │  Layer 2: Endocrine Signal Tagging System                │
  │  Hormone-driven evaluative signals                       │
  │  (good/bad/urgent/irrelevant)                            │
  ├──────────────── ↕ Bidirectional Feedback ────────────────┤
  │  Layer 1: Enteric-Brain Survival System                  │
  │  ~500 million neurons · Autonomous operation ·           │
  │  Origin of ~95% of serotonin                             │
  └─────────────────────────────────────────────────────────┘
  Note: Arrows indicate bidirectional feedback coupling
  between layers, not a unidirectional pipeline. Prefrontal
  cortex, amygdala, hypothalamus, brainstem, autonomic nerves,
  gut, immune, and endocrine systems form a multi-loop
  parallel system. The four-layer stratification is an
  analytical framework, not physical isolation.
  

A clarification is necessary: the four-layer stratification is a structural simplification made for analytical clarity — in the actual biological system, these four layers are bidirectionally coupled with parallel feedback, not sequentially processed layer by layer. The prefrontal cortex can regulate gut activity (top-down), and gut signals can bypass the cognitive system to directly affect mood and behavior (bottom-up). Describing them in layers is meant to expose lower-level variables neglected by traditional cognitive science, not to claim they are physically isolated operating system stacks.

Layer 1: The Enteric-Brain Survival System

The human gut contains approximately 500 million neurons, forming an autonomously operating enteric nervous system (ENS), which researchers have for decades called the “second brain.” The ENS operates in a genuinely autonomous manner, independently executing complex tasks and controlling vital functions regardless of the central nervous system. Approximately 95% of the body’s serotonin is produced in the gut, not in the brain. In many cases the gut is the first responder — emotional reactions are often generated by the gut before conscious awareness.

This means: the human lower-level survival regulatory system is not a purely intracranial system, but a distributed survival network jointly constituted by the brainstem, hypothalamus, autonomic nervous system, endocrine system, and enteric-brain axis. With its approximately 500 million neurons and high degree of autonomy, the enteric nervous system is a critical node in this network that has long been neglected by cognitive science. A person requires no abstract thought whatsoever for this distributed survival network to maintain their existence — hunger produces feeding impulses, danger triggers avoidance responses, drowsiness drives sleep. One can go an entire lifetime without thinking, but cannot survive a single second without the survival network’s maintenance.

Layer 2: The Endocrine Signal Tagging System

The signals that perceive preferences are endocrine hormones, not products of the abstraction and concretization systems. This distinction is critical. Researchers have explicitly proposed that neuronal processes in the brain are primarily used for information processing and stimulus handling, while the endocrine system serves as the necessary “output medium” for emotions and sensations — without the endocrine system, there would be no emotions or sensations. Valence and arousal have been shown to originate from two independent neurophysiological systems: valence is primarily associated with the orbitofrontal cortex and mesolimbic dopamine system, while arousal is primarily associated with the amygdala and reticular activating system.

The endocrine system’s operation on information is not “processing” but tagging — it assigns evaluative labels to incoming information: good or bad, urgent or irrelevant, approach or avoid. It is a hardware system that exists prior to the cognitive systems (System 1 and System 2) and is evolutionarily more ancient.

Layers 3 and 4: The Ascension and Reduction Engines

After System 2 receives information tagged by the endocrine system, it executes abstraction operations — classification (assigning information to existing conceptual categories), ordering (establishing hierarchical priority), analogy (discovering structural mappings between new information and existing knowledge), distillation (extracting core patterns from informational noise), alignment (matching new information to existing cognitive frameworks), and internalization (integrating aligned information into long-term knowledge structures). This is a process of information dimensionality ascension: transforming raw sensory data into abstract conceptual networks.

