Tight connection between neural cells and their micro-environment is crucial for processes such as neurite outgrowth and nerve regeneration. However, characterizing neuron adhesion remains challenging because of its rate-dependent nature as well as its coupling with the viscoelastic cellular response. In this study, by conducting successive forced peeling and relaxation tests on the same neurite, we managed to extract both adhesion and viscoelastic characteristics of neural cells simultaneously for the first time. Specifically, well-developed neurites were peeled away from the substrate by an atomic force microscopy (AFM) probe under different loading rates and then held at a fixed separation distance for relaxation. A computational model was also developed to explain the observed peeling-relaxation response, where the neurite was treated as a standard linear viscoelastic material while a viscous-regularized cohesive law was introduced to represent neuron–substrate adhesion. Our combined experimental and simulation results indicated that the adhesion energy is of the order of 0.04–0.1 $mJ∕m^2$, albeit being strongly rate-dependent, and relaxation takes place inside neurite with a characteristic time of $\sim$3 s. These findings could be critical for our physical understanding and modeling of different adhesion-mediated processes like neuron migration and synapse formation in the future.

神经细胞及其微环境之间的紧密连接对于神经突向外生长和神经再生等过程至关重要。然而，表征神经元粘附仍然具有挑战性，因为它的速率依赖性及其与粘弹性细胞反应的耦合。在这项研究中，通过对同一神经突进行连续的强制剥离和松弛测试，我们首次设法同时提取了神经细胞的粘附和粘弹性特征。具体而言，通过原子力显微镜（AFM）探针在不同的加载速率下将发达的神经突从基材上剥离下来，然后保持在固定的分离距离处进行松弛。还开发了一个计算模型来解释观察到的剥离松弛反应，其中神经突被视为标准的线性粘弹性材料，而引入了粘性规则的内聚法则来表示神经元与基底的粘附。我们的组合实验和模拟结果表明，粘附能为0.04–0.1$米Ĵ∕{米}^2$，尽管强烈依赖于速率，并且弛豫发生在神经突内部，其特征时间为 $〜$3秒 这些发现对于将来我们对不同粘附介导的过程（例如神经元迁移和突触形成）的物理理解和建模至关重要。