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This study was designed to identify the neural substrates activated during a phoria adaptation task using functional magnetic resonance imaging (MRI) in young adults with normal binocular vision and to test the repeatability of the fMRI measurements for this protocol. The phoria adaptation task consisted of a block protocol of 90 seconds of near visual crossed fixation followed by 90 seconds of far visual uncrossed fixation, repeated three times; the data were collected during two different experimental sessions. Results showed that the oculomotor vermis, cuneus, and primary visual cortex had the greatest functional activity within the regions of interest studied when stimulated by the phoria adaptation task. The oculomotor vermis functional activity had an intraclass correlation coefficient (ICC) of 0.3, whereas the bilateral cuneus and primary visual cortex had good ICC results of greater than 0.6. These results suggest that the sustained visual fixation task described within this study reliably activates the neural substrates of phoria adaptation. This protocol establishes a methodology that can be used in future longitudinal studies investigating therapeutic interventions that may modify phoria adaptation.

Vergence eye movements are the inward and outward rotation of the eyes responsible for binocular coordination. While studies have mapped and investigated the neural substrates of vergence, it is not well understood whether vergence eye movements evoke the blood oxygen level-dependent signal reliably in separate experimental visits. The test-retest reliability of stimulus-induced vergence eye movement tasks during a functional magnetic resonance imaging (fMRI) experiment is important for future randomized clinical trials (RCTs). In this study, we established region of interest (ROI) masks for the vergence neural circuit. Twenty-seven binocularly normal young adults participated in two functional imaging sessions measured on different days on the same 3T Siemens scanner. The fMRI experiments used a block design of sustained visual fixation and rest blocks interleaved between task blocks that stimulated eight or four vergence eye movements. The test-retest reliability of task-activation was assessed using the intraclass correlation coefficient (ICC), and that of spatial extent was assessed using the Dice coefficient. Functional activation during the vergence eye movement task of eight movements compared to rest was repeatable within the primary visual cortex (ICC = 0.8), parietal eye fields (ICC = 0.6), supplementary eye field (ICC = 0.5), frontal eye fields (ICC = 0.5), and oculomotor vermis (ICC = 0.6). The results demonstrate significant test-retest reliability in the ROIs of the vergence neural substrates for functional activation magnitude and spatial extent using the stimulus protocol of a task block stimulating eight vergence eye movements compared to sustained fixation. These ROIs can be used in future longitudinal RCTs to study patient populations with vergence dysfunctions.

Objective: To examine the differences in whole brain topology and connectivity in 17 children of the ages 3-8 years across severity of ASD, we performed resting state fMRI using a 3T MRI scanner and graph theoretical analysis of networks., Method: Patients were partitioned into two cohorts based on the severity of ASD, determined using the Childhood Autism Rating Scale (CARS) scores (Mild, 30-36; Severe, 37+). Standard preprocessing pipeline was used, followed by independent component analysis (ICA) to identify regions of interest (ROIs) to construct subject-specific Z-correlation matrices representing the whole brain network. Following which, graph theory measures were calculated in the range of sparsity 6%-35% and statistically analyzed, and corrected for significance (FDR corrected, p < 0.05). Regional clustering coefficient that revealed significant between-group (mild vs. severe) differences were correlated against clinical scores (CARS)., Results: Children with severe ASD revealed significantly increased clustering coefficient and small-worldness compared to those with mild or moderate ASD. Region of interest analysis revealed altered clustering in the Heschl's gyrus that significantly correlated with CARS scores., Conclusion: The findings from the current study provide early stage evidence of aberrant brain connectivity appearing in severe ASD, prior to the effect of environmental bias and pruning mechanisms. The clustering of the Heschl's gyrus correlated to the severity of ASD symptoms and agrees with current literature on ASD-associated cortical changes, reflecting early changes to language processing regions., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Resting state functional magnetic resonance imaging studies of psychosis have focused primarily on the amplitude of low-frequency fluctuations in the blood oxygen level dependent (BOLD) signal ranging from .01 to 0.1 Hz. Few studies, however, have investigated the amplitude of frequency fluctuations within discrete frequency bands and higher than 0.1 Hz in patients with psychosis at different illness stages. We investigated BOLD signal within three frequency ranges including slow-4 (.027-.073 Hz), slow-3 (.074-0.198 Hz) and slow-2 (0.199-0.25 Hz) in 89 patients with either first-episode or chronic psychosis and 119 healthy volunteers. We investigated the amplitude of frequency fluctuations within three frequency bands using 47 regions-of-interest placed within 14 known resting state networks derived using group independent component analysis. There were significant group x frequency interactions for the visual and motor cortex networks, with the largest significant group differences (patients < healthy volunteers) evident in slow-4 and slow-3, respectively. Also, healthy volunteers had an overall higher amplitude of frequency fluctuations compared to patients across the three frequency ranges in the visual cortex, dorsal attention and motor cortex networks with the opposite effect (patients > healthy volunteers) evident within the salience and frontal gyrus networks. Subsequent analyses indicated that these effects were evident in both first-episode and chronic patients. Our study provides new data regarding the importance of BOLD signal fluctuations within different frequency bands in the neurobiology of psychosis., (© 2018 Wiley Periodicals, Inc.)

