References

2016

Hyden, J; Petty, B

Sideline Management of Concussion Journal Article

In: Physical Medicine & Rehabilitation Clinics of North America, vol. 27, no. 2, pp. 395–409, 2016.

Links | BibTeX | Tags: anamnesis, athlete, Balance, Balance Error Scoring System, brain concussion, Concussion, Electroencephalography, human, King Devick Test, neurologic examination, neuropsychological test, Physical Examination, priority journal, response time, Review, SCAT3, scoring system, sensor, Sensory Organization Test, Sideline, sport concussion assessment tool, Standardized Assessment of Concussion, symptom, Symptom scale, virtual reality, Vision

Beiske, K K; Kostov, K H; Kostov, H

Rhythmic midtemporal discharge in a youth during light sleep Journal Article

In: Neurodiagnostic Journal, vol. 56, no. 1, pp. 32–36, 2016.

Abstract | Links | BibTeX | Tags: Adolescent, Article, Automobile Driving, Benign EEG pattern, car driving, case report, case reports, complication, computer assisted tomography, Concussion, Craniocerebral Trauma, drowsiness, EEG pattern, electroencephalogram, Electroencephalography, Epilepsy, epileptic discharge, febrile convulsion, football, Functional Laterality, head injury, hemispheric dominance, human, Humans, hyperventilation, Injuries, Light sleep, Male, neuroimaging, neurologic examination, nuclear magnetic resonance imaging, Pathophysiology, Patient treatment, Rhythmic midtemporal discharge, RMTD, SLEEP, Sleep research, spike wave, temporal lobe, temporal lobe epilepsy, theta rhythm, tonic clonic seizure, unconsciousness, wakefulness

Kontos, A P; Reches, A; Elbin, R J; Dickman, D; Laufer, I; Geva, A B; Shacham, G; DeWolf, R; Collins, M W

Preliminary evidence of reduced brain network activation in patients with post-traumatic migraine following concussion Journal Article

In: Brain Imaging & Behavior, vol. 10, no. 2, pp. 594–603, 2016.

Abstract | Links | BibTeX | Tags: Brain network activation, Electroencephalography, Post-traumatic migraine, Sport-related concussion

@article{Kontos2016d,

title = {Preliminary evidence of reduced brain network activation in patients with post-traumatic migraine following concussion},

author = {Kontos, A P and Reches, A and Elbin, R J and Dickman, D and Laufer, I and Geva, A B and Shacham, G and DeWolf, R and Collins, M W},

doi = {10.1007/s11682-015-9412-6},

year  = {2016},

date = {2016-01-01},

journal = {Brain Imaging \& Behavior},

volume = {10},

number = {2},

pages = {594--603},

abstract = {Post-traumatic migraine (PTM) (i.e., headache, nausea, light and/or noise sensitivity) is an emerging risk factor for prolonged recovery following concussion. Concussions and migraine share similar pathophysiology characterized by specific ionic imbalances in the brain. Given these similarities, patients with PTM following concussion may exhibit distinct electrophysiological patterns, although researchers have yet to examine the electrophysiological brain activation in patients with PTM following concussion. A novel approach that may help differentiate brain activation in patients with and without PTM is brain network activation (BNA) analysis. BNA involves an algorithmic analysis applied to multichannel EEG-ERP data that provides a network map of cortical activity and quantitative data during specific tasks. A prospective, repeated measures design was used to evaluate BNA (during Go/NoGo task), EEG-ERP, cognitive performance, and concussion related symptoms at 1, 2, 3, and 4 weeks post-injury intervals among athletes with a medically diagnosed concussion with PTM (n = 15) and without (NO-PTM) (n = 22); and age, sex, and concussion history matched controls without concussion (CONTROL) (n = 20). Participants with PTM had significantly reduced BNA compared to NO-PTM and CONTROLS for Go and NoGo components at 3 weeks and for NoGo component at 4 weeks post-injury. The PTM group also demonstrated a more prominent deviation of network activity compared to the other two groups over a longer period of time. The composite BNA algorithm may be a more sensitive measure of electrophysiological change in the brain that can augment established cognitive assessment tools for detecting impairment in individuals with PTM. © 2015, Springer Science+Business Media New York.},

keywords = {Brain network activation, Electroencephalography, Post-traumatic migraine, Sport-related concussion},

pubstate = {published},

tppubtype = {article}

}

2015

Liu, C Y; Law, M; Romano, R

Rational approach to understanding and preventing sports-related traumatic brain injuries Journal Article

