New resting-state fMRI related studies at PubMed

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resting state fMRI; +18 new citations

Thu, 03/09/2017 - 12:03

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resting state fMRI

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Task and resting-state fMRI studies in first-episode schizophrenia: A systematic review.

Wed, 03/08/2017 - 12:55
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Task and resting-state fMRI studies in first-episode schizophrenia: A systematic review.

Schizophr Res. 2017 Mar 03;:

Authors: Mwansisya TE, Hu A, Li Y, Chen X, Wu G, Huang X, Lv D, Li Z, Liu C, Xue Z, Feng J, Liu Z

Abstract
In the last two decades there has been an increase on task and resting-state functional Magnetic Resonance Imaging (fMRI) studies that explore the brain's functional changes in schizophrenia. However, it remains unclear as to whether the brain's functional changes during the resting state are sensitive to the same brain regions during task fMRI. Therefore, we conducted a systematic literature search of task and resting-state fMRI studies that investigated brain pathological changes in first-episode schizophrenia (Fleischhacker et al.). Nineteen studies met the inclusion criteria; seven were resting state fMRI studies with 371 FES patients and 363 healthy controls and twelve were task fMRI studies with 235 FES patients and 291 healthy controls. We found overlapping task and resting-state fMRI abnormalities in the prefrontal regions, including the dorsal lateral prefrontal cortex, the orbital frontal cortex and the temporal lobe, especially in the left superior temporal gyrus (STG). The findings of this systematic review support the frontotemporal hypothesis of schizophrenia, and the disruption in prefrontal and STG might represent the pathophysiology of schizophrenia disorder at a relatively early stage.

PMID: 28268041 [PubMed - as supplied by publisher]

Bayesian Switching Factor Analysis for Estimating Time-varying Functional Connectivity in fMRI.

Wed, 03/08/2017 - 12:55
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Bayesian Switching Factor Analysis for Estimating Time-varying Functional Connectivity in fMRI.

Neuroimage. 2017 Mar 03;:

Authors: Taghia J, Ryali S, Chen T, Supekar K, Cai W, Menon V

Abstract
There is growing interest in understanding the dynamical properties of functional interactions between distributed brain regions. However, robust estimation of temporal dynamics from functional magnetic resonance imaging (fMRI) data remains challenging due to limitations in extant multivariate methods for modeling time-varying functional interactions between multiple brain areas. Here, we develop a Bayesian generative model for fMRI time-series within the framework of hidden Markov models (HMMs). The model is a dynamic variant of the static factor analysis model (Ghahramani and Beal, 2000). We refer to this model as Bayesian switching factor analysis (BSFA) as it integrates factor analysis into a generative HMM in a unified Bayesian framework. In BSFA, brain dynamic functional networks are represented by latent states which are learnt from the data. Crucially, BSFA is a generative model which estimates the temporal evolution of brain states and transition probabilities between states as a function of time. An attractive feature of BSFA is the automatic determination of the number of latent states via Bayesian model selection arising from penalization of excessively complex models. Key features of BSFA are validated using extensive simulations on carefully designed synthetic data. We further validate BSFA using fingerprint analysis of multisession resting-state fMRI data from the Human Connectome Project (HCP). Our results show that modeling temporal dependencies in the generative model of BSFA results in improved fingerprinting of individual participants. Finally, we apply BSFA to elucidate the dynamic functional organization of the salience, central-executive, and default mode networks-three core neurocognitive systems with central role in cognitive and affective information processing (Menon, 2011). Across two HCP sessions, we demonstrate a high level of dynamic interactions between these networks and determine that the salience network has the highest temporal flexibility among the three networks. Our proposed methods provide a novel and powerful generative model for investigating dynamic brain connectivity.

PMID: 28267626 [PubMed - as supplied by publisher]

Ensuring that novel resting-state fMRI metrics are physiologically grounded, interpretable, and meaningful (A commentary on Canna et al., 2017).

Wed, 03/08/2017 - 12:55
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Ensuring that novel resting-state fMRI metrics are physiologically grounded, interpretable, and meaningful (A commentary on Canna et al., 2017).

Eur J Neurosci. 2017 Mar 07;:

Authors: Dunlop K, Downar J

PMID: 28267225 [PubMed - as supplied by publisher]

Alteration of Spontaneous Brain Activity After Hypoxia-Reoxygenation: A Resting-State fMRI Study.

Wed, 03/08/2017 - 12:55
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Alteration of Spontaneous Brain Activity After Hypoxia-Reoxygenation: A Resting-State fMRI Study.