After System 2 completes processing, the resulting information is transferred to System 1 for concretization — generating multimodal cognitive units that humans can directly invoke. Visual images are the most common concrete output (a veteran traditional medicine practitioner “sees” the lesion while reading the pulse; a veteran detective “sees” the anomaly at a crime scene), but concretization equally produces auditory patterns (a musician “hears” an unwritten melody internally), motor schemata (an athlete’s body “knows” how to execute a movement), and visceral somesthesia (“my gut tells me something is wrong” — somatic marking). These are all concrete representations where countless rounds of System 2 abstraction have been internalized and then reduced to “instant knowing” — different channels produce different output modalities, with images merely being the highest-bandwidth channel among them.

III Channel Parameters and Individual Cognitive Differences
채널 파라미터와 인지적 개인차

Not all individuals can execute abstraction and concretization operations at high speed and efficiency. This fact requires a precise explanatory framework. Borrowing the information-theoretic concept of channels, this paper proposes that individual differences in cognitive ability are essentially differences in three channel parameters:

Neuroscience research has precisely validated this framework. Myelination provides internet-like processing properties — speed, bandwidth, and online connectivity. Myelination dramatically increases signal transmission speed, enables the brain to integrate spatially distributed neural network information, and shortens the refractory period by up to 34-fold, thereby producing sufficient bandwidth for information-dense encoding. Working memory capacity and working memory processing speed have been shown in behavioral research to be interrelated, sharing neural substrates in the right prefrontal region. High working memory capacity individuals can more efficiently utilize neural resources to maintain attentional focus on task-relevant information, exhibiting qualitative neural differences.

From Metaphor to Operationalization: Measurable Mappings of the Channel Model

The “channel, bandwidth, noise” terminology used in this paper is primarily information-theoretic metaphor. To equip this framework with the potential to evolve from a thought model toward a researchable model, the following operationalization mapping from theoretical variables to measurable indicators is provided:

It must be candidly acknowledged: this paper has not yet completed the full transition from metaphor to operationalized variables. The table above is a roadmap, not a destination. When “channel count” can be concretely defined as the number of white matter tracts measured by DTI or the number of functional connectivity modules from fMRI, and “noise intensity” can be defined as the coefficient of variation from multi-day retesting on the same task, this framework will be upgraded from a thought paper to an experimentally testable scientific theory.

This means: when classmates receive the same education yet produce different grades, the root cause lies not in differences in the effectiveness of educational methods, but in differences in the hardware parameters of the receiving end. If education were equally effective for everyone, grade differentiation within the same classroom would not occur. Education is software-level optimization — it can help each person run better processing protocols on existing channels, but it cannot change the physical specifications of the channels themselves. A two-lane highway, no matter how optimized the traffic regulations, cannot match the throughput of an eight-lane highway.

IV The Biochemical Environment: The Dual Role of the Endocrine System
생화학적 환경: 내분비 시스템의 이중 역할

Humans are not fixed-cycle systems. This fact is the key to understanding cognitive performance fluctuation. A machine’s CPU has a stable crystal oscillator frequency, doing the same thing every clock cycle. Humans have no such stability. The endocrine system is in a state of perpetual flux — its signal output is continuously fluctuating, unpredictable, and beyond volitional control. And the biological signals emitted by this perpetually fluctuating endocrine system continuously modulate the cognitive system’s operating state — enhancing channel performance at moderate levels, and impairing it at excessively high or low levels.

Blood Glucose Supply Fluctuation

The brain is an extreme energy consumer, constituting 2% of body weight yet consuming approximately 20% of glucose. Blood glucose is one of the cognitive channel’s power supply systems. The healthy human body possesses blood glucose homeostatic regulation mechanisms (hepatic glycogen release, insulin-glucagon feedback) capable of buffering fluctuations within a certain range. But this buffering is not unlimited: under conditions of extreme dietary patterns, insulin resistance, or high-GI intake following prolonged fasting, blood glucose fluctuations may exceed the homeostatic regulation range, producing measurable effects on cognitive processing. Regarding the relationship between glucose and self-control, the classic “willpower fuel” hypothesis has undergone replication controversies and revision — a more cautious formulation is: blood glucose fluctuations may modulate cognitive performance under specific conditions, but the effect size depends on individual metabolic state, meal structure, task type, and time interval.

