Associations between neurological examination at term-equivalent age and cerebral hemodynamics and oxygen metabolism in infants born preterm.

Background: Infants born at 29-36 weeks gestational age (GA) are at risk of experiencing neurodevelopmental challenges. We hypothesize that cerebral hemodynamics and oxygen metabolism measured by bedside optical brain monitoring are potential biomarkers of brain development and are associated with neurological examination at term-equivalent age (TEA).

Methods: Preterm infants ( = 133) born 29-36 weeks GA and admitted in the neonatal intensive care unit were enrolled in this prospective cohort study.

Opioid analgesia and temperature regulation are associated with EEG background activity and MRI outcomes in neonates with mild-to-moderate hypoxic-ischemic encephalopathy undergoing therapeutic hypothermia.

Background: Therapeutic hypothermia (TH) without sedation may lead to discomfort, which may be associated with adverse consequences in neonates with hypoxic-ischemic encephalopathy (HIE). The aim of this study was to assess the association between level of exposure to opioids and temperature, with electroencephalography (EEG) background activity post-TH and magnetic resonance imaging (MRI) brain injury in neonates with HIE.

Methods: Thirty-one neonates with mild-to-moderate HIE who underwent TH were identified.

Diffuse optical reconstructions of functional near infrared spectroscopy data using maximum entropy on the mean.

Functional near-infrared spectroscopy (fNIRS) measures the hemoglobin concentration changes associated with neuronal activity. Diffuse optical tomography (DOT) consists of reconstructing the optical density changes measured from scalp channels to the oxy-/deoxy-hemoglobin concentration changes within the cortical regions. In the present study, we adapted a nonlinear source localization method developed and validated in the context of Electro- and Magneto-Encephalography (EEG/MEG): the Maximum Entropy on the Mean (MEM), to solve the inverse problem of DOT reconstruction.

Reproducibility of EEG-MEG fusion source analysis of interictal spikes: Relevance in presurgical evaluation of epilepsy.

Fusion of electroencephalography (EEG) and magnetoencephalography (MEG) data using maximum entropy on the mean method (MEM-fusion) takes advantage of the complementarities between EEG and MEG to improve localization accuracy. Simulation studies demonstrated MEM-fusion to be robust especially in noisy conditions such as single spike source localizations (SSSL). Our objective was to assess the reliability of SSSL using MEM-fusion on clinical data.

Clinical yield of magnetoencephalography distributed source imaging in epilepsy: A comparison with equivalent current dipole method.

Objective: Source localization of interictal epileptic discharges (IEDs) is clinically useful in the presurgical workup of epilepsy patients. It is usually obtained by equivalent current dipole (ECD) which localizes a point source and is the only inverse solution approved by clinical guidelines. In contrast, magnetic source imaging using distributed methods (dMSI) provides maps of the location and the extent of the generators, but its yield has not been clinically validated.

MEG-EEG Information Fusion and Electromagnetic Source Imaging: From Theory to Clinical Application in Epilepsy.

The purpose of this study is to develop and quantitatively assess whether fusion of EEG and MEG (MEEG) data within the maximum entropy on the mean (MEM) framework increases the spatial accuracy of source localization, by yielding better recovery of the spatial extent and propagation pathway of the underlying generators of inter-ictal epileptic discharges (IEDs). The key element in this study is the integration of the complementary information from EEG and MEG data within the MEM framework. MEEG was compared with EEG and MEG when localizing single transient IEDs.

MEG source localization of spatially extended generators of epileptic activity: comparing entropic and hierarchical bayesian approaches.

Localizing the generators of epileptic activity in the brain using Electro-EncephaloGraphy (EEG) or Magneto-EncephaloGraphy (MEG) signals is of particular interest during the pre-surgical investigation of epilepsy. Epileptic discharges can be detectable from background brain activity, provided they are associated with spatially extended generators. Using realistic simulations of epileptic activity, this study evaluates the ability of distributed source localization methods to accurately estimate the location of the generators and their sensitivity to the spatial extent of such generators when using MEG data.