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.
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.
Anticipating future outcomes is central to decision making and a failure to consider long-term consequences may lead to impulsive choices. Adolescence is a vulnerable period during which underdeveloped prefrontal cortical systems may contribute to poor judgment, impulsive choices, and substance abuse. Conversely, substance abuse during this period may alter neural systems involved in decision making and lead to greater impulsivity. Although a broad neural network which supports decision making undergoes extensive change during adolescent development, one region that may be critical is the medial prefrontal cortex. Altered functional integrity of this region may be specifically related to reward perception, substance abuse, and dependence. In the present investigation, we acquired structural magnetic resonance images (MRI), using a 3T Siemens Trio scanner, from 18 cannabis abusing adolescents (CA; 2 female and 16 male subjects; mean age, 17.7 years; range 16–19 years), and 18 healthy controls (HC; 6 female and 12 male subjects; mean age, 17.2 years; range 16–19 years). In order to measure medial orbital prefrontal cortex (moPFC) morphology related to substance abuse and impulsivity, semi-automated cortical reconstruction and volumetric segmentation of MRIs was performed with FreeSurfer. Impulsivity was evaluated with the Barratt Impulsiveness Scale (BIS). Our results indicate that cannabis abusing adolescents have decreased right moPFC volume compared to controls, p = 0.01, d = 0.92, CI0.95 = 0.21, 1.59. Cannabis abusing adolescents also show decreased future orientation, as indexed by the BIS non-planning subscale, when compared to controls, p = 0.01, d = 0.89, CI0.95 = 0.23, 1.55. Moreover, total moPFC volume was positively correlated with age of first use r (18) = 0.49, p < 0.03, suggesting that alterations in this region may be related to initiation of cannabis use or that early initiation may lead to reduced moPFC volume.
Functional imaging studies have shown reduced activity within the default mode network during attention-demanding tasks. The network circuitry underlying this suppression remains unclear. Proposed hypotheses include an attentional “switch” in the right anterior insula and reciprocal inhibition between the default mode and attention control networks. We analyzed resting state BOLD data from 1278 subjects from 26 sites and constructed whole brain maps of functional connectivity between 7266 ROIs covering the gray matter at approximately 5 mm resolution. ROIs belonging to the default mode network and attention control network were identified based on correlation to six published seed locations. Spatial heterogeneity of correlation between the default mode and attention control networks was observed, with smoothly varying gradients in every hub of both networks that ranged smoothly from weakly but significantly anticorrelated to positively correlated. Such gradients were reproduced in 3 separate groups of subjects. Anticorrelated subregions were identified in major hubs of both networks. Between-network connectivity gradients strengthen with age during late adolescence and early adulthood, with associated sharpening of the boundaries of the default mode network, integration of the insula and cingulate with frontoparietal attentional regions, and decreasing correlation between the default mode and attention control networks with age.
There were no limbic volumetric differences between BPD and SZ. However, there were diagnosis-by-sex interactions in the amygdala and hippocampus, structures that are rich in sex hormone receptors. In addition, smaller thalamus was associated with SZ while larger right NA volumes were most related to BPD. This study underscores the importance of assessing diagnostic effects and sex effects on the brain in future studies and provides evidence that boys and girls with SZ and BPD may have differential patterns of neuropathology associated with disease expression.
The intraparietal sulcus (IPS) region is uniquely situated at the intersection of visual, somatosensory, and auditory association cortices, ideally located for processing of multisensory attention. We examined the internal architecture of the IPS region and its connectivity to other regions in the dorsal attention and cinguloinsular networks using maximal connectivity clustering. We show with resting state fMRI data from 58 healthy adolescent and young adult volunteers that points of maximal connectivity between the IPS and other regions in the dorsal attention and cinguloinsular networks are topographically organized, with at least seven maps of the IPS region in each hemisphere. Distinct clusters of the IPS exhibited differential connectivity to auditory, visual, somatosensory, and default mode networks, suggesting local specialization within the IPS region for different sensory modalities. In an independent task activation paradigm with 16 subjects, attention to different sensory modalities showed similar functional specialization within the left intraparietal sulcus region. The default mode network, in contrast, did not show a topographical relationship between regions in the network, but rather maximal connectivity in each region to a single central cluster of the other regions. The topographical architecture of multisensory attention may represent a mechanism for specificity in top-down control of attention from dorsolateral prefrontal and lateral orbitofrontal cortex and may represent an organizational unit for multisensory representations in the brain. show synchrony of slow (<0.08 Hz) fluctuations in functional MRI (fMRI) signal (1-3). A network of brain regions known to be active during states of high attention to sensory stimuli or performance of attention-demanding tasks, the attention control network, or task positive network (4-6), reproducibly shows high functional connectivity between regions in the network. A separate interconnected network, the default mode, or task negative network (7-9), is comprised of brain regions more active during rest or attention to internal stimuli or narrative (10). We use here the nomenclature "attention control" and "default mode" networks rather than "task positive" or "task negative" networks because the positive or negative activation of each of these networks depends entirely on whether the task measures internal mentalization or attention to external stimuli (11), and both may be coactivated or have similar behavioral associations (12).The attention control network consists of two primary subnetworks. The dorsal attention network is composed of bilateral intraparietal sulcus (IPS), frontal eye fields (FEF), and lateral prefrontal cortex (4, 5) and has also been termed the executive control network (13). This network frequently shows coactivation with the cinguloinsular, or salience detection network, consisting of bilateral anterior insula, dorsal anterior cingulate/supplementary motor area (SMA), and bilateral middle temporal (MT + ) regions (13). These netwo...
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