New resting-state fMRI related studies at PubMed

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Early Development of Functional Network Segregation Revealed by Connectomic Analysis of the Preterm Human Brain.

Sun, 04/30/2017 - 11:40
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Early Development of Functional Network Segregation Revealed by Connectomic Analysis of the Preterm Human Brain.

Cereb Cortex. 2017 Mar 01;27(3):1949-1963

Authors: Cao M, He Y, Dai Z, Liao X, Jeon T, Ouyang M, Chalak L, Bi Y, Rollins N, Dong Q, Huang H

Abstract
Human brain functional networks are topologically organized with nontrivial connectivity characteristics such as small-worldness and densely linked hubs to support highly segregated and integrated information processing. However, how they emerge and change at very early developmental phases remains poorly understood. Here, we used resting-state functional MRI and voxel-based graph theory analysis to systematically investigate the topological organization of whole-brain networks in 40 infants aged around 31 to 42 postmenstrual weeks. The functional connectivity strength and heterogeneity increased significantly in primary motor, somatosensory, visual, and auditory regions, but much less in high-order default-mode and executive-control regions. The hub and rich-club structures in primary regions were already present at around 31 postmenstrual weeks and exhibited remarkable expansions with age, accompanied by increased local clustering and shortest path length, indicating a transition from a relatively random to a more organized configuration. Moreover, multivariate pattern analysis using support vector regression revealed that individual brain maturity of preterm babies could be predicted by the network connectivity patterns. Collectively, we highlighted a gradually enhanced functional network segregation manner in the third trimester, which is primarily driven by the rapid increases of functional connectivity of the primary regions, providing crucial insights into the topological development patterns prior to birth.

PMID: 26941380 [PubMed - indexed for MEDLINE]

Magnetic resonance imaging connectivity for the prediction of seizure outcome in temporal lobe epilepsy.

Fri, 04/28/2017 - 10:20

Magnetic resonance imaging connectivity for the prediction of seizure outcome in temporal lobe epilepsy.

Epilepsia. 2017 Apr 27;:

Authors: Morgan VL, Englot DJ, Rogers BP, Landman BA, Cakir A, Abou-Khalil BW, Anderson AW

Abstract
OBJECTIVE: Currently, approximately 60-70% of patients with unilateral temporal lobe epilepsy (TLE) remain seizure-free 3 years after surgery. The goal of this work was to develop a presurgical connectivity-based biomarker to identify those patients who will have an unfavorable seizure outcome 1-year postsurgery.
METHODS: Resting-state functional and diffusion-weighted 3T magnetic resonance imaging (MRI) was acquired from 22 unilateral (15 right, 7 left) patients with TLE and 35 healthy controls. A seizure propagation network was identified including ipsilateral (to seizure focus) and contralateral hippocampus, thalamus, and insula, with bilateral midcingulate and precuneus. Between each pair of regions, functional connectivity based on correlations of low frequency functional MRI signals, and structural connectivity based on streamline density of diffusion MRI data were computed and transformed to metrics related to healthy controls of the same age.
RESULTS: A consistent connectivity pattern representing the network expected in patients with seizure-free outcome was identified using eight patients who were seizure-free at 1-year postsurgery. The hypothesis that increased similarity to the model would be associated with better seizure outcome was tested in 14 other patients (Engel class IA, seizure-free: n = 5; Engel class IB-II, favorable: n = 4; Engel class III-IV, unfavorable: n = 5) using two similarity metrics: Pearson correlation and Euclidean distance. The seizure-free connectivity model successfully separated all the patients with unfavorable outcome from the seizure-free and favorable outcome patients (p = 0.0005, two-tailed Fisher's exact test) through the combination of the two similarity metrics with 100% accuracy. No other clinical and demographic predictors were successful in this regard.
SIGNIFICANCE: This work introduces a methodologic framework to assess individual patients, and demonstrates the ability to use network connectivity as a potential clinical tool for epilepsy surgery outcome prediction after more comprehensive validation.

PMID: 28448683 [PubMed - as supplied by publisher]

Spontaneous migraine attack causes alterations in default mode network connectivity: a resting-state fMRI case report.

Fri, 04/28/2017 - 10:20
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Spontaneous migraine attack causes alterations in default mode network connectivity: a resting-state fMRI case report.

BMC Res Notes. 2017 Apr 26;10(1):165

Authors: Edes AE, Kozak LR, Magyar M, Zsombok T, Kokonyei G, Bagdy G, Juhasz G

Abstract
BACKGROUND: Although migraine is one of the most investigated neurologic disorders, we do not have a perfect neuroimaging biomarker for its pathophysiology. One option to improve our knowledge is to study resting-state functional connectivity in and out of headache pain. However, our understanding of the functional connectivity changes during spontaneous migraine attack is partial and incomplete.
CASE PRESENTATION: Using resting-state functional magnetic resonance imaging we assessed a 24-year old woman affected by migraine without aura at two different times: during a spontaneous migraine attack and in interictal phase. Seed-to-voxel whole brain analysis was carried out using the posterior cingulate cortex as a seed, representing the default mode network (DMN). Our results showed decreased intrinsic connectivity within core regions of the DMN with an exception of a subsystem including the dorsal medial and superior frontal gyri, and the mid-temporal gyrus which is responsible for pain interpretation and control. In addition, increased connectivity between the DMN and pain and specific migraine-related areas, such as the pons and hypothalamus, developed during the spontaneous migraine attack.
CONCLUSION: Our preliminary results provide further support for the hypothesis that alterations of the DMN functional connectivity during migraine headache may lead to maladaptive top-down modulation of migraine pain-related areas which might be a specific biomarker for migraine.

PMID: 28446211 [PubMed - in process]

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