Paul L. Nunez and Ramesh Srinivasan
- Published in print:
- 2006
- Published Online:
- May 2009
- ISBN:
- 9780195050387
- eISBN:
- 9780199865673
- Item type:
- book
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195050387.001.0001
- Subject:
- Neuroscience, Neuroendocrine and Autonomic, Techniques
This text is the second edition of this book. It expands the widely acclaimed 1981 book, filling more gaps between EEG and the physical sciences. EEG opens a “window on the mind” by finding new ...
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This text is the second edition of this book. It expands the widely acclaimed 1981 book, filling more gaps between EEG and the physical sciences. EEG opens a “window on the mind” by finding new connections between psychology and physiology. Topics include synaptic sources, electrode placement, choice of reference, volume conduction, power and coherence, projection of scalp potentials to dura surface, dynamic signatures of conscious experience, and neural networks immersed in global fields of synaptic action.Less
This text is the second edition of this book. It expands the widely acclaimed 1981 book, filling more gaps between EEG and the physical sciences. EEG opens a “window on the mind” by finding new connections between psychology and physiology. Topics include synaptic sources, electrode placement, choice of reference, volume conduction, power and coherence, projection of scalp potentials to dura surface, dynamic signatures of conscious experience, and neural networks immersed in global fields of synaptic action.
Markus Ullsperger and Stefan Debener (eds)
- Published in print:
- 2010
- Published Online:
- May 2010
- ISBN:
- 9780195372731
- eISBN:
- 9780199776283
- Item type:
- book
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195372731.001.0001
- Subject:
- Neuroscience, Techniques
Systemic interactions in brain networks have been successfully studied in vivo using non-invasive methods such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), for ...
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Systemic interactions in brain networks have been successfully studied in vivo using non-invasive methods such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), for many years. The rate-limiting step, however, is that each method can only map selective aspects of brain function, while missing other key aspects. Furthermore, the inferences on neuronal processes and information flow are often rather indirect. By simultaneously combining both methods, the researcher is better able to make optimal use of their specific advantages while compensating for their disadvantages. In recent years, research has shifted and expanded, from demonstrating technical feasibility, to methodological issues of artifact control, new ways of analyzing and integrating data, and to applications for scientific and clinical questions. Combined EEG and fMRI methods now cover everything from physiological questions on the bases of the two recorded signals, to more specific questions on the mechanisms of certain cognitive and pathological functions like epileptic brain activity. Simultaneous EEG and fMRI provides the interested researcher with the tools to establish a simultaneous EEG-fMRI laboratory, as well as for those scientists who are interested in integrating electrophysiological and hemodynamic data. As evidenced by the diversity of topics presented, this is a dynamically developing field in which several approaches are being tested, validated, and compared. Chapters are dedicated to the physiological bases of the measured signals, technical setup, sources of artifacts and data de-noising, various approaches of data analysis and fusion, as well as applications. In addition, open questions and directions for future research are outlined.Less
Systemic interactions in brain networks have been successfully studied in vivo using non-invasive methods such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), for many years. The rate-limiting step, however, is that each method can only map selective aspects of brain function, while missing other key aspects. Furthermore, the inferences on neuronal processes and information flow are often rather indirect. By simultaneously combining both methods, the researcher is better able to make optimal use of their specific advantages while compensating for their disadvantages. In recent years, research has shifted and expanded, from demonstrating technical feasibility, to methodological issues of artifact control, new ways of analyzing and integrating data, and to applications for scientific and clinical questions. Combined EEG and fMRI methods now cover everything from physiological questions on the bases of the two recorded signals, to more specific questions on the mechanisms of certain cognitive and pathological functions like epileptic brain activity. Simultaneous EEG and fMRI provides the interested researcher with the tools to establish a simultaneous EEG-fMRI laboratory, as well as for those scientists who are interested in integrating electrophysiological and hemodynamic data. As evidenced by the diversity of topics presented, this is a dynamically developing field in which several approaches are being tested, validated, and compared. Chapters are dedicated to the physiological bases of the measured signals, technical setup, sources of artifacts and data de-noising, various approaches of data analysis and fusion, as well as applications. In addition, open questions and directions for future research are outlined.
Markus Ullsperger
- Published in print:
- 2010
- Published Online:
- May 2010
- ISBN:
- 9780195372731
- eISBN:
- 9780199776283
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195372731.003.0010
- Subject:
- Neuroscience, Techniques
This chapter gives an overview of data integration methods for simultaneous EEG-fMRI, in which EEG features are extracted and used to parametrically model the fMRI data. Up to now, variants of ...