In: World Neurosurgery, vol. 84, no. 6, pp. 1556–1557, 2015.

Links | BibTeX | Tags: accelerometer, ACCELEROMETRY, biological marker, brain, brain concussion, brain hemorrhage, cognitive defect, Diffusion Tensor Imaging, Electroencephalography, emergency health service, Female, Head Protective Devices, Helmet, high risk patient, human, Humans, Injuries, Male, neuroimaging, neuromodulation, neuroprotective agent, nuclear magnetic resonance imaging, Occupational Exposure, protective equipment, Review, risk factor, risk reduction, SAFETY, skiing, Snowboarding, sport injury, Traumatic, traumatic brain injury, viscoelastic substance

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}

}

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.

Reference Search

Hyden, J; Petty, B

Sideline Management of Concussion Journal Article

In: Physical Medicine & Rehabilitation Clinics of North America, vol. 27, no. 2, pp. 395–409, 2016.

Links | BibTeX

Beiske, K K; Kostov, K H; Kostov, H

Rhythmic midtemporal discharge in a youth during light sleep Journal Article

In: Neurodiagnostic Journal, vol. 56, no. 1, pp. 32–36, 2016.

Abstract | Links | BibTeX

Kontos, A P; Reches, A; Elbin, R J; Dickman, D; Laufer, I; Geva, A B; Shacham, G; DeWolf, R; Collins, M W

Preliminary evidence of reduced brain network activation in patients with post-traumatic migraine following concussion Journal Article

In: Brain Imaging & Behavior, vol. 10, no. 2, pp. 594–603, 2016.

Abstract | Links | BibTeX

@article{Kontos2016d,

title = {Preliminary evidence of reduced brain network activation in patients with post-traumatic migraine following concussion},

author = {Kontos, A P and Reches, A and Elbin, R J and Dickman, D and Laufer, I and Geva, A B and Shacham, G and DeWolf, R and Collins, M W},

doi = {10.1007/s11682-015-9412-6},

year  = {2016},

date = {2016-01-01},

journal = {Brain Imaging \& Behavior},

volume = {10},

number = {2},

pages = {594--603},

abstract = {Post-traumatic migraine (PTM) (i.e., headache, nausea, light and/or noise sensitivity) is an emerging risk factor for prolonged recovery following concussion. Concussions and migraine share similar pathophysiology characterized by specific ionic imbalances in the brain. Given these similarities, patients with PTM following concussion may exhibit distinct electrophysiological patterns, although researchers have yet to examine the electrophysiological brain activation in patients with PTM following concussion. A novel approach that may help differentiate brain activation in patients with and without PTM is brain network activation (BNA) analysis. BNA involves an algorithmic analysis applied to multichannel EEG-ERP data that provides a network map of cortical activity and quantitative data during specific tasks. A prospective, repeated measures design was used to evaluate BNA (during Go/NoGo task), EEG-ERP, cognitive performance, and concussion related symptoms at 1, 2, 3, and 4 weeks post-injury intervals among athletes with a medically diagnosed concussion with PTM (n = 15) and without (NO-PTM) (n = 22); and age, sex, and concussion history matched controls without concussion (CONTROL) (n = 20). Participants with PTM had significantly reduced BNA compared to NO-PTM and CONTROLS for Go and NoGo components at 3 weeks and for NoGo component at 4 weeks post-injury. The PTM group also demonstrated a more prominent deviation of network activity compared to the other two groups over a longer period of time. The composite BNA algorithm may be a more sensitive measure of electrophysiological change in the brain that can augment established cognitive assessment tools for detecting impairment in individuals with PTM. © 2015, Springer Science+Business Media New York.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

Liu, C Y; Law, M; Romano, R

Rational approach to understanding and preventing sports-related traumatic brain injuries Journal Article

In: World Neurosurgery, vol. 84, no. 6, pp. 1556–1557, 2015.

