File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1007/978-3-642-13318-3_46
- Scopus: eid_2-s2.0-77954391094
- Find via
Supplementary
-
Citations:
- Scopus: 0
- Appears in Collections:
Conference Paper: Applications of second order blind identification to high-density EEG-based brain imaging: A review
Title | Applications of second order blind identification to high-density EEG-based brain imaging: A review |
---|---|
Authors | |
Keywords | BSS |
Issue Date | 2010 |
Citation | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2010, v. 6064 LNCS, n. PART 2, p. 368-377 How to Cite? |
Abstract | In the context of relating specific brain functions to specific brain structures, second-order blind identification (SOBI) is one of the blind source separation algorithms that have been validated extensively in the data domain of human high-density EEG. Here we provide a review of empirical data that (1) validate the claim that SOBI is capable of separating correlated neuronal sources from each other and from typical noise sources present during an EEG experiment; (2) demonstrating the range of experimental conditions under which SOBI is able to recover functionally and neuroanatomically meaningful sources; (3) demonstrating cross- as well as within-subjects (cross-time) reliability of SOBI-recovered sources; (4) demonstrating efficiency of SOBI separation of neuronal sources. We conclude that SOBI may offer neuroscientists as well as clinicians a cost-effective way to image the dynamics of brain activity in terms of signals originating from specific brain regions using the widely available EEG recording technique. © 2010 Springer-Verlag. |
Persistent Identifier | http://hdl.handle.net/10722/228101 |
ISSN | 2023 SCImago Journal Rankings: 0.606 |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Tang, Akaysha | - |
dc.date.accessioned | 2016-08-01T06:45:11Z | - |
dc.date.available | 2016-08-01T06:45:11Z | - |
dc.date.issued | 2010 | - |
dc.identifier.citation | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2010, v. 6064 LNCS, n. PART 2, p. 368-377 | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.uri | http://hdl.handle.net/10722/228101 | - |
dc.description.abstract | In the context of relating specific brain functions to specific brain structures, second-order blind identification (SOBI) is one of the blind source separation algorithms that have been validated extensively in the data domain of human high-density EEG. Here we provide a review of empirical data that (1) validate the claim that SOBI is capable of separating correlated neuronal sources from each other and from typical noise sources present during an EEG experiment; (2) demonstrating the range of experimental conditions under which SOBI is able to recover functionally and neuroanatomically meaningful sources; (3) demonstrating cross- as well as within-subjects (cross-time) reliability of SOBI-recovered sources; (4) demonstrating efficiency of SOBI separation of neuronal sources. We conclude that SOBI may offer neuroscientists as well as clinicians a cost-effective way to image the dynamics of brain activity in terms of signals originating from specific brain regions using the widely available EEG recording technique. © 2010 Springer-Verlag. | - |
dc.language | eng | - |
dc.relation.ispartof | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | - |
dc.subject | BSS | - |
dc.title | Applications of second order blind identification to high-density EEG-based brain imaging: A review | - |
dc.type | Conference_Paper | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1007/978-3-642-13318-3_46 | - |
dc.identifier.scopus | eid_2-s2.0-77954391094 | - |
dc.identifier.volume | 6064 LNCS | - |
dc.identifier.issue | PART 2 | - |
dc.identifier.spage | 368 | - |
dc.identifier.epage | 377 | - |
dc.identifier.eissn | 1611-3349 | - |
dc.identifier.issnl | 0302-9743 | - |