Neural Network Connectivity of Financial Capacity in Mild Cognitive Impairment

项目摘要/摘要 候选人的长期职业目标是成为一名独立调查员，其研究重点是 认知障碍伴功能性残疾患者的脑网络。具体来说，候选人是 重点了解与轻度患者财务能力(FC)丧失相关的神经网络连接性 认知障碍(MCI)。大脑网络的功能和结构连接性与 然而，对MCI的基础功能障碍(MCI-FCB)和复杂功能障碍(MCI-FCC)的认识还不是很清楚。因此， 以病人为本的研究生涯发展奖(K23) 候选人、背景、兴趣和公认的认知神经科学和 神经成像以了解MCI-FCB和MCI-FCC与正常对照组(NC)的脑连接。在……里面 根据应聘者的职业目标，职业发展计划将重点放在：1) 神经生物学决策；2)先进的神经成像方法；3)高级神经成像技能 分析和生物统计；4)行政职能和财务能力的评估和解释；5) 负责任的研究行为。拟议的研究计划将集中在关联扩散张量上。 成像(DTI)和静息状态fMRI(rS-fMRI)测量大规模神经认知网络到认知 和功能性措施。这项研究的具体目的是：1)考察一体化的变化 执行控制网络内相对于其他大脑的结构和功能连通性测量 网络因组而异；以及2)调查特定域和任务之间的关联 金融能力工具，以应对大规模网络连接的变化。这些目标和总体 方法将应用于三个参与者组：1)30名年龄和教育程度匹配的NC；2)30名MCI-FCC；3)30名 MCI-FCB。需要检验的具体假设是：1)MCI-FCC组将表现出功能下降 执行网络的连通性和下半部内特定区域的白质完整性降低 额叶回、前脑岛、前额叶皮质背侧和腹外侧区；2)角回，如 默认模式网络中的关键节点的结构和功能连接性将显著降低 在MCI-FCB与MCI-FCC的比较中；3)在基本算术和货币技能和账单任务上的表现 付款将与两种默认模式的相对结构和功能连接性呈正相关 网络和显著网络；4)财务能力的复杂任务，包括财务概念知识 投资决策将与前额叶皮质内连接的丧失密切相关 执行控制网络的区域。在K奖结束时，候选人将组装一个 在拟议研究中获得的具有良好特征的队列和见解可能会导致制定更有效的 认知疗法、评估工具和辅助技术。

PROJECT SUMMARY/ABSTRACT The candidate’s long-term career goal is to become an independent investigator whose research focuses on brain networks in patients with cognitive impairment with functional disability. Specifically, the candidate is focused on understanding neural network connectivity associated with the loss of financial capacity (FC) in mild cognitive impairment (MCI). The functional and structural connectivity of brain networks associated with impairment in basic (MCI-FCb) and complex (MCI-FCc) FC in MCI, however, are not well understood. Thus, the proposed application for the Mentored Patient-Oriented Research Career Development Award (K23) integrates the candidates, background, interests, and established technical skills in cognitive neuroscience and neuroimaging to understand brain connectivity in MCI-FCb and MCI-FCc compared to normal controls (NC). In accordance with the candidate’s career goals, the career development plan will focus on training in: 1) neurobiology decision-making; 2) advanced neuroimaging methods; 3) high-level skills for neuroimaging analysis and biostatistics; 4) the assessment and interpretation of executive function, and financial capacity; 5) the responsible conduct of research. The proposed research plan will focus on correlating diffusion tensor imaging (DTI) and resting state fMRI (rs-fMRI) measurements large-scale neurocognitive networks to cognitive and functional measures. The specific aims of the research are: 1) To examine how changes in integrated structural and functional connectivity measurements within the executive control network relative to other brain networks will differ between groups; and 2) To investigate associations between specific domains and tasks on the Financial Capacity Instrument to changes to large-scale network connectivity. These aims and general methods will be applied to three participant groups: 1) 30 age- and education-matched NC; 2) 30 MCI-FCc; 3) 30 MCI-FCb. The specific hypotheses to be tested are that: 1) The MCI-FCc group will exhibit decreased functional connectivity in the executive network and decreased white matter integrity in specific tracts within the inferior frontal gyrus, anterior insula, and dorsal and ventrolateral prefrontal cortical regions; 2) The angular gyrus, as a key node in the default mode network, will exhibit significantly decreased structural and functional connectivity in MCI-FCb compared to MCI-FCc; 3) Performance on tasks of basic arithmetic and monetary skills and bill payment will positively correlate with relative structural and functional connectivity of both the default mode network and salience network; 4) Complex tasks of financial capacity including financial conceptual knowledge and investment decision making will be strongly associated with loss of connectivity within prefrontal cortical regions of the executive control network. At the conclusion of the K award, the candidate will have assembled a well-characterized cohort of and insights obtained in the proposed study may lead to developing more effective cognitive therapies, instruments for assessments, and assistive technologies.