High Alt Med Biol. 2017 Mar 07;:

Authors: Zhang J, Chen J, Fan C, Li J, Lin J, Yang T, Fan M

Abstract
Zhang, Jiaxing, Ji Chen, Cunxiu Fan, Jinqiang Li, Jianzhong Lin, Tianhe Yang, and Ming Fan. Alteration of spontaneous brain activity after hypoxia-reoxygenation: A resting-state fMRI study. High Alt Med Biol. 18:000-000, 2017.-The present study was designed to investigate the effect of hypoxia-reoxygenation on the spontaneous neuronal activity in brain. Sixteen sea-level (SL) soldiers (20.5 ± 0.7 years), who garrisoned the frontiers in high altitude (HA) (2300-4400 m) for two years and subsequently descended to sea level for one to seven days, were recruited. Control group consisted of 16 matched SL natives. The amplitude of low-frequency fluctuations (ALFF) of regional brain functional magnetic resonance imaging signal in resting state and functional connectivity (FC) between brain regions was analyzed. HA subjects showed significant increases of ALFF at several sites within the bilateral occipital cortices and significant decreases of ALFF in the right anterior insula and extending to the caudate, putamen, inferior frontal orbital cortex, temporal pole, and superior temporal gyrus; lower ALFF values in the right insula were positively correlated with low respiratory measurements. The right insula in HA subjects had increases of FC with the right superior temporal gyrus, postcentral gyrus, rolandic operculum, supramarginal gyrus, and inferior frontal triangular area. We thus demonstrated that hypoxia-reoxygenation had influence on the spontaneous neuronal activity in brain. The decrease of insular neuronal activity may be related to the reduction of ventilatory drive, while the increase of FC with insula may indicate a central compensation.

PMID: 28266873 [PubMed - as supplied by publisher]

Intact sensory-motor network structure and function in far from onset premanifest Huntington's disease.

Wed, 03/08/2017 - 12:55
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Intact sensory-motor network structure and function in far from onset premanifest Huntington's disease.

Sci Rep. 2017 Mar 07;7:43841

Authors: Gorges M, Müller HP, Mayer IM, Grupe GS, Kammer T, Grön G, Kassubek J, Landwehrmeyer GB, Wolf RC, Orth M

Abstract
Structural and functional changes attributable to the neurodegenerative process in Huntington's disease (HD) may be evident in HTT CAG repeat expansion carriers before the clinical manifestations of HD. It remains unclear, though, how far from motor onset a consistent signature of the neurodegenerative process in HD can be detected. Twelve far from onset preHD and 22 age-matched healthy control participants underwent volumetric structural magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), and resting-state functional MRI (11 preHD, 22 controls) as well as electrophysiological measurements (12 preHD, 13 controls). There were no significant differences in white matter macro- and microstructure between far from onset preHD participants and controls. Functional connectivity in a basal ganglia-thalamic and motor networks, all measures of the motor efferent and sensory afferent pathways as well as sensory-motor integration were also similar in far from onset preHD and controls. With the methods used in far from onset preHD sensory-motor neural macro- or micro-structure and brain function were similar to healthy controls. This suggests that any observable structural and functional change in preHD nearer to onset, or in manifest HD, at least using comparable techniques such as in this study, most likely reflects an ongoing neurodegenerative process.

PMID: 28266655 [PubMed - in process]

The left middle temporal gyrus in the middle of an impaired social-affective communication network in social anxiety disorder.

Wed, 03/08/2017 - 12:55
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The left middle temporal gyrus in the middle of an impaired social-affective communication network in social anxiety disorder.

J Affect Disord. 2017 Mar 04;214:53-59

Authors: Yun JY, Kim JC, Ku J, Shin JE, Kim JJ, Choi SH

Abstract
BACKGROUND: Previous studies on patients diagnosed with social anxiety disorder (SAD) reported changed patterns of the resting-state functional connectivity network (rs-FCN) between the prefrontal cortices and other prefrontal, amygdalar or striatal regions. Using a graph theory approach, this study explored the modularity-based community profile and patterns of inter-/intra-modular communication for the rs-FCN in SAD.
METHODS: In total, for 28 SAD patients and 27 healthy controls (HC), functional magnetic resonance imaging (fMRI) data were acquired in resting-state and subjected to a graph theory analysis.
RESULTS: The within-module degree z-score for a hub region [out of a total of 10 hub regions ranked using the participation coefficient] named left middle temporal gyrus was impaired in SAD compared to HC, proportional to the severity of clinician-scored and patient-reported functional impairment in SAD.
LIMITATIONS: Most of participants included in this study were undergraduate students in their early-to-mid 20's.
CONCLUSIONS: This study showed the importance of functional communication from the left middle temporal gyrus with other opercular-insular-subcortical regions for better objective functioning and lesser subjective disability in SAD.

