” EEG has been around for about 100 years, and some kinds of neural activity are really well-studied,” the research studys lead author, Senior Research Scientist Nikolay Yavich of Skoltech described. “For example, it is relatively simple for a knowledgeable physician to study a sleep condition by checking out raw EEG data. Other cases are harder. To identify the accurate hotspots in a patients brain that are accountable for epileptic seizures, EEG or MEG data are integrated with high-resolution MRI scans, which model the head of the patient, and processed with advanced computer algorithms. Offered that the problematic region is properly localized, it can then be operated without damaging the surrounding tissue to aid a client with epilepsy when drugs do not work.”
The MRI scans utilized in conjunction with brain activity maps are not always ideal. They are often corrupted by noise and other image artifacts.
” We found that when modeling neural activity on low-resolution head designs, our approach was up to five times more precise than the traditional method. While it likewise demands a higher computational load, the benefits seem to justify its application,” Yavich commented.
This means that the approach can help cognitive scientists, neurologists, and brain cosmetic surgeons working with less than perfect data to understand the neurological basis underlying illness such as epilepsy, attention deficit disorder, and autism, as well as healthy cognition procedures associated with memory, sensuous understanding, locomotion, and more.
Recommendation: “Conservative Finite Element Modeling of EEG and MEG on Unstructured Grids” by N. Yavich; N. Koshev; M. Malovichko; A. Razorenova and M. Fedorov, 13 October 2021, IEEE Transactions on Medical Imaging.DOI: 10.1109/ TMI.2021.3119851.
The method utilized by the scientists is called the mixed-hybrid limited element technique, or MHFEM. The purpose of both methods in analyzing EEG and MEG data is to resolve the equations constituting whats known as the forward problem.
The primary private investigator of the research study reported in this story, Maxim Fedorov is Skoltechs previous vice president for AI and mathematical modeling. He now serves as the rector of Sirius University of Science and Technology.
Skoltech researchers have actually proposed a method for analyzing brain activity data that showed to be up to five times more precise than the traditionally utilized strategy in cases when MRI data contained artifacts or only a low-resolution head model was readily available. Reported in IEEE Transactions on Medical Imaging, the findings are of usage for treating drug-resistant epilepsy and understanding cognitive processes in the healthy brain, including how it responds to visual stimuli and records brand-new words.
Mapping brain activity is the standard way to determine which parts of the brain are included in a specific cognitive job — for instance, getting sensory input from poking a feline with a finger — or implicated in pathological processes, such as epileptic seizures or sleep conditions. Brain activity is normally recorded with electro- or magnetoencephalography, shortened EEG and MEG, respectively. The first technique involves placing a range of electrodes on the scalp surface for measuring regional electrical capacities. The 2nd one utilizes sensing units to tape the electromagnetic field instead of potentials, however both steps are proxies for identifying and localizing the electrical currents in the brain.
Brain activity is typically taped with electro- or magnetoencephalography, shortened EEG and MEG, respectively. To determine the precise hotspots in a patients brain that are accountable for epileptic seizures, EEG or MEG data are integrated with high-resolution MRI scans, which model the head of the client, and processed with advanced computer algorithms. The MRI scans used in conjunction with brain activity maps are not always perfect. The purpose of both approaches in analyzing EEG and MEG data is to resolve the equations constituting whats known as the forward issue.
