Connectome-constrained neural networks are often evaluated against sparse random controls and then interpreted as evidence that biological graph topology improves learning efficiency. We revisit that claim in a controlled flyvis-based study using a Drosophila connectome, a naive self-loop-matched random graph, and a degree-preserving rewired null. Under weak controls, in which both models were recovered from a connectome-trained checkpoint and the null matched only global graph counts, the connectome appeared substantially better in early loss, mean activity, and runtime. That picture changed under stricter controls. Training both graphs from a shared random initialization removed the early loss advantage, and replacing the naive null by a degree-preserving null removed the apparent activity advantage. A five-sample degree-preserving ensemble and a pre-training activity-scale diagnostic further strengthened this revised interpretation. We also report a descriptive mechanism analysis of the earlier weak-control comparison, but we treat it as behavioral characterization rather than proof of causal superiority. We show that previously reported topology advantages in connectome-constrained neural networks can arise from initialization and null-model confounds, and largely disappear under fair from-scratch initialization and degree-preserving controls.
Discovering Subtypes of Neurodegenerative Progression with a Scalable Connectome-Constrained Dynamic Model
Illinois Institute of Technology（伊利诺伊理工学院）；Amsterdam UMC（阿姆斯特丹大学医学中心）；Inria, Université Côte d’Azur（法国国家信息与自动化研究所，蔚蓝海岸大学）；University of Southern California（南加州大学）
Overlooked weak structural connections support human cognition under nonlinear connectome scaling
Xi’an Jiaotong University（西安交通大学）；Hong Kong Baptist University（香港浸会大学）；Carl von Ossietzky Universität Oldenburg（奥尔登堡卡尔·冯·奥西茨基大学）；University of California San Francisco（加州大学旧金山分校）；Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）；University of Roehampton（罗汉普顿大学）；Zhejiang University（浙江大学）
A frozen rate operator from the complete larval connectome: degree and weight govern the gross response, exact wiring governs input routing and mushroom-body modes
