Magnetoencephalography (MEG) aims at reconstructing the unknown neuroelectric activity in the brain from non-invasive measurements of the magnetic field induced by neural sources. The solution of this ill-posed, ill-conditioned inverse problem is usually dealt with using regularization techniques that are often time-consuming, and computationally and memory storage demanding. In this paper we analyze how a slimmer procedure, random sampling, affects the estimation of the brain activity generated by both synthetic and real sources.
Less is enough: assessment of the random sampling method for the analysis of magnetoencephalography (MEG) data / Campi, Cristina; Pascarella, Annalisa; Pitolli, Francesca. - In: MATHEMATICAL AND COMPUTATIONAL APPLICATIONS. - ISSN 2297-8747. - 24:4(2019). [10.3390/mca24040098]
Less is enough: assessment of the random sampling method for the analysis of magnetoencephalography (MEG) data
Pitolli, Francesca
2019
Abstract
Magnetoencephalography (MEG) aims at reconstructing the unknown neuroelectric activity in the brain from non-invasive measurements of the magnetic field induced by neural sources. The solution of this ill-posed, ill-conditioned inverse problem is usually dealt with using regularization techniques that are often time-consuming, and computationally and memory storage demanding. In this paper we analyze how a slimmer procedure, random sampling, affects the estimation of the brain activity generated by both synthetic and real sources.| File | Dimensione | Formato | |
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