Concomitant cannabis and nicotine use is more prevalent than cannabis use alone; however, to date, most of the literature has focused on associations of isolated cannabis and nicotine use limiting the generalizability of existing research. To determine differential associations of concomitant use of cannabis and nicotine, isolated cannabis use and isolated nicotine use on brain network connectivity, we examined systems-level neural functioning via independent components analysis (ICA) on resting state networks (RSNs) in cannabis users (CAN, n = 53), nicotine users (NIC, n = 28), concomitant nicotine and cannabis users (NIC + CAN, n = 26), and non-users (CTRL, n = 30). Our results indicated that the CTRL group and NIC + CAN users had the greatest functional connectivity relative to CAN users and NIC users in 12 RSNs: anterior default mode network (DMN), posterior DMN, left frontal parietal network, lingual gyrus, salience network, right frontal parietal network, higher visual network, insular cortex, cuneus/precuneus, posterior cingulate gyrus/middle temporal gyrus, dorsal attention network, and basal ganglia network. Post hoc tests showed no significant differences between (1) CTRL and NIC + CAN and (2) NIC and CAN users. These findings of differential associations of isolated vs. combined nicotine and cannabis use demonstrate an interaction between cannabis and nicotine use on RSNs. These unique and combined mechanisms through which cannabis and nicotine influence cortical network functional connectivity are important to consider when evaluating the neurobiological pathways associated with cannabis and nicotine use.