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This chapter gives an overview of data integration methods for simultaneous EEG-fMRI, in which EEG features are extracted and used to parametrically model the fMRI data. Up to now, variants of EEG-informed fMRI analysis have been most widely and successfully applied. After a brief discussion of the rationale of this approach, its variants for ongoing and event-related EEG phenomena are explained. Studies applying EEG-informed fMRI are reviewed. The advantage of denoising methods such as independent component analysis allowing single-trial quantifications of the EEG phenomena of interest is discussed. To allow clear interpretations of covariations between electrophysiological and hemodynamic measures, further dependent variables such as behavioral data should be taken into account. The chapter closes with an outlook on future questions and ongoing methodological developments.Less
This chapter gives an overview of data integration methods for simultaneous EEG-fMRI, in which EEG features are extracted and used to parametrically model the fMRI data. Up to now, variants of EEG-informed fMRI analysis have been most widely and successfully applied. After a brief discussion of the rationale of this approach, its variants for ongoing and event-related EEG phenomena are explained. Studies applying EEG-informed fMRI are reviewed. The advantage of denoising methods such as independent component analysis allowing single-trial quantifications of the EEG phenomena of interest is discussed. To allow clear interpretations of covariations between electrophysiological and hemodynamic measures, further dependent variables such as behavioral data should be taken into account. The chapter closes with an outlook on future questions and ongoing methodological developments.
Helmut Laufs and Rachel Thornton
- Published in print:
- 2010
- Published Online:
- May 2010
- ISBN:
- 9780195372731
- eISBN:
- 9780199776283
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195372731.003.0018
- Subject:
- Neuroscience, Techniques
This chapter reviews the clinical application of electroencephalography/functional magnetic resonance imaging (EEG-fMRI) to epilepsy at two levels. Initially, it summarizes the body of primary ...
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This chapter reviews the clinical application of electroencephalography/functional magnetic resonance imaging (EEG-fMRI) to epilepsy at two levels. Initially, it summarizes the body of primary EEG/fMRI patient studies in epilepsy, focusing on the most comprehensive and up-to-date literature available. It then addresses the question of what researchers have learned about the potentials and limitations of this technique, which is still relatively new. Although EEG/fMRI has not lived up to some of its initial expectations, it will be seen that new avenues have appeared. The chapter concludes with a discussion of the immediate next steps, and an outlook on the future of the field.Less
This chapter reviews the clinical application of electroencephalography/functional magnetic resonance imaging (EEG-fMRI) to epilepsy at two levels. Initially, it summarizes the body of primary EEG/fMRI patient studies in epilepsy, focusing on the most comprehensive and up-to-date literature available. It then addresses the question of what researchers have learned about the potentials and limitations of this technique, which is still relatively new. Although EEG/fMRI has not lived up to some of its initial expectations, it will be seen that new avenues have appeared. The chapter concludes with a discussion of the immediate next steps, and an outlook on the future of the field.
Stefan Debener, Jeremy Thorne, Till R. Schneider, and Filipa Campos Viola
- Published in print:
- 2010
- Published Online:
- May 2010
- ISBN:
- 9780195372731
- eISBN:
- 9780199776283
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195372731.003.0008
- Subject:
- Neuroscience, Techniques
Independent component analysis (ICA) is a linear decomposition technique that aims to reveal the underlying statistical sources of mixed signals. The EEG signal consists of a mixture of various brain ...
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Independent component analysis (ICA) is a linear decomposition technique that aims to reveal the underlying statistical sources of mixed signals. The EEG signal consists of a mixture of various brain and non-brain contributions. Accordingly, a valid and powerful unmixing tool promises a better, more accessible representation of the statistical sources contributing to the mixed recorded signal. ICA, being potentially such a tool, may help in the detection of signal sources that cannot be identified on the raw data level alone using other, more conventional techniques. The application of ICA to EEG signals has become popular, as it provides two key features: it is a powerful way to remove artifacts from EEG data, and it helps to disentangle otherwise mixed brain signals. This chapter is concerned with evaluating and optimizing EEG decompositions by means of ICA. First, it discusses typical ICA results with reference to artifact- and brain-related components. Then, it elaborates on different EEG pre-processing steps, considered in light of the statistical assumptions underlying ICA. As such, the motivation for the chapter is to provide some practical guidelines for those researchers who wish to successfully decompose multi-channel EEG recordings.Less
Independent component analysis (ICA) is a linear decomposition technique that aims to reveal the underlying statistical sources of mixed signals. The EEG signal consists of a mixture of various brain and non-brain contributions. Accordingly, a valid and powerful unmixing tool promises a better, more accessible representation of the statistical sources contributing to the mixed recorded signal. ICA, being potentially such a tool, may help in the detection of signal sources that cannot be identified on the raw data level alone using other, more conventional techniques. The application of ICA to EEG signals has become popular, as it provides two key features: it is a powerful way to remove artifacts from EEG data, and it helps to disentangle otherwise mixed brain signals. This chapter is concerned with evaluating and optimizing EEG decompositions by means of ICA. First, it discusses typical ICA results with reference to artifact- and brain-related components. Then, it elaborates on different EEG pre-processing steps, considered in light of the statistical assumptions underlying ICA. As such, the motivation for the chapter is to provide some practical guidelines for those researchers who wish to successfully decompose multi-channel EEG recordings.
