New resting-state fMRI related studies at PubMed

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Linking Entropy at Rest with the Underlying Structural Connectivity in the Healthy and Lesioned Brain.

Fri, 10/06/2017 - 14:00

Linking Entropy at Rest with the Underlying Structural Connectivity in the Healthy and Lesioned Brain.

Cereb Cortex. 2017 Jul 13;:1-11

Authors: Saenger VM, Ponce-Alvarez A, Adhikari M, Hagmann P, Deco G, Corbetta M

Abstract
The brain is a network that mediates information processing through a wide range of states. The extent of state diversity is a reflection of the entropy of the network. Here we measured the entropy of brain regions (nodes) in empirical and modeled functional networks reconstructed from resting state fMRI to address the connection of entropy at rest with the underlying structure measured through diffusion spectrum imaging. Using 18 empirical and 18 modeled stroke networks, we also investigated the effect that focal lesions have on node entropy and information diffusion. Overall, positive correlations between node entropy and structure were observed, especially between node entropy and node strength in both empirical and modeled data. Although lesions were restricted to one hemisphere in all stroke patients, entropy reduction was not only present in nodes from the damaged hemisphere, but also in nodes from the contralesioned hemisphere, an effect replicated in modeled stroke networks. Globally, information diffusion was also affected in empirical and modeled strokes compared with healthy controls. This is the first study showing that artificial lesions affect local and global network aspects in very similar ways compared with empirical strokes, shedding new light into the functional nature of stroke.

PMID: 28981635 [PubMed - as supplied by publisher]

Local-Global Parcellation of the Human Cerebral Cortex from Intrinsic Functional Connectivity MRI.

Fri, 10/06/2017 - 14:00

Local-Global Parcellation of the Human Cerebral Cortex from Intrinsic Functional Connectivity MRI.

Cereb Cortex. 2017 Jul 18;:1-20

Authors: Schaefer A, Kong R, Gordon EM, Laumann TO, Zuo XN, Holmes AJ, Eickhoff SB, Yeo BTT

Abstract
A central goal in systems neuroscience is the parcellation of the cerebral cortex into discrete neurobiological "atoms". Resting-state functional magnetic resonance imaging (rs-fMRI) offers the possibility of in vivo human cortical parcellation. Almost all previous parcellations relied on 1 of 2 approaches. The local gradient approach detects abrupt transitions in functional connectivity patterns. These transitions potentially reflect cortical areal boundaries defined by histology or visuotopic fMRI. By contrast, the global similarity approach clusters similar functional connectivity patterns regardless of spatial proximity, resulting in parcels with homogeneous (similar) rs-fMRI signals. Here, we propose a gradient-weighted Markov Random Field (gwMRF) model integrating local gradient and global similarity approaches. Using task-fMRI and rs-fMRI across diverse acquisition protocols, we found gwMRF parcellations to be more homogeneous than 4 previously published parcellations. Furthermore, gwMRF parcellations agreed with the boundaries of certain cortical areas defined using histology and visuotopic fMRI. Some parcels captured subareal (somatotopic and visuotopic) features that likely reflect distinct computational units within known cortical areas. These results suggest that gwMRF parcellations reveal neurobiologically meaningful features of brain organization and are potentially useful for future applications requiring dimensionality reduction of voxel-wise fMRI data. Multiresolution parcellations generated from 1489 participants are publicly available (https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/brain_parcellation/Schaefer2018_LocalGlobal).

PMID: 28981612 [PubMed - as supplied by publisher]

A New Modular Brain Organization of the BOLD Signal during Natural Vision.

Fri, 10/06/2017 - 14:00

A New Modular Brain Organization of the BOLD Signal during Natural Vision.

Cereb Cortex. 2017 Jul 13;:1-17

Authors: Kim D, Kay K, Shulman GL, Corbetta M

Abstract
The resting blood oxygen level-dependent (BOLD) signal is synchronized in large-scale brain networks (resting-state networks, RSNs) defined by interregional temporal correlations (functional connectivity, FC). RSNs are thought to place strong constraints on task-evoked processing since they largely match the networks observed during task performance. However, this result may simply reflect the presence of spontaneous activity during both rest and task. Here, we examined the BOLD network structure of natural vision, as simulated by viewing of movies, using procedures that minimized the contribution of spontaneous activity. We found that the correlation between resting and movie-evoked FC (ρ = 0.60) was lower than previously reported. Hierarchical clustering and graph-theory analyses indicated a well-defined network structure during natural vision that differed from the resting structure, and emphasized functional groupings adaptive for natural vision. The visual network merged with a network for navigation, scene analysis, and scene memory. Conversely, the dorsal attention network was split and reintegrated into 2 groupings likely related to vision/scene and sound/action processing. Finally, higher order groupings from the clustering analysis combined internally directed and externally directed RSNs violating the large-scale distinction that governs resting-state organization. We conclude that the BOLD FC evoked by natural vision is only partly constrained by the resting network structure.

