The brain is an inherently dynamic system, and much work has focused on the ability to modify neural activity through both local perturbations and changes in the function of global network ensembles. Network controllability is a recent concept in network neuroscience that purports to predict the influence of individual cortical sites on global network states and state changes, thereby creating a unifying account of local influences on global brain dynamics. While this notion is accepted in engineering science, it is subject to ongoing debates in neuroscience as empirical evidence linking network controllability to brain activity and human behavior remains scarce. Here, we present an integrated set of multimodal brain–behavior relationships derived from fMRI, diffusion tensor imaging, and online repetitive transcranial magnetic stimulation (rTMS) applied during an individually calibrated working memory task performed by individuals of both sexes. The modes describing the structural network system dynamics showed direct relationships to brain activity associated with task difficulty, with difficult-to-reach modes contributing to functional brain states in the hard task condition. Modal controllability (a measure quantifying the contribution of difficult-to-reach modes) at the stimulated site predicted both fMRI activations associated with increasing task difficulty and rTMS benefits on task performance. Furthermore, fMRI explained 64% of the variance between modal controllability and the working memory benefit associated with 5 Hz online rTMS. These results therefore provide evidence toward the functional validity of network control theory, and outline a clear technique for integrating structural network topology and functional activity to predict the influence of stimulation on subsequent behavior.

SIGNIFICANCE STATEMENT The network controllability concept proposes that specific cortical nodes are able to steer the brain into certain physiological states. By applying external perturbation to these control nodes, it is theorized that brain stimulation is able to selectively target difficult-to-reach states, potentially aiding processing and improving performance on cognitive tasks. The current study used rTMS and fMRI during a working memory task to test this hypothesis. We demonstrate that network controllability correlates with fMRI modulation because of working memory load and with the behavioral improvements that result from a multivisit intervention using 5 Hz rTMS. This study demonstrates the validity of network controllability and offers a new targeting approach to improve efficacy.

大脑是一个固有的动态系统，许多工作都集中在通过局部扰动和全局网络集成功能变化来修改神经活动的能力上。网络可控性是网络神经科学中的最新概念，旨在预测单个皮质位点对全球网络状态和状态变化的影响，从而对全球脑动力学的局部影响进行统一描述。尽管这一概念已在工程科学中被接受，但由于将网络可控制性与大脑活动和人类行为联系起来的经验证据仍然很少，因此神经科学界对此争论不断。在这里，我们介绍了一组从功能磁共振成像，扩散张量成像，和在线重复经颅磁刺激（rTMS）在男女双方进行的单独校准的工作记忆任务中应用。描述结构网络系统动力学的模式显示出与任务任务相关的大脑活动的直接关系，在难以完成任务的情况下，难以到达的模式有助于大脑的功能状态。刺激部位的模态可控性（一种量化难以到达的模式的量度）可预测与任务难度增加相关的功能磁共振成像激活以及rTMS对任务执行的益处。此外，fMRI解释了模态可控性与5 Hz在线rTMS相关的工作记忆效益之间的差异的64％。

意义声明网络可控性概念提出，特定的皮质节点能够将大脑引导到某些生理状态。通过对这些控制节点施加外部干扰，可以得出理论上的看法，即大脑刺激能够选择性地针对难以到达的状态，从而有可能帮助进行处理并改善认知任务的表现。当前的研究在工作记忆任务中使用了rTMS和fMRI来检验这一假设。我们证明网络可控性与fMRI调制有关，这是因为工作内存负荷以及使用5 Hz rTMS进行多次干预所导致的行为改善。这项研究证明了网络可控性的有效性，并提供了一种新的靶向方法来提高疗效。