用大脑视觉机制模拟古文字生成，揭示符号演化规律
From edges to meaning: Semantic line sketches as a cognitive scaffold for ancient pictograph invention
- 构建类脑视觉模型，从图像生成轮廓草图并迭代优化
- 生成符号与古埃及象形文字等高度相似，可辅助破译未解文字
- 为理解人类如何把感知转为符号提供神经计算框架，适合认知科学与AI研究者
人类能从稀疏线条中快速识别物体，这种能力在发育早期即出现且跨文化普遍存在，暗示其神经基础而非纯后天习得。然而大脑如何将高层语义知识转化为低层视觉符号仍不清楚。本文提出，古代象形文字源于大脑将视觉输入压缩为稳定边界抽象的固有倾向。我们构建了一个生物启发的数字孪生视觉系统，通过前馈与反馈回路，将图像编码为低级特征，生成轮廓草图并基于语义表示进行迭代优化，模拟人脑视觉皮层结构。生成的符号与不同文化系统的早期文字（如埃及象形文字、甲骨文、原始楔形文字）在结构上高度相似，并为未破译文字提供了可能解释。研究支持象形文字具有神经-计算起源，建立了一个让AI重现人类首次将感知外化为符号的认知过程的框架。
原文摘要 · Abstract (English)
Humans readily recognize objects from sparse line drawings, a capacity that appears early in development and persists across cultures, suggesting neural rather than purely learned origins. Yet the computational mechanism by which the brain transforms high-level semantic knowledge into low-level visual symbols remains poorly understood. Here we propose that ancient pictographic writing emerged from the brain's intrinsic tendency to compress visual input into stable, boundary-based abstractions. We construct a biologically inspired digital twin of the visual hierarchy that encodes an image into low-level features, generates a contour sketch, and iteratively refines it through top-down feedback guided by semantic representations, mirroring the feedforward and recurrent architecture of the human visual cortex. The resulting symbols bear striking structural resemblance to early pictographs across culturally distant writing systems, including Egyptian hieroglyphs, Chinese oracle bone characters, and proto-cuneiform, and offer candidate interpretations for undeciphered scripts. Our findings support a neuro-computational origin of pictographic writing and establish a framework in which AI can recapitulate the cognitive processes by which humans first externalized perception into symbols.
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