This study examined the effects of age and HIV infection on the resting state (RS) functional connectivity (FC) of the brain and cognitive functioning. The objective was to evaluate the moderating role of age and HIV on the relationship between RS-FC and cognition. To examine RS-FC we implemented the Independent Component Analysis (ICA) and Regional Homogeneity (ReHo). Neurocognition was evaluated with comprehensive battery of standardized neuropsychological tests. Age and HIV were entered as the independent variables. The independent effects of age, HIV, and interaction effects of age-HIV on RS-fMRI measures (ICA, ReHo) were tested in 108 participants (age M = 42). RS-FC indices that exhibited age-HIV interactions were entered into further analysis. Bivariate correlation analysis was performed between the retained RS-FC indices and T-scores of neurocognitive domains (Attention, Executive, Memory, Psychomotor, Semantic Skills). Multivariate regression modeling determined the impact of age and HIV on these relationships. We found that in the ICA measures, HIV-seropositivity was decreasing RS-FC in the left middle occipital gyrus (p < .001). Age-HIV interaction was observed in the left superior frontal gyrus (LSupFrontG), where FC was decreasing with age in HIV+ (p < .001) and increasing in HIV- (p = .031). ReHo indices did not reveal significant effects. HIV strengthened the relationship between RS-FC in LSupFrontG, Memory and Psychomotor Factor scores. Aging weakened those relationships only in control group. In sum, age-HIV interaction effects are prominent rather in remote than local RS-FC. Seroconversion strengthens relationships between intrinsic brain activity and neurocognition, but no acceleration with years of age was noted in HIV+ individuals., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Relationships between spatially remote brain regions in human have typically been estimated by moment-to-moment correlations of blood-oxygen-level dependent signals in resting-state using functional MRI (fMRI). Recently, studies using subject-to-subject covariance of anatomical volumes, cortical thickness, and metabolic activity are becoming increasingly popular. However, question remains on whether these measures reflect the same inter-region connectivity and brain network organizations. In the current study, we systematically analyzed inter-subject volumetric covariance from anatomical MRI images, metabolic covariance from fluorodeoxyglucose positron emission tomography images from 193 healthy subjects, and resting-state moment-to-moment correlations from fMRI images of a subset of 44 subjects. The correlation matrices calculated from the three methods were found to be minimally correlated, with higher correlation in the range of 0.31, as well as limited proportion of overlapping connections. The volumetric network showed the highest global efficiency and lowest mean clustering coefficient, leaning toward random-like network, while the metabolic and resting-state networks conveyed properties more resembling small-world networks. Community structures of the volumetric and metabolic networks did not reflect known functional organizations, which could be observed in resting-state network. The current results suggested that inter-subject volumetric and metabolic covariance do not necessarily reflect the inter-regional relationships and network organizations as resting-state correlations, thus calling for cautions on interpreting results of inter-subject covariance networks.

Fetal alcohol spectrum disorders (FASD) are characterized by impairment in cognitive function that may or may not be accompanied by craniofacial anomalies, microcephaly, and/or growth retardation. Resting-state functional MRI (rs-fMRI), which examines the low-frequency component of the blood oxygen level dependent (BOLD) signal in the absence of an explicit task, provides an efficient and powerful mechanism for studying functional brain networks even in low-functioning and young subjects. Studies using independent component analysis (ICA) have identified a set of resting-state networks (RSNs) that have been linked to distinct domains of cognitive and perceptual function, which are believed to reflect the intrinsic functional architecture of the brain. This study is the first to examine resting-state functional connectivity within these RSNs in FASD. Rs-fMRI scans were performed on 38 children with FASD (19 with either full fetal alcohol syndrome (FAS) or partial FAS (PFAS), 19 nonsyndromal heavily exposed (HE)), and 19 controls, mean age 11.3 ± 0.9 years, from the Cape Town Longitudinal Cohort. Nine resting-state networks were generated by ICA. Voxelwise group comparison between a combined FAS/PFAS group and controls revealed localized dose-dependent functional connectivity reductions in five regions in separate networks: anterior default mode, salience, ventral and dorsal attention, and R executive control. The former three also showed lower connectivity in the HE group. Gray matter connectivity deficits in four of the five networks appear to be related to deficits in white matter tracts that provide intra-RSN connections. Hum Brain Mapp 38:5217-5233, 2017. © 2017 Wiley Periodicals, Inc., (© 2017 Wiley Periodicals, Inc.)

Past research involving cocaine and resting-state functional connectivity (RSFC) has shown altered functional connectivity within the frontal and between the frontal and other cortical and subcortical brain regions in chronic users of cocaine. However, there have been discrepancies in literature regarding the relationship between RSFC between brain regions and cocaine use behavior. This study explored the RSFC between brain regions in cocaine smokers abstinent from cocaine use for 72 h and healthy controls. Also, the relationship between RSFC between brain regions and various cocaine use measures (cocaine use duration; frequency, and money spent on cocaine/week) was examined. Twenty chronic cocaine users and 17 controls completed a resting-state scan and an anatomical MPRAGE scan. Group independent component analysis performed on functional magnetic resonance imaging data identified 13 ICs pertaining to distinct resting-state networks, and group-level differences were examined. To examine inter-network functional connectivity between brain regions, these 13 ICs were divided into 61 distinct regions of interest (ROIs). Correlations were calculated between 61 ROI time series. For the ROI pairs that significantly differed from controls in connectivity strength, correlations were computed between connectivity strength and cocaine use measures. Results showed an enhanced RSFC within the sensory motor cortex and the left frontal-parietal network in cocaine users than controls. An increased inter-network RSFC between frontal-temporal and frontal-parietal brain regions, and a decreased RSFC between parietal-parietal, occipital-limbic, occipital-occipital, and occipital-parietal brain regions was found in cocaine users. This study demonstrated that intra-network connectivity strength of sensory motor cortex was negatively correlated with years of cocaine use. Inter-network connectivity strength between occipital-limbic brain regions was positively correlated with years of cocaine use, while connectivity strength within occipital brain regions was negatively related to cocaine use frequency and money spent on cocaine per week in abstinent cocaine users.

