Forum of resting-state fMRI

Precuneus is a functional core of the default-mode network.

J Neurosci. 2014 Jan 15;34(3):932-40

Authors: Utevsky AV, Smith DV, Huettel SA

Abstract
Efforts to understand the functional architecture of the brain have consistently identified multiple overlapping large-scale neural networks that are observable across multiple states. Despite the ubiquity of these networks, it remains unclear how regions within these large-scale neural networks interact to orchestrate behavior. Here, we collected functional magnetic resonance imaging data from 188 human subjects who engaged in three cognitive tasks and a resting-state scan. Using multiple tasks and a large sample allowed us to use split-sample validations to test for replication of results. We parceled the task-rest pairs into functional networks using a probabilistic spatial independent components analysis. We examined changes in connectivity between task and rest states using dual-regression analysis, which quantifies voxelwise connectivity estimates for each network of interest while controlling for the influence of signals arising from other networks and artifacts. Our analyses revealed systematic state-dependent functional connectivity in one brain region: the precuneus. Specifically, task performance led to increased connectivity (compared with rest) between the precuneus and the right frontoparietal network, whereas rest increased connectivity between the precuneus and the default-mode network (DMN). The absolute magnitude of this effect was greater for DMN, suggesting a heightened specialization for resting-state cognition. All results replicated within the two independent samples. Our results indicate that the precuneus plays a core role not only in DMN, but also more broadly through its engagement under a variety of processing states.

PMID: 24431451 [PubMed - in process]

Method for Simultaneous fMRI/EEG Data Collection during a Focused Attention Suggestion for Differential Thermal Sensation.

J Vis Exp. 2014;(83)

Authors: Douglas PK, Pisani M, Reid R, Head A, Lau E, Mirakhor E, Bramen J, Gordon B, Anderson A, Kerr WT, Cheong C, Cohen MS

Abstract
In the present work, we demonstrate a method for concurrent collection of EEG/fMRI data. In our setup, EEG data are collected using a high-density 256-channel sensor net. The EEG amplifier itself is contained in a field isolation containment system (FICS), and MRI clock signals are synchronized with EEG data collection for subsequent MR artifact characterization and removal. We demonstrate this method first for resting state data collection. Thereafter, we demonstrate a protocol for EEG/fMRI data recording, while subjects listen to a tape asking them to visualize that their left hand is immersed in a cold-water bath and referred to, here, as the cold glove paradigm. Thermal differentials between each hand are measured throughout EEG/fMRI data collection using an MR compatible temperature sensor that we developed for this purpose. We collect cold glove EEG/fMRI data along with simultaneous differential hand temperature measurements both before and after hypnotic induction. Between pre and post sessions, single modality EEG data are collected during the hypnotic induction and depth assessment process. Our representative results demonstrate that significant changes in the EEG power spectrum can be measured during hypnotic induction, and that hand temperature changes during the cold glove paradigm can be detected rapidly using our MR compatible differential thermometry device.

PMID: 24429915 [PubMed - in process]

Correction: Resting State fMRI Reveals Diminished Functional Connectivity in a Mouse Model of Amyloidosis.

PLoS One. 2014;9(1)

Authors: Shah D, Jonckers E, Praet J, Vanhoutte G, Delgado Y Palacios R, Bigot C, D'Souza DV, Verhoye M, Van der Linden A

Abstract
[This corrects the article on p. e84241 in vol. 8.].

PMID: 24427258 [PubMed - as supplied by publisher]

Disruption of brain connectivity in acute stroke patients with early impairment in consciousness.