PMID: 28981593 [PubMed - as supplied by publisher]

Contrasting resting-state fMRI abnormalities from sickle and non-sickle anemia.

Fri, 10/06/2017 - 14:00

Contrasting resting-state fMRI abnormalities from sickle and non-sickle anemia.

PLoS One. 2017;12(10):e0184860

Authors: Coloigner J, Kim Y, Bush A, Choi S, Balderrama MC, Coates TD, O'Neil SH, Lepore N, Wood JC

Abstract
Sickle cell disease (SCD) is a chronic blood disorder that is often associated with acute and chronic cerebrovascular complications, including strokes and impaired cognition. Using functional resting state magnetic resonance images, we performed whole-brain analysis of the amplitude of low frequency fluctuations (ALFF), to detect areas of spontaneous blood oxygenation level dependent signal across brain regions. We compared the ALFF of 20 SCD patients to that observed in 19 healthy, age and ethnicity-matched, control subjects. Significant differences were found in several brain regions, including the insula, precuneus, anterior cingulate cortex and medial superior frontal gyrus. To identify the ALFF differences resulting from anemia alone, we also compared the ALFF of SCD patients to that observed in 12 patients having comparable hemoglobin levels but lacking sickle hemoglobin. Increased ALFF in the orbitofrontal cortex and the anterior and posterior cingulate cortex and decreased ALFF in the frontal pole, cerebellum and medial superior frontal gyrus persisted after accounting for the effect of anemia. The presence of white matter hyperintensities was associated with depressed frontal and medial superior frontal gyri activity in the SCD subjects. Decreased ALFF in the frontal lobe was correlated with decreased verbal fluency and cognitive flexibility. These findings may lead to a better understanding of the pathophysiology of SCD.

PMID: 28981541 [PubMed - in process]

Two days' sleep debt causes mood decline during resting state via diminished amygdala-prefrontal connectivity.

Thu, 10/05/2017 - 13:20

Two days' sleep debt causes mood decline during resting state via diminished amygdala-prefrontal connectivity.

Sleep. 2017 Jul 29;:

Authors: Motomura Y, Katsunuma R, Yoshimura M, Mishima K

Abstract
Study objectives: Sleep debt has been suggested to evoke emotional instability by diminishing the suppression of the amygdala by the medial prefrontal cortex (MPFC). Here, we investigated how short-term sleep debt affects resting-state functional connectivity between the amygdala and MPFC, subjective mood, and sleep parameters.
Methods: Eighteen healthy adult men aged 29±8.24 years participated in a 2-day sleep control session (SC; time in bed, 9 h) and 2-day sleep debt session (SD; time in bed, 3 h). On day 2 of each session, resting-state functional magnetic resonance imaging (fMRI) was performed, followed immediately by measuring subjective mood on the State-Trait Anxiety Inventory-State subscale (STAI-S).
Results: STAI-S score was significantly increased and functional connectivity between the amygdala and MPFC was significantly decreased in SD compared with SC. Significant correlations were observed between reduced rapid eye movement (REM) sleep and reduced left amygdala-MPFC functional connectivity (FCL_amg-MPFC) and between reduced FCL_amg-MPFC and increased STAI-S score in SD compared with SC.
Conclusions: These findings suggest that reduced MPFC functional connectivity of amygdala activity is involved in mood deterioration under sleep debt, and that REM sleep reduction is involved in functional changes in the corresponding brain regions. Having adequate REM sleep may be important for mental health maintenance.

PMID: 28977527 [PubMed - as supplied by publisher]

Resting-State Functional Connectivity-Based Biomarkers and Functional MRI-Based Neurofeedback for Psychiatric Disorders: A Challenge for Developing Theranostic Biomarkers.

Thu, 10/05/2017 - 13:20

Resting-State Functional Connectivity-Based Biomarkers and Functional MRI-Based Neurofeedback for Psychiatric Disorders: A Challenge for Developing Theranostic Biomarkers.

Int J Neuropsychopharmacol. 2017 Oct 01;20(10):769-781

Authors: Yamada T, Hashimoto RI, Yahata N, Ichikawa N, Yoshihara Y, Okamoto Y, Kato N, Takahashi H, Kawato M

Abstract
Psychiatric research has been hampered by an explanatory gap between psychiatric symptoms and their neural underpinnings, which has resulted in poor treatment outcomes. This situation has prompted us to shift from symptom-based diagnosis to data-driven diagnosis, aiming to redefine psychiatric disorders as disorders of neural circuitry. Promising candidates for data-driven diagnosis include resting-state functional connectivity MRI (rs-fcMRI)-based biomarkers. Although biomarkers have been developed with the aim of diagnosing patients and predicting the efficacy of therapy, the focus has shifted to the identification of biomarkers that represent therapeutic targets, which would allow for more personalized treatment approaches. This type of biomarker (i.e., "theranostic biomarker") is expected to elucidate the disease mechanism of psychiatric conditions and to offer an individualized neural circuit-based therapeutic target based on the neural cause of a condition. To this end, researchers have developed rs-fcMRI-based biomarkers and investigated a causal relationship between potential biomarkers and disease-specific behavior using functional MRI (fMRI)-based neurofeedback on functional connectivity. In this review, we introduce a recent approach for creating a theranostic biomarker, which consists mainly of 2 parts: (1) developing an rs-fcMRI-based biomarker that can predict diagnosis and/or symptoms with high accuracy, and (2) the introduction of a proof-of-concept study investigating the relationship between normalizing the biomarker and symptom changes using fMRI-based neurofeedback. In parallel with the introduction of recent studies, we review rs-fcMRI-based biomarker and fMRI-based neurofeedback, focusing on the technological improvements and limitations associated with clinical use.