Studies of resting-state fMRI have shown that blood oxygen level dependent (BOLD) signals giving rise to temporal correlation across voxels (or regions) are dominated by low-frequency fluctuations in the range of ∼ 0.01-0.1 Hz. These low-frequency fluctuations have been further divided into multiple distinct frequency bands (slow-5 and -4) based on earlier neurophysiological studies, though low sampling frequency of fMRI (∼ 0.5 Hz) has substantially limited the exploration of other known frequency bands of neurophysiological origins (slow-3, -2, and -1). In this study, we used resting-state fMRI data acquired from 21 healthy subjects at a higher sampling frequency of 1.5 Hz to assess the presence of resting-state functional connectivity (RSFC) across multiple frequency bands: slow-5 to slow-1. The effect of different frequency bands on spatial extent and connectivity strength for known resting-state networks (RSNs) was also evaluated. RSNs were derived using independent component analysis and seed-based correlation. Commonly known RSNs, such as the default mode, the fronto-parietal, the dorsal attention, and the visual networks, were consistently observed at multiple frequency bands. Significant inter-hemispheric connectivity was observed between each seed and its contra lateral brain region across all frequency bands, though overall spatial extent of seed-based correlation maps decreased in slow-2 and slow-1 frequency bands. These results suggest that functional integration between brain regions at rest occurs over multiple frequency bands and RSFC is a multiband phenomenon. These results also suggest that further investigation of BOLD signal in multiple frequency bands for related cognitive processes should be undertaken.

In this study, we investigate a new approach for examining the separation of the brain into resting-state networks (RSNs) on a group level using resting-state parameters (amplitude of low-frequency fluctuation [ALFF], fractional ALFF [fALFF], the Hurst exponent, and signal standard deviation). Spatial independent component analysis is used to reveal covariance patterns of the relevant resting-state parameters (not the time series) across subjects that are shown to be related to known, standard RSNs. As part of the analysis, nonresting state parameters are also investigated, such as mean of the blood oxygen level-dependent time series and gray matter volume from anatomical scans. We hypothesize that meaningful RSNs will primarily be elucidated by analysis of the resting-state functional connectivity (RSFC) parameters and not by non-RSFC parameters. First, this shows the presence of a common influence underlying individual RSFC networks revealed through low-frequency fluctation (LFF) parameter properties. Second, this suggests that the LFFs and RSFC networks have neurophysiological origins. Several of the components determined from resting-state parameters in this manner correlate strongly with known resting-state functional maps, and we term these "functional covariance networks".