Serotonin and Enteric-Brain Coupling

95% of serotonin is produced in the gut. A precise qualification is needed: peripheral serotonin and central serotonin are not a single freely miscible pool — the blood-brain barrier restricts peripheral serotonin from directly entering the brain. The gut’s influence on cognition is indirect: through vagal afferents, immune signaling molecules, tryptophan metabolites (serotonin precursors can cross the blood-brain barrier), and short-chain fatty acids produced by gut microbiota, it modulates the central neurotransmitter environment. Therefore, the accurate formulation is not “gut serotonin directly regulates cognitive channels,” but rather “the gut microenvironment continuously influences the functional state of the central serotonin system through multiple indirect pathways.” The existence of these indirect pathways is sufficient to support this paper’s core thesis — that the enteric-brain system exerts continuous, uncontrollable biochemical influence on the cognitive system — but does not support a simplistic direct regulation narrative.

Endocrine Cycles and Sex Differences

The uncontrollable hormone secretion triggered by food intake generates uncertainty that is one of the core exogenous factors affecting the cognitive and perceptual systems. And this uncertainty exhibits enormous individual and sex differences. The female endocrine system is structurally more complex — the menstrual cycle produces large periodic fluctuations in estradiol, progesterone, luteinizing hormone, and follicle-stimulating hormone, with a complete oscillation approximately every 28 days. Progesterone regulates more bottom-up emotional processing, while estradiol activates top-down lateralized regulatory control. Male testosterone also has diurnal fluctuations, but with amplitude and cycle complexity far lower than the female pattern.

Evolution may have already developed partial adaptive hedging mechanisms for neural circuits chronically exposed to periodic hormonal fluctuation. But regardless of the efficacy of compensatory mechanisms, single-snapshot assessment is inherently harder at accurately sampling a system with greater dynamic fluctuation — this assessment-methodological argument is independent of any empirical disputes about the direction and magnitude of sex differences.

The Inverted-U Effect of the Endocrine System: The Dialectic of Noise and Signal

The endocrine system is not a pure noise source. The Yerkes-Dodson Law states that there is an inverted-U relationship between arousal level and cognitive performance — arousal that is too low leads to attentional diffusion and sluggish information processing; moderate arousal (driven by appropriate levels of norepinephrine and cortisol) actually expands attentional bandwidth, improves signal-to-noise ratio, and enhances working memory stability; only excessive arousal drowns cognitive channels.

This means the relationship between the endocrine system and the cognitive system is dual in nature. The endocrine system is both a noise source and a signal amplifier — the same hardware plays opposite roles at different activation levels. The problem lies not in the endocrine system itself, but in humans’ inability to precisely control where they sit on the inverted-U curve. Food, sleep, emotional events, digestive state — all these uncontrollable variables continuously push the individual into random drift along the curve. The ascetic practices of deep thinkers, within this framework, are not about “eliminating” endocrine activation, but about stabilizing it within the optimal zone of the inverted-U curve — high enough to sustain cognitive arousal, yet not so high as to drown the channels. This is tuning, not noise reduction.

Top-Down Regulation: Cognitive Reverse Control of Biochemical State

The preceding sections of this paper emphasized the bottom-up direction — how the enteric-brain and endocrine systems affect cognition. But the bidirectionally coupled model demands equal attention to the reverse pathway: the cognitive system’s top-down regulation of biochemical state. The empirical basis for this direction is equally robust. Cognitive reappraisal can significantly reduce cortisol levels and amygdala activation; mindfulness meditation produces long-term changes in autonomic nervous system balance (increasing parasympathetic activity); cognitive behavioral therapy can ameliorate irritable bowel syndrome and other enteric-brain axis-related conditions; the placebo effect regulates dopamine, endorphins, and immune responses through purely cognitive expectations.

