The original Human Connectome Project yielded a rich data set on structural and functional connectivity in a large sample of healthy young adults using improved methods of data acquisition, analysis, and sharing. More recent efforts are extending this approach to include infants, children, older adults, and brain disorders. This paper introduces and describes the Human Connectome Project in Aging (HCP-A), which is currently recruiting 1200 + healthy adults aged 36 to 100+, with a subset of 600 + participants returning for longitudinal assessment. Four acquisition sites using matched Siemens Prisma 3T MRI scanners with centralized quality control and data analysis are enrolling participants. Data are acquired across multimodal imaging and behavioral domains with a focus on factors known to be altered in advanced aging. MRI acquisitions include structural (whole brain and high resolution hippocampal) plus multiband resting state functional (rfMRI), task fMRI (tfMRI), diffusion MRI (dMRI), and arterial spin labeling (ASL). Behavioral characterization includes cognitive (such as processing speed and episodic memory), psychiatric, metabolic, and socioeconomic measures as well as assessment of systemic health (with a focus on menopause via hormonal assays). This dataset will provide a unique resource for examining how brain organization and connectivity changes across typical aging, and how these differences relate to key characteristics of aging including alterations in hormonal status and declining memory and general cognition. A primary goal of the HCP-A is to make these data freely available to the scientific community, supported by the Connectome Coordination Facility (CCF) platform for data quality assurance, preprocessing and basic analysis, and shared via the NIMH Data Archive (NDA). Here we provide the rationale for our study design and sufficient details of the resource for scientists to plan future analyses of these data. A companion paper describes the related Human Connectome Project in Development (HCP-D, Somerville et al., 2018), and the image acquisition protocol common to both studies (Harms et al., 2018).

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OBJECTIVE Brain tumors located close to the language cortex may distort functional MRI (fMRI)–based estimates of language dominance. The nature of this distortion, and whether this is an artifact of numerous confounders, remains unknown. The authors hypothesized tumor bias based on laterality estimates independent of confounders and that the effects are the greatest for tumors proximal to Broca's area. METHODS To answer this question, the authors reviewed more than 1113 patients who underwent preoperative fMRI to match samples on 11 known confounders (tumor location, size, type, and grade; seizure history; prior neurosurgery; aphasia presence and severity; and patient age, sex, and handedness). The samples included 30 patients with left hemisphere tumors (15 anterior and 15 posterior) and 30 with right hemisphere tumors (15 anterior and 15 posterior), thus totaling 60 patients (25 women; 18 left-handed and 4 ambidextrous; mean age 47 [SD 14.1] years). Importantly, the authors matched not only patients with left and right hemisphere tumors but also those with anterior and posterior tumors. Standard fMRI laterality indices (LIs) were calculated using whole-brain and region of interest (ROI) approaches (Broca's and Wernicke's areas). RESULTS Tumors close to Broca's area in the left hemisphere decreased LIs independently of known confounders. At the whole-brain level, this appeared to reflect a decrease in LI values in patients with left anterior tumors compared with patients with right anterior tumors. ROI analysis replicated these findings. Broca's area LIs were significantly lower (p = 0.02) in patients with left anterior tumors (mean LI 0.28) when compared with patients with right anterior tumors (mean LI 0.70). Changes in Wernicke's area–based LIs did not differ as a function of the tumor hemisphere. Therefore, in patients with left anterior tumors, it is essential to assess language laterality using left posterior ROIs. In all remaining tumor groups (left posterior tumors and right hemisphere tumors), language laterality derived from the anterior language ROI was the most robust measure of language dominance. CONCLUSIONS Patients with tumors close to Broca's area showed more bilateral fMRI language maps independent of known confounders. The authors caution against the assumption that this reduced language laterality suggests no or little risk to language function following tumor resection in the left inferior frontal gyrus. Their results address how to interpret fMRI data for neurosurgical purposes, along with theoretical questions of contralesional functional compensation and disinhibition.