Graph-based computational network analysis has proven a powerful tool to quantitatively characterize functional architectures of the brain. However, the test-retest (TRT) reliability of graph metrics of functional networks has not been systematically examined. Here, we investigated TRT reliability of topological metrics of functional brain networks derived from resting-state functional magnetic resonance imaging data. Specifically, we evaluated both short-term (<1 hour apart) and long-term (>5 months apart) TRT reliability for 12 global and 6 local nodal network metrics. We found that reliability of global network metrics was overall low, threshold-sensitive and dependent on several factors of scanning time interval (TI, long-term>short-term), network membership (NM, networks excluding negative correlations>networks including negative correlations) and network type (NT, binarized networks>weighted networks). The dependence was modulated by another factor of node definition (ND) strategy. The local nodal reliability exhibited large variability across nodal metrics and a spatially heterogeneous distribution. Nodal degree was the most reliable metric and varied the least across the factors above. Hub regions in association and limbic/paralimbic cortices showed moderate TRT reliability. Importantly, nodal reliability was robust to above-mentioned four factors. Simulation analysis revealed that global network metrics were extremely sensitive (but varying degrees) to noise in functional connectivity and weighted networks generated numerically more reliable results in compared with binarized networks. For nodal network metrics, they showed high resistance to noise in functional connectivity and no NT related differences were found in the resistance. These findings provide important implications on how to choose reliable analytical schemes and network metrics of interest.

Purpose: The purpose of this study is to investigate the functional neural anatomy that generates vergence eye movement responses from predictive versus random symmetrical vergence step stimuli in humans and compare it to a similar saccadic task via the blood oxygenation level dependent signal from functional MRI., Methods: Eight healthy subjects participated in fMRI scans obtained from a 3T Siemens Allegra scanner. Subjects tracked random and predictable vergent steps and then tracked random and predictable saccadic steps each within a block design. A general linear model (GLM) was used to determine significantly (p < 0.001) active regions of interest through a combination of correlation threshold and cluster extent. A paired t-test of the GLM beta weight coefficients was computed to determine significant spatial differences between the saccade and vergence data sets., Results: Predictive saccadic and vergent eye movements induced many common sites of significant functional cortical activity including: the dorsolateral prefrontal cortex (DLPFC), parietal eye field (PEF), cuneus, precuneus, anterior and posterior cingulate, and the cerebellum. However, differentiation in spatial location was observed within the frontal lobe for the functional activity of the saccadic and vergent network induced while studying prediction. A paired t-test of the beta weights from the individual subjects showed that peak activity induced by predictive versus random vergent eye movements was significantly (t > 2.7, p < 0.03) more anterior within the frontal eye field (FEF) and the supplementary eye field (SEF) when compared to the functional activity from predictive saccadic eye movements., Conclusion: This research furthers our knowledge of which cortical sites facilitate a subject's ability to predict within the vergence and saccade networks. Using a predictive versus random visual task, saccadic and vergent eye movements induced activation in many shared cortical sites and also stimulated differentiation in the FEF and SEF., (Copyright © 2010 Elsevier Ltd. All rights reserved.)

Although it is being successfully implemented for exploration of the genome, discovery science has eluded the functional neuroimaging community. The core challenge remains the development of common paradigms for interrogating the myriad functional systems in the brain without the constraints of a priori hypotheses. Resting-state functional MRI (R-fMRI) constitutes a candidate approach capable of addressing this challenge. Imaging the brain during rest reveals large-amplitude spontaneous low-frequency (<0.1 Hz) fluctuations in the fMRI signal that are temporally correlated across functionally related areas. Referred to as functional connectivity, these correlations yield detailed maps of complex neural systems, collectively constituting an individual's "functional connectome." Reproducibility across datasets and individuals suggests the functional connectome has a common architecture, yet each individual's functional connectome exhibits unique features, with stable, meaningful interindividual differences in connectivity patterns and strengths. Comprehensive mapping of the functional connectome, and its subsequent exploitation to discern genetic influences and brain-behavior relationships, will require multicenter collaborative datasets. Here we initiate this endeavor by gathering R-fMRI data from 1,414 volunteers collected independently at 35 international centers. We demonstrate a universal architecture of positive and negative functional connections, as well as consistent loci of inter-individual variability. Age and sex emerged as significant determinants. These results demonstrate that independent R-fMRI datasets can be aggregated and shared. High-throughput R-fMRI can provide quantitative phenotypes for molecular genetic studies and biomarkers of developmental and pathological processes in the brain. To initiate discovery science of brain function, the 1000 Functional Connectomes Project dataset is freely accessible at www.nitrc.org/projects/fcon&#95;1000/.