We exploit flow propagation on the directed neuronal network of the nematode
Caenorhabditis elegans to reveal dynamically relevant features of its
connectome. We find flow-based groupings of neurons at different levels of
granularity, which we relate to functional and anatomical constituents of its
nervous system. A systematic in silico evaluation of the full set of single and
double neuron ablations is used to identify deletions that induce the most
severe disruptions of the multi-resolution flow structure. Such ablations are
linked to functionally relevant neurons, and suggest potential candidates for
further in vivo investigation. In addition, we use the directional patterns of
incoming and outgoing network flows at all scales to identify flow profiles for
the neurons in the connectome, without pre-imposing a priori categories. The
four flow roles identified are linked to signal propagation motivated by
biological input-response scenarios.

本文探讨了费城线虫的神经元有向网络的流传播，从而揭示了其连接组的动态相关特征。作者发现在不同的粒度级别上有基于流的神经元分组，并将其与其神经系统的功能和解剖组织相关联，并确定那些最严重破坏多重分辨率流结构的单个和双个神经元切除。此外，还使用所有尺度上的传入和传出网络流的定向模式，以识别连接组中神经元的流特征。所识别的四种流角色与应答于生物输入的传播信号相关。