Rapp, P E; Keyser, D O; Albano, A; Hernandez, R; Gibson, D B; Zambon, R A; David Hairston, W; Hughes, J D; Krystal, A; Nichols, A S
Traumatic brain injury detection using electrophysiological methods Journal Article
In: Frontiers in Human Neuroscience, vol. 9, no. FEB, 2015.
Abstract | Links | BibTeX | Tags: Article, brain electrophysiology, computer assisted tomography, Concussion, connectome, diagnostic accuracy, EEG, electroencephalogram, Electroencephalography, event related potential, Event-Related Potentials, evidence based medicine, executive function, human, intermethod comparison, latent period, neuroimaging, neuropathology, Non-linear dynamical analysis, nuclear magnetic resonance imaging, QEEG, Signal Processing, traumatic brain injury
@article{Rapp2015,
title = {Traumatic brain injury detection using electrophysiological methods},
author = {Rapp, P E and Keyser, D O and Albano, A and Hernandez, R and Gibson, D B and Zambon, R A and {David Hairston}, W and Hughes, J D and Krystal, A and Nichols, A S},
doi = {10.3389/fnhum.2015.00011},
year = {2015},
date = {2015-01-01},
journal = {Frontiers in Human Neuroscience},
volume = {9},
number = {FEB},
abstract = {Measuring neuronal activity with electrophysiological methods may be useful in detecting neurological dysfunctions, such as mild traumatic brain injury (mTBI).This approach may be particularly valuable for rapid detection in at-risk populations including military service members and athletes. Electrophysiological methods, such as quantitative electroencephalography (qEEG) and recording event-related potentials (ERPs) may be promising; however, the field is nascent and significant controversy exists on the efficacy and accuracy of the approaches as diagnostic tools. For example, the specific measures derived from an electroencephalogram (EEG) that are most suitable as markers of dysfunction have not been clearly established. A study was conducted to summarize and evaluate the statistical rigor of evidence on the overall utility of qEEG as an mTBI detection tool. The analysis evaluated qEEG measures/parameters that may be most suitable as fieldable diagnostic tools, identified other types of EEG measures and analysis methods of promise, recommended specific measures and analysis methods for further development as mTBI detection tools, identified research gaps in the field, and recommended future research and development thrust areas. The qEEG study group formed the following conclusions: (1) Individual qEEG measures provide limited diagnostic utility for mTBI. However, many measures can be important features of qEEG discriminant functions, which do show significant promise as mTBI detection tools. (2) ERPs offer utility in mTBI detection. In fact, evidence indicates that ERPs can identify abnormalities in cases where EEGs alone are non-disclosing. (3)The standard mathematical procedures used in the characterization of mTBI EEGs should be expanded to incorporate newer methods of analysis including non-linear dynamical analysis, complexity measures, analysis of causal interactions, graph theory, and information dynamics. (4) Reports of high specificity in qEEG evaluations of TBI must be interpreted with care. High specificities have been reported in carefully constructed clinical studies in which healthy controls were compared against a carefully selected TBI population. The published literature indicates, however, that similar abnormalities in qEEG measures are observed in other neuropsychiatric disorders. While it may be possible to distinguish a clinical patient from a healthy control participant with this technology, these measures are unlikely to discriminate between, for example, major depressive disorder, bipolar disorder, or TBI. The specificities observed in these clinical studies may well be lost in real world clinical practice. (5)The absence of specificity does not preclude clinical utility. The possibility of use as a longitudinal measure of treatment response remains. However, efficacy as a longitudinal clinical measure does require acceptable test-retest reliability. To date, very few test-retest reliability studies have been published with qEEG data obtained from TBI patients or from healthy controls. This is a particular concern because high variability is a known characteristic of the injured central nervous system. © 2015 Rapp, Keyser , Albano, Hernandez, Gibson, Zambon, Hairston, Hughes, Krystal and Nichols.},
keywords = {Article, brain electrophysiology, computer assisted tomography, Concussion, connectome, diagnostic accuracy, EEG, electroencephalogram, Electroencephalography, event related potential, Event-Related Potentials, evidence based medicine, executive function, human, intermethod comparison, latent period, neuroimaging, neuropathology, Non-linear dynamical analysis, nuclear magnetic resonance imaging, QEEG, Signal Processing, traumatic brain injury},
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Rapp, P E; Keyser, D O; Albano, A; Hernandez, R; Gibson, D B; Zambon, R A; David Hairston, W; Hughes, J D; Krystal, A; Nichols, A S
Traumatic brain injury detection using electrophysiological methods Journal Article
In: Frontiers in Human Neuroscience, vol. 9, no. FEB, 2015.
