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Cognitive Interpolation: The Mechanics of Visual Closure and Amodal Completion

Author: Samuelson G.

Contact: gsamuelsonguna@gmail.com

DOI
Zenodo
Academia.edu
OSF License: CC BY 4.0

📌 Overview

This repository contains the research paper, empirical data summaries, and interactive visualization code for "Cognitive Interpolation: The Mechanics of Visual Closure and Amodal Completion." Visual perception is not a passive recording of the environment; it is an active, predictive construction. This research investigates the neurological imperative of "amodal completion"—the brain's ability to instinctively generate the "other half" of an object when presented with partial, occluded, or fragmented visual data. By synthesizing Gestalt psychology with modern neurocomputational models, this paper explores the quantitative thresholds, qualitative experiences, and profound applied implications of this cognitive heuristic.

🧠 Key Findings

  • Neural Latency: Amodal completion occurs within 100–200 milliseconds in the primary visual cortex (V1/V2), functioning as a hard-wired survival circuit rather than a conscious assumption.

  • The 50% Threshold: Quantitative trials indicate that up to a 50% occlusion threshold, the brain's interpolation engine operates with near-zero latency penalty compared to processing whole objects.

  • Amodal Presence: Qualitative surveys reveal that users experience a "quasi-perceptual" phenomenon, reporting high certainty regarding the shape, color, and texture of unseen elements based on surrounding context.

📂 Repository Structure

  • /paper - Contains the full research manuscript in PDF and LaTeX/Markdown formats.

  • /interactive-spa - Source code (HTML/JS/Tailwind) for the Single-Page Application (SPA) designed to visually demonstrate the Kanizsa Triangle illusion and interactive data charts.

  • /assets - Static images and graphs generated from the empirical data.

🌍 Applications & Ethics

Understanding the brain's drive for visual closure has significant implications across multiple fields:

  • UI/UX Design: Utilizing whitespace and implied boundaries reduces cognitive load and creates highly efficient interfaces.

  • Aviation & Medical Imaging: Identifying where human predictive coding fails (e.g., "black hole" illusions in flying, false positives in radiology) allows for better training and interface safety.

  • Digital Ethics: The brain is highly susceptible to manipulation if provided with "half-truths." The research outlines the risks of AI-generated deepfakes and misinformation that weaponize our natural need for cognitive closure.

🏁 Conclusion

The human necessity to "see something one time halfly" and neurologically construct the remainder is a testament to the evolutionary efficiency of the brain. It is a sophisticated predictive system designed to prioritize rapid decision-making over pixel-perfect accuracy in natural, visually noisy environments.

However, as we navigate increasingly synthetic, digital landscapes, this same biological strength becomes a critical vulnerability. Our reliance on cognitive interpolation can lead to spatial disorientation, diagnostic errors, and susceptibility to manipulated media. Moving forward, the integration of human-in-the-loop systems—whether in aircraft cockpits, diagnostic AI, or social media platforms—must account for the brain’s autonomous creative power. We must design systems that leverage the speed of visual closure while implementing safeguards against the dangers of over-interpolation.

📜 Citation

If you utilize the data, concepts, or code from this repository in your own work, please cite the paper:

Samuelson, G. (2026). Cognitive Interpolation: The Mechanics of Visual Closure and Amodal Completion. Journal/Repository. DOI: 10.13140/RG.2.2.30145.11362

⚖️ License

The code for the interactive elements is licensed under the MIT License. The research text and data are licensed under CC BY 4.0.

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Official repository for "Cognitive Interpolation: The Mechanics of Visual Closure." Includes the full research paper, empirical datasets, and an interactive SPA demonstrating amodal completion and predictive coding.

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