Synchronized low-frequency BOLD fluctuations are observed in dissociable large-scale, distributed networks with functional specialization. Two such networks, referred to as the task-positive network (TPN) and the task-negative network (TNN) because they tend to be active or inactive during cognitively demanding tasks, show reproducible anticorrelation of resting BOLD fluctuations after removal of the global brain signal. Because global signal regression mandates that anticorrelated regions to a given seed region must exist, it is unclear whether such anticorrelations are an artifact of global regression or an intrinsic property of neural activity. In this study, we demonstrate from simulated data that spurious anticorrelations are introduced during global regression for any two networks as a linear function of their size. Using actual resting state data, we also show that both the TPN and TNN become anticorrelated with the orbits when soft tissues are included in the global regression algorithm. Finally, we propose a technique using phase-shifted soft tissue regression (PSTCor) that allows improved correction of global physiological artifacts without global regression that shows improved anatomic specificity to global regression but does not show significant network anticorrelations. These results imply that observed anticorrelations between TNN and TPN may be largely or entirely artifactual in the resting state. These results also imply that differences in network anticorrelations attributed to pathophysiological or behavioral states may be due to differences in network size or recruitment rather than actual anticorrelations.

Background and Purpose Measurements of resting state functional connectivity have increasingly been used for characterization of neuropathological and neurodevelopmental populations. We collected data to characterize how much imaging time is necessary to obtain reproducible quantitative functional connectivity measurements needed for a reliable single-subject diagnostic test. Materials and Methods We obtained 100 five-minute BOLD scans on a single subject, divided into 10 sessions of 10 scans each, with the subject at rest or while watching video clips of cartoons. These data were compared to resting state BOLD scans from 36 normal control subjects by evaluating correlation between each pair of 64 small spherical ROI's obtained from a published functional parcellation of the brain. Results Single-subject and group data converged to reliable estimates of individual and population connectivity values proportional to 1/sqrt(n). Dramatic improvements in reliability were seen using up to 25 minutes of imaging time, with smaller improvements for additional time. Functional connectivity “fingerprints” for the individual studied and the population began diverging at about 15 minutes imaging time with increasing reliability even at 4 hours of imaging time. A classifier discriminating scans during which our subject was resting or watching cartoons was 95% accurate at 10 minutes and 100% accurate at 15 minutes imaging time. An individual subject and control population converged to reliable, different functional connectivity profiles that were task-modulated and could be discriminated with sufficient imaging time. Conclusion We suggest that quantitative single-subject diagnostic testing or classification use at least 25 minutes of BOLD imaging time if feasible.

No abstract

Introduction There are limited data regarding the impact of marijuana (MJ) on cortical development during adolescence. Adolescence is a period of substantial brain maturation and cortical thickness abnormalities may be indicative of disruptions of normal cortical development. This investigation applied cortical-surface based techniques to compare cortical thickness measures in MJ using adolescents compared to non-using controls. Methods Eighteen adolescents with heavy MJ use and 18 non-using controls similar in age received MRI scans using a 3T Siemens scanner. Cortical reconstruction and volumetric segmentation was performed with FreeSurfer. Group differences in cortical thickness were assessed using statistical difference maps covarying for age and gender. Results Compared to non-users, MJ users had decreased cortical thickness in right caudal middle frontal, bilateral insula and bilateral superior frontal corticies. Marijuana users had increased cortical thickness in the bilateral lingual, right superior temporal, right inferior parietal and left paracentral regions. In the MJ users, negative correlations were found between frontal and lingual regions for urinary cannabinoid levels and between age of onset of use and the right superior frontal gyrus. Conclusion This is one of the first studies to evaluate cortical thickness in a group of adolescents with heavy MJ use compared to non-users. Our findings are consistent with prior studies that documented abnormalities in prefrontal and insular regions. Our results suggest that age of regular use may be associated with altered prefrontal cortical gray matter development in adolescents. Furthermore, reduced insular cortical thickness may be a biological marker for increased risk of substance dependence.