RII Track-4:NSF:Multimodal imaging of large-scale neural networks for optimized neurostimulation

精神疾病，包括抑郁和焦虑，是一种慢性、致残性和破坏性的疾病。然而，由于卫生服务短缺和缺乏最先进的治疗选择，许多人没有得到他们完全从疾病中恢复所需的护理。研究证明，寻求对情绪障碍进行标准药物和/或心理干预的患者中，多达三分之二的人不会有反应。非侵入性神经刺激方法，如经颅磁刺激(TMS)，是治疗多次标准干预失败的患者的新兴技术。然而，在大量治疗抑郁症和其他精神疾病的研究中，出现了反应效应可变和受试者间差异的问题，这阻碍了非侵入性神经刺激在临床上的广泛应用。这项EPSCoR研究人员RII Track-4：NSF奖学金将使俄克拉荷马大学的PI与南卡罗来纳医科大学的精神病学家和科学家合作开发一种新的神经刺激技术，该技术在闭环设计中与神经成像相结合。这项研究和相关的合作伙伴关系将为开发个性化治疗铺平道路，大大改善精神疾病患者的治疗结果。这一成功可以进一步推广到其他疾病的神经刺激治疗。非侵入性神经刺激是近十年来迅速发展起来的一项新兴技术，用于治疗许多神经和神经精神疾病。然而，对标准方案的反应在不同的人之间差别很大。解决不同反应的问题将是向前迈出的重要一步，以充分发挥神经刺激作为治疗选择的潜力。该项目的关键创新是利用大规模神经网络作为生物标记物，使用PI先前建立的算法，单独优化神经刺激的治疗结果。该项目将使用高密度、全头蒙太奇的多模式脑电(EEG)和功能近红外光谱(FNIRS)在人类参与者中进行记录。多模式成像数据的计算分析将主要集中于确定神经网络的功能连通性作为神经刺激治疗反应的生物标记物。解决这些研究问题将是迈向下一代神经刺激方法的重要一步，通过基于生物标记物的闭环方法来优化个人治疗。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Mental illnesses, including depression and anxiety, are chronic, disabling, and devastating conditions. However, many people are not receiving the care they need to fully recover from their illnesses because of a shortage of health services and a lack of state-of-the-art treatment options. Studies have documented that up to two-thirds of patients who seek standard pharmacological and/or psychological interventions to emotional disorders will not respond. Noninvasive neurostimulation methods, such as transcranial magnetic stimulation (TMS), are emerging techniques to treat patients who have failed multiple attempts of standard interventions. However, issues of variable response effects and inter-subject variability have arisen in numerous investigations of treating depression and other mental illnesses, which have prevented the broad application of noninvasive neurostimulation for clinical use. This EPSCoR Research Fellows RII Track-4:NSF fellowship will enable the PI from the University of Oklahoma, to partner with psychiatrists and scientists at the Medical University of South Carolina to develop a novel neurostimulation technology that is integrated with neuroimaging in a closed-loop design. This research and the associated partnerships will pave the way for developing individualized treatment with much improved outcomes in people with mental illness. This success can be further generalized to the neurostimulation treatment of other disorders.Noninvasive neurostimulation is an emerging technology that is rapidly booming in the recent decade for treating many neurological and neuropsychiatric disorders. However, the responses to a standard protocol varied greatly among individuals. Addressing the issue of heterogeneous responses will be an important step forward to exploit the full potential of neurostimulation as the treatment option. The key innovation of the project is to leverage the large-scale neural networks as biomarkers, using the algorithms previously established by the PI, to individually optimize the therapeutic outcomes of neurostimulations. A high-density, whole-head montage of multimodal electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) will be used in the project for recording in the human participants. The computational analysis of the multimodal imaging data will primarily focus on identifying the functional connectivity of neural networks as biomarkers in response to neurostimulation treatment. Addressing these research questions will be important steps towards the next-generation neurostimulation methods via a biomarker-based, closed-loop approach to optimize individual treatment.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.