Connectome-Based Modelling Reveals Orientation Maps in the Drosophila Optic Lobe
Jia-Nuo Liew, Shenghan Lin, Bowen Chen, Wei Zhang, Xiaowei Zhu, Wei Zhang, Xiaolin Hu
The ability to extract oriented edges from visual input is a core computation across animal vision systems. Orientation maps, long associated with the layered architecture of the mammalian visual cortex, systematically organise neurons by their preferred edge orientation. Despite lacking cortical structures, the $\textit{ Drosophila melanogaster}$ brain contains feature-selective neurons and exhibits complex visual detection capacity, raising the question of whether map-like vision representations can emerge without cortical infrastructure. We integrate a complete fruit fly brain connectome with biologically grounded spiking neuron models to simulate neuroprocessing in the fly visual system. By driving the network with oriented stimuli and analysing downstream responses, we show that coherent orientation maps can emerge from purely connectome-constrained dynamics. These results suggest that species of independent origin could evolve similar visual structures, offering new insights into the evolution of visual processing and bio-inspired AI architectures.