Within this framework, top-down regulation means: System 2 is not merely a passive receiver disrupted by lower-level noise — it also possesses a limited capacity to actively adjust the gain knob through specific operations (reappraisal, meditation, attentional management). This is the other half of the explanation for deep thinkers’ ascetic practices within the inverted-U framework — asceticism achieves state tuning not only by reducing food and stimulus input (lowering noise sources bottom-up), but also through meditation and attentional training (adjusting the gain set-point top-down). The relative contributions of the two pathways vary by individual and practice modality.

V The Cognitive Output Function: A Multi-Variable Dynamic Model
인지 출력 함수: 다변수 동적 모델

Based on the preceding analysis, this paper proposes that human cognitive performance at any given moment can be described as the following function:

Among these six variables, channel hardware parameters and software strategy are relatively constant — the former determined by genetics, the latter shaped by education and training. But the latter four variables are all dynamic, uncontrollable, and continuously fluctuating, and they are also coupled to each other: blood glucose decline causes irritability, irritability alters attentional allocation, attentional allocation alters information intake quality, information quality alters abstract processing output, and output quality in turn affects mood. This is not a linear causal chain; it is circular coupling.

This means: does a human being actually have a “true intelligence value”? Pushed to its logical conclusion within this framework, the answer may be negative. Because the cognitive system never operates in isolation — it is perpetually embedded within the hormonal system and the enteric-brain survival system. So-called intelligence is the coordinated performance of three system layers at a particular temporal slice. Hardware parameters define the theoretical upper limit, but actual output is always modulated by the real-time states of the two lower layers. It is like a computer whose CPU specifications are fixed, but if the power supply voltage is unstable and the cooling system malfunctions, the benchmark score will differ every time.

VI Self-Control: The Noise Suppression Mechanism of Cognitive Systems
자기 통제: 인지 시스템의 노이즈 억제 메커니즘

If endocrine noise is a persistent source of interference for the cognitive system, a natural question arises: does the individual have the ability to actively suppress this interference? The answer is: yes, but this suppressive capacity is subject to significant genetic influence.

A meta-analysis encompassing 31 twin studies and over 30,000 twin pairs showed that the self-control correlation coefficient for monozygotic twins was 0.58 and for dizygotic twins was 0.28, yielding a heritability estimate for self-control of approximately 60%. A strict qualification is essential: heritability is a population-level statistic, indicating what proportion of individual differences within a specific population and environmental range is associated with genetic differences. It does not mean “60% of a given person’s self-control is fixed by DNA.” A more accurate formulation is: self-control has significant genetic contributions; genetics sets the initial constraints and sensitivity range, but environment, training, stress, sleep, social structure, and developmental experiences jointly determine the actualization pathway.

The neural mechanisms of self-control correspond precisely to this paper’s architecture. The prefrontal cortex achieves self-regulation by exerting top-down control over subcortical regions (the striatum, responsible for reward, and the amygdala, responsible for emotion). Sustained self-control depends on the balance between impulse-control brain regions and brain regions representing the reward value and emotional valence of stimuli. When impulse intensity exceeds regulatory capacity, self-control fails.

More critically, self-control exhibits depletion characteristics: following an episode of self-control exertion, lateral prefrontal cortex activity declines, and the magnitude of decline is directly correlated with performance deficits on subsequent cognitive tasks. This constitutes a self-reinforcing degradation loop: each self-control failure depletes prefrontal resources, making the next failure more likely, endocrine noise interference more severe, and cognitive performance further degraded.

The State Tuning Engineering of Deep Thinkers

Throughout history, a large number of deep thinkers have exhibited behavioral patterns of asceticism, fasting, and celibacy — behaviors that run counter to human biological needs. Within this framework, these behaviors have an engineering explanation: they are state tuning engineering — pushing the cognitive system’s operating state toward the optimal zone of the inverted-U curve through multiple pathways.