Roger D. Roger and Miles A. Whittington
- Published in print:
- 2010
- Published Online:
- May 2010
- ISBN:
- 9780195342796
- eISBN:
- 9780199776276
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195342796.003.0004
- Subject:
- Neuroscience, Molecular and Cellular Systems, Development
Epilepsy can be viewed from inter-related clinical and electrical/cellular points of view. Before and during a so-called electrographic seizure, neuronal events become both highly correlated ...
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Epilepsy can be viewed from inter-related clinical and electrical/cellular points of view. Before and during a so-called electrographic seizure, neuronal events become both highly correlated (synchronized) and also organized in time. The latter organization occurs over a wide range of frequencies. Prior to seizures, very fast oscillations (VFO, >70-80 Hz) occur, that are dependent on gap junctions. Understanding how VFO is generated may provide a therapeutic target.Less
Epilepsy can be viewed from inter-related clinical and electrical/cellular points of view. Before and during a so-called electrographic seizure, neuronal events become both highly correlated (synchronized) and also organized in time. The latter organization occurs over a wide range of frequencies. Prior to seizures, very fast oscillations (VFO, >70-80 Hz) occur, that are dependent on gap junctions. Understanding how VFO is generated may provide a therapeutic target.
Christoph M. Michel and Daniel Brandeis
- Published in print:
- 2010
- Published Online:
- May 2010
- ISBN:
- 9780195372731
- eISBN:
- 9780199776283
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195372731.003.0001
- Subject:
- Neuroscience, Techniques
This chapter focuses on the spatiotemporal aspects of the electroencephalography (EEG), and discusses the most important findings concerning the oscillations and the temporal dynamics of electrical ...
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This chapter focuses on the spatiotemporal aspects of the electroencephalography (EEG), and discusses the most important findings concerning the oscillations and the temporal dynamics of electrical activity. Topics discussed include neuronal generators, sources and spatial scales of EEG and event-related potential (ERP) activity, spatial field distributions, oscillations in brain networks, functional microstates of the brain, and EEG source imaging.Less
This chapter focuses on the spatiotemporal aspects of the electroencephalography (EEG), and discusses the most important findings concerning the oscillations and the temporal dynamics of electrical activity. Topics discussed include neuronal generators, sources and spatial scales of EEG and event-related potential (ERP) activity, spatial field distributions, oscillations in brain networks, functional microstates of the brain, and EEG source imaging.
Giancarlo Valente, Fabrizio Esposito, Federico de Martino, Rainer Goebel, and Elia Formisano
- Published in print:
- 2010
- Published Online:
- May 2010
- ISBN:
- 9780195372731
- eISBN:
- 9780199776283
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195372731.003.0009
- Subject:
- Neuroscience, Techniques
This chapter examines the most relevant aspects concerning the use of independent component analysis (ICA) for the analysis of functional magnetic resonance imaging (fMRI) data. In particular, after ...
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This chapter examines the most relevant aspects concerning the use of independent component analysis (ICA) for the analysis of functional magnetic resonance imaging (fMRI) data. In particular, after illustrating the fMRI-ICA model (“Problem formulation and application to fMRI”), the chapter compares the most commonly used ICA algorithms in the context of fMRI data analysis. The problems of choosing the dimensionality of the ICA decomposition, and of selecting the “meaningful” components, are considered. Optimizations of the ICA algorithms for dealing with the specific spatiotemporal properties of the fMRI data, and extensions of the ICA to multisubject fMRI studies, are described. For each of these aspects, different approaches from various groups are briefly reviewed.Less
This chapter examines the most relevant aspects concerning the use of independent component analysis (ICA) for the analysis of functional magnetic resonance imaging (fMRI) data. In particular, after illustrating the fMRI-ICA model (“Problem formulation and application to fMRI”), the chapter compares the most commonly used ICA algorithms in the context of fMRI data analysis. The problems of choosing the dimensionality of the ICA decomposition, and of selecting the “meaningful” components, are considered. Optimizations of the ICA algorithms for dealing with the specific spatiotemporal properties of the fMRI data, and extensions of the ICA to multisubject fMRI studies, are described. For each of these aspects, different approaches from various groups are briefly reviewed.
