Exciting networks: multi-modal mapping and modulating network breakdown in early Alzheimers disease

细胞、动物和人类的神经成像研究表明，阿尔茨海默病(AD)与内侧颞区和顶区之间的神经网络中断有关，这是观察到的认知问题的基础。这种分解与病理的空间分布密切相关。到目前为止，很少有研究研究改变这些网络中的神经元兴奋性是否会对AD患者的认知功能产生积极影响，也没有研究通过应用经颅直流电刺激(TDC)来改变AD患者多模式网络完整性的可能性。因此，我们将在AD早期实施tDCs干预，这被认为是非侵入性地改变神经元兴奋性。本申请中提出的研究的主要目的是通过多模式成像研究老年受试者和患有轻度认知障碍(MCI)和AD早期的患者1)疾病相关神经网络结构和功能的变化，2)tDCs的认知和生理效应，3)tDCs对结构和功能连通性的影响。随着财富的增加，寿命的延长，以及老年带来痴呆症的风险，阿尔茨海默病预计会急剧增加。到目前为止，AD既不能被成功地预防，也不能被成功地治疗。这给卫生保健带来了一个世界性的问题，迫切需要开发新的治疗方法。拟议的研究旨在通过加深我们对与AD相关的神经网络病理学及其调节的理解来促进这一问题的解决。

Cellular, animal and human neuroimaging studies indicate that Alzheimer’s disease (AD) is associated with a disruption of neural networks between the medial temporal and parietal regions, underlying the cognitive problems observed. This breakdown is closely associated with the spatial distribution of pathology. To date, few studies have examined whether changing neuronal excitability in these networks could have a positive effect on cognitive functioning in AD, and no study has yet investigated the potential of altering multi-modal network integrity in AD patients by applying transcranial direct current stimulation (tDCS). Therefore, we will implement a tDCS intervention in early AD, which is believed to alter neuronal excitability non-invasively. The main aims of the studies proposed in this application are to investigate in elderly subjects and patients suffering from mild cognitive impairment (MCI) and early AD 1) the disease associated changes in neural network structure and function 2) the cognitive and physiological effects of tdcs and 3) the effects of tdcs on structural and functional connectivity via multimodal imaging. As prosperity increases, longevity increases, and old age carries the risk of dementia, AD is expected to increase dramatically. To date, AD can neither be successfully prevented nor treated. This poses a world-wide problem to health care, making the need to develop novel treatments urgent. The proposed studies aim at contributing to this issue by furthering our understanding of neural network pathology associated with AD and the modulation thereof.