PMID: 28977523 [PubMed - in process]

Cortical cores in network dynamics.

Thu, 10/05/2017 - 13:20

Cortical cores in network dynamics.

Neuroimage. 2017 Sep 30;:

Authors: de Pasquale F, Corbetta M, Betti V, Della Penna S

Abstract
Spontaneous brain activity at rest is spatially and temporally organized in networks of cortical and subcortical regions specialized for different functional domains. Even though brain networks were first studied individually through functional Magnetic Resonance Imaging, more recent studies focused on their dynamic 'integration'. Integration depends on two fundamental properties: the structural topology of brain networks and the dynamics of functional connectivity. In this scenario, cortical hub regions, that are central regions highly connected with other areas of the brain, play a fundamental role in serving as way stations for network traffic. In this review, we focus on the functional organization of a set of hub areas that we define as the 'dynamic core'. In the resting state, these regions dynamically interact with other regions of the brain linking multiple networks. First, we introduce and compare the statistical measures used for detecting hubs. Second, we discuss their identification based on different methods (functional Magnetic Resonance Imaging, Diffusion Weighted Imaging, Electro/Magneto Encephalography). Third, we show that the degree of interaction between these core regions and the rest of the brain varies over time, indicating that their centrality is not stationary. Moreover, alternating periods of strong and weak centrality of the core relate to periods of strong and weak global efficiency in the brain. These results indicate that information processing in the brain is not stable, but fluctuates and its temporal and spectral properties are discussed. In particular, the hypothesis of 'pulsed' information processing, discovered in the slow temporal scale, is explored for signals at higher temporal resolution.

PMID: 28974453 [PubMed - as supplied by publisher]

Brain functional connectivity patterns in children and adolescents with gender dysphoria: Sex-atypical or not?

Wed, 10/04/2017 - 12:00

Brain functional connectivity patterns in children and adolescents with gender dysphoria: Sex-atypical or not?

Psychoneuroendocrinology. 2017 Sep 18;86:187-195

Authors: Nota NM, Kreukels BPC, den Heijer M, Veltman DJ, Cohen-Kettenis PT, Burke SM, Bakker J

Abstract
Various previous studies have reported that brains of people diagnosed with gender dysphoria (GD) show sex-atypical features. In addition, recent functional magnetic resonance imaging studies found that several brain resting-state networks (RSNs) in adults with GD show functional connectivity (FC) patterns that are not sex-atypical, but specific for GD. In the current study we examined whether FC patterns are also altered in prepubertal children and adolescents with GD in comparison with non-gender dysphoric peers. We investigated FC patterns within RSNs that were previously examined in adults: visual networks (VNs), sensorimotor networks (SMNs), default mode network (DMN) and salience network. Thirty-one children (18 birth assigned males; 13 birth assigned females) and 40 adolescents with GD (19 birth assigned males or transgirls; 21 birth assigned females or transboys), and 39 cisgender children (21 boys; 18 girls) and 41 cisgender adolescents (20 boys; 21 girls) participated. We used independent component analysis to obtain the network maps of interest and compared these across groups. Within one of the three VNs (VN-I), adolescent transgirls showed stronger FC in the right cerebellum compared with all other adolescent groups. Sex differences in FC between the cisgender adolescent groups were observed in the right supplementary motor area within one of the two SMNs (SMN-II; girls>boys) and the right posterior cingulate gyrus within the posterior DMN (boys>girls). Within these networks adolescent transgirls showed FC patterns similar to their experienced gender (female). Also adolescent transboys showed a FC pattern similar to their experienced gender (male), but within the SMN-II only. The prepubertal children did not show any group differences in FC, suggesting that these emerge with aging and during puberty. Our findings provide evidence for the existence of both GD-specific and sex-atypical FC patterns in adolescents with GD.

PMID: 28972892 [PubMed - as supplied by publisher]

Combined PET/MRI: Global Warming-Summary Report of the 6th International Workshop on PET/MRI, March 27-29, 2017, Tübingen, Germany.

Wed, 10/04/2017 - 12:00

Combined PET/MRI: Global Warming-Summary Report of the 6th International Workshop on PET/MRI, March 27-29, 2017, Tübingen, Germany.