Paull Nunez
- Published in print:
- 2010
- Published Online:
- May 2010
- ISBN:
- 9780195340716
- eISBN:
- 9780199776269
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195340716.003.0005
- Subject:
- Neuroscience, Development
This chapter focuses on electroencephalography (EEG). The first EEG recordings from the human scalp were obtained in the early 1920s by the German psychiatrist Hans Berger. It took more than 10 years ...
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This chapter focuses on electroencephalography (EEG). The first EEG recordings from the human scalp were obtained in the early 1920s by the German psychiatrist Hans Berger. It took more than 10 years for the scientific community to accept Berger's scalp potentials as genuine brain signals rather than system noise or biological artifact like eye or muscle potentials. By 1950, EEG was widely viewed as a genuine window on the mind, with important applications in neurosurgery, neurology, and psychology. The dynamics of consciousness motivates emphasis on EEG with its excellent temporal resolution, whilst acknowledging the importance of complementary measures applied at different time and space scales.Less
This chapter focuses on electroencephalography (EEG). The first EEG recordings from the human scalp were obtained in the early 1920s by the German psychiatrist Hans Berger. It took more than 10 years for the scientific community to accept Berger's scalp potentials as genuine brain signals rather than system noise or biological artifact like eye or muscle potentials. By 1950, EEG was widely viewed as a genuine window on the mind, with important applications in neurosurgery, neurology, and psychology. The dynamics of consciousness motivates emphasis on EEG with its excellent temporal resolution, whilst acknowledging the importance of complementary measures applied at different time and space scales.
Paull Nunez
- Published in print:
- 2010
- Published Online:
- May 2010
- ISBN:
- 9780195340716
- eISBN:
- 9780199776269
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195340716.003.0006
- Subject:
- Neuroscience, Development
This chapter discusses EEG's shadows of thought, revealing a number of newly discovered relationships between mind and brain. A healthy consciousness seems to be associated with a proper “balance” ...
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This chapter discusses EEG's shadows of thought, revealing a number of newly discovered relationships between mind and brain. A healthy consciousness seems to be associated with a proper “balance” between the functional isolation of brain tissue and global integration; such balance is achieved only in states of high dynamic complexity. Lack of such dynamic balance due to faulty chemical (neurotransmitter) actions may be partly responsible for diseases like schizophrenia and Parkinson's.Less
This chapter discusses EEG's shadows of thought, revealing a number of newly discovered relationships between mind and brain. A healthy consciousness seems to be associated with a proper “balance” between the functional isolation of brain tissue and global integration; such balance is achieved only in states of high dynamic complexity. Lack of such dynamic balance due to faulty chemical (neurotransmitter) actions may be partly responsible for diseases like schizophrenia and Parkinson's.
Alan Gevins and Michael E. Smith
- Published in print:
- 2006
- Published Online:
- May 2009
- ISBN:
- 9780195177619
- eISBN:
- 9780199864683
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195177619.003.0002
- Subject:
- Neuroscience, Sensory and Motor Systems, Behavioral Neuroscience
This chapter considers the utility of the ongoing, scalp-recorded, human electroencephalogram (EEG) as a tool in neuroergonomics research and practice. It first describes how the spectral composition ...
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This chapter considers the utility of the ongoing, scalp-recorded, human electroencephalogram (EEG) as a tool in neuroergonomics research and practice. It first describes how the spectral composition of the EEG changes in response to variations in task difficulty or level of alertness during highly controlled cognitive tasks. It also considers methods for analysis of such signals that might be suitable for use in a continuous monitoring context. Finally, it reviews generalizations of those methods to assess complex, computer-based tasks that are more representative of real-world tasks.Less
This chapter considers the utility of the ongoing, scalp-recorded, human electroencephalogram (EEG) as a tool in neuroergonomics research and practice. It first describes how the spectral composition of the EEG changes in response to variations in task difficulty or level of alertness during highly controlled cognitive tasks. It also considers methods for analysis of such signals that might be suitable for use in a continuous monitoring context. Finally, it reviews generalizations of those methods to assess complex, computer-based tasks that are more representative of real-world tasks.