Front Psychol. 2014;4:956

Authors: Tsai YH, Yuan R, Huang YC, Yeh MY, Lin CP, Biswal BB

Abstract
Impairment in consciousness is common in acute stroke patients and is correlated with the clinical outcome after stroke. The underlying mechanism is not completely understood, with little known about brain activity and connectivity changes in acute stroke patients having impaired consciousness. In this study, we investigated changes in regional brain activity and brain networks of consciousness impaired stroke patients, as well as the amplitude of spontaneous low frequency fluctuation (ALFF) of each time series. Regional homogeneity (ReHo) of each voxel was measured, and resting state network analysis was consequently conducted. Results from this study demonstrate that, compared to normal subjects, the intensities of ALFF and ReHo, as well as the strength of the default mode network (DMN) connectivity, were significantly decreased in the precuneus and posterior cingulate cortex regions among stroke patients with impaired consciousness. Furthermore, the strength of the DMN was highly correlated with differences in the Glasgow Coma Scale (GCS) scores between the onset time and the scanning time. Results from this study suggest that the resting state fMRI is a feasible tool for the evaluation of acute stroke patients with an early impairment of consciousness. The detailed mechanisms, implications of these brain activities and networks exhibiting changes will require further investigation.

PMID: 24427147 [PubMed]

Abnormal baseline brain activity in drug-naïve patients with Tourette syndrome: a resting-state fMRI study.

Front Hum Neurosci. 2014;7:913

Authors: Cui Y, Jin Z, Chen X, He Y, Liang X, Zheng Y

Abstract
Tourette syndrome (TS) is a childhood-onset chronic disorder characterized by the presence of multiple motor and vocal tics. This study investigated spontaneous low-frequency fluctuations in TS patients during resting-state functional magnetic resonance imaging (rs-fMRI) scans. We obtained rs-fMRI scans from 17 drug-naïve TS children and 15 demographically matched healthy children. We computed the amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) of rs-fMRI data to measure spontaneous brain activity, and assessed the between-group differences in ALFF/fALFF and the relationship between ALFF/fALFF and tic severity scores. Our results showed that the children with TS exhibited significantly decreased ALFF in the posterior cingulate gyrus/precuneus and bilateral parietal gyrus. fALFF was decreased in TS children in the anterior cingulated cortex, bilateral middle and superior frontal cortices and superior parietal lobule, and increased in the left putamen and bilateral thalamus. Moreover, we found significantly positive correlations between fALFF and tic severity scores in the right thalamus. Our study provides empirical evidence for abnormal spontaneous neuronal activity in TS patients, which may implicate the underlying neurophysiological mechanism in TS and demonstrate the possibility of applying ALFF/fALFF for clinical TS studies.

PMID: 24427134 [PubMed]

Neuroimaging of Epilepsy: Lesions, Networks, Oscillations.

Clin Neuroradiol. 2014 Jan 15;

Authors: Abela E, Rummel C, Hauf M, Weisstanner C, Schindler K, Wiest R

Abstract
While analysis and interpretation of structural epileptogenic lesion is an essential task for the neuroradiologist in clinical practice, a substantial body of epilepsy research has shown that focal lesions influence brain areas beyond the epileptogenic lesion, across ensembles of functionally and anatomically connected brain areas. In this review article, we aim to provide an overview about altered network compositions in epilepsy, as measured with current advanced neuroimaging techniques to characterize the initiation and spread of epileptic activity in the brain with multimodal noninvasive imaging techniques. We focus on resting-state functional magnetic resonance imaging (MRI) and simultaneous electroencephalography/fMRI, and oppose the findings in idiopathic generalized versus focal epilepsies. These data indicate that circumscribed epileptogenic lesions can have extended effects on many brain systems. Although epileptic seizures may involve various brain areas, seizure activity does not spread diffusely throughout the brain but propagates along specific anatomic pathways that characterize the underlying epilepsy syndrome. Such a functionally oriented approach may help to better understand a range of clinical phenomena such as the type of cognitive impairment, the development of pharmacoresistance, the propagation pathways of seizures, or the success of epilepsy surgery.

PMID: 24424576 [PubMed - as supplied by publisher]

The wandering mood: psychological and neural determinants of rest-related negative affect.