@article{Rapp2015,
title = {Traumatic brain injury detection using electrophysiological methods},
author = {Rapp, P E and Keyser, D O and Albano, A and Hernandez, R and Gibson, D B and Zambon, R A and {David Hairston}, W and Hughes, J D and Krystal, A and Nichols, A S},
doi = {10.3389/fnhum.2015.00011},
year = {2015},
date = {2015-01-01},
journal = {Frontiers in Human Neuroscience},
volume = {9},
number = {FEB},
abstract = {Measuring neuronal activity with electrophysiological methods may be useful in detecting neurological dysfunctions, such as mild traumatic brain injury (mTBI).This approach may be particularly valuable for rapid detection in at-risk populations including military service members and athletes. Electrophysiological methods, such as quantitative electroencephalography (qEEG) and recording event-related potentials (ERPs) may be promising; however, the field is nascent and significant controversy exists on the efficacy and accuracy of the approaches as diagnostic tools. For example, the specific measures derived from an electroencephalogram (EEG) that are most suitable as markers of dysfunction have not been clearly established. A study was conducted to summarize and evaluate the statistical rigor of evidence on the overall utility of qEEG as an mTBI detection tool. The analysis evaluated qEEG measures/parameters that may be most suitable as fieldable diagnostic tools, identified other types of EEG measures and analysis methods of promise, recommended specific measures and analysis methods for further development as mTBI detection tools, identified research gaps in the field, and recommended future research and development thrust areas. The qEEG study group formed the following conclusions: (1) Individual qEEG measures provide limited diagnostic utility for mTBI. However, many measures can be important features of qEEG discriminant functions, which do show significant promise as mTBI detection tools. (2) ERPs offer utility in mTBI detection. In fact, evidence indicates that ERPs can identify abnormalities in cases where EEGs alone are non-disclosing. (3)The standard mathematical procedures used in the characterization of mTBI EEGs should be expanded to incorporate newer methods of analysis including non-linear dynamical analysis, complexity measures, analysis of causal interactions, graph theory, and information dynamics. (4) Reports of high specificity in qEEG evaluations of TBI must be interpreted with care. High specificities have been reported in carefully constructed clinical studies in which healthy controls were compared against a carefully selected TBI population. The published literature indicates, however, that similar abnormalities in qEEG measures are observed in other neuropsychiatric disorders. While it may be possible to distinguish a clinical patient from a healthy control participant with this technology, these measures are unlikely to discriminate between, for example, major depressive disorder, bipolar disorder, or TBI. The specificities observed in these clinical studies may well be lost in real world clinical practice. (5)The absence of specificity does not preclude clinical utility. The possibility of use as a longitudinal measure of treatment response remains. However, efficacy as a longitudinal clinical measure does require acceptable test-retest reliability. To date, very few test-retest reliability studies have been published with qEEG data obtained from TBI patients or from healthy controls. This is a particular concern because high variability is a known characteristic of the injured central nervous system. © 2015 Rapp, Keyser , Albano, Hernandez, Gibson, Zambon, Hairston, Hughes, Krystal and Nichols.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Rapp, P E; Keyser, D O; Albano, A; Hernandez, R; Gibson, D B; Zambon, R A; David Hairston, W; Hughes, J D; Krystal, A; Nichols, A S
Traumatic brain injury detection using electrophysiological methods Journal Article
In: Frontiers in Human Neuroscience, vol. 9, no. FEB, 2015.