Mol Imaging Biol. 2017 Oct 02;:

Authors: Bailey DL, Pichler BJ, Gückel B, Antoch G, Barthel H, Bhujwalla ZM, Biskup S, Biswal S, Bitzer M, Boellaard R, Braren RF, Brendle C, Brindle K, Chiti A, la Fougère C, Gillies R, Goh V, Goyen M, Hacker M, Heukamp L, Knudsen GM, Krackhardt AM, Law I, Morris JC, Nikolaou K, Nuyts J, Ordonez AA, Pantel K, Quick HH, Riklund K, Sabri O, Sattler B, Troost EGC, Zaiss M, Zender L, Beyer T

Abstract
The 6th annual meeting to address key issues in positron emission tomography (PET)/magnetic resonance imaging (MRI) was held again in Tübingen, Germany, from March 27 to 29, 2017. Over three days of invited plenary lectures, round table discussions and dialogue board deliberations, participants critically assessed the current state of PET/MRI, both clinically and as a research tool, and attempted to chart future directions. The meeting addressed the use of PET/MRI and workflows in oncology, neurosciences, infection, inflammation and chronic pain syndromes, as well as deeper discussions about how best to characterise the tumour microenvironment, optimise the complementary information available from PET and MRI, and how advanced data mining and bioinformatics, as well as information from liquid biomarkers (circulating tumour cells and nucleic acids) and pathology, can be integrated to give a more complete characterisation of disease phenotype. Some issues that have dominated previous meetings, such as the accuracy of MR-based attenuation correction (AC) of the PET scan, were finally put to rest as having been adequately addressed for the majority of clinical situations. Likewise, the ability to standardise PET systems for use in multicentre trials was confirmed, thus removing a perceived barrier to larger clinical imaging trials. The meeting openly questioned whether PET/MRI should, in all cases, be used as a whole-body imaging modality or whether in many circumstances it would best be employed to give an in-depth study of previously identified disease in a single organ or region. The meeting concluded that there is still much work to be done in the integration of data from different fields and in developing a common language for all stakeholders involved. In addition, the participants advocated joint training and education for individuals who engage in routine PET/MRI. It was agreed that PET/MRI can enhance our understanding of normal and disrupted biology, and we are in a position to describe the in vivo nature of disease processes, metabolism, evolution of cancer and the monitoring of response to pharmacological interventions and therapies. As such, PET/MRI is a key to advancing medicine and patient care.

PMID: 28971346 [PubMed - as supplied by publisher]

Resting-state functional magnetic resonance imaging in clade C HIV: within-group association with neurocognitive function.

Wed, 10/04/2017 - 12:00

Resting-state functional magnetic resonance imaging in clade C HIV: within-group association with neurocognitive function.

J Neurovirol. 2017 Oct 02;:

Authors: du Plessis L, Paul RH, Hoare J, Stein DJ, Taylor PA, Meintjes EM, Joska JA

Abstract
Neuroimaging abnormalities are common in chronically infected HIV-positive individuals. The majority of studies have focused on structural or functional brain outcomes in samples infected with clade B HIV. While preliminary work reveals a similar structural imaging phenotype in patients infected with clade C HIV, no study has examined functional connectivity (FC) using resting-state functional magnetic resonance imaging (rs-fMRI) in clade C HIV. In particular, we were interested to explore HIV-only effects on neurocognitive function using associations with rs-fMRI. In the present study, 56 treatment-naïve, clade C HIV-infected participants (age 32.27 ± 5.53 years, education 10.02 ± 1.72 years, 46 female) underwent rs-fMRI and cognitive testing. Individual resting-state networks were correlated with global deficit scores (GDS) in order to explore associations between them within an HIV-positive sample. Results revealed ten regions in six resting-state networks where FC inversely correlated with GDS scores (worse performance). The networks affected included three independent attention networks: the default mode network (DMN), sensorimotor network, and basal ganglia. Connectivity in these regions did not correlate with plasma viral load or CD4 cell count. The design of this study is unique and has not been previously reported in clade B. The abnormalities related to neurocognitive performance reported in this study of clade C may reflect late disease stage and/or unique host/viral dynamics. Longitudinal studies will help to clarify the clinical significance of resting-state alterations in clade C HIV.

PMID: 28971331 [PubMed - as supplied by publisher]

Distinctive pretreatment features of bilateral nucleus accumbens networks predict early response to antidepressants in major depressive disorder.

Wed, 10/04/2017 - 12:00

Distinctive pretreatment features of bilateral nucleus accumbens networks predict early response to antidepressants in major depressive disorder.