Front Psychol. 2013;4:961

Authors: Gruberger M, Maron-Katz A, Sharon H, Hendler T, Ben-Simon E

Abstract
Rest related negative affect (RRNA) has gained scientific interest in the past decade. However, it is mostly studied within the context of mind-wandering (MW), and the relevance of other psychological and neural aspects of the resting state to its' occurrence has never been studied. Several indications associate RRNA with internally directed attention, yet the nature of this relation remains largely unknown. Moreover, the role of neural networks associated with rest related phenomenology - the default mode (DMN), executive (EXE), and salience (SAL) networks, has not been studied in this context. To this end, we explored two 5 (baseline) and 15-minute resting-state simultaneous fMRI-EEG scans of 29 participants. As vigilance has been shown to affect attention, and thus its availability for inward allocation, EEG-based vigilance levels were computed for each participant. Questionnaires for affective assessment were administered before and after scans, and retrospective reports of MW were additionally collected. Results revealed increased negative affect following rest, but only among participants who retained high vigilance levels. Among low-vigilance participants, changes in negative affect were negligible, despite reports of MW occurrence in both groups. In addition, in the high-vigilance group only, a significant increase in functional connectivity (FC) levels was found between the DMN-related ventral anterior cingulate cortex (ACC), associated with emotional processing, and the EXE-related dorsal ACC, associated with monitoring of self and other's behavior. These heightened FC levels further correlated with reported negative affect among this group. Taken together, these results demonstrate that, rather than an unavoidable outcome of the resting state, RRNA depends on internal allocation of attention at rest. Results are discussed in terms of two rest-related possible scenarios which defer in mental and neural processing, and subsequently, in the occurrence of RRNA.

PMID: 24421771 [PubMed]

Addressing head motion dependencies for small-world topologies in functional connectomics.

Front Hum Neurosci. 2013;7:910

Authors: Yan CG, Craddock RC, He Y, Milham MP

Abstract
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 density 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.

PMID: 24421764 [PubMed]

Noncontrast mapping of arterial delay and functional connectivity using resting-state functional MRI: A study in Moyamoya patients.

J Magn Reson Imaging. 2014 Jan 13;

Authors: Christen T, Jahanian H, Ni WW, Qiu D, Moseley ME, Zaharchuk G

Abstract
PURPOSE: To investigate if delays in resting-state spontaneous fluctuations of the BOLD (sfBOLD) signal can be used to create maps similar to time-to-maximum of the residue function (Tmax) in Moyamoya patients and to determine whether sfBOLD delays affect the results of brain connectivity mapping.
MATERIALS AND METHODS: Ten patients were scanned at 3 Tesla using a gradient-echo echo planar imaging sequence for sfBOLD imaging. Cross correlation analysis was performed between each brain voxel signal and a reference signal comprised of either the superior sagittal sinus (SSS) or whole brain (WB) average time course. sfBOLD delay maps were created based on the time shift necessary to maximize the correlation coefficient, and compared with dynamic susceptibility contrast Tmax maps. Standard and time-shifted resting-state BOLD connectivity analyses of the default mode network were compared.
RESULTS: Good linear correlations were found between sfBOLD delays and Tmax using the SSS as reference (r(2)  = 0.8, slope = 1.4, intercept = -4.6) or WB (r(2)  = 0.7, slope = 0.8, intercept = -3.2). New nodes of connectivity were found in delayed regions when accounting for delays in the analysis.
CONCLUSION: Resting-state sfBOLD imaging can create delay maps similar to Tmax maps without the use of contrast agents in Moyamoya patients. Accounting for these delays may affect the results of functional connectivity maps.J. Magn. Reson. Imaging 2014. © 2014 Wiley Periodicals, Inc.

PMID: 24419985 [PubMed - as supplied by publisher]

Dynamic changes of spatial functional network connectivity in healthy individuals and schizophrenia patients using independent vector analysis.

