EEG is traditionally described as a neuroimaging technique with high temporal and low spatial resolution. Recent advances in biophysical modelling and signal processing make it possible to exploit information from other imaging modalities like structural MRI that provide high spatial resolution to overcome this constraint. This is especially useful for investigations that require high resolution in the temporal as well as spatial domain. In addition, due to the easy application and low cost of EEG recordings, EEG is often the method of choice when working with populations, such as young children, that do not tolerate functional MRI scans well. However, in order to investigate which neural substrates are involved, anatomical information from structural MRI is still needed. Most EEG analysis packages work with standard head models that are based on adult anatomy. The accuracy of these models when used for children is limited, because the composition and spatial configuration of head tissues changes dramatically over development. In the present paper, we provide an overview of our recent work in utilizing head models based on individual structural MRI scans or age specific head models to reconstruct the cortical generators of high density EEG. This article describes how EEG recordings are acquired, processed, and analyzed with pediatric populations at the London Baby Lab, including laboratory setup, task design, EEG preprocessing, MRI processing, and EEG channel level and source analysis.
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http://dx.doi.org/10.3791/51705 | DOI Listing |
Epilepsia Open
January 2025
Division of Pediatric Critical Care Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Objectives: Pediatric status epilepticus (SE) carries a high risk of morbidity and mortality and can result in neurologic injury. Establishing seizure activity on conventional EEG (cEEG) is essential but can delay treatment of seizures due to technician limitations. Rapid response EEG (rrEEG) device Ceribell and its Brain Stethoscope function can be used and interpreted rapidly by bedside providers with minimal training.
View Article and Find Full Text PDFJ Neurodev Disord
January 2025
Graduate Neuroscience Program, University of California, Riverside, CA, USA.
Background: Fragile X syndrome (FXS) is a leading known genetic cause of intellectual disability and autism spectrum disorders (ASD)-associated behaviors. A consistent and debilitating phenotype of FXS is auditory hypersensitivity that may lead to delayed language and high anxiety. Consistent with findings in FXS human studies, the mouse model of FXS, the Fmr1 knock out (KO) mouse, shows auditory hypersensitivity and temporal processing deficits.
View Article and Find Full Text PDFActa Pharmacol Sin
January 2025
Laboratory for Neurophysiology, Department of Cell and Chemical Biology, Leiden University, Medical Centre, Leiden, 2333, ZC, The Netherlands.
Daylength (i.e., photoperiod) provides essential information for seasonal adaptations of organisms.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Physics, University of Trento, Trento, 38123, Italy.
The analysis of electrophysiological recordings of the human brain in resting state is a key experimental technique in neuroscience. Resting state is the default condition to characterize brain dynamics. Its successful implementation relies both on the capacity of subjects to comply with the requirement of staying awake while not performing any cognitive task, and on the capacity of the experimenter to validate that compliance.
View Article and Find Full Text PDFNPJ Parkinsons Dis
January 2025
Brain Electrophysiology and Epilepsy Lab (BEE-L), Epilepsy and EEG Unit, Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
We aimed to study the effect of Parkinson's disease (PD) and motor-cognitive load on the interplay between activation level and spatial complexity. To that end, 68 PD patients and 30 controls underwent electroencephalography (EEG) recording while executing visual single- and dual- Go/No-go tasks. The EEG underwent source localization, followed by parcellation of the neural activity into 116 regions of interest.
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