A single interface module of the brain (human sensory
inputs) provides an accessible pattern and data to the brain structure from
external surroundings. Algorithmic codes of environmental input transfer in
distinct biological neural networks emerge, comprising both subconscious and
conscious components, through vibrational frequencies, and generate a conceptual desire for future planning.
Visualization is not simply a product of neural activity. However, a
multi-layered process is governed by the interaction between the Subconscious
and Conscious Components, orchestrated through algorithmic codes within a
holographic cognitive system.
Algorithmic patterns and inferences in the physical
world are explored in the visual category of daily life, allowing individuals
to expand their knowledge and achieve desired outcomes by interpreting and
transforming abstract phenomena into concrete forms. However, the brain
structural interface and neural networks cannot distinguish between real-life
experiences and imagined or visualized events.
Humans can establish algorithmic codes beyond
visualization without inferences from the physical world through emerging
algorithmic codes beyond the Subconscious and Conscious Components. The brain
structure is not involved in creating and processing algorithmic visualization
codes. Therefore, primary memory may not capture algorithmic codes of
visualization.
1.
Subconscious Component
1.1-Generates
symbolic images, emotional tones, and abstract patterns.
1.2-Draws
from deep memory, the Instinct Component, the Superego/ Ego framework, the
Belief System, and internalized experiences.
1.3-Often
active in dreams, meditative states, and spontaneous imagination.
1.4-Role:
Provides the raw data, emotional context, symbols, and patterns for
visualization.
1.5-Sources:
Deep memory, instinctual processing, dream-like imagery, archetypes of culture.
1.6-Activity:
Active during sleep (dreams), hypnosis, meditative states, and spontaneous
imagination.
Brief
definition:
Operate through nonlinear logic, emotional pattern
recognition, symbolic compression, and archetypal imagery. These codes generate
the raw content of visualization, images, sensations, emotional textures, and
intuitive symbols. Example:
When individuals suddenly see a symbolic image in the physical brain without
effort, external algorithmic codes are likely emerging into the Subconscious
and Conscious Components modules. It creates a new prototype and concepts to
navigate the evolutionary path of life.
2.
Conscious Component
2.1-Directs
and organizes visualization with intention and awareness.
2.2-Uses
logic, attention, and willpower to shape mental imagery in the secondary
memory.
2.3-Active
during planning, problem-solving, and deliberate imagination.
2.4-Role:
Directs, refines, optimizes, and gives intention to visualization.
2.5-Sources: Logical thinking, attention, goal-directed
imagination, and mental rehearsal are stored in the secondary memory.
2.6-Activity: Active during conscious visualization,
like planning, designing, or mentally simulating events, exploring repository
data from past experiences, and theoretical analysis of frameworks.
Brief
definition:
Execute sequential logic, goal-oriented simulation, and
attentional prioritization. These codes refine, direct, and give structure and
narrative to the imagery.
Example: When an athlete visualizes performing
a routine step-by-step, the Conscious Component generates the plan blueprint
and is supported by Subconscious memory.
3. The
brain is an interface of human sensory input
Although
the brain is not the origin of visualization, it is the biological interface
where mental images are constructed and experienced. Key regions include:
1.
Visual Cortex (Occipital Lobe): Renders mental images stored in the primary
memory.
2.
Prefrontal Cortex: Provides focus, sequencing, and control in short-term
memory.
3.
Temporal and Parietal Lobes: Retrieve memories and organize spatial details.
4.
Default Mode Network (DMN): Supports self-generated thoughts and inner
simulations.
4.
Construction process for creating visual representations
Visual
representation emerges and interacts through three components as follows.
1. The brain submodules are explored as interfaces that
create the final mental data image for the Subconscious and Conscious
Components.
2. The subconscious unit generates the content that
generates symbols, emotions, and visual elements.
3. The
Conscious shapes the structure, clarity, rationality, purpose, sequencing, and
narration.
5.
Holographic Cognition and the Visualization Process
The mind operates as a holographic field, where every
part contains the informational structure of the whole. Visualization reflects
this principle:
5.1-Each mental image is a compressed
holographic packet containing spatial, emotional, and informational data.
5.2-Like a projection lens, the brain serves as the
interface, decoding and displaying this holographic information into conscious
awareness.
5.3-Every visualization contains fractal references to
broader inner and outer realities—this is why dreams, imagination, and
spiritual visions can hold multi-layered significance.