Neuroimage. 2014 Jan 10;

Authors: Ma S, Calhoun VD, Phlypo R, Adalı T

Abstract
Recent work on both task-induced and resting-state functional magnetic resonance imaging (fMRI) data suggests that functional connectivity may fluctuate, rather than being stationary during an entire scan. Most dynamic studies are based on second-order statistics between fMRI time series or time courses derived from blind source separation, e.g., independent component analysis (ICA), to investigate changes of temporal interactions among brain regions. However, fluctuations related to spatial components over time are of interest as well. In this paper, we examine higher-order statistical dependence between pairs of spatial components, which we define as spatial functional network connectivity (sFNC), and changes of sFNC across a resting-state scan. We extract time-varying components from healthy controls and patients with schizophrenia to represent brain networks using independent vector analysis (IVA), which is an extension of ICA to multiple data sets and enables one to capture spatial variations. Based on mutual information among IVA components, we perform statistical analysis and Markov modeling to quantify the changes in spatial connectivity. Our experimental results suggest significantly more fluctuations in patient group and show that patients with schizophrenia have more variable patterns of spatial concordance primarily between frontoparietal, cerebellum and temporal lobe regions. This study extends upon earlier studies showing temporal connectivity differences in similar areas on average by providing evidence that the dynamic spatial interplay between these regions is also impacted by schizophrenia.

PMID: 24418507 [PubMed - as supplied by publisher]

Functional connectivity-based parcellation of the human sensorimotor cortex.

Eur J Neurosci. 2014 Jan 13;

Authors: Long X, Goltz D, Margulies DS, Nierhaus T, Villringer A

Abstract
Task-based functional magnetic resonance imaging (fMRI) has been successfully employed to obtain somatotopic maps of the human sensorimotor cortex. Here, we showed through direct comparison that a similar functional map can be obtained, independently of a task, by performing a connectivity-based parcellation of the sensorimotor cortex based on resting-state fMRI. Cortex corresponding to two adjacent Brodmann areas (BA 3 and BA 4) was selected as the sensorimotor area. Parcellation was obtained along a medial-lateral axis, which was confirmed to be somatotopic (corresponding roughly to an upper, middle and lower limb, respectively) by comparing it with maps obtained using motoric task-based fMRI in the same participants. Interestingly, the resting-state parcellation map demonstrated higher correspondence to the task-based divisions after individuals performed the motor task. Using the resting-state fMRI data, we also observed higher functional correlations between the centrally located hand region and the other two regions, than between the foot and tongue. The functional relevance of these somatosensory parcellation results indicates the feasibility of a wide range of potential applications to brain mapping.

PMID: 24417550 [PubMed - as supplied by publisher]

First-episode medication-naive major depressive disorder is associated with altered resting brain function in the affective network.

PLoS One. 2014;9(1):e85241

Authors: Zhang X, Zhu X, Wang X, Zhu X, Zhong M, Yi J, Rao H, Yao S

Abstract
BACKGROUND: Major depressive disorder (MDD) has been associated with abnormal structure and function of the brain's affective network, including the amygdala and orbitofrontal cortex (OFC). However, it is unclear if alterations of resting-state function in this affective network are present at the initial onset of MDD.
AIMS: To examine resting-state function of the brain's affective network in first-episode, medication-naive patients with MDD compared to healthy controls (HCs).
METHODS: Resting-state functional magnetic resonance imaging (rs-fMRI) was performed on 32 first-episode, medication-naive young adult patients with MDD and 35 matched HCs. The amplitude of low-frequency fluctuations (ALFF) of the blood oxygen level-dependent (BOLD) signal and amygdala-seeded functional connectivity (FC) were investigated.
RESULTS: Compared to HC, MDD patients showed reduced ALFF in the bilateral OFC and increased ALFF in the bilateral temporal lobe extending to the insular and left fusiform cortices. Enhanced anti-correlation of activity between the left amygdala seed and the left OFC was found in MDD patients but not in HCs.
CONCLUSIONS: Reduced ALFF in the OFC suggests hypo-functioning of emotion regulation in the affective network. Enhanced anti-correlation of activity between the amygdala and OFC may reflect dysfunction of the amygdala-OFC network and additionally represent a pathological process of MDD.

PMID: 24416367 [PubMed - in process]

Contribution of the resting-state functional connectivity of the contralesional primary sensorimotor cortex to motor recovery after subcortical stroke.