Brain Imaging Behav. 2017 Oct 02;:

Authors: Hou Z, Gong L, Zhi M, Yin Y, Zhang Y, Xie C, Yuan Y

Abstract
The pretreatment neuroimaging markers from the resting-state brain network that could predict the early response to antidepressants are still unclear. The aim of the present study was to identify the performance of reward network features for discriminating patients with a dampened response to antidepressants. A total of 81 major depressive disorder (MDD) patients (44 patients with treatment-responsive depression (RD) and 37 patients with non-responding depression (NRD)) and 43 healthy controls (HC) underwent resting-state functional magnetic resonance imaging scans and clinical estimates. Bilateral nucleus accumbens (NAcc)-based networks were constructed for further functional connectivity (FC) analysis. The FC of the right superior frontal gyrus (SFG) (area under curve (AUC) = 0.837) and left parahippocampus (AUC = 0.770) within the left NAcc reward network, as well as the FC of the left SFG (AUC = 0.827) within the right NAcc reward network, could distinguish NRD subjects from RD subjects relatively well. Taken together, when considering the distinctive connectional pattern of the bilateral reward circuits, the synthetical differentiating effect was achieved to an optimal performance for discriminating NRD patients (AUC = 0.869), with balanced sensitivity (0.838) and specificity (0.818). The distinct pretreatment characteristics of the reward network make specific contributions to the early response to antidepressants and establish a promising imaging predictor for the classification of early efficacy.

PMID: 28971301 [PubMed - as supplied by publisher]

Presurgical thalamocortical connectivity is associated with response to vagus nerve stimulation in children with intractable epilepsy.

Wed, 10/04/2017 - 12:00

Presurgical thalamocortical connectivity is associated with response to vagus nerve stimulation in children with intractable epilepsy.

Neuroimage Clin. 2017;16:634-642

Authors: Ibrahim GM, Sharma P, Hyslop A, Guillen MR, Morgan BR, Wong S, Abel TJ, Elkaim L, Cajigas I, Shah AH, Fallah A, Weil AG, Altman N, Bernal B, Medina S, Widjaja E, Jayakar P, Ragheb J, Bhatia S

Abstract
Although chronic vagus nerve stimulation (VNS) is an established treatment for medically-intractable childhood epilepsy, there is considerable heterogeneity in seizure response and little data are available to pre-operatively identify patients who may benefit from treatment. Since the therapeutic effect of VNS may be mediated by afferent projections to the thalamus, we tested the hypothesis that intrinsic thalamocortical connectivity is associated with seizure response following chronic VNS in children with epilepsy. Twenty-one children (ages 5-21 years) with medically-intractable epilepsy underwent resting-state fMRI prior to implantation of VNS. Ten received sedation, while 11 did not. Whole brain connectivity to thalamic regions of interest was performed. Multivariate generalized linear models were used to correlate resting-state data with seizure outcomes, while adjusting for age and sedation status. A supervised support vector machine (SVM) algorithm was used to classify response to chronic VNS on the basis of intrinsic connectivity. Of the 21 subjects, 11 (52%) had 50% or greater improvement in seizure control after VNS. Enhanced connectivity of the thalami to the anterior cingulate cortex (ACC) and left insula was associated with greater VNS efficacy. Within our test cohort, SVM correctly classified response to chronic VNS with 86% accuracy. In an external cohort of 8 children, the predictive model correctly classified the seizure response with 88% accuracy. We find that enhanced intrinsic connectivity within thalamocortical circuitry is associated with seizure response following VNS. These results encourage the study of intrinsic connectivity to inform neural network-based, personalized treatment decisions for children with intractable epilepsy.

PMID: 28971013 [PubMed - in process]

Structurofunctional resting-state networks correlate with motor function in chronic stroke.

Wed, 10/04/2017 - 12:00

Structurofunctional resting-state networks correlate with motor function in chronic stroke.

Neuroimage Clin. 2017;16:610-623

Authors: Kalinosky BT, Berrios Barillas R, Schmit BD

Abstract
PURPOSE: Motor function and recovery after stroke likely rely directly on the residual anatomical connections in the brain and its resting-state functional connectivity. Both structural and functional properties of cortical networks after stroke are revealed using multimodal magnetic resonance imaging (MRI). Specifically, functional connectivity MRI (fcMRI) can extract functional networks of the brain at rest, while structural connectivity can be estimated from white matter fiber orientations measured with high angular-resolution diffusion imaging (HARDI). A model that marries these two techniques may be the key to understanding functional recovery after stroke. In this study, a novel set of voxel-level measures of structurofunctional correlations (SFC) was developed and tested in a group of chronic stroke subjects.
METHODS: A fully automated method is presented for modeling the structure-function relationship of brain connectivity in individuals with stroke. Brains from ten chronic stroke subjects and nine age-matched controls were imaged with a structural T1-weighted scan, resting-state fMRI, and HARDI. Each subject's T1-weighted image was nonlinearly registered to a T1-weighted 152-brain MNI template using a local histogram-matching technique that alleviates distortions caused by brain lesions. Fractional anisotropy maps and mean BOLD images of each subject were separately registered to the individual's T1-weighted image using affine transformations. White matter fiber orientations within each voxel were estimated with the q-ball model, which approximates the orientation distribution function (ODF) from the diffusion-weighted measurements. Deterministic q-ball tractography was performed in order to obtain a set of fiber trajectories. The new structurofunctional correlation method assigns each voxel a new BOLD time course based on a summation of its structural connections with a common fiber length interval. Then, the voxel's original time-course was correlated with this fiber-distance BOLD signal to derive a novel structurofunctional correlation coefficient. These steps were repeated for eight fiber distance intervals, and the maximum of these correlations was used to define an intrinsic structurofunctional correlation (iSFC) index. A network-based SFC map (nSFC) was also developed in order to enhance resting-state functional networks derived from conventional functional connectivity analyses. iSFC and nSFC maps were individually compared between stroke subjects and controls using a voxel-based two-tailed Student's t-test (alpha = 0.01). A linear regression was also performed between the SFC metrics and the Box and Blocks Score, a clinical measure of arm motor function.
RESULTS: Significant decreases (p < 0.01) in iSFC were found in stroke subjects within functional hubs of the brain, including the precuneus, prefrontal cortex, posterior parietal cortex, and cingulate gyrus. Many of these differences were significantly correlated with the Box and Blocks Score. The nSFC maps of prefrontal networks in control subjects revealed localized increases within the cerebellum, and these enhancements were diminished in stroke subjects. This finding was further supported by a reduction in functional connectivity between the prefrontal cortex and cerebellum. Default-mode network nSFC maps were higher in the contralesional hemisphere of lower-functioning stroke subjects.
CONCLUSION: The results demonstrate that changes after a stroke in both intrinsic and network-based structurofunctional correlations at rest are correlated with motor function, underscoring the importance of residual structural connectivity in cortical networks.

