NeuroFLY: An In-Silico Connectomic-Spiking Framework for Simulating Sensory-Driven Neural Dynamics and Modulatory State Transitions in Drosophila melanogaster

NeuroFLY: An In-Silico Connectomic-Spiking Framework for Simulating Sensory-Driven Neural Dynamics and Modulatory State Transitions in Drosophila melanogaster ABSTRACTConnectomic reconstructions have achieved dense synaptic resolution across complete insect central nervous systems, exemplified by the Drosophila melanogaster male central nervous system dataset (male-cns:v1.0). However, bridging static anatomical wiring diagrams with continuous, real-time functional dynamics driven by non-synthetic, real-world sensory environments remains an open challenge. In this paper, we present NeuroFLY, an open-source, decoupled in-silico simulation and WebGL exploration framework that integrates empirical Drosophila connectomics with continuous Leaky Integrate-and-Fire (LIF) spiking neural network dynamics, real-time multimodal sensory feature injection, persistent neuromodulatory adaptation, and zero-copy GPU skeletal rendering. KEY CONTRIBUTIONS• Empirical Connectome Fidelity: Direct ingestion of the Janelia male-cns:v1.0 graph preserving observed EM synaptic weights, soma coordinates, and cell classifications (Kenyon cells, MBONs, PAM/PPL1 dopaminergic clusters) without synthetic structural edges.• Multimodal Sensory Transduction: A deterministic mathematical pipeline translating live broadcast video luminance, contrast, color diversity, edge density, and textual semantic salience into dynamic Poisson spike trains driving sensory populations.• Persistent Causal State Modeling: A formalized, strictly causal state-space model governing short-term adaptation (A_t), long-term habituation (H_t), and dopaminergic modulatory output (D_t) across continuous exposures, accompanied by a mathematical proof of trajectory dependence.• Factorial In-Silico Experimentation: An automated test harness crossing dopaminergic excitability sweeps with targeted structural synaptic ablations, demonstrating connectome-constrained computation (Two-way ANOVA F(4, 90) = 482.3, p < 10^-15).• Zero-Copy WebGL Streaming (.nbf): Specification and implementation of the NeuroFly Binary Format (.nbf), bypassing browser JSON serialization overhead to achieve interactive 60 FPS skeletal rendering on consumer hardware. PROJECT RESOURCES• GitHub Repository: https://github.com/iamnih4l/NeuroFLY• Live Demonstration & Article: https://www.linkedin.com/pulse/imagine-being-able-make-fly-watch-news-see-how-would-react-nihal-txmac• Author: Mohammed Nihal (Independent Researcher, Kasaragod, India)• Contact Email: [email protected] CITATIONMohammed Nihal. (2026). NeuroFLY: An In-Silico Connectomic-Spiking Framework for Simulating Sensory-Driven Neural Dynamics and Modulatory State Transitions in Drosophila melanogaster. Figshare. Preprint. https://doi.org/10.6084/m9.figshare.34877853