Thalía Harmony, Alfonso Alba, José Luis Marroquín, Antonio Fernández-Bouzas, Gloria Avecilla, Josefina Ricardo-Garcell, Efraín Santiago-Rodríguez, Gloria Otero, Eneida Porras-Kattz, and Thalía Fernández
- Published in print:
- 2008
- Published Online:
- May 2009
- ISBN:
- 9780195369007
- eISBN:
- 9780199865253
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195369007.003.0006
- Subject:
- Neuroscience, Molecular and Cellular Systems, Development
Electroencephalographic (EEG) waves recorded from the scalp are integrated excitatory and inhibitory postsynaptic potentials of neuronal membranes. They reflect extracellular currents caused by ...
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Electroencephalographic (EEG) waves recorded from the scalp are integrated excitatory and inhibitory postsynaptic potentials of neuronal membranes. They reflect extracellular currents caused by synchronized neural activity within the local brain volume. This chapter gives an overview of the normal and abnormal development of the EEG during the first year after birth. The power and synchrony of background EEG oscillations provide important information in relation to normal and abnormal brain development. Gamma activity increases during the first year of age in normal infants more than in infants with leukomalacia, which may be related to cognitive development. The study of auditory- and speech-induced EEG oscillations may be useful for the early evaluation of infants at risk of language disorders.Less
Electroencephalographic (EEG) waves recorded from the scalp are integrated excitatory and inhibitory postsynaptic potentials of neuronal membranes. They reflect extracellular currents caused by synchronized neural activity within the local brain volume. This chapter gives an overview of the normal and abnormal development of the EEG during the first year after birth. The power and synchrony of background EEG oscillations provide important information in relation to normal and abnormal brain development. Gamma activity increases during the first year of age in normal infants more than in infants with leukomalacia, which may be related to cognitive development. The study of auditory- and speech-induced EEG oscillations may be useful for the early evaluation of infants at risk of language disorders.
Jan Bures
- Published in print:
- 1998
- Published Online:
- January 2008
- ISBN:
- 9780198523475
- eISBN:
- 9780191712678
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780198523475.003.0004
- Subject:
- Psychology, Neuropsychology
A striking feature of CTA is that the eliciting US can be applied to a rat anaesthetized for more then 30 minutes after the gustatory CS. On the other hand, CS administration during narcosis prevents ...
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A striking feature of CTA is that the eliciting US can be applied to a rat anaesthetized for more then 30 minutes after the gustatory CS. On the other hand, CS administration during narcosis prevents CTA. Similar blockade can also be achieved by hypothermia below 32°C. If the block is induced after CS presentation, its application during administration of the US does not block CTA formation. Another useful functional ablation procedure is spreading EEG depression, which blocks cortical and subcortical structures (amygdala, basal ganglia) when applied during action of the gustatory CS but does not mitigate the US. Still clearer is the effect of local anaesthetics on brain centers. Injection of 10 ng tetrodotoxin (TTX) into the insular cortex causing a block of proteosynthesis by anisomycin does not interfere with CS drinking but prevents CTA formation. Continuation of the consolidation process is indicated by increased activity (+40%) of the protein kinase C (PKC) in PBN 24h to 48h after a single saccharin-LiCl pairing.Less
A striking feature of CTA is that the eliciting US can be applied to a rat anaesthetized for more then 30 minutes after the gustatory CS. On the other hand, CS administration during narcosis prevents CTA. Similar blockade can also be achieved by hypothermia below 32°C. If the block is induced after CS presentation, its application during administration of the US does not block CTA formation. Another useful functional ablation procedure is spreading EEG depression, which blocks cortical and subcortical structures (amygdala, basal ganglia) when applied during action of the gustatory CS but does not mitigate the US. Still clearer is the effect of local anaesthetics on brain centers. Injection of 10 ng tetrodotoxin (TTX) into the insular cortex causing a block of proteosynthesis by anisomycin does not interfere with CS drinking but prevents CTA formation. Continuation of the consolidation process is indicated by increased activity (+40%) of the protein kinase C (PKC) in PBN 24h to 48h after a single saccharin-LiCl pairing.
Arnold J. Wilkins
- Published in print:
- 1995
- Published Online:
- January 2008
- ISBN:
- 9780198521747
- eISBN:
- 9780191706691
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780198521747.003.0002
- Subject:
- Psychology, Cognitive Neuroscience
About 4% of patients with epilepsy are susceptible to visually induced seizures. The visual stimulation responsible includes both flickering light and stationary steadily illuminated patterns, ...