PMID: 28971011 [PubMed - in process]

Distinct alterations in Parkinson's medication-state and disease-state connectivity.

Wed, 10/04/2017 - 12:00

Distinct alterations in Parkinson's medication-state and disease-state connectivity.

Neuroimage Clin. 2017;16:575-585

Authors: Ng B, Varoquaux G, Poline JB, Thirion B, Greicius MD, Poston KL

Abstract
Altered brain connectivity has been described in people with Parkinson's disease and in response to dopaminergic medications. However, it is unclear whether dopaminergic medications primarily 'normalize' disease related connectivity changes or if they induce unique alterations in brain connectivity. Further, it is unclear how these disease- and medication-associated changes in brain connectivity relate differently to specific motor manifestations of disease, such as bradykinesia/rigidity and tremor. In this study, we applied a novel covariance projection approach in combination with a bootstrapped permutation test to resting state functional MRI data from 57 Parkinson's disease and 20 healthy control participants to determine the Parkinson's medication-state and disease-state connectivity changes associated with different motor manifestations of disease. First, we identified brain connections that best classified Parkinson's disease ON versus OFF dopamine and Parkinson's disease versus healthy controls, achieving 96.9 ± 5.9% and 72.7 ± 12.4% classification accuracy, respectively. Second, we investigated the connections that significantly contribute to the classifications. We found that the connections greater in Parkinson's disease OFF compared to ON dopamine are primarily between motor (cerebellum and putamen) and posterior cortical regions, such as the posterior cingulate cortex. By contrast, connections that are greater in ON compared to OFF dopamine are between the right and left medial prefrontal cortex. We also identified the connections that are greater in healthy control compared to Parkinson's disease and found the most significant connections are associated with primary motor regions, such as the striatum and the supplementary motor area. Notably, these are different connections than those identified in Parkinson's disease OFF compared to ON. Third, we determined which of the Parkinson's medication-state and disease-state connections are associated with the severity of different motor symptoms. We found two connections correlate with both bradykinesia/rigidity severity and tremor severity, whereas four connections correlate with only bradykinesia/rigidity severity, and five connections correlate with only tremor severity. Connections that correlate with only tremor severity are anchored by the cerebellum and the supplemental motor area, but only those connections that include the supplemental motor area predict dopaminergic improvement in tremor. Our results suggest that dopaminergic medications do not simply 'normalize' abnormal brain connectivity associated with Parkinson's disease, but rather dopamine drives distinct connectivity changes, only some of which are associated with improved motor symptoms. In addition, the dissociation between of connections related to severity of bradykinesia/rigidity versus tremor highlights the distinct abnormalities in brain circuitry underlying these specific motor symptoms.

PMID: 28971008 [PubMed - in process]

Altered Functional Connectivity Density in Subtypes of Parkinson's Disease.

Wed, 10/04/2017 - 12:00

Altered Functional Connectivity Density in Subtypes of Parkinson's Disease.

