New resting-state fMRI related studies at PubMed

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Neuronal Correlates of Individual Differences in the Big Five Personality Traits: Evidences from Cortical Morphology and Functional Homogeneity.

Sat, 08/05/2017 - 15:00
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Neuronal Correlates of Individual Differences in the Big Five Personality Traits: Evidences from Cortical Morphology and Functional Homogeneity.

Front Neurosci. 2017;11:414

Authors: Li T, Yan X, Li Y, Wang J, Li Q, Li H, Li J

Abstract
There have been many neuroimaging studies of human personality traits, and it have already provided glimpse into the neurobiology of complex traits. And most of previous studies adopt voxel-based morphology (VBM) analysis to explore the brain-personality mechanism from two levels (vertex and regional based), the findings are mixed with great inconsistencies and the brain-personality relations are far from a full understanding. Here, we used a new method of surface-based morphology (SBM) analysis, which provides better alignment of cortical landmarks to generate about the associations between cortical morphology and the personality traits across 120 healthy individuals at both vertex and regional levels. While to further reveal local functional correlates of the morphology-personality relationships, we related surface-based functional homogeneity measures to the regions identified in the regional-based SBM correlation. Vertex-wise analysis revealed that people with high agreeableness exhibited larger areas in the left superior temporal gyrus. Based on regional parcellation we found that extroversion was negatively related with the volume of the left lateral occipito-temporal gyrus and agreeableness was negatively associated with the sulcus depth of the left superior parietal lobule. Moreover, increased regional homogeneity in the left lateral occipito-temporal gyrus is related to the scores of extroversion, and increased regional homogeneity in the left superior parietal lobule is related to the scores of agreeableness. These findings provide supporting evidence of a link between personality and brain structural mysteries with a method of SBM, and further suggest that local functional homogeneity of personality traits has neurobiological relevance that is likely based on anatomical substrates.

PMID: 28769751 [PubMed]

Commentary: BRAIN NETWORKS. Correlated Gene Expression Supports Synchronous Activity in Brain Networks. Science 348, 1241-4.

Sat, 08/05/2017 - 15:00
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Commentary: BRAIN NETWORKS. Correlated Gene Expression Supports Synchronous Activity in Brain Networks. Science 348, 1241-4.

Front Neurosci. 2017;11:412

Authors: Pantazatos SP, Li X

Abstract
A recent report claims that functional brain networks defined with resting-state functional magnetic resonance imaging (fMRI) can be recapitulated with correlated gene expression (i.e., high within-network tissue-tissue "strength fraction," SF) (Richiardi et al., 2015). However, the authors do not adequately control for spatial proximity. We replicated their main analysis, performed a more effective adjustment for spatial proximity, and tested whether "null networks" (i.e., clusters with center coordinates randomly placed throughout cortex) also exhibit high SF. Removing proximal tissue-tissue correlations by Euclidean distance, as opposed to removing correlations within arbitrary tissue labels as in Richiardi et al. (2015), reduces within-network SF to no greater than null. Moreover, randomly placed clusters also have significantly high SF, indicating that high within-network SF is entirely attributable to proximity and is unrelated to functional brain networks defined by resting-state fMRI. We discuss why additional validations in the original article are invalid and/or misleading and suggest future directions.

PMID: 28769750 [PubMed]

Mechanism of Cerebralcare Granule® for Improving Cognitive Function in Resting-State Brain Functional Networks of Sub-healthy Subjects.

Sat, 08/05/2017 - 15:00
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Mechanism of Cerebralcare Granule® for Improving Cognitive Function in Resting-State Brain Functional Networks of Sub-healthy Subjects.

