Emergent Individuality and Neural Integration in Whole-Brain Connectome Simulations of Drosophila melanogaster

Abstract

This study presents whole-brain connectome simulations of Drosophila melanogaster using the FlyWire dataset (139,255 neurons, 54.5 million synapses), incorporating Hebbian plasticity, embodied biomechanics via NeuroMechFly v2, and a novel consciousness index (CI) combining integrated information theory (Phi), global workspace theory, and neural complexity metrics. Results demonstrate emergent individuality across repeated simulations: distinct behavioral trajectories, unique plasticity patterns, and differentiated consciousness profiles arise from identical initial conditions. Peak CI values of 0.31 were observed during escape responses, with Phi reaching 0.089 during high-integration states. This work establishes a framework for studying emergent cognition in biologically realistic neural simulations and provides open-source tools for whole-brain embodied modeling.

Abstract of "Emergent Individuality and Neural Integration in Whole-Brain Connectome Simulations of Drosophila melanogaster" by Enrique Manuel Rojas Aliaga, https://doi.org/10.5281/zenodo.19152237, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified.