Biophysical linkage between MRI and EEG amplitude in closed head injury

Point-of-Care Electroencephalography in Acute Neurological Care: A Narrative Review

Point-of-care electroencephalography (POC-EEG) systems are rapid-access, reduced-montage devices designed to address the limitations of conventional EEG (conv-EEG), enabling faster neurophysiological assessment in acute settings. This review evaluates their clinical impact, diagnostic performance, and feasibility in non-convulsive status epilepticus (NCSE), traumatic brain injury (TBI), stroke, and delirium. A comprehensive search of Medline, Scopus, and Embase identified 69 studies assessing 15 devices. In suspected NCSE, POC-EEG facilitates rapid seizure detection and prompt diagnosis, making it particularly effective in time-sensitive and resource-limited settings. Its after-hours availability and telemedicine integration ensure continuous coverage. AI-assisted tools enhance interpretability and accessibility, enabling use by non-experts. Despite variability in accuracy, it supports triaging, improving management, treatment decisions and outcomes while reducing hospital stays, transfers, and costs. In TBI, POC-EEG-derived quantitative EEG (qEEG) indices reliably detect structural lesions, support triage, and minimize unnecessary CT scans. They also help assess concussion severity and predict recovery. For strokes, POC-EEG aids triage by detecting large vessel occlusions (LVOs) with high feasibility in hospital and prehospital settings. In delirium, spectral analysis and AI-assisted models enhance diagnostic accuracy, broadening its clinical applications. Although POC-EEG is a promising screening tool, challenges remain in diagnostic variability, technical limitations, and AI optimization, requiring further research.

Age-Related Characteristics of Resting-State Electroencephalographic Signals and the Corresponding Analytic Approaches: A Review

The study of the effects of aging on neural activity in the human brain has attracted considerable attention in neurophysiological, neuropsychiatric, and neurocognitive research, as it is directly linked to an understanding of the neural mechanisms underlying the disruption of the brain structures and functions that lead to age-related pathological disorders. Electroencephalographic (EEG) signals recorded during resting-state conditions have been widely used because of the significant advantage of non-invasive signal acquisition with higher temporal resolution. These advantages include the capability of a variety of linear and nonlinear signal analyses and state-of-the-art machine-learning and deep-learning techniques. Advances in artificial intelligence (AI) can not only reveal the neural mechanisms underlying aging but also enable the assessment of brain age reliably by means of the age-related characteristics of EEG signals. This paper reviews the literature on the age-related features, available analytic methods, large-scale resting-state EEG databases, interpretations of the resulting findings, and recent advances in age-related AI models.

Circuits and Biomarkers of the Central Nervous System Relating to Astronaut Performance: Summary Report for a NASA-Sponsored Technical Interchange Meeting

Biomarkers, ranging from molecules to behavior, can be used to identify thresholds beyond which performance of mission tasks may be compromised and could potentially trigger the activation of countermeasures. Identification of homologous brain regions and/or neural circuits related to operational performance may allow for translational studies between species. Three discussion groups were directed to use operationally relevant performance tasks as a driver when identifying biomarkers and brain regions or circuits for selected constructs. Here we summarize small-group discussions in tables of circuits and biomarkers categorized by (a) sensorimotor, (b) behavioral medicine and (c) integrated approaches (e.g., physiological responses). In total, hundreds of biomarkers have been identified and are summarized herein by the respective group leads. We hope the meeting proceedings become a rich resource for NASA's Human Research Program (HRP) and the community of researchers.

Quantitative Electroencephalographic Markers of Delirium in the Pediatric Intensive Care Unit: Insights From a Heterogenous Convenience Sample

OBJECTIVE

Little is known about the underlying neurophysiology of pediatric delirium. In adult patients, the sensitivity of EEG to clinical symptoms of delirium has been noted, with a slowing of background activity (alpha) and an increase in slow-wave activity (delta-theta). In this pilot study, the authors extended this investigation to a pediatric cohort.

METHODS

In a convenience sample, 23 critically ill children were screened for delirium, using the Cornell Assessment for Pediatric Delirium (CAPD), every 12 hours throughout their pediatric intensive care unit stay as part of standard intensive care unit procedure, and EEGs were performed as part of their clinical care. After hospital discharge, EEGs were reviewed using quantitative analysis, and the maximum delta-alpha ratio (DAR; eyes closed) was derived for each 12-hour period. DAR values were compared between delirious and nondelirious episodes, and the linear relationship between DAR and CAPD was assessed.