Front Neurosci. 2017;11:410

Authors: Li J, Guo H, Ge L, Cheng L, Wang J, Li H, Zhang K, Xiang J, Chen J, Zhang H, Xu Y

Abstract
Cerebralcare Granule® (CG), a Chinese herbal medicine, has been used to ameliorate cognitive impairment induced by ischemia or mental disorders. The ability of CG to improve health status and cognitive function has drawn researchers' attention, but the relevant brain circuits that underlie the ameliorative effects of CG remain unclear. The present study aimed to explore the underlying neurobiological mechanisms of CG in ameliorating cognitive function in sub-healthy subjects using resting-state functional magnetic resonance imaging (fMRI). Thirty sub-healthy participants were instructed to take one 2.5-g package of CG three times a day for 3 months. Clinical cognitive functions were assessed with the Chinese Revised Wechsler Adult Intelligence Scale (WAIS-RC) and Wechsler Memory Scale (WMS), and fMRI scans were performed at baseline and the end of intervention. Functional brain network data were analyzed by conventional network metrics (CNM) and frequent subgraph mining (FSM). Then 21 other sub-healthy participants were enrolled as a blank control group of cognitive functional. We found that administrating CG can improve the full scale of intelligence quotient (FIQ) and Memory Quotient (MQ) scores. At the same time, following CG treatment, in CG group, the topological properties of functional brain networks were altered in various frontal, temporal, occipital cortex regions, and several subcortical brain regions, including essential components of the executive attention network, the salience network, and the sensory-motor network. The nodes involved in the FSM results were largely consistent with the CNM findings, and the changes in nodal metrics correlated with improved cognitive function. These findings indicate that CG can improve sub-healthy subjects' cognitive function through altering brain functional networks. These results provide a foundation for future studies of the potential physiological mechanism of CG.

PMID: 28769748 [PubMed]

Brain imaging in myotonic dystrophy type 1: A systematic review.

Sat, 08/05/2017 - 15:00
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Brain imaging in myotonic dystrophy type 1: A systematic review.

Neurology. 2017 Aug 02;:

Authors: Okkersen K, Monckton DG, Le N, Tuladhar AM, Raaphorst J, van Engelen BGM

Abstract
OBJECTIVE: To systematically review brain imaging studies in myotonic dystrophy type 1 (DM1).
METHODS: We searched Embase (index period 1974-2016) and MEDLINE (index period 1946-2016) for studies in patients with DM1 using MRI, magnetic resonance spectroscopy (MRS), functional MRI (fMRI), CT, ultrasound, PET, or SPECT. From 81 studies, we extracted clinical characteristics, primary outcomes, clinical-genetic correlations, and information on potential risk of bias. Results were summarized and pooled prevalence of imaging abnormalities was calculated, where possible.
RESULTS: In DM1, various imaging changes are widely dispersed throughout the brain, with apparently little anatomical specificity. We found general atrophy and widespread gray matter volume reductions in all 4 cortical lobes, the basal ganglia, and cerebellum. The pooled prevalence of white matter hyperintensities is 70% (95% CI 64-77), compared with 6% (95% CI 3-12) in unaffected controls. DTI shows increased mean diffusivity in all 4 lobes and reduced fractional anisotropy in virtually all major association, projection, and commissural white matter tracts. Functional studies demonstrate reduced glucose uptake and cerebral perfusion in frontal, parietal, and temporal lobes, and abnormal fMRI connectivity patterns that correlate with personality traits. There is significant between-study heterogeneity in terms of imaging methods, which together with the established clinical variability of DM1 may explain divergent results. Longitudinal studies are remarkably scarce.
CONCLUSIONS: DM1 brains show widespread white and gray matter involvement throughout the brain, which is supported by abnormal resting-state network, PET/SPECT, and MRS parameters. Longitudinal studies evaluating spatiotemporal imaging changes are essential.

PMID: 28768849 [PubMed - as supplied by publisher]

Resting-state fMRI and social cognition: An opportunity to connect.

Thu, 08/03/2017 - 13:00
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Resting-state fMRI and social cognition: An opportunity to connect.

Hum Psychopharmacol. 2017 Aug 01;:

Authors: Doruyter A, Groenewold NA, Dupont P, Stein DJ, Warwick JM

Abstract
Many psychiatric disorders are characterized by altered social cognition. The importance of social cognition has previously been recognized by the National Institute of Mental Health Research Domain Criteria project, in which it features as a core domain. Social task-based functional magnetic resonance imaging (fMRI) currently offers the most direct insight into how the brain processes social information; however, resting-state fMRI may be just as important in understanding the biology and network nature of social processing. Resting-state fMRI allows researchers to investigate the functional relationships between brain regions in a neutral state: so-called resting functional connectivity (RFC). There is evidence that RFC is predictive of how the brain processes information during social tasks. This is important because it shifts the focus from possibly context-dependent aberrations to context-independent aberrations in functional network architecture. Rather than being analysed in isolation, the study of resting-state brain networks shows promise in linking results of task-based fMRI results, structural connectivity, molecular imaging findings, and performance measures of social cognition-which may prove crucial in furthering our understanding of the social brain.

