Von Economo neurons (VENs) are selectively lost in behavioural-variant frontotemporal dementia (bvFTD) and reduced in autism spectrum conditions (ASC), yet their computational role in social learning remains unexplained. We train a spiking neural network (the VENCircuit) embedding VEN-like projection neurons (K=40, 2% of total) in a recurrent pyramidal circuit across 50 matched random initialisations with and without VENs. The network is trained on a controlled binary classification task; we make no claim to model social cognition directly. VEN-intact networks converged in 49/50 cases (98%) versus 35/50 (70%) for VEN-ablated networks (Fisher's exact OR=21.0, 95% CI 2.7-167, p=8.7e-5). Failed ablated networks showed complete absence of learning, inconsistent with a speed-of-learning account. Phase-ablation experiments show VEN removal is most disruptive during mid-training (epochs 5-25), when a co-adaptive dependency forms in the pyramidal circuit. We derive a formal account showing VENs provide a direct gradient pathway immune to Jacobian instabilities affecting the recurrent circuit. Inference-time VEN ablation caused a significant performance drop (Wilcoxon p=0.022), ranging from no change (16/20 networks) to catastrophic collapse (0.989 to 0.620). VENs function as acquisition scaffolds whose developmental absence produces stochastic learning failure - a computational analogue of variable social skill acquisition in ASC - with falsifiable predictions for organoid and electrophysiology studies.

翻译：冯·埃科诺莫神经元（VENs）在行为变异型额颞叶痴呆（bvFTD）中选择性丧失，在自闭症谱系障碍（ASC）中数量减少，但其在社会学习中的计算作用仍不明确。我们训练了一个脉冲神经网络（VENCircuit），该网络将类似VEN的投射神经元（K=40，占总数的2%）嵌入到递归锥体电路中，基于50个匹配的随机初始条件，分别在有和无VEN的情况下进行训练。该网络在一个受控的二分类任务上训练；我们并不声称直接建模社会认知。VEN完整的网络在49/50（98%）的案例中收敛，而VEN缺失的网络为35/50（70%）（Fisher精确检验OR=21.0，95% CI 2.7–167，p=8.7e-5）。失败缺失网络表现为完全无学习能力，与速度驱动学习的解释不一致。消融实验表明，VEN移除在训练中期（第5–25个周期）最具破坏性，此时锥体电路中形成一种共适应依赖关系。我们推导出一个形式化解释，表明VEN提供了一条直接梯度通路，该通路不受影响递归电路的雅可比不稳定性影响。推理时VEN消融导致显著性能下降（Wilcoxon检验p=0.022），变化范围从无影响（16/20个网络）到灾难性崩溃（从0.989降至0.620）。VEN作为习得支架发挥作用，其发育缺失会产生随机性学习失败——这是自闭症谱系障碍中可变社会技能习得的计算类似物——并可为类器官和电生理学研究提供可证伪的预测。