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High-accuracy MEG/EEG diagnostics with SCA

Project: Research

  • University of Helsinki
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Description

The accuracy of electroencephalography (EEG) and magnetoencephalography (MEG) is challenged by overlapping neural sources. This lack of accuracy is a severe limitation to the application of MEG/EEG to clinical diagnostics. As a solution, we here introduce a spike density component analysis (SCA) method for isolating specific neural sources.

Layman's description

When we sense and think, magnetoencephalography (MEG) sensors and electroencephalography (EEG) electrodes placed outside the head can measure related electrical activity generated by neurons in the brain. MEG/EEG is widely applied to measure healthy sensing and cognition in the brain and effects of illness and recovery in patients. However, these measures are not yet used for clinical routine, since the electrical brain activity is very weak, and it needs to be isolated from many interfering signals. As a solution, we developed a novel data analysis method, which isolates neural signals from different brain regions by modeling their shape in time.
StatusActive
Effective start/end date01/01/2019 → …

Research outputs

ID: 209586378