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Electrical Neuroimaging (Cambridge Medicine (Hardcover))

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  • 250 pages
  • 9 hours of reading

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Electrical neuroimaging is based on the analysis of brain electrical activity recorded from the human scalp with multichannel EEG. It offers enormous potential for the dynamic mapping of brain functions, and for the non-invasive diagnosis of neurological and psychiatric conditions. This authoritative reference gives a systematic overview of new electrical imaging methods, with a sound introduction to the basics of multichannel recording of EEG and event-related potential (ERP) data, as well as spatio-temporal analysis of the potential fields. The book enables researchers to measure valid data, select and apply appropriate analysis strategies, and avoid the most common mistakes when analyzing and interpreting EEG/ERP data. Importantly, it informs the research communities of the possibilities opened by these space-domain oriented approaches to the analysis of brain electrical activity, and of their potential to offer even more powerful diagnostic techniques when integrated with other clinically relevant data.

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Electrical Neuroimaging (Cambridge Medicine (Hardcover)), Christoph M. Michel, Lorena R.R. Gianotti, Thomas Koenig, Daniel Brandeis

Language
Released
2009
Binding
(Hardcover)
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Title
Electrical Neuroimaging (Cambridge Medicine (Hardcover))
Language
English
Released
2009
Format
Hardcover
Pages
250
ISBN10
0521879795
ISBN13
9780521879798
Series
Description
Electrical neuroimaging is based on the analysis of brain electrical activity recorded from the human scalp with multichannel EEG. It offers enormous potential for the dynamic mapping of brain functions, and for the non-invasive diagnosis of neurological and psychiatric conditions. This authoritative reference gives a systematic overview of new electrical imaging methods, with a sound introduction to the basics of multichannel recording of EEG and event-related potential (ERP) data, as well as spatio-temporal analysis of the potential fields. The book enables researchers to measure valid data, select and apply appropriate analysis strategies, and avoid the most common mistakes when analyzing and interpreting EEG/ERP data. Importantly, it informs the research communities of the possibilities opened by these space-domain oriented approaches to the analysis of brain electrical activity, and of their potential to offer even more powerful diagnostic techniques when integrated with other clinically relevant data.