What fasting does is: temporarily reduce the activity level of the digestive system — a major noise source. When digestion slows, enteric-brain signal output decreases and the endocrine system enters a relatively stable low-fluctuation state. Animal experiments have found improvements in cognitive function, learning, and memory indicators when the brain and body are in a fasted state. However, a cautious qualification is needed: in healthy human subjects, the cognitive-enhancing effects of intermittent fasting currently lack clear and consistent evidence. A 2021 systematic review explicitly stated that evidence for short-term cognitive gains from intermittent fasting in healthy populations is insufficient. A more robust framework formulation is: fasting may, in some adapted individuals and for some task types, improve cognitive conditions through metabolic switching (glucose → ketone bodies), reduction of systemic inflammation, and improvement of the gut microbial environment, but its effects depend on individual adaptation state, fasting duration, and task demands. For non-adapted individuals, fasting may equally cause attentional decline, irritability, and headaches — this is not a “clean channel” but power supply insufficiency.

The theoretical mechanism of celibacy is reducing the frequency of high-amplitude endocrine oscillations. Sexual activity can cause transient autonomic nervous system and hormonal state changes — momentary spikes in heart rate and blood pressure, sustained prolactin elevation following orgasm. Theoretically, these changes may affect cognitive arousal and attentional allocation for a subsequent period. But the direction and effect size still require task-specific measurement verification — one cannot directly infer a universal bandwidth reduction. Celibacy’s positioning within this framework is: a strategy for reducing high-amplitude biochemical oscillations, whose cognitive effect evidence base is weaker than that for fasting — currently a theoretical inference only.

Retreat/seclusion packages fasting, celibacy, and environmental isolation together as a systematic tuning regimen. From Pythagoras establishing proto-monastic communities in the West to the minimalist lives of Jain monks, these practices have been interpreted in traditional contexts as “spiritual pursuits,” but within this framework they achieve cognitive state tuning through two pathways: the lower-level metabolic pathway (reducing food input to stabilize power supply, decreasing endocrine oscillation frequency, lowering systemic inflammation) and the upper-level attentional pathway (reducing social interference, lowering attentional switching costs, decreasing task-switching frequency). The two pathways operate jointly to push the cognitive system toward the optimal zone of the inverted-U curve. The relative contributions of the two pathways require experimental separation — the cognitive effects of retreat may to a large extent derive from attentional management rather than metabolic switching.

Applicability Boundary of Tuning: Isolated Thinking vs. Collaborative Cognition

It must be noted that the optimality of ascetic tuning is limited to isolated deep thinking — independent mathematical derivation, philosophical contemplation, theoretical construction. For modern cognitive tasks requiring high-frequency interaction, rapid response, and high-intensity collaboration, thoroughly suppressing endocrine activation may push arousal below the inverted-U curve’s optimal point, actually reducing system throughput. A scholar who needs to provide instant responses and engage in competitive debate at an academic conference requires moderate adrenaline and cortisol to maintain cognitive acuity — at which point the excessively low arousal brought by fasting and celibacy may be a disadvantage rather than an advantage. The implementation of tuning strategies must match the type of cognitive task: isolated tasks require a low-arousal baseline; collaborative tasks require moderate activation within the optimal zone of the inverted-U curve. One-size-fits-all asceticism is not a universal prescription.

VII Genetic Transmission and Environmental Shaping
유전적 전달과 환경적 형성

The significant genetic contribution to self-control implies: an individual’s ability to suppress lower-level biological system interference is importantly constrained by genetic factors from birth. What DNA and ancestral evolutionary history transmit to descendants is not a deterministic “fate value,” but rather a sensitivity range and initial constraint conditions. When specific environmental selection pressures (such as famine mortality) weaken, genetic variants associated with those selection pressures may drift more freely in the population. But modern society is not pressure-free; rather, the form of selection pressures has changed (educational attainment, health behaviors, mate selection, etc., may constitute new indirect screening forces). This inference is currently a theoretical hypothesis only, requiring direct support from population genetics data.