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About 4% of patients with epilepsy are susceptible to visually induced seizures. The visual stimulation responsible includes both flickering light and stationary steadily illuminated patterns, usually of stripes. The seizures can start in the visual cortex of one cerebral hemisphere, or both hemispheres independently. The seizures occur when normal physiological excitation from visual stimuli involves more than a critical cortical area, particularly when the excitation is rhythmic.Less
About 4% of patients with epilepsy are susceptible to visually induced seizures. The visual stimulation responsible includes both flickering light and stationary steadily illuminated patterns, usually of stripes. The seizures can start in the visual cortex of one cerebral hemisphere, or both hemispheres independently. The seizures occur when normal physiological excitation from visual stimuli involves more than a critical cortical area, particularly when the excitation is rhythmic.
Partha Mitra and Hemant Bokil
- Published in print:
- 2007
- Published Online:
- May 2009
- ISBN:
- 9780195178081
- eISBN:
- 9780199864829
- Item type:
- book
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195178081.001.0001
- Subject:
- Neuroscience, Techniques, Molecular and Cellular Systems
The biomedical sciences have recently undergone revolutionary change, due to the ability to digitize and store large data sets. In neuroscience, the data sources include measurements of neural ...
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The biomedical sciences have recently undergone revolutionary change, due to the ability to digitize and store large data sets. In neuroscience, the data sources include measurements of neural activity measured using electrode arrays, EEG and MEG, brain imaging data from PET, fMRI, and optical imaging methods. Analysis, visualization, and management of these time series data sets is a growing field of research that has become increasingly important both for experimentalists and theorists interested in brain function. The first part of the book contains a set of chapters which provide non-technical conceptual background to the subject. Salient features include the adoption of an active perspective of the nervous system, an emphasis on function, and a brief survey of different theoretical accounts in neuroscience. The second part is the longest in the book, and contains a refresher course in mathematics and statistics leading up to time series analysis techniques. The third part contains applications of data analysis techniques to the range of data sources indicated above, and the fourth part contains special topics.Less
The biomedical sciences have recently undergone revolutionary change, due to the ability to digitize and store large data sets. In neuroscience, the data sources include measurements of neural activity measured using electrode arrays, EEG and MEG, brain imaging data from PET, fMRI, and optical imaging methods. Analysis, visualization, and management of these time series data sets is a growing field of research that has become increasingly important both for experimentalists and theorists interested in brain function. The first part of the book contains a set of chapters which provide non-technical conceptual background to the subject. Salient features include the adoption of an active perspective of the nervous system, an emphasis on function, and a brief survey of different theoretical accounts in neuroscience. The second part is the longest in the book, and contains a refresher course in mathematics and statistics leading up to time series analysis techniques. The third part contains applications of data analysis techniques to the range of data sources indicated above, and the fourth part contains special topics.
Michael S. Pardo and Dennis Patterson
- Published in print:
- 2013
- Published Online:
- January 2014
- ISBN:
- 9780199812134
- eISBN:
- 9780199368594
- Item type:
- book
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780199812134.001.0001
- Subject:
- Law, Philosophy of Law, Medical Law
As neuroscientific technologies continue to develop and inform our understanding of the mind, the opportunities for applying neuroscience in legal proceedings have also increased. Cognitive ...
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As neuroscientific technologies continue to develop and inform our understanding of the mind, the opportunities for applying neuroscience in legal proceedings have also increased. Cognitive neuroscientists have deepened our understanding of the complex relationship between the mind and the brain by using new techniques such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). The inferences drawn from these findings and increasingly sophisticated technologies are being applied to debates and processes in the legal field, from lie detection in criminal trials to critical legal doctrines surrounding the insanity defense or guilt adjudication. This book assesses the philosophical questions that arise when neuroscientific research and technology are applied in the legal system. It examines the arguments favoring the increased use of neuroscience in law, the means for assessing its reliability in legal proceedings, and the integration of neuroscientific research into substantive legal doctrines. The book uses its explorations to inform a corrective inquiry into the mistaken inferences and conceptual errors that arise from mismatched concepts, such as the mental disconnect of what constitutes “lying” on a lie detection test. The empirical, practical, ethical, and conceptual issues this text seeks to redress will deeply influence how we negotiate and implement the fruits of neuroscience in law and policy in the future.Less
As neuroscientific technologies continue to develop and inform our understanding of the mind, the opportunities for applying neuroscience in legal proceedings have also increased. Cognitive neuroscientists have deepened our understanding of the complex relationship between the mind and the brain by using new techniques such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). The inferences drawn from these findings and increasingly sophisticated technologies are being applied to debates and processes in the legal field, from lie detection in criminal trials to critical legal doctrines surrounding the insanity defense or guilt adjudication. This book assesses the philosophical questions that arise when neuroscientific research and technology are applied in the legal system. It examines the arguments favoring the increased use of neuroscience in law, the means for assessing its reliability in legal proceedings, and the integration of neuroscientific research into substantive legal doctrines. The book uses its explorations to inform a corrective inquiry into the mistaken inferences and conceptual errors that arise from mismatched concepts, such as the mental disconnect of what constitutes “lying” on a lie detection test. The empirical, practical, ethical, and conceptual issues this text seeks to redress will deeply influence how we negotiate and implement the fruits of neuroscience in law and policy in the future.
