Abstract
Interfacing artificial decision-making systems with biological neural substrates requires sub-millisecond response latency, zero memory overhead, and strict adherence to biophysical homeostasis. Here, we present the design, mathematical formulation, and in silico empirical validation of a bio-synthetic brain-machine interface coupling the complete 158,262-neuron, 3,990,039-synapse Drosophila melanogaster connectome (Princeton FlyWire) with an implantable 1,024-pin WERR neuromorphic fractal coprocessor. Rather than deploying parameterized tensor-based deep neural networks or spiking transformers that incur prohibitive memory-wall bottlenecks and 15–200 ms inference latencies, the coprocessor generates instantaneous System-1 reflex decisions by sampling chaotic Mandelbrot boundary escape trajectories (∂M), completely eliminating VRAM overhead (0 Bytes VRAM) and evaluating decisions in 0.461 ms. Four penetrating micro-electrode shanks target the Ellipsoid Body (EB) heading compass, the Descending Motor Neuron (DN) pool, and the bilateral Mushroom Bodies (MB). Official Patent Priority: TÜRKPATENT National Priority Application TR 2026/016633 (Priority Date: September 27, 2026, 06:16:04 UTC+3). All bio-synthetic neuromorphic coprocessor architectures, whole-brain connectome steering methods, and biophysical anti-burnout gating mechanisms are officially secured under the Paris Convention 12-month priority umbrella. Replication Package Contents: Complete open-source replication bundle (zenodo_bundle_werrsoma_drosophila_v1.0.zip) containing the CSR-compiled FlyWire 158k connectome cache, the 6-experiment empirical runner (run_scientific_experiments.py), raw benchmark telemetry (scientific_benchmark_results.json), the native Python 3D dual-viewport simulator (bioneural_fly_app.py), and the WebGL Three.js interactive visualizer (fly_bioneural_flight_sim.html).
Abstract of "Bio-Synthetic Neuromorphic Interfacing: In Silico Integration of a Zero-Memory Fractal Decision Engine with the Whole-Brain Drosophila Melanogaster Connectome" by Daghan Dagli, Volkan Dağlı, https://doi.org/10.5281/zenodo.22996625, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified.
Record
- Archive ID
- doi:10.5281/zenodo.22996625
- Published
- Sep 27, 2026
- Venue
- Zenodo (CERN European Organization for Nuclear Research)
- DOI
- 10.5281/zenodo.22996625
- Categories
- Advanced Memory and Neural Computing
- License
- cc-by
- Provenance
- openalex
