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- aggregation classification "A1".
- aggregation creator person.
- aggregation creator person.
- aggregation creator person.
- aggregation creator person.
- aggregation date "2012".
- aggregation format "application/pdf".
- aggregation hasFormat 3060256.bibtex.
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- aggregation isPartOf urn:issn:2190-5444.
- aggregation language "eng".
- aggregation rights "I have transferred the copyright for this publication to the publisher".
- aggregation subject "Medicine and Health Sciences".
- aggregation title "Mapping the epileptic brain with EEG dynamical connectivity: established methods and novel approaches".
- aggregation abstract "Several algorithms rooted in statistical physics, mathematics and machine learning are used to analyze neuroimaging data from patients suffering from epilepsy, with the main goals of localizing the brain region where the seizure originates from and of detecting upcoming seizure activity in order to trigger therapeutic neurostimulation devices. Some of these methods explore the dynamical connections between brain regions, exploiting the high temporal resolution of the electroencephalographic signals recorded at the scalp or directly from the cortical surface or in deeper brain areas. In this paper we describe this specific class of algorithms and their clinical application, by reviewing the state of the art and reporting their application on EEG data from an epileptic patient.".
- aggregation authorList BK769982.
- aggregation issue "11".
- aggregation volume "127".
- aggregation aggregates 3193487.
- aggregation aggregates 4246504.
- aggregation isDescribedBy 3060256.
- aggregation similarTo i2012-12144-5.
- aggregation similarTo LU-3060256.