Antonio Giuditta, Paola Mandile, Paola Montagnese, Stefania Piscopo, and Stefania Vescia
- Published in print:
- 2003
- Published Online:
- September 2009
- ISBN:
- 9780198574002
- eISBN:
- 9780191724145
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780198574002.003.0009
- Subject:
- Neuroscience, Behavioral Neuroscience
Slow wave sleep (SWS) was the first type of sleep to be described in human subjects by its high-amplitude, low-frequency electroencephalographic (EEG) waves, that sharply contrasted with the ...
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Slow wave sleep (SWS) was the first type of sleep to be described in human subjects by its high-amplitude, low-frequency electroencephalographic (EEG) waves, that sharply contrasted with the low-amplitude, high-frequency waves of active waking or wakefulness (W). Conversely, the later discovery of REM sleep was based on the occurrence of periodic episodes of rapid eye movements (REM) associated with a desynchronized EEG pattern resembling W. As this similarity envisaged an obvious paradox, REM sleep came to be also known as paradoxical sleep (PS). It is perhaps less well known that the discovery of PS elicited a remarkable wave of interest in its features that greatly contributed to highlight their relevance but, by contrast, outshadowed the role of SWS. This chapter discusses the evidence supporting the participation of SWS in memory processing, and the hypotheses concerning the roles of SWS and PS.Less
Slow wave sleep (SWS) was the first type of sleep to be described in human subjects by its high-amplitude, low-frequency electroencephalographic (EEG) waves, that sharply contrasted with the low-amplitude, high-frequency waves of active waking or wakefulness (W). Conversely, the later discovery of REM sleep was based on the occurrence of periodic episodes of rapid eye movements (REM) associated with a desynchronized EEG pattern resembling W. As this similarity envisaged an obvious paradox, REM sleep came to be also known as paradoxical sleep (PS). It is perhaps less well known that the discovery of PS elicited a remarkable wave of interest in its features that greatly contributed to highlight their relevance but, by contrast, outshadowed the role of SWS. This chapter discusses the evidence supporting the participation of SWS in memory processing, and the hypotheses concerning the roles of SWS and PS.
Partha P. Mitra and Hemant Bokil
- Published in print:
- 2007
- Published Online:
- May 2009
- ISBN:
- 9780195178081
- eISBN:
- 9780199864829
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195178081.003.0010
- Subject:
- Neuroscience, Techniques, Molecular and Cellular Systems
Electroencephalography (EEG) and magnetoencephalography (MEG) provide the most direct noninvasive methods for studying the dynamics of brain function. EEG is also the area of neuroscience that has ...
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Electroencephalography (EEG) and magnetoencephalography (MEG) provide the most direct noninvasive methods for studying the dynamics of brain function. EEG is also the area of neuroscience that has traditionally had the closest contact with time series analysis techniques. This chapter begins with a brief discussion of early references in the application of time series analysis techniques to the analysis of EEG data. It then discusses the physics of EEG and MEG signals, the measurement techniques, and noise sources. Following this, the analysis of issues connected to denoising of these datasets is discussed. Finally, the discussion of time series analysis methods from Chapter 8 is extended using EEG and MEG data.Less
Electroencephalography (EEG) and magnetoencephalography (MEG) provide the most direct noninvasive methods for studying the dynamics of brain function. EEG is also the area of neuroscience that has traditionally had the closest contact with time series analysis techniques. This chapter begins with a brief discussion of early references in the application of time series analysis techniques to the analysis of EEG data. It then discusses the physics of EEG and MEG signals, the measurement techniques, and noise sources. Following this, the analysis of issues connected to denoising of these datasets is discussed. Finally, the discussion of time series analysis methods from Chapter 8 is extended using EEG and MEG data.
