PriMera Scientific Engineering (ISSN: 2834-2550)

Research Article

Volume 8 Issue 3

Neuro-Symbiotic Loops: A Framework for Trust Calibration and Adaptive Synchronization in Human-AI Decision Making

Fernando May Fuentes*

March 02, 2026

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Abstract

The rapid integration of Large Language Models (LLMs) and autonomous agents into high-stakes decision-making loops has precipitated a critical challenge: the “black box” opacity of AI reasoning fosters user distrust and cognitive misalignment. While previous research, such as the NeuroDigital Adaptive Network (NDAN), established the architectural infrastructure for bidirectional neural data flow, the mechanism by which human physiological states dynamically calibrate trust in real-time remains under-explored. This paper introduces the Neuro-Symbiotic Synchronization (NSS) Protocol, a novel framework that utilizes continuous physiological monitoring (EEG, HRV, eye-tracking) to construct a dynamic “Trust Oscillator”. This closed-loop system adapts the complexity and explanation depth of AI responses based on the user’s inferred cognitive load and trust levels. We present a mathematical model of trust dynamics and validate the architecture through a simulated human-in-the-loop scenario involving crisis management. Results indicate that biologically-informed adaptive interfaces significantly reduce cognitive load and improve decision accuracy compared to static AI interfaces, providing a robust pathway toward trustworthy human-AI symbiosis.

Keywords: Human-AI Collaboration; Trustworthy AI; Human-in-the-loop; Physiological Computing; Adaptive Interfaces; Neuro-Symbiotic Systems

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