On seeing the trees and the forest: Single-signal and multisignal analysis of periictal intracranial EEG.
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| Title: | On seeing the trees and the forest: Single-signal and multisignal analysis of periictal intracranial EEG. |
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| Authors: | Schindler, Kaspar, Gast, Heidemarie, Goodfellow, Marc, Rummel, Christian |
| Source: | Epilepsia (Series 4). Sep2012, Vol. 53 Issue 9, p1658-1668. 11p. |
| Subjects: | Electroencephalography, People with epilepsy, Brain function localization, Signal processing, Temporal lobe epilepsy, Clinical trials |
| Abstract: | Purpose: Epileptic seizures are associated with a dysregulation of electrical brain activity on many different spatial scales. To better understand the dynamics of epileptic seizures, that is, how the seizures initiate, propagate, and terminate, it is important to consider changes of electrical brain activity on different spatial scales. Herein we set out to analyze periictal electrical brain activity on comparatively small and large spatial scales by assessing changes in single intracranial electroencephalography (EEG) signals and of averaged interdependences of pairs of EEG signals. Methods: Single and multiple EEG signals are analyzed by combining methods from symbolic dynamics and information theory. This computationally efficient approach is chosen because at its core it consists of analyzing the occurrence of patterns and bears analogy to classical visual EEG reading. Symbolization is achieved by first mapping the EEG signals into bit strings, that is, long sequences of zeros and ones, depending solely on whether their amplitudes increase or decrease. Bit strings reflect relational aspects between consecutive values of the original EEG signals, but not the values themselves. For each bit string the relative frequencies of the different constituent short bit patterns are then determined and used to compute two information theoretical measures: (1) redundancy (R) of single bit strings characterizes electrical brain activity on a comparatively small spatial scale represented by a single EEG signal and (2) averaged pair-wise mutual information with all other bit strings (M), which allows tracking of larger-scale EEG dynamics. Key Findings: We analyzed 20 periictal intracranial EEG recordings from five patients with pharmacoresistant temporal lobe epilepsy. At seizure onset, R first strongly increased and then decreased toward seizure termination, whereas M gradually increased throughout the seizure. Bit strings with maximal R were always derived from EEG signals recorded from the visually identified seizure-onset zone. When compared to the bit strings derived from other EEG signals, their M was relatively smaller. These findings are consistent with a strong but transient occurrence of information-poor, that is, redundant electrical brain activity on a smaller spatial scale, which is particularly pronounced in the seizure-onset zone. On a larger spatial scale, a progressively more collective state emerges, as revealed by increasing amounts of mutual information. Significance: Information theoretical analysis of bit patterns derived from EEG signals helps to characterize periictal brain activity on different spatial scales in a quantitative and efficient way and may provide clinically relevant results. [ABSTRACT FROM AUTHOR] |
| Copyright of Epilepsia (Series 4) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: pbh DbLabel: Psychology and Behavioral Sciences Collection An: 79720904 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: On seeing the trees and the forest: Single-signal and multisignal analysis of periictal intracranial EEG. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Schindler%2C+Kaspar%22">Schindler, Kaspar</searchLink><br /><searchLink fieldCode="AR" term="%22Gast%2C+Heidemarie%22">Gast, Heidemarie</searchLink><br /><searchLink fieldCode="AR" term="%22Goodfellow%2C+Marc%22">Goodfellow, Marc</searchLink><br /><searchLink fieldCode="AR" term="%22Rummel%2C+Christian%22">Rummel, Christian</searchLink> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Epilepsia+%28Series+4%29%22">Epilepsia (Series 4)</searchLink>. Sep2012, Vol. 53 Issue 9, p1658-1668. 11p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Electroencephalography%22">Electroencephalography</searchLink><br /><searchLink fieldCode="DE" term="%22People+with+epilepsy%22">People with epilepsy</searchLink><br /><searchLink fieldCode="DE" term="%22Brain+function+localization%22">Brain function localization</searchLink><br /><searchLink fieldCode="DE" term="%22Signal+processing%22">Signal processing</searchLink><br /><searchLink fieldCode="DE" term="%22Temporal+lobe+epilepsy%22">Temporal lobe epilepsy</searchLink><br /><searchLink fieldCode="DE" term="%22Clinical+trials%22">Clinical trials</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Purpose: Epileptic seizures are associated with a dysregulation of electrical brain activity on many different spatial scales. To better understand the dynamics of epileptic seizures, that is, how the seizures initiate, propagate, and terminate, it is important to consider changes of electrical brain activity on different spatial scales. Herein we set out to analyze periictal electrical brain activity on comparatively small and large spatial scales by assessing changes in single intracranial electroencephalography (EEG) signals and of averaged interdependences of pairs of EEG signals. Methods: Single and multiple EEG signals are analyzed by combining methods from symbolic dynamics and information theory. This computationally efficient approach is chosen because at its core it consists of analyzing the occurrence of patterns and bears analogy to classical visual EEG reading. Symbolization is achieved by first mapping the EEG signals into bit strings, that is, long sequences of zeros and ones, depending solely on whether their amplitudes increase or decrease. Bit strings reflect relational aspects between consecutive values of the original EEG signals, but not the values themselves. For each bit string the relative frequencies of the different constituent short bit patterns are then determined and used to compute two information theoretical measures: (1) redundancy (R) of single bit strings characterizes electrical brain activity on a comparatively small spatial scale represented by a single EEG signal and (2) averaged pair-wise mutual information with all other bit strings (M), which allows tracking of larger-scale EEG dynamics. Key Findings: We analyzed 20 periictal intracranial EEG recordings from five patients with pharmacoresistant temporal lobe epilepsy. At seizure onset, R first strongly increased and then decreased toward seizure termination, whereas M gradually increased throughout the seizure. Bit strings with maximal R were always derived from EEG signals recorded from the visually identified seizure-onset zone. When compared to the bit strings derived from other EEG signals, their M was relatively smaller. These findings are consistent with a strong but transient occurrence of information-poor, that is, redundant electrical brain activity on a smaller spatial scale, which is particularly pronounced in the seizure-onset zone. On a larger spatial scale, a progressively more collective state emerges, as revealed by increasing amounts of mutual information. Significance: Information theoretical analysis of bit patterns derived from EEG signals helps to characterize periictal brain activity on different spatial scales in a quantitative and efficient way and may provide clinically relevant results. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Epilepsia (Series 4) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1111/j.1528-1167.2012.03588.x Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 11 StartPage: 1658 Subjects: – SubjectFull: Electroencephalography Type: general – SubjectFull: People with epilepsy Type: general – SubjectFull: Brain function localization Type: general – SubjectFull: Signal processing Type: general – SubjectFull: Temporal lobe epilepsy Type: general – SubjectFull: Clinical trials Type: general Titles: – TitleFull: On seeing the trees and the forest: Single-signal and multisignal analysis of periictal intracranial EEG. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Schindler, Kaspar – PersonEntity: Name: NameFull: Gast, Heidemarie – PersonEntity: Name: NameFull: Goodfellow, Marc – PersonEntity: Name: NameFull: Rummel, Christian IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 09 Text: Sep2012 Type: published Y: 2012 Identifiers: – Type: issn-print Value: 00139580 Numbering: – Type: volume Value: 53 – Type: issue Value: 9 Titles: – TitleFull: Epilepsia (Series 4) Type: main |
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