PLoS One. 2014;9(1):e84729

Authors: Xu H, Qin W, Chen H, Jiang L, Li K, Yu C

Abstract
It remains uncertain if the contralesional primary sensorimotor cortex (CL_PSMC) contributes to motor recovery after stroke. Here we investigated longitudinal changes in the resting-state functional connectivity (rsFC) of the CL_PSMC and their association with motor recovery. Thirteen patients who had experienced subcortical stroke underwent a series of resting-state fMRI and clinical assessments over a period of 1 year at 5 time points, i.e., within the first week, at 2 weeks, 1 month, 3 months, and 1 year after stroke onset. Thirteen age- and gender-matched healthy subjects were recruited as controls. The CL_PSMC was defined as a region centered at the voxel that had greatest activation during hand motion task. The dynamic changes in the rsFCs of the CL_PSMC within the whole brain were evaluated and correlated with the Motricity Index (MI) scores. Compared with healthy controls, the rsFCs of the CL_PSMC with the bilateral PSMC were initially decreased, then gradually increased, and finally restored to the normal level 1 year later. Moreover, the dynamic change in the inter-hemispheric rsFC between the bilateral PSMC in these patients was positively correlated with the MI scores. However, the intra-hemispheric rsFC of the CL_PSMC was not correlated with the MI scores. This study shows dynamic changes in the rsFCs of the CL_PSMC after stroke and suggests that the increased inter-hemispheric rsFC between the bilateral PSMC may facilitate motor recovery in stroke patients. However, generalization of our findings is limited by the small sample size of our study and needs to be confirmed.

PMID: 24416273 [PubMed - in process]

The effect of theta-burst TMS on cognitive control networks measured with resting state fMRI.

Front Syst Neurosci. 2013;7:124

Authors: Gratton C, Lee TG, Nomura EM, D'Esposito M

Abstract
IT HAS BEEN PROPOSED THAT TWO RELATIVELY INDEPENDENT COGNITIVE CONTROL NETWORKS EXIST IN THE BRAIN: the cingulo-opercular network (CO) and the fronto-parietal network (FP). Past work has shown that chronic brain lesions affect these networks independently. It remains unclear, however, how these two networks are affected by acute brain disruptions. To examine this, we conducted a within-subject theta-burst transcranial magnetic stimulation (TBS) experiment in healthy individuals that targeted left anterior insula/frontal operculum (L aI/fO, a region in the CO network), left dorsolateral prefrontal cortex (L dlPFC, a region in the FP network), or left primary somatosensory cortex (L S1, an experimental control region). Functional connectivity (FC) was measured in resting state fMRI scans collected before and after continuous TBS on each day. We found that TBS was accompanied by generalized increases in network connectivity, especially FP network connectivity, after TBS to either region involved in cognitive control. Whole-brain analyses demonstrated that the L dlPFC and L aI/fO showed increased connectivity with regions in frontal, parietal, and cingulate cortex after TBS to either L dlPFC or L aI/fO, but not to L S1. These results suggest that acute disruption by TBS to cognitive control regions causes widespread changes in network connectivity not limited to the targeted networks.

PMID: 24416003 [PubMed]

Effective Preprocessing Procedures Virtually Eliminate Distance-Dependent Motion Artifacts in Resting State FMRI.

J Appl Math. 2013 May 21;2013

Authors: Jo HJ, Gotts SJ, Reynolds RC, Bandettini PA, Martin A, Cox RW, Saad ZS

Abstract
Artifactual sources of resting-state (RS) FMRI can originate from head motion, physiology, and hardware. Of these sources, motion has received considerable attention and was found to induce corrupting effects by differentially biasing correlations between regions depending on their distance. Numerous corrective approaches have relied on the identification and censoring of high-motion time points and the use of the brain-wide average time series as a nuisance regressor to which the data are orthogonalized (Global Signal Regression, GSReg). We first replicate the previously reported head-motion bias on correlation coefficients using data generously contributed by Power et al. (2012). We then show that while motion can be the source of artifact in correlations, the distance-dependent bias-taken to be a manifestation of the motion effect on correlation-is exacerbated by the use of GSReg. Put differently, correlation estimates obtained after GSReg are more susceptible to the presence of motion and by extension to the levels of censoring. More generally, the effect of motion on correlation estimates depends on the preprocessing steps leading to the correlation estimate, with certain approaches performing markedly worse than others. For this purpose, we consider various models for RS FMRI preprocessing and show that WMeLOCAL, as subset of the ANATICOR discussed by Jo et al. (2010), denoising approach results in minimal sensitivity to motion and reduces by extension the dependence of correlation results on censoring.

