NeuroImage
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Epilepsy is a neurological disorder characterized by seizures, i.e. abnormal synchronous activity of neurons in the brain. During a focal seizure, the abnormal synchronous activity starts in a specific brain region and rapidly propagates to neighboring regions. Intracranial ElectroEncephaloGraphy (IEEG) is the recording of brain activity at a high temporal resolution through electrodes placed within different brain regions. ⋯ The full frequency ADTF outperforms the integrated ADTF and masked ADTF. Accordingly, we applied this full frequency ADTF to 4 seizure onset and 29 subclinical seizure IEEG recordings of a patient with refractory epilepsy. Hereby, we showed that connectivity patterns derived from IEEG recordings can provide useful information about seizure propagation and may improve the accuracy of the pre-surgical evaluation in patients with refractory epilepsy.
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Pseudocontinuous arterial spin labeling (PCASL), a newly proposed perfusion magnetic resonance imaging (MRI) technique, has the potential of providing a better balance between labeling efficiency and signal-to-noise ratio than conventional ASL methods. The advantage will not be exploitable until adequate reproducibility can be achieved. In this study, we investigated the reproducibility of PCASL on twelve healthy volunteers by taking into account the inclusion of correction for coil sensitivity (CS) and labeling efficiency (α). ⋯ With CS correction alone, coefficient of variance (CV) remained larger with PCASL than PASL (p=0.02). CV was 12% with CS-corrected PASL and 11% with PCASL when CS and α were corrected for in conjunction. We concluded that CS correction is necessary for ASL imaging when using phased array receiver and that after CS correction, PCASL requires α correction to provide reproducibility comparable to PASL.
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The cognitive activity of the human brain benefits from the functional connectivity of multiple brain regions that form specific, functional brain networks. Recent studies have indicated that the relationship between brain regions can be investigated by examining the temporal interaction (known as functional connectivity) of spontaneous blood oxygen level-dependent (BOLD) signals derived from resting-state functional MRI. Most of these studies plausibly assumed that inter-regional interactions were temporally stationary. ⋯ This dynamic pattern was also observed for the interactions between different functional networks. In addition, the spatial pattern of dynamic connectivity maps obtained from neighboring time points had a high similarity. Overall, this study provides insights into the dynamic properties of resting-state functional networks.
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Characterization and quantification of magnetic resonance perfusion images is important for clinical interpretation, though this calls for a reproducible and accurate method of analysis and a robust healthy reference. The few studies which have examined the perfusion of the healthy brain using dynamic susceptibility contrast (DSC) imaging were largely limited to manual definition of the regions of interest (ROI) and results were dependent on the location of the ROI. The current study aimed to develop a methodology for DSC data analysis and to obtain reference values of healthy subjects. ⋯ Additionally, regional perfusion differences were studied and revealed a prolonged mean transient time and a trend for higher vascularity in the posterior compared with the anterior and middle cerebral vascular territories. While additional studies are required to confirm our findings, this result may have important clinical implications. The proposed unsupervised multiparametric method enabled accurate tissue differentiation, is easy replicable and has a wide range of applications in both pathological and healthy brains.
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Analyses of spontaneous hemodynamic fluctuations observed on functional magnetic resonance imaging (fMRI) have revealed the existence of temporal correlations in signal changes between widely separated brain regions during the resting state, termed "resting state functional connectivity." Recent studies have demonstrated that these correlations are also present in the hemodynamic signals measured by near infrared spectroscopy (NIRS). However, it is still uncertain whether frequency-specific characteristics exist in these signals. In the present study, we used multichannel NIRS to investigate the frequency dependency of functional connectivity between diverse regions in the cerebral cortex by decomposing fluctuations of oxygenated hemoglobin (oxy-Hb) and deoxygenated hemoglobin (deoxy-Hb) signals into various frequency bands. ⋯ This approach demonstrated that functional connectivity based on the oxy-Hb signals between homologous cortical regions of the contralateral hemisphere (homologous connectivity) showed high coherence over a wide frequency range (0.009-0.1Hz), whereas connectivity between the prefrontal and occipital regions (fronto-posterior connectivity) showed high coherence only within a specific narrow frequency range (0.04-0.1Hz). Our findings suggest that homologous connectivity may reflect synchronization of neural activation over a wide frequency range through direct neuroanatomical connections, whereas fronto-posterior connectivity as revealed by high coherence only within a specific narrow frequency range corresponding to the time scale of typical hemodynamic response to a single event may reflect synchronization of transient neural activation among distant cortical regions. The present study demonstrated that NIRS provides a powerful tool to elucidate network properties of the cortex during resting state.