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

精神疾病，包括抑郁症和焦虑症，是慢性的，致残的和毁灭性的条件。然而，由于缺乏卫生服务和最先进的治疗方案，许多人没有得到他们从疾病中完全康复所需的护理。研究表明，多达三分之二的患者寻求标准的药物和/或心理干预情绪障碍将不会响应。非侵入性神经刺激方法，如经颅磁刺激（TMS），是治疗多次尝试标准干预失败的患者的新兴技术。然而，在治疗抑郁症和其他精神疾病的众多研究中出现了可变反应效应和受试者间变异性的问题，这阻碍了无创神经刺激在临床上的广泛应用。EPSCoR研究员RII Track-4：NSF奖学金将使来自俄克拉荷马州大学的PI与南卡罗来纳州医科大学的精神科医生和科学家合作，开发一种新型神经刺激技术，该技术与神经成像集成在闭环设计中。这项研究和相关的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结果。这种成功可以进一步推广到其他疾病的神经刺激治疗。无创神经刺激是一种新兴技术，在最近十年迅速蓬勃发展，用于治疗许多神经系统和神经精神疾病。然而，对标准方案的反应在个体之间差异很大。解决异质性反应的问题将是开发神经刺激作为治疗选择的全部潜力的重要一步。该项目的关键创新是利用大规模神经网络作为生物标志物，使用PI先前建立的算法，单独优化神经刺激的治疗结果。一个高密度，全头部蒙太奇的多模态脑电图（EEG）和功能性近红外光谱（fNIRS）将被用于该项目中记录在人类参与者。多模态成像数据的计算分析将主要集中在识别神经网络的功能连接作为响应神经刺激治疗的生物标志物。解决这些研究问题将是通过基于生物标志物的闭环方法优化个体治疗的下一代神经刺激方法的重要步骤。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估而被认为值得支持。

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.