PMID: 24415902 [PubMed - as supplied by publisher]

Dopamine precursor depletion impairs structure and efficiency of resting state brain functional networks.

Neuropharmacology. 2014 Jan 9;

Authors: Carbonell F, Nagano-Saito A, Leyton M, Cisek P, Benkelfat C, He Y, Dagher A

Abstract
Spatial patterns of functional connectivity derived from resting brain activity may be used to elucidate the topological properties of brain networks. Such networks are amenable to study using graph theory, which shows that they possess small world properties and can be used to differentiate healthy subjects and patient populations. Of particular interest is the possibility that some of these differences are related to alterations in the dopamine system. To investigate the role of dopamine in the topological organization of brain networks at rest, we tested the effects of reducing dopamine synthesis in 13 healthy subjects undergoing functional magnetic resonance imaging. All subjects were scanned twice, in a resting state, following ingestion of one of two amino acid drinks in a randomized, double-blind manner. One drink was a nutritionally balanced amino acid mixture, and the other was tyrosine and phenylalanine deficient. Functional connectivity between 90 cortical and subcortical regions was estimated for each individual subject under each dopaminergic condition. The lowered dopamine state caused the following network changes: reduced global and local efficiency of the whole brain network, reduced regional efficiency in limbic areas, reduced modularity of brain networks, and greater connection between the normally anti-correlated task-positive and default-mode networks. We conclude that dopamine plays a role in maintaining the efficient small-world properties and high modularity of functional brain networks, and in segregating the task-positive and default-mode networks. This article is part of a Special Issue entitled 'Neuroimaging'.

PMID: 24412649 [PubMed - as supplied by publisher]

Increased Insula Coactivation with Salience Networks in Insomnia.

Biol Psychol. 2014 Jan 7;

Authors: Chen MC, Chang C, Glover GH, Gotlib IH

Abstract
Insomnia is among the most prevalent and costly of all sleep-related disorders. To characterize the neural mechanisms underlying subjective dysfunction in insomnia, we examined brain activity in 17 female insomniacs and 17 female healthy controls using simultaneous functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) while they were resting and while they were trying to fall asleep. In examining the dynamic regional activity within intrinsic brain networks, we found that, compared with controls, insomniacs had greater involvement of the anterior insula with salience networks, as well as insula BOLD correlation with EEG gamma frequency power during rest in insomniacs. This increased involvement of the anterior insula was associated with negative affect in insomniacs. Aberrant activation of the insula, which integrates temporal and bodily states, in arousal networks may underlie the misperception of sleep quality and subjective distress in insomnia.

PMID: 24412227 [PubMed - as supplied by publisher]

Functional connectivity alterations in brain networks relevant to self-awareness in chronic cannabis users.

J Psychiatr Res. 2013 Dec 28;

Authors: Pujol J, Blanco-Hinojo L, Batalla A, López-Solà M, Harrison BJ, Soriano-Mas C, Crippa JA, Fagundo AB, Deus J, de la Torre R, Nogué S, Farré M, Torrens M, Martín-Santos R

