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One limitation of our study is the reliance upon one type of neural network model. CTRNN models are widely used and well-justified <>19] but we expect that follow-up work using models with more <>62] or less <>63] detailed neural implementations can test the robustness of our predictions. In particular, highly-constrained models have been indispensible for understanding anatomically well-described systems like the pyloric network of the crustacean stomatogastric ganglion <>64, 65]. Although the anatomy and physiology of Drosophila AS circuits are not sufficiently well-characterized to build such detailed models, the body of anatomical and physiological data is growing <>11, 16, 30, 31]. This information will help to constrain neural network topologies <>66– 68] and to reveal how anatomical motifs contribute to the computation of Drosophila action timing.
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