The behavioral and neural effects of the endogenous release of acetylcholine following stimulation of the nucleus basalis (NB) of Meynert have been recently examined in two male monkeys (Qi et al., 2021). Counterintuitively, NB stimulation enhanced behavioral performance while broadening neural tuning in the prefrontal cortex (PFC). The mechanism by which a weaker mnemonic neural code could lead to better performance remains unclear. Here, we show that increased neural excitability in a simple continuous bump attractor model can induce broader neural tuning and decrease bump diffusion, provided neural rates are saturated. Increased memory precision in the model overrides memory accuracy, improving overall task performance. Moreover, we show that bump attractor dynamics can account for the nonuniform impact of neuromodulation on distractibility, depending on distractor distance from the target. Finally, we delve into the conditions under which bump attractor tuning and diffusion balance in biologically plausible heterogeneous network models. In these discrete bump attractor networks, we show that reducing spatial correlations or enhancing excitatory transmission can improve memory precision. Altogether, we provide a mechanistic understanding of how cholinergic neuromodulation controls spatial working memory through perturbed attractor dynamics in the PFC.

最近在两只雄性猴子中研究了刺激 Meynert 基底核 (NB) 后内源性释放乙酰胆碱的行为和神经效应 (Qi et al., 2021)。与直觉相反，NB 刺激增强了行为表现，同时扩大了前额皮质 (PFC) 的神经调节范围。较弱的助记神经代码可以带来更好的性能的机制仍不清楚。在这里，我们表明，只要神经速率饱和，简单的连续凹凸吸引子模型中增加的神经兴奋性可以引起更广泛的神经调节并减少凹凸扩散。模型中内存精度的提高超越了内存准确性，从而提高了整体任务性能。此外，我们表明，碰撞吸引子动力学可以解释神经调节对分散注意力的不均匀影响，具体取决于分散物与目标的距离。最后，我们深入研究了在生物学上合理的异构网络模型中凹凸吸引子调整和扩散平衡的条件。在这些离散的凹凸吸引子网络中，我们表明减少空间相关性或增强兴奋性传输可以提高记忆精度。总而言之，我们对胆碱能神经调节如何通过 PFC 中吸引子动力学的扰动来控制空间工作记忆提供了机械理解。