Front Hum Neurosci. 2017;11:458

Authors: Hu X, Jiang Y, Jiang X, Zhang J, Liang M, Li J, Zhang Y, Yao D, Luo C, Wang J

Abstract
Parkinson's disease (PD) can be classified into tremor-dominant and akinetic-rigid subtypes, each of which exhibits a unique clinical course and prognosis. The neural basis for these disparate manifestations is not well-understood, however. This study comprehensively investigated the altered functional connectivity patterns of these two subtypes. Twenty-five tremor-dominant patients, 25 akinetic-rigid patients and 26 normal control subjects participated in this study. Resting-state functional MRI data were analyzed using functional connectivity density (FCD) and seed-based functional connectivity approaches. Correlations between neuroimaging measures and clinical variables were also calculated. Compared with normal control, increased global FCD occurred most extensively in frontal lobe and cerebellum in both subtypes. Compared with akinetic-rigid patients, the tremor-dominant patients showed significantly increased global FCD in the cerebellum and decreased global FCD in portions of the bilateral frontal lobe. Furthermore, different subtypes demonstrated different cerebello-cortical functional connectivity patterns. Moreover, the identified FCD and functional connectivity correlated significantly with clinical variables in the PD patients, and particularly the FCD indices distinguished the different subtypes with high sensitivity (95%) and specificity (80%). These findings indicate that the functional connectivity patterns in the cerebellum and frontal lobe are altered in both subtypes of PD, especially cerebellum are highly related to tremor.

PMID: 28970788 [PubMed]

Serotonin-1A receptor C-1019G polymorphism affects brain functional networks.

Wed, 10/04/2017 - 12:00

Serotonin-1A receptor C-1019G polymorphism affects brain functional networks.

Sci Rep. 2017 Oct 02;7(1):12536

Authors: Zheng H, Onoda K, Wada Y, Mitaki S, Nabika T, Yamaguchi S

Abstract
The serotonin-1A (5-HT1A) receptor is strongly implicated in major depression and other affective disorders due to its negative regulation of serotonin neurone firing rates. Behavioural and clinical studies have repeatedly reported that the -1019G allele carries a high susceptibility for affective disorders. However, the underlying pathophysiology remains unknown. Here, we employed a genetic neuroimaging strategy in 99 healthy human subjects to explore the effect of serotonin-1A receptor polymorphism on brain resting-state functional connectivity (FC). We used functional magnetic resonance imaging, along with a seed-based approach, to identify three main brain networks: the default mode network (DMN), the salience network (SN) and the central executive network. We observed a significant decrease in the FC of the DMN within the dorsolateral and ventromedial prefrontal cortices in G-carriers. Furthermore, compared with the C-homozygote group, we observed decreased FC of the SN within the ventromedial prefrontal cortex and subgenual anterior cingulate cortex in the G-carrier group. Our results indicate that 5-HT1A receptor genetic polymorphism modulates the activity of resting-state FC within brain networks including the DMN and SN. These genotype-related alterations in brain networks and FC may provide novel insights into the neural mechanism underlying the predisposition for affective disorders in G allele carriers.

PMID: 28970569 [PubMed - in process]

Dynamic functional connectivity states between the dorsal and ventral sensorimotor networks revealed by Dynamic Conditional Correlation analysis of resting state functional MRI.

Wed, 10/04/2017 - 12:00

Dynamic functional connectivity states between the dorsal and ventral sensorimotor networks revealed by Dynamic Conditional Correlation analysis of resting state functional MRI.

Brain Connect. 2017 Oct 02;:

Authors: Syed MF, Lindquist M, Pillai JJ, Agarwal S, Gujar SK, Choe AS, Caffo BS, Sair HI

Abstract
Functional connectivity in resting state functional Magnetic Resonance Imaging (rs-fMRI) has received substantial attention since the initial findings of Biswal et al. Traditional network correlation metrics assume that the functional connectivity in the brain remains stationary over time. However, recent studies have shown that robust temporal fluctuations of functional connectivity among as well as within functional networks exist, challenging this assumption. In this study, these dynamic correlation differences were investigated between the dorsal and ventral sensorimotor networks by applying the Dynamic Conditional Correlation (DCC) model to rs-fMRI data of 20 healthy subjects. K-means clustering was used to determine an optimal number of discrete connectivity states (k=10) of the sensorimotor system across all subjects. Our analysis confirms the existence of differences in dynamic correlation between the dorsal and ventral networks, with highest connectivity found within the ventral motor network.

PMID: 28969437 [PubMed - as supplied by publisher]

Reduced functional connectivity between ventromedial prefrontal cortex and insula relates to longer corrected QT interval in HIV+ and HIV- individuals.

Wed, 10/04/2017 - 12:00
Related Articles

Reduced functional connectivity between ventromedial prefrontal cortex and insula relates to longer corrected QT interval in HIV+ and HIV- individuals.