Links | BibTeX

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

@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}

}

Most Referenced Keywords

Show all

2016

Hyden, J; Petty, B

Sideline Management of Concussion Journal Article

In: Physical Medicine & Rehabilitation Clinics of North America, vol. 27, no. 2, pp. 395–409, 2016.

Beiske, K K; Kostov, K H; Kostov, H

Rhythmic midtemporal discharge in a youth during light sleep Journal Article

In: Neurodiagnostic Journal, vol. 56, no. 1, pp. 32–36, 2016.

Kontos, A P; Reches, A; Elbin, R J; Dickman, D; Laufer, I; Geva, A B; Shacham, G; DeWolf, R; Collins, M W

Preliminary evidence of reduced brain network activation in patients with post-traumatic migraine following concussion Journal Article

In: Brain Imaging & Behavior, vol. 10, no. 2, pp. 594–603, 2016.

Abstract | Links | BibTeX | Tags: Brain network activation, Electroencephalography, Post-traumatic migraine, Sport-related concussion

@article{Kontos2016d,

title = {Preliminary evidence of reduced brain network activation in patients with post-traumatic migraine following concussion},

author = {Kontos, A P and Reches, A and Elbin, R J and Dickman, D and Laufer, I and Geva, A B and Shacham, G and DeWolf, R and Collins, M W},

doi = {10.1007/s11682-015-9412-6},

year  = {2016},

date = {2016-01-01},

journal = {Brain Imaging \& Behavior},

volume = {10},

number = {2},

pages = {594--603},

abstract = {Post-traumatic migraine (PTM) (i.e., headache, nausea, light and/or noise sensitivity) is an emerging risk factor for prolonged recovery following concussion. Concussions and migraine share similar pathophysiology characterized by specific ionic imbalances in the brain. Given these similarities, patients with PTM following concussion may exhibit distinct electrophysiological patterns, although researchers have yet to examine the electrophysiological brain activation in patients with PTM following concussion. A novel approach that may help differentiate brain activation in patients with and without PTM is brain network activation (BNA) analysis. BNA involves an algorithmic analysis applied to multichannel EEG-ERP data that provides a network map of cortical activity and quantitative data during specific tasks. A prospective, repeated measures design was used to evaluate BNA (during Go/NoGo task), EEG-ERP, cognitive performance, and concussion related symptoms at 1, 2, 3, and 4 weeks post-injury intervals among athletes with a medically diagnosed concussion with PTM (n = 15) and without (NO-PTM) (n = 22); and age, sex, and concussion history matched controls without concussion (CONTROL) (n = 20). Participants with PTM had significantly reduced BNA compared to NO-PTM and CONTROLS for Go and NoGo components at 3 weeks and for NoGo component at 4 weeks post-injury. The PTM group also demonstrated a more prominent deviation of network activity compared to the other two groups over a longer period of time. The composite BNA algorithm may be a more sensitive measure of electrophysiological change in the brain that can augment established cognitive assessment tools for detecting impairment in individuals with PTM. © 2015, Springer Science+Business Media New York.},

keywords = {Brain network activation, Electroencephalography, Post-traumatic migraine, Sport-related concussion},

pubstate = {published},

tppubtype = {article}

}

2015

Liu, C Y; Law, M; Romano, R

Rational approach to understanding and preventing sports-related traumatic brain injuries Journal Article

In: World Neurosurgery, vol. 84, no. 6, pp. 1556–1557, 2015.

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 = {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}

}

2016

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2016

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