The principle of constraint-induced therapy is widely practiced in rehabilitation. In hemiplegic cerebral palsy (CP) with impaired contralateral corticospinal projection due to unilateral injury, function improves after imposing a temporary constraint on limbs from the less affected hemisphere. This type of partially-reversible impairment in motor control by early brain injury bears a resemblance to the experience-dependent plastic acquisition and modification of neuronal response selectivity in the visual cortex. Previously, such mechanism was modeled within the framework of BCM (Bienenstock-Cooper-Munro) theory, a rate-based synaptic modification theory. Here, we demonstrate a minimally complex yet sufficient neural network model which provides a fundamental explanation for inter-hemispheric competition using a simplified spike-based model of information transmission and plasticity. We emulate the restoration of function in hemiplegic CP by simulating the competition between cells of the ipsilateral and contralateral corticospinal tracts. We use a high-speed hardware neural simulation to provide realistic numbers of spikes and realistic magnitudes of synaptic modification. We demonstrate that the phenomenon of constraint-induced partial reversal of hemiplegia can be modeled by simplified neural descending tracts with 2 layers of spiking neurons and synapses with spike-timing-dependent plasticity (STDP). We further demonstrate that persistent hemiplegia following unilateral cortical inactivation or deprivation is predicted by the STDP-based model but is inconsistent with BCM model. Although our model is a highly simplified and limited representation of the corticospinal system, it offers an explanation of how constraint as an intervention can help the system to escape from a suboptimal solution. This is a display of an emergent phenomenon from the synaptic competition.

约束诱导疗法的原则在康复中得到广泛应用。在由于单侧损伤导致对侧皮质脊髓投射受损的偏瘫性脑瘫 (CP) 中，在对受影响较小半球的肢体施加临时约束后，功能得到改善。这种由早期脑损伤引起的运动控制的部分可逆性损伤与视觉皮层中神经元反应选择性的依赖于经验的塑性获取和修饰相似。以前，这种机制是在 BCM (Bienenstock-Cooper-Munro) 理论框架内建模的，这是一种基于速率的突触修饰理论。这里，我们展示了一个最小复杂但足够的神经网络模型，该模型使用简化的基于尖峰的信息传输和可塑性模型为半球间竞争提供了基本解释。我们通过模拟同侧和对侧皮质脊髓束细胞之间的竞争来模拟偏瘫 CP 的功能恢复。我们使用高速硬件神经模拟来提供真实的尖峰数量和真实的突触修改幅度。我们证明了约束引起的偏瘫部分逆转现象可以通过具有 2 层尖峰神经元和具有尖峰时间依赖性可塑性 (STDP) 的突触的简化神经下行束来建模。我们进一步证明基于 STDP 的模型可以预测单侧皮质失活或剥夺后的持续性偏瘫，但与 BCM 模型不一致。尽管我们的模型是对皮质脊髓系统的高度简化和有限的表示，但它提供了对作为干预的约束如何帮助系统摆脱次优解决方案的解释。这是突触竞争中出现的一种新兴现象的展示。