Clin Neurophysiol. 2017 Oct;128(10):1839-1850

Authors: McIntosh RC, Chow DC, Lum CJ, Hidalgo M, Shikuma CM, Kallianpur KJ

Abstract
OBJECTIVE: Prolongation of the QT interval, i.e., measure of the time between the start of the Q wave and the end of the T wave, is a precursor to fatal cardiac arrhythmias commonly observed in individuals infected with the Human Immunodeficiency Virus (HIV), and is related to dysregulation of the autonomic nervous system. We investigated the relationship between QT interval length and resting state functional connectivity (rsFC) of the ventromedial prefrontal cortex (VMPFC), a core region of the brain that is involved with cardio-autonomic regulation.
METHOD: Eighteen HIV+ men on antiretroviral therapy and with no history of heart disease were compared with 26 HIV-negative control subjects who had similar demographic and cardio-metabolic characteristics. A seed-based rsFC analysis of the right and left VMPFC was performed at the individual subject level, and 2nd-level analyses were conducted to identify the following: group differences in connectivity, brain regions correlating with corrected (QTc) interval length before and after controlling for those group differences, and regions where seed-based rsFC correlates with CD4 count and QTc interval within HIV+ individuals.
RESULTS: HIV-negative adults showed greater rsFC between the VMPFC seed regions and several default mode network structures. Across groups greater rsFC with the left anterior insula was associated with shorter QTc intervals, whereas right posterior insula connectivity with the VMPFC correlated with greater QTc intervals. HIV patients with lower CD4 counts and higher QTc intervals showed greater rsFC between the right VMPFC and the right posterior insula and dorsal cingulate gyrus.
CONCLUSIONS: This study demonstrates that QTc interval lengths are associated with distinct patterns of VMPFC rsFC with posterior and anterior insula. In HIV patients, longer QTc interval and lower CD4 count corresponded to weaker VMPFC connectivity with the dorsal striatrum.
SIGNIFICANCE: A forebrain control mechanism may be implicated in the suppression of cardiovagal influence that confers risk for ventricular arrhythmias and sudden cardiac death in HIV+ individuals.

PMID: 28826014 [PubMed - indexed for MEDLINE]

Frontotemporal correlates of impulsivity and machine learning in retired professional athletes with a history of multiple concussions.

Wed, 10/04/2017 - 12:00
Related Articles

Frontotemporal correlates of impulsivity and machine learning in retired professional athletes with a history of multiple concussions.

Brain Struct Funct. 2016 May;221(4):1911-25

Authors: Goswami R, Dufort P, Tartaglia MC, Green RE, Crawley A, Tator CH, Wennberg R, Mikulis DJ, Keightley M, Davis KD

Abstract
The frontotemporal cortical network is associated with behaviours such as impulsivity and aggression. The health of the uncinate fasciculus (UF) that connects the orbitofrontal cortex (OFC) with the anterior temporal lobe (ATL) may be a crucial determinant of behavioural regulation. Behavioural changes can emerge after repeated concussion and thus we used MRI to examine the UF and connected gray matter as it relates to impulsivity and aggression in retired professional football players who had sustained multiple concussions. Behaviourally, athletes had faster reaction times and an increased error rate on a go/no-go task, and increased aggression and mania compared to controls. MRI revealed that the athletes had (1) cortical thinning of the ATL, (2) negative correlations of OFC thickness with aggression and task errors, indicative of impulsivity, (3) negative correlations of UF axial diffusivity with error rates and aggression, and (4) elevated resting-state functional connectivity between the ATL and OFC. Using machine learning, we found that UF diffusion imaging differentiates athletes from healthy controls with significant classifiers based on UF mean and radial diffusivity showing 79-84 % sensitivity and specificity, and 0.8 areas under the ROC curves. The spatial pattern of classifier weights revealed hot spots at the orbitofrontal and temporal ends of the UF. These data implicate the UF system in the pathological outcomes of repeated concussion as they relate to impulsive behaviour. Furthermore, a support vector machine has potential utility in the general assessment and diagnosis of brain abnormalities following concussion.

PMID: 25721800 [PubMed - indexed for MEDLINE]

Multidimensional Neuroanatomical Subtyping of Autism Spectrum Disorder.

Tue, 10/03/2017 - 11:00

Multidimensional Neuroanatomical Subtyping of Autism Spectrum Disorder.

Cereb Cortex. 2017 Sep 14;:1-11

Authors: Hong SJ, Valk SL, Di Martino A, Milham MP, Bernhardt BC

Abstract
Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders with multiple biological etiologies and highly variable symptoms. Using a novel analytical framework that integrates cortex-wide MRI markers of vertical (i.e., thickness, tissue contrast) and horizontal (i.e., surface area, geodesic distance) cortical organization, we could show that a large multi-centric cohort of individuals with ASD falls into 3 distinctive anatomical subtypes (ASD-I: cortical thickening, increased surface area, tissue blurring; ASD-II: cortical thinning, decreased distance; ASD-III: increased distance). Bootstrap analysis indicated a high consistency of these biotypes across thousands of simulations, while analysis of behavioral phenotypes and resting-state fMRI showed differential symptom load (i.e., Autism Diagnostic Observation Schedule; ADOS) and instrinsic connectivity anomalies in communication and social-cognition networks. Notably, subtyping improved supervised learning approaches predicting ADOS score in single subjects, with significantly increased performance compared to a subtype-blind approach. The existence of different subtypes may reconcile previous results so far not converging on a consistent pattern of anatomical anomalies in autism, and possibly relate the presence of diverging corticogenic and maturational anomalies. The high accuracy for symptom severity prediction indicates benefits of MRI biotyping for personalized diagnostics and may guide the development of targeted therapeutic strategies.

PMID: 28968847 [PubMed - as supplied by publisher]

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