The Empirical Brain: Language Processing as Sensory Experience

The Empirical Brain proposes a theoretical framework for understanding language as an embodied, sensory-based cognitive process. Contrary to traditional views of language as a formal symbolic system, this theory holds that words in the human brain are grounded in experience — not as abstract signs, but as complex constellations of multisensory information. Drawing on predictive processing models (Friston, 2010) and embodied cognition (Clark, 2016), the paper argues that linguistic meaning emerges through the brain’s active interpretation of sensory inputs, guided by prior experience and contextual inference.To formalize this view, the paper introduces a three-layered cognitive architecture: sensory input space, a learned empirical representation space, and a symbolic layer linked through a grounding function. This model — the Grounded Symbol Processing System (GSPS) — addresses the Symbol Grounding Problem (Harnad, 1990) by connecting abstract symbols to structured experiential content.The framework clarifies why current AI systems lack true understanding: they manipulate symbols statistically, without grounding them in perception or lived experience. This theory offers a unified perspective on human meaning-making and provides conceptual guidance for the future development of cognitively plausible AI.