More critically, the process of self-control degradation is also influenced by external physical-world environmental variables. El Niño events, glacial periods, uncontrollable natural disasters — these extreme environmental events affect descendants’ cognitive architecture through two pathways.

Pathway One: Natural Selection

The “thrifty gene” hypothesis proposes that in harsh environments with uncertain food supply, genotypes that maximize fat storage and minimize caloric expenditure provided the best survival odds. During glacial periods and famines, natural selection systematically filtered for individuals with stronger lower-level biological drives and greater difficulty suppressing food impulses — because “losing control and eating everything upon seeing food” was a survival advantage. Natural selection does not care whether System 2 works well; it only cares whether the individual survives to reproduce.

Pathway Two: Epigenetic Inheritance

The following evidence comes primarily from animal models and a small number of human observational studies (limited sample sizes, numerous confounding variables). The effect magnitude, persistence, and generalizability of transgenerational epigenetic transmission in humans remain at the verification stage; results from animal models cannot be seamlessly extrapolated to humans. With this qualification, existing research shows: the effects of traumatic experiences may be transmitted transgenerationally through non-genetic means. Observed effects include increased methylation and decreased expression of stress-regulatory axis genes (POMC gene), elevated corticosterone responses, and increased anxiety in behavioral tests. A single major famine triggered by El Niño need not wait tens of thousands of years for natural selection — through epigenetic inheritance, it can alter descendants’ endocrine stress response patterns within two to three generations. These descendants are born with biochemical presets of “high vigilance, high feeding impulse, high stress reactivity” — presets that continuously generate high noise in their enteric-brain and endocrine systems, interfering with cognitive channels, while the individuals themselves may not even know that the source of this noise is a famine experienced by their grandparents.

VIII Critique of Educational Assessment: The Signal-to-Noise Ratio Problem
교육 평가 비판: 신호 대 잡음비 문제

Based on the complete architecture described above, this paper presents a systematic critique of the current educational assessment system: it commits a dual structural error.

The compounded result of the two errors is: exam scores can neither accurately reflect channel parameters (because channels are disrupted by noise) nor accurately reflect software optimization levels (because the physiological state at the moment of assessment is random). A large portion of what they measure is noise. To truly measure the upper limit of a person’s channel parameters, one would theoretically need to take multiple samples at optimal physiological states and extract the peak value — rather than performing a single test at a random physiological state and treating that value as “ability.”

Can education itself change channel parameters? The answer requires stratified discussion. During childhood, myelination is still underway; intensive cognitive training at this stage can indeed physically widen channels — this is education’s most valuable window. In adulthood, channel parameters are no longer fully fixed, but the range of adjustability narrows significantly. Adult brain neuroplasticity genuinely exists — high-intensity cognitive training can induce cortical thickness changes and synaptic remodeling, constituting fine-tuning of the hardware. But a distinction must be drawn between “fine-tuning” and “architectural change”: adult plasticity can optimize synaptic efficiency on existing channels (equivalent to improving road surface quality on a two-lane highway), but cannot add new channels (cannot expand a two-lane highway into an eight-lane highway). The effects of fine-tuning are real but limited; they do not change the order of magnitude of hardware parameters. Education after the critical period operates more at the software level — teaching more efficient abstraction strategies, more precise analogical models — essentially improving the efficiency of compression algorithms on fixed bandwidth. The ceiling of education remains the physiological ceiling, but this ceiling is not absolutely rigid — it has slight elasticity.

IX Theoretical Boundaries, Counterexamples, and Falsifiable Predictions
이론적 한계, 반례, 반증 가능한 예측

Epistemological Positioning of This Framework

The four-layer architecture and channel-noise model proposed in this paper is a conceptual integration framework — its originality lies not in discovering new physiological facts, but in reorganizing the explanatory structure of existing facts. It is a prototype theoretical model, not a mature scientific theory. A mature theory requires completing variable operationalization, proposing falsifiable predictions, designing experiments, and distinguishing alternative explanations. This section attempts a first step in that direction.