RESULTS

Higher DARs were associated with episodes of delirium. The DAR also positively correlated with CAPD assessments, with higher DARs relating to higher delirium scores.

CONCLUSIONS

Future prospective studies may further investigate this relationship in a more homogeneous and larger sample, and the DAR should be considered to track delirium and assess the effectiveness of therapeutic interventions.

Distinct Slow-Wave Activity Patterns in Resting-State Electroencephalography and Their Relation to Language Functioning in Low-Grade Glioma and Meningioma Patients

Introduction

Brain tumours frequently cause language impairments and are also likely to co-occur with localised abnormal slow-wave brain activity. However, it is unclear whether this applies specifically to low-grade brain tumours. We investigate slow-wave activity in resting-state electroencephalography (EEG) in low-grade glioma and meningioma patients, and its relation to pre- and postoperative language functioning.

Method

Patients with a glioma (N = 15) infiltrating the language-dominant hemisphere and patients with a meningioma (N = 10) with mass effect on this hemisphere underwent extensive language testing before and 1 year after surgery. EEG was registered preoperatively, postoperatively (glioma patients only), and once in healthy individuals. Slow-wave activity in delta- and theta- frequency bands was evaluated visually and quantitatively by spectral power at three levels over the scalp: the whole brain, the affected hemisphere, and the affected region.

Results

Glioma patients had increased delta activity (affected area) and increased theta activity (all levels) before and after surgery. In these patients, increased preoperative theta activity was related to the presence of language impairment, especially to poor word retrieval and grammatical performance. Preoperative slow-wave activity was also related to postoperative language outcomes. Meningioma patients showed no significant increase in EEG slow-wave activity compared to healthy individuals, but they presented with word retrieval, grammatical, and writing problems preoperatively, as well as with writing impairments postoperatively.

Discussion

Although the brain-tumour pathology in low-grade gliomas and meningiomas has a different effect on resting-state brain activity, patients with low-grade gliomas and meningiomas both suffer from language impairments. Increased theta activity in glioma patients can be considered as a language-impairment marker, with prognostic value for language outcome after surgery.

Evaluating Performance of EEG Data-Driven Machine Learning for Traumatic Brain Injury Classification

Objectives:

Big data analytics can potentially benefit the assessment and management of complex neurological conditions by extracting information that is difficult to identify manually. In this study, we evaluated the performance of commonly used supervised machine learning algorithms in the classification of patients with traumatic brain injury (TBI) history from those with stroke history and/or normal EEG.

Methods:

Support vector machine (SVM) and K-nearest neighbors (KNN) models were generated with a diverse feature set from Temple EEG Corpus for both two-class classification of patients with TBI history from normal subjects and three-class classification of TBI, stroke and normal subjects.

Results:

For two-class classification, an accuracy of 0.94 was achieved in 10-fold cross validation (CV), and 0.76 in independent validation (IV). For three-class classification, 0.85 and 0.71 accuracy were reached in CV and IV respectively. Overall, linear discriminant analysis (LDA) feature selection and SVM models consistently performed well in both CV and IV and for both two-class and three-class classification. Compared to normal control, both TBI and stroke patients showed an overall reduction in coherence and relative PSD in delta frequency, and an increase in higher frequency (alpha, mu, beta and gamma) power. But stroke patients showed a greater degree of change and had additional global decrease in theta power.

Conclusions:

Our study suggests that EEG data-driven machine learning can be a useful tool for TBI classification.

Significance:

Our study provides preliminary evidence that EEG ML algorithm can potentially provide specificity to separate different neurological conditions.

Longitudinal Functional Assessment of Brain Injury Induced by High-Intensity Ultrasound Pulse Sequences

Exposure of the brain to high-intensity stress waves creates the potential for long-term functional deficits not related to thermal or cavitational damage. Possible sources of such exposure include overpressure from blast explosions or high-intensity focused ultrasound (HIFU). While current ultrasound clinical protocols do not normally produce long-term neurological deficits, the rapid expansion of potential therapeutic applications and ultrasound pulse-train protocols highlights the importance of establishing a safety envelope beyond which therapeutic ultrasound can cause neurological deficits not detectable by standard histological assessment for thermal and cavitational damage. In this study, we assessed the neuroinflammatory response, behavioral effects, and brain micro-electrocorticographic (µECoG) signals in mice following exposure to a train of transcranial pulses above normal clinical parameters. We found that the HIFU exposure induced a mild regional neuroinflammation not localized to the primary focal site, and impaired locomotor and exploratory behavior for up to 1 month post-exposure. In addition, low frequency (δ) and high frequency (β, γ) oscillations recorded by ECoG were altered at acute and chronic time points following HIFU application. ECoG signal changes on the hemisphere ipsilateral to HIFU exposure are of greater magnitude than the contralateral hemisphere, and persist for up to three months. These results are useful for describing the upper limit of transcranial ultrasound protocols, and the neurological sequelae of injury induced by high-intensity stress waves.