Abstract | Links | BibTeX | Tags: Article, brain electrophysiology, computer assisted tomography, Concussion, connectome, diagnostic accuracy, EEG, electroencephalogram, Electroencephalography, event related potential, Event-Related Potentials, evidence based medicine, executive function, human, intermethod comparison, latent period, neuroimaging, neuropathology, Non-linear dynamical analysis, nuclear magnetic resonance imaging, QEEG, Signal Processing, traumatic brain injury
@article{Rapp2015,
title = {Traumatic brain injury detection using electrophysiological methods},
author = {Rapp, P E and Keyser, D O and Albano, A and Hernandez, R and Gibson, D B and Zambon, R A and {David Hairston}, W and Hughes, J D and Krystal, A and Nichols, A S},
doi = {10.3389/fnhum.2015.00011},
year = {2015},
date = {2015-01-01},
journal = {Frontiers in Human Neuroscience},
volume = {9},
number = {FEB},
abstract = {Measuring neuronal activity with electrophysiological methods may be useful in detecting neurological dysfunctions, such as mild traumatic brain injury (mTBI).This approach may be particularly valuable for rapid detection in at-risk populations including military service members and athletes. Electrophysiological methods, such as quantitative electroencephalography (qEEG) and recording event-related potentials (ERPs) may be promising; however, the field is nascent and significant controversy exists on the efficacy and accuracy of the approaches as diagnostic tools. For example, the specific measures derived from an electroencephalogram (EEG) that are most suitable as markers of dysfunction have not been clearly established. A study was conducted to summarize and evaluate the statistical rigor of evidence on the overall utility of qEEG as an mTBI detection tool. The analysis evaluated qEEG measures/parameters that may be most suitable as fieldable diagnostic tools, identified other types of EEG measures and analysis methods of promise, recommended specific measures and analysis methods for further development as mTBI detection tools, identified research gaps in the field, and recommended future research and development thrust areas. The qEEG study group formed the following conclusions: (1) Individual qEEG measures provide limited diagnostic utility for mTBI. However, many measures can be important features of qEEG discriminant functions, which do show significant promise as mTBI detection tools. (2) ERPs offer utility in mTBI detection. In fact, evidence indicates that ERPs can identify abnormalities in cases where EEGs alone are non-disclosing. (3)The standard mathematical procedures used in the characterization of mTBI EEGs should be expanded to incorporate newer methods of analysis including non-linear dynamical analysis, complexity measures, analysis of causal interactions, graph theory, and information dynamics. (4) Reports of high specificity in qEEG evaluations of TBI must be interpreted with care. High specificities have been reported in carefully constructed clinical studies in which healthy controls were compared against a carefully selected TBI population. The published literature indicates, however, that similar abnormalities in qEEG measures are observed in other neuropsychiatric disorders. While it may be possible to distinguish a clinical patient from a healthy control participant with this technology, these measures are unlikely to discriminate between, for example, major depressive disorder, bipolar disorder, or TBI. The specificities observed in these clinical studies may well be lost in real world clinical practice. (5)The absence of specificity does not preclude clinical utility. The possibility of use as a longitudinal measure of treatment response remains. However, efficacy as a longitudinal clinical measure does require acceptable test-retest reliability. To date, very few test-retest reliability studies have been published with qEEG data obtained from TBI patients or from healthy controls. This is a particular concern because high variability is a known characteristic of the injured central nervous system. © 2015 Rapp, Keyser , Albano, Hernandez, Gibson, Zambon, Hairston, Hughes, Krystal and Nichols.},
keywords = {Article, brain electrophysiology, computer assisted tomography, Concussion, connectome, diagnostic accuracy, EEG, electroencephalogram, Electroencephalography, event related potential, Event-Related Potentials, evidence based medicine, executive function, human, intermethod comparison, latent period, neuroimaging, neuropathology, Non-linear dynamical analysis, nuclear magnetic resonance imaging, QEEG, Signal Processing, traumatic brain injury},
pubstate = {published},
tppubtype = {article}
}