Abstract
BACKGROUND: Recreational drugs are generally used to intentionally alter conscious experience. Long-lasting cannabis users frequently seek this effect as a means to relieve negative affect states. As with conventional anxiolytic drugs, however, changes in subjective feelings may be associated with memory impairment. We have tested whether the use of cannabis, as a psychoactive compound, is associated with alterations in spontaneous activity in brain networks relevant to self-awareness, and whether such potential changes are related to perceived anxiety and memory performance.
METHODS: Functional connectivity was assessed in the Default and Insula networks during resting state using fMRI in 28 heavy cannabis users and 29 control subjects. Imaging assessments were conducted during cannabis use in the unintoxicated state and repeated after one month of controlled abstinence.
RESULTS: Cannabis users showed increased functional connectivity in the core of the Default and Insula networks and selective enhancement of functional anticorrelation between both. Reduced functional connectivity was observed in areas overlapping with other brain networks. Observed alterations were associated with behavioral measurements in a direction suggesting anxiety score reduction and interference with memory performance. Alterations were also related to the amount of cannabis used and partially persisted after one month of abstinence.
CONCLUSIONS: Chronic cannabis use was associated with significant effects on the tuning and coupling of brain networks relevant to self-awareness, which in turn are integrated into brain systems supporting the storage of personal experience and motivated behavior. The results suggest potential mechanisms for recreational drugs to interfere with higher-order network interactions generating conscious experience.

PMID: 24411594 [PubMed - as supplied by publisher]

Graph independent component analysis reveals repertoires of intrinsic network components in the human brain.

PLoS One. 2014;9(1):e82873

Authors: Park B, Kim DS, Park HJ

Abstract
Does each cognitive task elicit a new cognitive network each time in the brain? Recent data suggest that pre-existing repertoires of a much smaller number of canonical network components are selectively and dynamically used to compute new cognitive tasks. To this end, we propose a novel method (graph-ICA) that seeks to extract these canonical network components from a limited number of resting state spontaneous networks. Graph-ICA decomposes a weighted mixture of source edge-sharing subnetworks with different weighted edges by applying an independent component analysis on cross-sectional brain networks represented as graphs. We evaluated the plausibility in our simulation study and identified 49 intrinsic subnetworks by applying it in the resting state fMRI data. Using the derived subnetwork repertories, we decomposed brain networks during specific tasks including motor activity, working memory exercises, and verb generation, and identified subnetworks associated with performance on these tasks. We also analyzed sex differences in utilization of subnetworks, which was useful in characterizing group networks. These results suggest that this method can effectively be utilized to identify task-specific as well as sex-specific functional subnetworks. Moreover, graph-ICA can provide more direct information on the edge weights among brain regions working together as a network, which cannot be directly obtained through voxel-level spatial ICA.

PMID: 24409279 [PubMed - in process]

Constructing the resting state structural connectome.

Front Neuroinform. 2013;7:30

Authors: Ajilore O, Zhan L, Gadelkarim J, Zhang A, Feusner JD, Yang S, Thompson PM, Kumar A, Leow A

Abstract
Background: Many recent studies have separately investigated functional and white matter (WM) based structural connectivity, yet their relationship remains less understood. In this paper, we proposed the functional-by-structural hierarchical (FSH) mapping to integrate multimodal connectome data from resting state fMRI (rsfMRI) and the whole brain tractography-derived connectome. Methods: FSH first observes that the level of resting-state functional correlation between any two regions in general decreases as the graph distance of the corresponding structural connectivity matrix between them increases. As not all white matter tracts are actively in use (i.e., "utilized") during resting state, FSH thus models the rsfMRI correlation as an exponential decay function of the graph distance of the rsfMRI-informed structural connectivity or rsSC. rsSC is mathematically computed by multiplying entry-by-entry the tractography-derived structural connectivity matrix with a binary white matter "utilization matrix" U. U thus encodes whether any specific WM tract is being utilized during rsFMRI, and is estimated using simulated annealing. We applied this technique and investigated the hierarchical modular structure of rsSC from 7 depressed subjects and 7 age/gender matched controls. Results: No significant group differences were detected in the modular structures of either the resting state functional connectome or the whole brain tractography-derived connectome. By contrast, FSH results revealed significantly different patterns of association in the bilateral posterior cingulate cortex and right precuneus, with the depressed group exhibiting stronger associations among regions instrumental in self-referential operations. Discussion: The results of this study support that enhanced sensitivity can be obtained by integrating multimodal imaging data using FSH, a novel computational technique that may increase power to detect group differences in brain connectomes.

PMID: 24409139 [PubMed]