PMID: 28766324 [PubMed - as supplied by publisher]

[Study of fraction amplitude of low frequency fluctuation on resting-state functional magnetic resonance imaging in adultperipheral facial paralysis].

Thu, 08/03/2017 - 13:00
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[Study of fraction amplitude of low frequency fluctuation on resting-state functional magnetic resonance imaging in adultperipheral facial paralysis].

Zhonghua Yi Xue Za Zhi. 2017 Jul 18;97(27):2081-2086

Authors: Zhu YJ, Ma GL, Song TB, Du L, Guo RC, Sun SL, Li H, Sun LG

Abstract
Objective: To analysis the change of brain functional activity in the left and right peripheral facial paralysis by using resting-state functional magnetic resonance imaging (R-fMRI) of fraction amplitude of low frequency fluctuation(fALFF) measurement technique, and research the abnormal brain region with different side patients whether there are differences. Methods: A total of 43 patients with peripheral facial paralysis patients (patient groups, divided into left / right two subgroups) and 21 healthy volunteers (control group) in this study.Resting-state fMRI were acquired for each volunteer and patient. The fALFF approach was used to compare the peripheral facial paralysis groups to healthy group.Functional analysis was performed with brain function analysis software REST and DPARSFA , and then analysis the difference of two groups of patients and control group in two sample t test.At the same time, the correlation analysis between fALFF parameters map of the left and right side of two groups of patients and corresponding facial nerve grading TFGS score.Ultimately obtain a statistically significant brain regions. Results: Compared to healthy group, the decreased fALFF areas in the left side facial paralysis were showed in the right superior temporal gyrus , the pole of the right temporal, right middle temporal gyrus, the left occipital gyrus, and left medial cingulate gyrus, left paracentral lobule, and the left supplementary motor area; while the increased brain regions have the right superior frontal gyrus, right middle frontal gyrus, the right precentral gyrus, bilateral inferior temporal gyrus and middle temporal gyrus.Compared to healthy group, the decreased fALFF areas in the right side facial paralysis were showed in the right inferior temporal gyrus and fusiform gyrus, the left inferior occipital gyrus, the left superior parietalgyrus, the left inferior parietalgyrus, left precuneus, left paracentral lobule, the left supplementary motor area; while the increased brain regions have the left Calcarine, right lingual gyrus, corpus callosum, right medial cingulum gyrus.In the left facial paralysis group TFGS score was positively correlated with brain regions have left middle frontal gyrus, left precuneus and left cuneus, while the negatively related brain area on the right lingual gyrus.In the right facial paralysis groups TFGS score was positively correlated with brain areas have right inferior temporal gyrus and middle temporal gyrus, left inferior parietalgyrus; while the negatively correlated brain area on the left superior temporal gyrus, the right medial frontal gyrus. Conclusion: The left and right side facial paralysis patient's mood and motor function integration mechanism may be different, and the patient's emotional and psychological changes may be associated with disease severity.

PMID: 28763879 [PubMed - in process]

BRAPH: A graph theory software for the analysis of brain connectivity.

Wed, 08/02/2017 - 12:00
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BRAPH: A graph theory software for the analysis of brain connectivity.