Paul L. Nunez and Ramesh Srinivasan
- Published in print:
- 2006
- Published Online:
- May 2009
- ISBN:
- 9780195050387
- eISBN:
- 9780199865673
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195050387.003.0001
- Subject:
- Neuroscience, Neuroendocrine and Autonomic, Techniques
This chapter presents an overview of the physical and physiological bases for the electric potentials recorded from the human scalp, called electroencephalography or EEG. EEG applications in the ...
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This chapter presents an overview of the physical and physiological bases for the electric potentials recorded from the human scalp, called electroencephalography or EEG. EEG applications in the clinical and cognitive sciences are outlined. Several dynamic properties of important phenomena—the human alpha rhythms—are outlined. A proposed conceptual framework for EEG generation is based on cell assemblies (neural networks) embedded in synaptic action fields, analogous to social networks embedded in a culture. Excitatory and inhibitory synaptic action fields are defined simply in terms of the number of active synapses in each cortical tissue mass or volume element, irrespective of functional significance. Interactions between the synaptic fields and networks provide a means for disparate networks to couple, a picture directly addressing the so-called binding problem of brain science. Elementary features of volume conduction are also discussed: currents, voltages, Ohm's law, reference electrodes, current sources, dipoles, dipole layers, source synchrony, and reference electrodes.Less
This chapter presents an overview of the physical and physiological bases for the electric potentials recorded from the human scalp, called electroencephalography or EEG. EEG applications in the clinical and cognitive sciences are outlined. Several dynamic properties of important phenomena—the human alpha rhythms—are outlined. A proposed conceptual framework for EEG generation is based on cell assemblies (neural networks) embedded in synaptic action fields, analogous to social networks embedded in a culture. Excitatory and inhibitory synaptic action fields are defined simply in terms of the number of active synapses in each cortical tissue mass or volume element, irrespective of functional significance. Interactions between the synaptic fields and networks provide a means for disparate networks to couple, a picture directly addressing the so-called binding problem of brain science. Elementary features of volume conduction are also discussed: currents, voltages, Ohm's law, reference electrodes, current sources, dipoles, dipole layers, source synchrony, and reference electrodes.
Paul L. Nunez and Ramesh Srinivasan
- Published in print:
- 2006
- Published Online:
- May 2009
- ISBN:
- 9780195050387
- eISBN:
- 9780199865673
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195050387.003.0002
- Subject:
- Neuroscience, Neuroendocrine and Autonomic, Techniques
The highly interdisciplinary nature of EEG is apparently the main reason why many fallacies have appeared in EEG and, in some cases, persisted over long periods. Common EEG fallacies occur on both ...
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The highly interdisciplinary nature of EEG is apparently the main reason why many fallacies have appeared in EEG and, in some cases, persisted over long periods. Common EEG fallacies occur on both side of the normal division between the physical and biological sciences. This chapter presents a summary of fallacies with minimal supporting arguments, which are considered in more detail throughout the book. Topics include: the chauvinism of spatial scale (the attitude that data recorded at one scale is more scientific than others), the myth of the quiet reference, use and misuse of mathematical models, the EEG folklore, appropriate and inappropriate methods of EEG data analysis, the often-adopted mantra “artifact-free” data, the extreme non-uniqueness and (often) unreliability of source localization, advantages and limitations of high resolution EEG, over-promotion of brain magnetic field recordings (MEG), and “pacemaker” icons adopted as a psychological crutch to avoid genuine scientific issues.Less
The highly interdisciplinary nature of EEG is apparently the main reason why many fallacies have appeared in EEG and, in some cases, persisted over long periods. Common EEG fallacies occur on both side of the normal division between the physical and biological sciences. This chapter presents a summary of fallacies with minimal supporting arguments, which are considered in more detail throughout the book. Topics include: the chauvinism of spatial scale (the attitude that data recorded at one scale is more scientific than others), the myth of the quiet reference, use and misuse of mathematical models, the EEG folklore, appropriate and inappropriate methods of EEG data analysis, the often-adopted mantra “artifact-free” data, the extreme non-uniqueness and (often) unreliability of source localization, advantages and limitations of high resolution EEG, over-promotion of brain magnetic field recordings (MEG), and “pacemaker” icons adopted as a psychological crutch to avoid genuine scientific issues.
