Impact Of Hematocrit On Measurements Of The Intrinsic Brain

Blood oxygenation level dependent (BOLD)–based functional MRI is a widely utilized neuroimaging technique for mapping brain function. Hematocrit (HCT), a global hematologic marker of the amount of hemoglobin in blood, is known to impact task-evoked BOLD activation. Yet, its impact on resting-state fMRI (R-fMRI) measures has not been characterized. We address this gap by testing for associations between HCT level and inter-individual variation in commonly employed R-fMRI indices of intrinsic brain function from 45 healthy adults. Given known sex differences in HCT, we also examined potential sex differences. Variation in baseline HCT among individuals were associated with regional differences in four of the six intrinsic brain indices examined. Portions of the default (anterior cingulate cortex/medial prefrontal cortex: ACC/MPFC), dorsal attention (intraparietal sulcus), and salience network (insular and opercular cortex) showed relationships with HCT for two measures. The relationships within MPFC, as well as visual and cerebellar networks, were modulated by sex. These results suggest that inter-individual variations in HCT can serve as a source of variations in R-fMRI derivatives at a regional level. Future work is needed to delineate whether this association is attributable to neural or non-neuronal source of variations and whether these effects are related to acute or chronic differences in HCT level

Addressing Head Motion Dependencies for Small-World Topologies in Functional Connectomics

Graph theoretical explorations of functional interactions within the human connectome, are rapidly advancing our understanding of brain architecture. In particular, global and regional topological parameters are increasingly being employed to quantify and characterize inter-individual differences in human brain function. Head motion remains a significant concern in the accurate determination of resting-state fMRI based assessments of the connectome, including those based on graph theoretical analysis (e.g., motion can increase local efficiency, while decreasing global efficiency and small-worldness). This study provides a comprehensive examination of motion correction strategies on the relationship between motion and commonly used topological parameters. At the individual-level, we evaluated different models of head motion regression and scrubbing, as well as the potential benefits of using partial correlation (estimated via graphical lasso) instead of full correlation. At the group-level, we investigated the utility of regression of motion and mean intrinsic functional connectivity before topological parameters calculation and/or after. Consistent with prior findings, none of the explicit motion-correction approaches at individual-level were able to remove motion relationships for topological parameters. Global signal regression (GSR) emerged as an effective means of mitigating relationships between motion and topological parameters; though at the risk of altering the connectivity structure and topological hub distributions when higher densities graphs are employed (e.g., > 6%). Group-level analysis correction for motion was once again found to be a crucial step. Finally, similar to recent work, we found a constellation of findings suggestive of the possibility that some of the motion-relationships detected may reflect neural or trait signatures of motion, rather than simply motion-induced artifact

Stereoscopic Three-Dimensional Visualization Applied to Multimodal Brain Images: Clinical Applications and a Functional Connectivity Atlas.

Effective visualization is central to the exploration and comprehension of brain imaging data. While MRI data are acquired in three-dimensional space, the methods for visualizing such data have rarely taken advantage of three-dimensional stereoscopic technologies. We present here results of stereoscopic visualization of clinical data, as well as an atlas of whole-brain functional connectivity. In comparison with traditional 3D rendering techniques, we demonstrate the utility of stereoscopic visualizations to provide an intuitive description of the exact location and the relative sizes of various brain landmarks, structures and lesions. In the case of resting state fMRI, stereoscopic 3D visualization facilitated comprehension of the anatomical position of complex large-scale functional connectivity patterns. Overall, stereoscopic visualization improves the intuitive visual comprehension of image contents, and brings increased dimensionality to visualization of traditional MRI data, as well as patterns of functional connectivity

The NKI-Rockland Sample: A Model for Accelerating the Pace of Discovery Science in Psychiatry

The National Institute of Mental Health strategic plan for advancing psychiatric neuroscience calls for an acceleration of discovery and the delineation of developmental trajectories for risk and resilience across the lifespan. To attain these objectives, sufficiently powered datasets with broad and deep phenotypic characterization, state-of-the-art neuroimaging, and genetic samples must be generated and made openly available to the scientific community. The enhanced Nathan Kline Institute Rockland Sample (NKI-RS) is a response to this need. NKI-RS is an ongoing, institutionally-centered endeavor aimed at creating a large-scale (N>1000), deeply phenotyped, community-ascertained, lifespan sample (ages 6-85 years old) with advanced neuroimaging and genetics. These data will be publically shared, openly and prospectively (i.e., on a weekly basis). Herein, we describe the conceptual basis of the NKI-RS, including study design, sampling considerations, and steps to synchronize phenotypic and neuroimaging assessment. Additionally, we describe our process for sharing the data with the scientific community while protecting participant confidentiality, maintaining an adequate database, and certifying data integrity. The pilot phase of the NKI-RS, including challenges in recruiting, characterizing, imaging, and sharing data, is discussed while also explaining how this experience informed the final design of the enhanced NKI-RS. It is our hope that familiarity with the conceptual underpinnings of the enhanced NKI-RS will facilitate harmonization with future data collection efforts aimed at advancing psychiatric neuroscience and nosology