PLoS One. 2017;12(8):e0178798

Authors: Mijalkov M, Kakaei E, Pereira JB, Westman E, Volpe G, Alzheimer's Disease Neuroimaging Initiative

Abstract
The brain is a large-scale complex network whose workings rely on the interaction between its various regions. In the past few years, the organization of the human brain network has been studied extensively using concepts from graph theory, where the brain is represented as a set of nodes connected by edges. This representation of the brain as a connectome can be used to assess important measures that reflect its topological architecture. We have developed a freeware MatLab-based software (BRAPH-BRain Analysis using graPH theory) for connectivity analysis of brain networks derived from structural magnetic resonance imaging (MRI), functional MRI (fMRI), positron emission tomography (PET) and electroencephalogram (EEG) data. BRAPH allows building connectivity matrices, calculating global and local network measures, performing non-parametric permutations for group comparisons, assessing the modules in the network, and comparing the results to random networks. By contrast to other toolboxes, it allows performing longitudinal comparisons of the same patients across different points in time. Furthermore, even though a user-friendly interface is provided, the architecture of the program is modular (object-oriented) so that it can be easily expanded and customized. To demonstrate the abilities of BRAPH, we performed structural and functional graph theory analyses in two separate studies. In the first study, using MRI data, we assessed the differences in global and nodal network topology in healthy controls, patients with amnestic mild cognitive impairment, and patients with Alzheimer's disease. In the second study, using resting-state fMRI data, we compared healthy controls and Parkinson's patients with mild cognitive impairment.

PMID: 28763447 [PubMed - in process]

Intranasal Oxytocin Selectively Modulates Large-Scale Brain Networks in Humans.

Wed, 08/02/2017 - 12:00
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Intranasal Oxytocin Selectively Modulates Large-Scale Brain Networks in Humans.

Brain Connect. 2017 Aug 01;:

Authors: Brodmann K, Gruber O, Goya-Maldonado R

Abstract
A growing body of evidence indicates that the neuropeptide oxytocin (OT) alters the neural correlates of socio-emotional and salience processing. Yet the effects of OT over important large-scale networks involved in these processes, such as the default mode (DM), ventral attention (VA) and cingulo-opercular (CO) networks, remain unknown. Therefore, we conducted a placebo-controlled crossover study with intranasal 24IU OT in 38 healthy male subjects using a resting-state fMRI (rs-fMRI) paradigm to investigate its impact over these three candidate networks. To understand the underlying mechanisms of the neuropeptide, we compared the intra-network connectivity for each network candidate and also the inter-network connectivity across all networks between both treatment conditions. Based on the relevance of inter-individual factors for OT effects, we correlated individual network changes with behavioral performance in a decision-making task and with impulsivity scores. Our results show that OT mainly alters connectivity in the VA, on one side reducing the coupling to regions that typically form the nodes of the DM, an introspective and self-referential network, and on the other side increasing the coupling to the edges of the CO, which is involved in salience processing. The results of the inter-network analyses confirmed the specificity of the OT effects. Indeed, we observed significant correlations with erroneous performance during decision-making but not with the obtained impulsivity scores. Overall, our data supports that the modulation of functional connectivity within the VA is a basic mechanism by which OT directs attentional resources from internal to external cues, preparing the brain for context-dependent salience processing.

PMID: 28762756 [PubMed - as supplied by publisher]

Low-frequency hippocampal-cortical activity drives brain-wide resting-state functional MRI connectivity.

Wed, 08/02/2017 - 12:00
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Low-frequency hippocampal-cortical activity drives brain-wide resting-state functional MRI connectivity.

Proc Natl Acad Sci U S A. 2017 Jul 31;:

Authors: Chan RW, Leong ATL, Ho LC, Gao PP, Wong EC, Dong CM, Wang X, He J, Chan YS, Lim LW, Wu EX

Abstract
The hippocampus, including the dorsal dentate gyrus (dDG), and cortex engage in bidirectional communication. We propose that low-frequency activity in hippocampal-cortical pathways contributes to brain-wide resting-state connectivity to integrate sensory information. Using optogenetic stimulation and brain-wide fMRI and resting-state fMRI (rsfMRI), we determined the large-scale effects of spatiotemporal-specific downstream propagation of hippocampal activity. Low-frequency (1 Hz), but not high-frequency (40 Hz), stimulation of dDG excitatory neurons evoked robust cortical and subcortical brain-wide fMRI responses. More importantly, it enhanced interhemispheric rsfMRI connectivity in various cortices and hippocampus. Subsequent local field potential recordings revealed an increase in slow oscillations in dorsal hippocampus and visual cortex, interhemispheric visual cortical connectivity, and hippocampal-cortical connectivity. Meanwhile, pharmacological inactivation of dDG neurons decreased interhemispheric rsfMRI connectivity. Functionally, visually evoked fMRI responses in visual regions also increased during and after low-frequency dDG stimulation. Together, our results indicate that low-frequency activity robustly propagates in the dorsal hippocampal-cortical pathway, drives interhemispheric cortical rsfMRI connectivity, and mediates visual processing.

