Evaluation of denoising strategies to address motion-correlated artifacts in resting-state functional magnetic resonance imaging data from the human connectome roject

Like all resting-state functional connectivity data, the data from the Human Connectome Project (HCP) are adversely affected by structured noise artifacts arising from head motion and physiological processes. Functional connectivity estimates (Pearson's correlation coefficients) were inflated for high-motion time points and for high-motion participants. This inflation occurred across the brain, suggesting the presence of globally distributed artifacts. The degree of inflation was further increased for connections between nearby regions compared with distant regions, suggesting the presence of distance-dependent spatially specific artifacts. We evaluated several denoising methods: censoring high-motion time points, motion regression, the FMRIB independent component analysis-based X-noiseifier (FIX), and mean grayordinate time series regression (MGTR; as a proxy for global signal regression). The results suggest that FIX denoising reduced both types of artifacts, but left substantial global artifacts behind. MGTR significantly reduced global artifacts, but left substantial spatially specific artifacts behind. Censoring high-motion time points resulted in a small reduction of distance-dependent and global artifacts, eliminating neither type. All denoising strategies left differences between high- and low-motion participants, but only MGTR substantially reduced those differences. Ultimately, functional connectivity estimates from HCP data showed spatially specific and globally distributed artifacts, and the most effective approach to address both types of motion-correlated artifacts was a combination of FIX and MGTR

Close encounters: Analyzing how social similarity and propinquity contribute to strong network connections.

Models of network formation emphasize the importance of social similarity and propinquity in producing strong interpersonal connections. The positive effect each factor can have on tie strength has been documented across a number of studies, and yet we know surprisingly very little about how the two factors combine to produce strong ties. Being in close proximity could either amplify or dampen the positive effect that social similarity can have on tie strength. Data on tie strength among teachers working in five public schools were analyzed to shed light on this theoretical question. The empirical results indicate that teachers who were similar in age were more likely to be connected by a strong tie, especially teachers for whom age similarity was more likely to be salient. Moreover, teachers who took breaks at the same time or who had classrooms on the same floor communicated more frequently and felt more emotionally attached. Among the public school teachers, propinquity amplified the positive effect that age similarity had on tie strength. The strongest network connections occurred among age-similar teachers who had classrooms on the same floor. The empirical results illustrate the value of considering how social similarity and propinquity contribute to strong ties independently and when combined with each other

Long-term neural and physiological phenotyping of a single human

Psychiatric disorders are characterized by major fluctuations in psychological function over the course of weeks and months, but the dynamic characteristics of brain function over this timescale in healthy individuals are unknown. Here, as a proof of concept to address this question, we present the MyConnectome project. An intensive phenome-wide assessment of a single human was performed over a period of 18 months, including functional and structural brain connectivity using magnetic resonance imaging, psychological function and physical health, gene expression and metabolomics. A reproducible analysis workflow is provided, along with open access to the data and an online browser for results. We demonstrate dynamic changes in brain connectivity over the timescales of days to months, and relations between brain connectivity, gene expression and metabolites. This resource can serve as a testbed to study the joint dynamics of human brain and metabolic function over time, an approach that is critical for the development of precision medicine strategies for brain disorders

Predicting sexual problems in women: The relevance of sexual excitation and sexual inhibition

This is the post-print version of the article. The official published version can be obtained from the link below.Data from a non-clinical sample of 540 heterosexual women were used to examine the relationships between scores on the Sexual Excitation/Sexual Inhibition Inventory for Women (SESII-W) and ratings of current sexual problems, lifetime arousal difficulty, lifetime orgasm difficulty, and lifetime problems with low sexual interest. Multiple regression analyses also included several demographic/background variables as predictors: age, full-time employment, completed college, children in household, married, health ratings, importance of sex, and whether the woman was in a sexual relationship. The strongest statistical predictors of both current and lifetime sexual problems were the SESII-W inhibition factors Arousal Contingency and Concerns about Sexual Function. Demographic factors did not feature largely in any of the models predicting sexual problems even when statistically significant relationships were found. If future research supports the predictive utility of the SESII-W in identifying women who are more likely to experience sexual difficulties, these scales may be used as prognostic factors in treatment studies.This study was funded, in part, by a grant from the Lilly Centre for Women's Health