Counterexamples Requiring Explanation

If this framework holds, the following phenomena must be absorbed rather than evaded:

Parameter Constraints on the Inverted-U Curve

This framework repeatedly uses the inverted-U relationship to absorb counterexamples. To prevent this tool from becoming an unfalsifiable universal explainer, constraining predictions must be imposed on its parameters: an individual’s optimal arousal zone (the inverted-U curve’s peak position and width) is not arbitrary, but is constrained by three parameters: channel bandwidth baseline, task cognitive load, and individual adaptation history. Specifically, this framework predicts that high-channel-bandwidth individuals have a wider optimal zone (more noise-tolerant, maintaining high performance across a broader arousal range), while low-bandwidth individuals have a narrower optimal zone (more sensitive to arousal deviation). This constitutes an independently testable prediction: channel parameters are positively correlated with inverted-U curve width. If experiments show that the arousal-performance curve widths of high and low working memory capacity individuals do not differ, then the inverted-U model’s mode of application within this framework requires revision.

Formal Hypothesis Set

The following hypotheses, if systematically falsified by experiment, will require substantive revision of this framework:

X Conclusion
결론

The four-layer cognitive architecture theory proposed in this paper redescribes the human information processing system as a bidirectionally coupled dynamic network: the enteric-brain survival layer and the endocrine tagging layer constitute a distributed lower-level survival-evaluation system; System 2’s dominant function is abstract dimensionality ascension; System 1’s dominant function is multimodal concrete dimensionality reduction. The four layers are not a unidirectional pipeline, but a complex system of multi-loop parallel coupling with continuous bidirectional feedback.

Individual differences in cognitive ability are described within this framework as differences in channel parameters — channel count, bandwidth, and transmission efficiency correspond to operationalizable neurophysiological indicators (functional connectivity module count, white matter integrity, working memory span, etc.). Genetic factors impose significant constraints on these parameters (approximately 60% of population-level variance is attributable to genetic differences), while developmental environment, training, long-term lifestyle, and adult-stage neuroplasticity jointly determine the parameters’ final actualized values. Channel parameters define a constraint range, not a fixed destiny.

An inverted-U relationship exists between the endocrine system and the cognitive system — moderate arousal expands attentional bandwidth; excessive arousal drowns channels; insufficient arousal produces inadequate signal. The human predicament is the inability to precisely control one’s position on the inverted-U curve. Blood glucose, digestive state, hormonal cycles, sleep debt — these uncontrollable variables continuously push the individual into random drift along the curve. At the same time, the cognitive system also exerts limited top-down regulation on biochemical state through cognitive reappraisal, meditation, and attentional management — the gain knob is partially in hand, but far from fully controllable.

Self-control, as System 2’s active regulatory capacity over lower-level signals, is subject to significant genetic influence and exhibits depletion characteristics. The ascetic practices of deep thinkers — fasting, celibacy, retreat — constitute systematic tuning of cognitive state, operating through dual pathways of lower-level metabolic routes and upper-level attentional routes to push the operating state toward the optimal zone of the inverted-U curve. The effectiveness of this tuning strategy varies by task type (isolated vs. collaborative), individual adaptation state, and practice modality — it is not a universal prescription.

This paper’s cognitive architecture theory, together with the companion paper “Dark Channels and the Intelligence Evaluation Formula” and the remaining three papers in this series, constitutes a cross-scale theoretical system. This paper provides the hardware-level foundation; the remaining papers extend the framework to scientific methodology critique and civilization-scale analysis. This framework is currently in the stage of evolving from a conceptual integration framework toward a testable theory; the five formal hypotheses (H1–H5) proposed in Chapter IX establish the experimental conditions required to falsify this framework.