מודל נוירוקומפוטציה: תשתית לתקשורת בין תרבויות נוירולוגיות ביולוגיות לבין תקיפה מאולתרת של תפקודי תגובה

תקציר מקורי באנגליתarXiv:2605.13315v2 Announce Type: replace-cross Abstract: Biological neural networks (BNNs) have been established as a powerful and adaptive substrate that offer the potential for incredibly energy and data efficient information processing with distinct learning mechanisms. Yet a core challenge to utilizing BNN for neurocomputation is determining the optimal encoding and decoding mechanisms between the traditional silicon computing interface and the living biology. Here, we propose an Embodied Neurocomputation framework as a systems-level approach to this multi-variable optimization encoding/decoding problem. We operationalize this approach through the first large-scale parameter optimization of encoding configurations for a BNN agent performing closed-loop navigation along an odor-style g