PMID: 28266321 [PubMed - as supplied by publisher]

Brain structural and functional signatures of impulsive-compulsive behaviours in Parkinson's disease.

Wed, 03/08/2017 - 12:55
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Brain structural and functional signatures of impulsive-compulsive behaviours in Parkinson's disease.

Mol Psychiatry. 2017 Mar 07;:

Authors: Imperiale F, Agosta F, Canu E, Markovic V, Inuggi A, Jecmenica-Lukic M, Tomic A, Copetti M, Basaia S, Kostic VS, Filippi M

Abstract
This study assessed brain structural and functional alterations in patients with Parkinson's disease and impulsive-compulsive behaviours (PD-ICB) compared with controls and PD no-ICB cases. Eighty-five PD patients (35 PD-ICB) and 50 controls were recruited. All subjects underwent three-dimensional T1-weighted, diffusion tensor (DT), and resting state functional magnetic resonance imaging (RS fMRI). We assessed cortical thickness with surface-based morphometry, subcortical volumes using FIRST, DT MRI metrics using region of interest and tractography approaches, and RS fMRI using a model free approach. Compared with controls, both PD groups showed a pattern of brain structural alterations in the basal ganglia (more evident in PD no-ICB patients), sensorimotor and associative systems. Compared with PD no-ICB, PD-ICB cases showed left precentral and superior frontal cortical thinning, and motor and extramotor white matter tract damage. Compared with controls, all patients had an increased functional connectivity within the visual network. Additionally, PD no-ICB showed increased functional connectivity of bilateral precentral and postcentral gyri within the sensorimotor network compared with controls and PD-ICB. Severity and duration of PD-ICB modulated the functional connectivity between sensorimotor, visual and cognitive networks. Relative to PD no-ICB, PD-ICB patients were characterised by a more severe involvement of frontal, meso-limbic and motor circuits. These data suggest ICB in PD as the result of a disconnection between sensorimotor, associative and cognitive networks with increasing motor impairment, psychiatric symptoms, and ICB duration. These findings may have important implications in understanding the neural substrates underlying ICB in PD.Molecular Psychiatry advance online publication, 7 March 2017; doi:10.1038/mp.2017.18.

PMID: 28265121 [PubMed - as supplied by publisher]

Emergence of a hierarchical brain during infancy reflected by stepwise functional connectivity.

Tue, 03/07/2017 - 12:15

Emergence of a hierarchical brain during infancy reflected by stepwise functional connectivity.

Hum Brain Mapp. 2017 Mar 06;:

Authors: Pendl SL, Salzwedel AP, Goldman BD, Barrett LF, Lin W, Gilmore JH, Gao W

Abstract
The hierarchical nature of the brain's functional organization has long been recognized, but when and how this architecture emerges during development remains largely unknown. Here the development of the brain's hierarchical organization was characterized using a modified stepwise functional connectivity approach based on resting-state fMRI in a fully longitudinal sample of infants (N = 28, with scans after birth, and at 1 and 2 years) and adults. Results obtained by placing seeds in early sensory cortices revealed novel hierarchical patterns of adult brain organization ultimately converging in limbic, paralimbic, basal ganglia, and frontoparietal brain regions. These findings are remarkably consistent with predictive coding accounts of neural processing that place these regions at the top of predictive coding hierarchies. Infants gradually developed toward this architecture in a region- and step-dependent manner, and displayed many of the same regions as adults in top hierarchical positions, starting from 1 year of age. The findings further revealed patterns of inter-sensory connectivity likely reflecting the emergence and development of multisensory processing strategies during infancy, the strengths of which were correlated with early cognitive development scores. Hum Brain Mapp, 2017. © 2017 Wiley Periodicals, Inc.

PMID: 28263011 [PubMed - as supplied by publisher]

Resting state synchrony in long-term abstinent alcoholics: Effects of a current major depressive disorder diagnosis.

Tue, 03/07/2017 - 12:15

Resting state synchrony in long-term abstinent alcoholics: Effects of a current major depressive disorder diagnosis.