6.
Brain as Interface (Biological Execution Layer)
Though visualization originates in deeper cognitive
layers, the brain acts as the biological decoding system. It shows algorithmic
functions in designated components as follows:
While
visualization and intention emerge from deeper cognitive and abstract layers of
the Conscious Component, the brain functions as the biological interface for
execution and translation. In this role, it decodes non-material cognitive inputs, such as
intention, imagery, emotion, and codes of belief, into structured neural
activity that can interact with the physical body and environment. The brain
does not originate meaning on its own; instead, it operates as an adaptive
processing system that converts higher-order cognition into actionable
biological signals.
From an algorithmic perspective, the brain can be understood as a distributed execution layer composed of specialized subsystems, each performing distinct but interdependent functions, as the following statements:
6.1-Perceptual
Decoding Modules
Sensory cortices
translate external stimuli into neural representations, effectively digitizing
physical inputs such as light, sound, touch, and chemical signals into data
that the system can process. These modules filter, compress, and prioritize
information before passing it upstream.
6.2-Pattern
Recognition and Prediction Engines
Associative regions, such as temporal and parietal networks, identify patterns,
compare them against stored models, and generate probabilistic predictions. Thus,
it enables anticipation, learning, and contextual interpretation, core
functions of adaptive intelligence.
6.3-Intent-to-Action
Translation Units
The prefrontal cortex and motor planning areas act as compilers. Abstract goals
and intentions are broken down into executable sequences, which are then
dispatched as motor commands or regulatory signals through the nervous system.
6.4-Emotional
Weighting and Signal Amplification
Limbic structures assign value, urgency, and salience to cognitive content.
Emotion functions as a gain control mechanism, amplifying or dampening signals
to influence decision-making, memory encoding, and behavioral output.
6.5-Feedback
and Error-Correction Loops
Continuous feedback from the body and environment is compared against predicted
outcomes. Discrepancies trigger adjustments, refining future responses. Thus,
it mirrors iterative optimization processes found in computational systems.
In this framework, the brain is not the source of the Conscious
Component or creativity but the interface layer that enables their
expression in biological form. It executes, optimizes, and regulates, bridging the
gap between abstract cognition and physical reality through electrochemical
processes. As such, the brain can be seen as a living operating system:
dynamic, self-modifying, and tightly coupled to both internal states and
external conditions.
7. Integrative Model:
Visualization can be created without data inferences
within abstract phenomena by the Subconscious and Conscious Components.
Otherwise, it establishes inferences with evidence and repository analysis of
statistical data in the real world through the Brain framework and is extended
to the Conscious Component. The power of visualization
can be developed by understanding knowledge bases and visualizing data to
gain valuable insights.
7.1-Create a visualization based on
external inferences
Multiple dissociation phenomena are initiated and
perpetrated from external environments via brain systems (visual cortex,
prefrontal cortex, hippocampus), so integrated brain structure models establish
and support logical codes within the Conscious Component to generate
visualization patterns. The outcome of visualization is modulated by emotional
tone, purpose, and intention. (Fig. 1)
Visualization = (Subconscious Content) × (Conscious
Direction)
The Subconscious and Conscious Components function
through distinct vibrational frequencies with interconnected algorithmic codes,
each contributing uniquely to the overall system's operations. These operations
are input-interfaced and mirror external surroundings through the brain's
neural architecture. The submodules of the Subconscious Component can reflect
preprogrammed symbolic codes, and the Conscious Component would contribute
logical codes from the repository unit to brief following the equation. (Fig.
1)
Visualization
= (Subconscious Symbolic Codes × Conscious Directive Codes)
7.2-Create a visualization of internal inferences
Algorithmic codes of visualization can be created
through a correlation between modules beyond the Subconscious and Conscious
components. The desired outcome of the visualization map is not transparent to
the brain framework and instance domains. (Fig. 2)
8. Summary
Visualization is generated through a dynamic
collaboration between the Subconscious and Conscious Components, using the
brain as an interface to translate external data into vivid mental imagery.
Individuals can establish algorithmic visualization codes through internal
processing and interpreting codes without the entanglement of brain structure.
Therefore, the brain and submodules cannot differentiate the correlation
between internal algorithmic codes beyond the visualization map and imagined or
visualized external events.
