Discovery Science of Human Brain Function Across the Lifespan

描述（由申请人提供）：面对在整个生命周期中绘制大脑功能和精神疾病起源的挑战，功能神经影像学社区正在遵循分子遗传学的先例，转向发现科学。1000个功能连接体项目（FCP）曾经是一个遥远的目标，但它证明了开展人类大脑功能发现科学的可行性。利用静息状态功能磁共振成像（R-fMRI）数据共享的便利性，FCP汇集了来自世界各地独立收集的1200多个个体的数据集。FCP数据集立即展示了大规模R-fMRI调查的力量，揭示了与性别和年龄相关的大脑内在功能结构的广泛差异，这些差异在典型样本量（例如n = 20-100）中不易检测到。FCP的努力代表了有效、开放的数据共享的开始，曾经努力获取20-30个数据集进行分析的研究人员突然获得了1200多个数据集的访问权限，用于方法创新和数据挖掘。在FCP初步成功的基础上，我们最近呼吁建立前瞻性数据共享，使用NKI-Rockland样本作为我们的原型，这是一个表型丰富的寿命样本。通过26种精神病学、行为和认知评估工具获得的300多个表型变量，NKI- Rockland样本证明了他们类型的数据收集模型非常适合于允许神经成像方法采用成功应用于分子遗传学的数据挖掘和发现方法。现在，神经成像学家可以识别大脑-行为之间的关系，并描绘出它们在整个生命周期中的动态轨迹。在确定了生成表型丰富数据集的可行性，并在未来的基础上与科学界公开分享这些数据集之后，本文提出的工作旨在生成一个更精心构建的寿命样本，规模更大，最大限度地代表社区，并使用适当的策略来描绘大脑内在功能结构指标的规范轨迹。具体来说，我们建议在四年的时间内招募1000名参与者（6-85岁），密集采样早期发育和晚期衰老阶段，其中年龄相关变化梯度最大，模型拟合技术最容易产生人为结果。招募和招生策略将被仔细控制，以最大限度地提高样本的社区代表性，并最大限度地减少机会主义招募中常见的偏见。所收集的数据集的70%将被随机选择用于发现，而剩下的30%将用于严格测试在发现阶段产生的假设。与为NKI-Rockland样本试点建立的模型一致，作为该提案一部分生成的数据将通过FCP和相关的国际神经成像数据共享倡议（INDI）每周前瞻性地共享。

DESCRIPTION (provided by applicant): Faced with the challenge of charting brain function and the origins of mental illness across the lifespan, the functional neuroimaging community is following the precedent set by molecular genetics in turning to discovery science. Once a distant goal, the 1000 Functional Connectomes Project (FCP) demonstrated the feasibility of conducting discovery science for human brain function. Capitalizing on the ease of data-sharing with resting state fMRI (R-fMRI), the FCP pooled datasets from over 1200 individuals independently collected at sites throughout the world. The FCP dataset immediately demonstrated the power of large-scale R-fMRI investigations, revealing widespread differences in the brain's intrinsic functional architecture related to sex and age that are not easily detected with typical sample sizes (e.g., n = 20-100). The FCP effort represented the inauguration of effective, open data-sharing, with researchers who once struggled to obtain 20-30 datasets for analyses suddenly granted access to over 1200 datasets for methods innovation and data mining. Building on the initial success of the FCP, we recently called for the establishment of prospective data-sharing, using the pilot NKI-Rockland Sample, a phenotypically rich, life-span sample, as our prototype. With more than 300 phenotypic variables obtained across 26 psychiatric, behavioral, and cognitive assessment tools, the NKI- Rockland Sample exemplifies they type of data collection model ideally suited to allow neuroimaging methods to employ the data mining and discovery approach applied successfully in molecular genetics. Neuroimagers can now identify brain-behavior relationships and delineate their dynamic trajectories across the lifespan. Having established the feasibility of generating phenotypically rich datasets and openly sharing them with the scientific community on a prospective basis, the proposed work aims to generate a more carefully constructed lifespan sample, larger in scale, maximally representative of the community and sampled using appropriate strategies for the delineation of normative trajectories for metrics of the brain's intrinsic functional architecture. Specifically, we propose to recruit 1000 participants (ages 6-85) over a four-year period, densely sampling early developmental and advanced aging periods, where age-related gradients of changes are maximal and model-fitting techniques are most prone to artifactual results. Recruitment and enrollment strategies will be carefully controlled to maximize the community representativeness of the sample and minimize biases commonly encountered with opportunistic recruiting. Seventy percent of the collected datasets will be randomly selected for discovery, while the remaining 30% will serve to rigorously test hypotheses generated during the discovery phase. Consistent with the model established for the pilot NKI-Rockland Sample, data generated as part of this proposal will be shared prospectively, on a weekly basis, via the FCP and the associated International Neuroimaging Data-sharing Initiative (INDI).