Department of Neurology, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA.
Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
J Neurodev Disord. 2022 Mar 12;14(1):19. doi: 10.1186/s11689-022-09433-1.
A wide variety of model systems and experimental techniques can provide insight into the structure and function of the human brain in typical development and in neurodevelopmental disorders. Unfortunately, this work, whether based on manipulation of animal models or observational and correlational methods in humans, has a high attrition rate in translating scientific discovery into practicable treatments and therapies for neurodevelopmental disorders.With new computational and neuromodulatory approaches to interrogating brain networks, opportunities exist for "bedside-to bedside-translation" with a potentially shorter path to therapeutic options. Specifically, methods like lesion network mapping can identify brain networks involved in the generation of complex symptomatology, both from acute onset lesion-related symptoms and from focal developmental anomalies. Traditional neuroimaging can examine the generalizability of these findings to idiopathic populations, while non-invasive neuromodulation techniques such as transcranial magnetic stimulation provide the ability to do targeted activation or inhibition of these specific brain regions and networks. In parallel, real-time functional MRI neurofeedback also allow for endogenous neuromodulation of specific targets that may be out of reach for transcranial exogenous methods.Discovery of novel neuroanatomical circuits for transdiagnostic symptoms and neuroimaging-based endophenotypes may now be feasible for neurodevelopmental disorders using data from cohorts with focal brain anomalies. These novel circuits, after validation in large-scale highly characterized research cohorts and tested prospectively using noninvasive neuromodulation and neurofeedback techniques, may represent a new pathway for symptom-based targeted therapy.
多种模型系统和实验技术可以深入了解人类大脑在正常发育和神经发育障碍中的结构和功能。不幸的是，无论是基于动物模型的操作，还是人类的观察和相关性方法，这些工作将科学发现转化为神经发育障碍的可行治疗方法和疗法的淘汰率都很高。随着新的计算和神经调节方法来探究大脑网络，存在着将“床边到床边的转化”的机会，从而为治疗选择提供了一条潜在的更短的途径。具体来说，像病变网络映射这样的方法可以识别与生成复杂症状相关的大脑网络，这些症状既来自急性发作的病变相关症状，也来自局灶性发育异常。传统的神经影像学可以检验这些发现对特发性人群的普遍性，而无创性神经调节技术，如经颅磁刺激，可以提供对这些特定大脑区域和网络进行靶向激活或抑制的能力。与此同时，实时功能磁共振神经反馈也允许对特定目标进行内源性神经调节，而这些目标可能是经颅外源性方法无法达到的。使用具有局灶性脑异常的队列中的数据，现在可能可以为神经发育障碍发现用于跨诊断症状和神经影像学内表型的新型神经解剖回路。这些新型回路在大规模高度特征化的研究队列中得到验证，并使用无创神经调节和神经反馈技术进行前瞻性测试后，可能代表了一种基于症状的靶向治疗的新途径。