PMID: 28760982 [PubMed - as supplied by publisher]

Reconfiguration of brain network architectures between resting state and complexity-dependent cognitive reasoning.

Wed, 08/02/2017 - 12:00
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Reconfiguration of brain network architectures between resting state and complexity-dependent cognitive reasoning.

J Neurosci. 2017 Jul 31;:

Authors: Hearne LJ, Cocchi L, Zalesky A, Mattingley JB

Abstract
Our capacity for higher cognitive reasoning has a measureable limit. This limit is thought to arise from the brain's capacity to flexibly reconfigure interactions between spatially distributed networks. Recent work, however, has suggested that reconfigurations of task-related networks are modest when compared with intrinsic 'resting state' network architecture. Here we combined resting state and task-driven functional magnetic resonance imaging to examine how flexible, task-specific reconfigurations associated with increasing reasoning demands are integrated within a stable intrinsic brain topology. Human participants (21 males and 28 females) underwent an initial resting state scan, followed by a cognitive reasoning task involving different levels of complexity, followed by a second resting state scan. The reasoning task required participants to deduce the identity of a missing element in a 4 x 4 matrix, and item difficulty was scaled parametrically as determined by relational complexity theory. Analyses revealed that external task engagement was characterized by a significant change in functional brain modules. Specifically, resting state and null-task demand conditions were associated with more segregated brain network topology, whereas increases in reasoning complexity resulted in merging of resting state modules. Further increments in task complexity did not change the established modular architecture, but impacted selective patterns of connectivity between fronto-parietal, subcortical, cingulo-opercular and default-mode networks. Larger increases in network efficiency within the newly established task modules were associated with higher reasoning accuracy. Our results shed light on the network architectures that underlie external task engagement, and highlight selective changes in brain connectivity supporting increases in task complexity.SIGNIFICANCE STATEMENTHumans have clear limits in their ability to solve complex reasoning problems. It is thought that such limitations arise from flexible, moment-to-moment reconfigurations of functional brain networks. It is less clear how such task-driven adaptive changes in connectivity relate to stable, intrinsic networks of the brain and behavioral performance. We found that increased reasoning demands rely on selective patterns of connectivity within cortical networks that emerged in addition to a more general, task-induced modular architecture. This task-driven architecture reverted to a more segregated resting state architecture both immediately before and after the task. These findings reveal how flexibility in human brain networks is integral to achieving successful reasoning performance across different levels of cognitive demand.

PMID: 28760864 [PubMed - as supplied by publisher]

Elucidating Functional Differences between Cortical Gyri and Sulci via Sparse Representation HCP Grayordinate fMRI Data.

Wed, 08/02/2017 - 12:00
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Elucidating Functional Differences between Cortical Gyri and Sulci via Sparse Representation HCP Grayordinate fMRI Data.

Brain Res. 2017 Jul 28;:

Authors: Liu H, Jiang X, Zhang T, Ren Y, Hu X, Guo L, Han J, Liu T

Abstract
The highly convoluted cerebral cortex is characterized by two different topographic structures: convex gyri and concave sulci. Increasing studies have demonstrated that cortical gyri and sulci exhibit different structural connectivity patterns. Inspired by the intrinsic structural differences between gyri and sulci, in this paper, we present a data-driven framework based on sparse representation of fMRI data for functional network inferences, then examine the interactions within and across gyral and sulcal functional networks and finally elucidate possible functional differences using graph theory based properties. We apply the proposed framework to the high-resolution Human Connectome Project (HCP) grayordinate fMRI data. Extensive experimental results on both resting state fMRI data and task-based fMRI data consistently suggested that gyri are more functionally integrated, while sulci are more functionally segregated in the organizational architecture of cerebral cortex, offering novel understanding of the byzantine cerebral cortex.

PMID: 28760438 [PubMed - as supplied by publisher]

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