Alcohol. 2017 Mar;59:17-25

Authors: Fein G, Camchong J, Cardenas VA, Stenger A

Abstract
Alcoholism is characterized by a lack of control over an impulsive and compulsive drive toward excessive alcohol consumption despite significant negative consequences; our previous work demonstrated that successful abstinence is characterized by decreased resting-state synchrony (RSS) as measured with functional magnetic resonance imaging (fMRI), within appetitive drive networks and increased RSS in emotion regulation and inhibitory executive control networks. Our hypothesis is that LTAA (Long-Term Abstinent Alcoholics) with a current major depressive disorder (MDD) drank primarily to deal with the negative affect associated with their MDD and not because of a heightened externalizing diathesis (including heightened appetitive drive), and consequently, in achieving and maintaining abstinence, such individuals would not exhibit the RSS adaptations characteristic of pure alcoholics. We studied 69 NSAC (Non Substance Abusing Controls) and 40 LTAA (8 with current MDD, 32 without a current MDD) using resting-state fMRI and seed based connectivity analyses. In the inhibitory executive control network (nucleus accumbens vs. left dorsolateral prefrontal cortex), LTAA with a current MDD showed increased synchrony compared to NSAC. In the emotion regulation executive control network (subgenual anterior cingulate cortex vs. right dorsolateral prefrontal cortex), LTAA with current MDD did not show increased RSS. In the appetitive drive networks (nucleus accumbens vs, aspects of the caudate nucleus and thalamus), LTAA with a current MDD did not show a reduction of RSS compared to NSAC, but LTAA without a current MDD did. These results suggest different pathways to their alcohol dependence in LTAA with vs. without a current MDD, and different patterns of brain activity in long-term abstinence, suggesting different treatment needs.

PMID: 28262184 [PubMed - in process]

Thalamo-Sensorimotor Functional Connectivity Correlates with World Ranking of Olympic, Elite, and High Performance Athletes.

Tue, 03/07/2017 - 12:15
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Thalamo-Sensorimotor Functional Connectivity Correlates with World Ranking of Olympic, Elite, and High Performance Athletes.

Neural Plast. 2017;2017:1473783

Authors: Huang Z, Davis Iv HH, Wolff A, Northoff G

Abstract
Brain plasticity studies have shown functional reorganization in participants with outstanding motor expertise. Little is known about neural plasticity associated with exceptionally long motor training or of its predictive value for motor performance excellence. The present study utilised resting-state functional magnetic resonance imaging (rs-fMRI) in a unique sample of world-class athletes: Olympic, elite, and internationally ranked swimmers (n = 30). Their world ranking ranged from 1st to 250th: each had prepared for participation in the Olympic Games. Combining rs-fMRI graph-theoretical and seed-based functional connectivity analyses, it was discovered that the thalamus has its strongest connections with the sensorimotor network in elite swimmers with the highest world rankings (career best rank: 1-35). Strikingly, thalamo-sensorimotor functional connections were highly correlated with the swimmers' motor performance excellence, that is, accounting for 41% of the individual variance in best world ranking. Our findings shed light on neural correlates of long-term athletic performance involving thalamo-sensorimotor functional circuits.

PMID: 28261504 [PubMed - in process]

Frequency Clustering Analysis for Resting State Functional Magnetic Resonance Imaging Based on Hilbert-Huang Transform.

Tue, 03/07/2017 - 12:15
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Frequency Clustering Analysis for Resting State Functional Magnetic Resonance Imaging Based on Hilbert-Huang Transform.

Front Hum Neurosci. 2017;11:61

Authors: Wu X, Wu T, Liu C, Wen X, Yao L

Abstract
Objective: Exploring resting-state functional networks using functional magnetic resonance imaging (fMRI) is a hot topic in the field of brain functions. Previous studies suggested that the frequency dependence between blood oxygen level dependent (BOLD) signals may convey meaningful information regarding interactions between brain regions. Methods: In this article, we introduced a novel frequency clustering analysis method based on Hilbert-Huang Transform (HHT) and a label-replacement procedure. First, the time series from multiple predefined regions of interest (ROIs) were extracted. Second, each time series was decomposed into several intrinsic mode functions (IMFs) by using HHT. Third, the improved k-means clustering method using a label-replacement method was applied to the data of each subject to classify the ROIs into different classes. Results: Two independent resting-state fMRI dataset of healthy subjects were analyzed to test the efficacy of method. The results show almost identical clusters when applied to different runs of a dataset or to different datasets, indicating a stable performance of our framework. Conclusions and Significance: Our framework provided a novel measure for functional segregation of the brain according to time-frequency characteristics of resting state BOLD activities.

PMID: 28261074 [PubMed - in process]

Resting State fMRI Functional Connectivity Analysis Using Dynamic Time Warping.

Tue, 03/07/2017 - 12:15
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Resting State fMRI Functional Connectivity Analysis Using Dynamic Time Warping.

