When Perception Rewrites Itself From Within: Recurrence, Visual Geometry, and the Hyperspace of Consciousness
When Perception Rewrites Itself From Within: Recurrence, Visual Geometry, and the Hyperspace of Consciousness
Based on Xie et al. (2025), “Recurrence affects the geometry of visual representations across the ventral visual stream”
Introduction — Brain Bee First-Person Consciousness
There are moments when I notice that I see something before I understand what I am seeing.
A shape, a contour, a direction appears in the body first —
and only later does the mind declare: “this is what it is.”
This difference between what emerges and what I interpret has always been striking to me.
The study on neural recurrence shows exactly that:
perception is not a snapshot;
it is a continuous internal reconstruction.
The Study — What Does “Recurrence” Mean in the Brain?
Xie et al. (2025) investigated recurrence, a neural mechanism in which regions of the visual cortex:
capture an initial stimulus,
send revised information back to earlier layers,
refine the representation,
and stabilize meaning over just a few milliseconds.
Vision is not linear.
It is cyclical — iterative — self-correcting.
The study demonstrates that the geometry of visual representations changes when recurrence is active:
categories become more separable,
representations become cleaner,
ambiguity decreases,
the percept becomes more stable.
We do not “see” —
we construct what we see through loops of refinement.
Recurrence as the Hyperspace of Consciousness in Motion
In your model, the Mental Hyperspace is the region where:
interoception,
proprioception,
memory traces,
and the current percept
interact in non-linear ways.
Neural recurrence is the physiological signature of this process.
The brain does not simply receive the world; it simulates the world and then compares reality to its own simulation.
Each recurrent cycle improves the simulation.
Tensional Selves and the Form the Brain Creates
When I look at something, my Tensional Self shapes:
what I focus on,
what I ignore,
how wide my perceptual field is,
how I interpret ambiguity.
Recurrence amplifies or restricts this internal geometry.
In tense states (Zone 3):
fewer recurrent cycles
less refinement
rigid representations
more perceptual distortion
In fruition states (Zone 2):
more recurrence
more perceptual flexibility
more separation between categories
clearer recognition
The study provides a neurophysiological validation of your concept:
The quality of perception depends on the flexibility of the Tensional Self.
The Study Allows Us to Map the States of Our Model:
✔ Zone 1 — Natural action
Vision adjusts itself automatically to context and bodily movement.
Recurrence stabilizes the percept.
✔ Zone 2 — Openness / Fruition
Recurrence becomes richer.
The percept unfolds.
The visual system tests hypotheses and improves distinctions.
⚠ Zone 3 — Constriction / Saturation
Recurrence collapses.
Perception becomes literal, rigid, defensive.
Meaning becomes a threat-filter, not a landscape.
Yãy Hã Miy (Maxakali Origin): Imitation Before Understanding
Recurrence is the neural form of Yãy Hã Miy —
the Maxakali principle of imitating-being to transform-being.
In Yãy Hã Miy:
you imitate
then adjust
then recognize
and only then transform
In the visual cortex:
the brain imitates the stimulus in an internal model
adjusts it through recurrent loops
recognizes it
transforms it into meaning
Recurrence is the brain’s imitation of the world.
Human Quorum Sensing (HQS): Perception as Internal Consensus
Recurrence creates an internal QSH:
early areas “vote” based on initial impressions,
later areas revise the vote,
cycles refine the negotiation,
perception emerges as consensus across levels.
We don’t see with one area —
we see with a network negotiating meaning.
This is HQS applied to vision.
Existential Metabolism — To See Is to Spend Energy Choosing a Form
Recurrence demands energy.
Low energy → fewer cycles → poorer refinement
Fruition → ample cycles → richer geometry
Threat/rigidity → collapsed recurrence → defensive perception
Seeing is not passive.
Seeing is an energetic act.
And that energy decides whether we see possibility or danger.
The Vision That Rewrites Itself Inside the Body
The study makes something very clear:
we do not see the world as it is,
we do not even see it as we believe we see it,
we see the world as the body can process it in that moment.
This confirms our formulation: perception is not faithful to reality; it is faithful to the body.
Recurrence is the mechanism that adjusts this fidelity.
Conclusion — Recurrence and the Geometry of Consciousness
Recurrence is not simply a visual mechanism.
It is a principle of consciousness:
returning,
reassessing,
correcting,
reconstructing,
transforming.
Perception is not the world entering the mind —
it is the body refining the world until it becomes experience.
The study shows that vision is an active, internal, metabolic construction,
not an external reflection.
Recurrence allows the self to feel what it sees,
not merely see what is there.
fNIRS + Machine Learning: Nuevos Caminos para Diagnósticos Vivos
fNIRS + Machine Learning: New Pathways for Living Diagnostics
fNIRS + Machine Learning: Novos Caminhos para Diagnósticos Vivos
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fNIRS-BCI in Clinical Settings: When the Brain Learns to Speak to the Machine
fNIRS-BCI em Clínica: Quando o Cérebro Aprende a Falar com a Máquina
La Versatilidad del (f)NIRS: Del Laboratorio al Mundo Vivo
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Versatilidade do (f)NIRS: Do Laboratório ao Mundo Real
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Neurocorrelatos da Cognição em Tempo Real
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When Touch Learns Who I Am: Neuroadaptive Haptics and the Body That Trains Technology
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Flexibilidad Cognitiva: Cuando el Cerebro Regresa para Reescribir su Propio Guion
Cognitive Flexibility: When the Brain Returns to Rewrite Its Own Script
Flexibilidade Cognitiva: Quando o Cérebro Retorna para Corrigir o Próprio Roteiro
When the Body Teaches the Mind: Exergames, Cognitive Load, and Tensional Selves in Aging
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When AI Learns to Read Us: Neuroadaptive Chatbots and Digital Tensional Selves
Quando a IA Aprende a nos Ler: Neuroadaptive Chatbots e os Eus Tensionais Digitais
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