Front Neurosci. 2017;11:75

Authors: Meszlényi RJ, Hermann P, Buza K, Gál V, Vidnyánszky Z

Abstract
Traditional resting-state network concept is based on calculating linear dependence of spontaneous low frequency fluctuations of the BOLD signals of different brain areas, which assumes temporally stable zero-lag synchrony across regions. However, growing amount of experimental findings suggest that functional connectivity exhibits dynamic changes and a complex time-lag structure, which cannot be captured by the static zero-lag correlation analysis. Here we propose a new approach applying Dynamic Time Warping (DTW) distance to evaluate functional connectivity strength that accounts for non-stationarity and phase-lags between the observed signals. Using simulated fMRI data we found that DTW captures dynamic interactions and it is less sensitive to linearly combined global noise in the data as compared to traditional correlation analysis. We tested our method using resting-state fMRI data from repeated measurements of an individual subject and showed that DTW analysis results in more stable connectivity patterns by reducing the within-subject variability and increasing robustness for preprocessing strategies. Classification results on a public dataset revealed a superior sensitivity of the DTW analysis to group differences by showing that DTW based classifiers outperform the zero-lag correlation and maximal lag cross-correlation based classifiers significantly. Our findings suggest that analysing resting-state functional connectivity using DTW provides an efficient new way for characterizing functional networks.

PMID: 28261052 [PubMed - in process]

Brain Network Dynamics Adhere to a Power Law.

Tue, 03/07/2017 - 12:15
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Brain Network Dynamics Adhere to a Power Law.

Front Neurosci. 2017;11:72

Authors: Tomasi DG, Shokri-Kojori E, Volkow ND

Abstract
The temporal dynamics of complex networks such as the Internet are characterized by a power scaling between the temporal mean and dispersion of signals at each network node. Here we tested the hypothesis that the temporal dynamics of the brain networks are characterized by a similar power law. This realization could be useful to assess the effects of randomness and external modulators on the brain network dynamics. Simulated data using a well-stablished random diffusion model allowed us to predict that the temporal dispersion of the amplitude of low frequency fluctuations (ALFF) and that of the local functional connectivity density (lFCD) scale with their temporal means. We tested this hypothesis in open-access resting-state functional magnetic resonance imaging datasets from 66 healthy subjects. A robust power law emerged from the temporal dynamics of ALFF and lFCD metrics, which was insensitive to the methods used for the computation of the metrics. The scaling exponents (ALFF: 0.8 ± 0.1; lFCD: 1.1 ± 0.1; mean ± SD) decreased with age and varied significantly across brain regions; multimodal cortical areas exhibited lower scaling exponents, consistent with a stronger influence of external inputs, than limbic and subcortical regions, which exhibited higher scaling exponents, consistent with a stronger influence of internal randomness. Findings are consistent with the notion that external inputs govern neuronal communication in the brain and that their relative influence differs between brain regions. Further studies will assess the potential of this metric as biomarker to characterize neuropathology.

PMID: 28261049 [PubMed - in process]

Caudate-Precuneus functional connectivity is associated with obesity preventive eating tendency.

Tue, 03/07/2017 - 12:15
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Caudate-Precuneus functional connectivity is associated with obesity preventive eating tendency.

Brain Connect. 2017 Mar 01;:

Authors: Nakamura Y, Ikuta T

Abstract
There exists diversity among individuals in difficulty controlling body weight. Body weight control, or obesity prevention, requires cognitive control over ingestive behavior, which may account for the diverse ability of body weight control. The caudate nuclei, especially the dorsal area, have been shown to play critical roles in ingestive behaviors, which significantly influences body weight control. However, the practice of body weight control is dependent on the body weight status, since the current obesity status determines the need for body weight control. In order to elucidate the underlying neural mechanism that accounts for individual differences in obesity prevention, we aimed to isolate functional caudate connectivity responsible for the underlying tendency of obesity prevention, independent of the current obesity status, using resting state fMRI data, body mass index, and assessment of ingestive behavior from 185 individuals from NKI-Rockland sample. The underlying tendency of obesity prevention was estimated from body mass index (BMI) and behavioral and cognitive components of food intake. Functional connectivities between the caudate head and the whole brain were tested as a function of the estimated tendency in voxel-wise fashion. The bilateral precuneus showed inverse association between its connectivity to the caudate and the estimated tendency. Caudate-precuneus connectivity may have significant implications to understanding personal differences that accounts for the success in body weight control.

PMID: 28260392 [PubMed - as supplied by publisher]

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