Frequency-Dependent Changes in Resting State Electroencephalogram Functional Networks after Traumatic Brain Injury in Piglets

Traumatic brain injury (TBI) is a major health concern in children, as it can cause chronic cognitive and behavioral deficits. The lack of objective involuntary metrics for the diagnosis of TBI makes prognosis more challenging, especially in the pediatric context, in which children are often unable to articulate their symptoms. Resting state electroencephalograms (EEG), which are inexpensive and non-invasive, and do not require subjects to perform cognitive tasks, have not yet been used to create functional brain networks in relation to TBI in children or non-human animals; here we report the first such study. We recorded resting state EEG in awake piglets before and after TBI, from which we generated EEG functional networks from the alpha (8-12 Hz), beta (16.5-25 Hz), broad (1-35 Hz), delta (1-3.5 Hz), gamma (30-35 Hz), sigma (13-16 Hz), and theta (4-7.5 Hz) frequency bands. We hypothesize that mild TBI will induce persistent frequency-dependent changes in the 4-week-old piglet at acute and chronic time points. Hyperconnectivity was found in several frequency band networks after TBI. This study serves as proof of concept that the study of EEG functional networks in awake piglets may be useful for the development of diagnostic metrics for TBI in children.

Analysis of Feature Fatigue EEG Signals Based on Wavelet Entropy

Fatigue driving is bringing more and more serious harm, but there are various reasons for fatigue driving, it is still difficult to test the driver’s fatigue. This paper defines a method to test driver’s fatigue based on the EEG, and different from other researches into fatigue driving, this paper mainly takes the fatigue features of EEG signals in fatigue state and uses wavelet entropy as the feature extraction method to analyze the features of wavelet entropy and spectral entropy features as well as the classification accuracy under the same classifier. The SVM is used to show the classifier’s results. The accuracy of the driver fatigue state monitoring using the wavelet entropy is 90.7%, which is higher than the use of spectral entropy as the characteristic accuracy rate of 81.3%. The results show that the frequency characteristics of EEG can be well applied to driving fatigue testing, but different frequency feature calculation methods will affect the classification accuracy.

Distinction in EEG slow oscillations between chronic mild traumatic brain injury and PTSD

Spectral information from resting state EEG is altered in acute mild traumatic brain injury (mTBI) and in disorders of consciousness, but there is disagreement about whether mTBI can elicit long term changes in the spectral profile. Even when identified, any long-term changes attributed to TBI can be confounded by psychiatric comorbidities such as PTSD, particularly for combat-related mTBI where postdeployment distress is commonplace. To address this question, we measured spectral power during the resting state in a large sample of service members and Veterans varying in mTBI history and active PTSD diagnosis but matched for having had combat blast exposure. We found that PTSD was associated with decreases in low frequency power, especially in the right temporoparietal region, while conversely, blast-related mTBI was associated with increases in low frequency power, especially in prefrontal and right temporal areas. Results support the idea that long-term neurophysiological effects of mTBI share some features with states of reduced arousal and cognitive dysfunction, suggesting a role for EEG in tracking the trajectory of recovery and persisting vulnerabilities to injury. Additionally, results suggest that EEG power reflects distinct pathophysiologies for current PTSD and chronic mTBI.

Real-Time Detection and Monitoring of Acute Brain Injury Utilizing Evoked Electroencephalographic Potentials

Rapid detection and diagnosis of a traumatic brain injury (TBI) can significantly improve the prognosis for recovery. Helmet-mounted sensors that detect impact severity based on measurements of acceleration or pressure show promise for aiding triage and transport decisions in active, field environments such as professional sports or military combat. The detected signals, however, report on the mechanics of an impact rather than directly indicating the presence and severity of an injury. We explored the use of cortical somatosensory evoked electroencephalographic potentials (SSEPs) to detect and track, in real-time, neural electrophysiological abnormalities within the first hour following head injury in an animal model. To study the immediate electrophysiological effects of injury in vivo, we developed an experimental paradigm involving focused ultrasound that permits continuous, real-time measurements and minimizes mechanical artifact. Injury was associated with a dramatic reduction of amplitude over the damaged hemisphere directly after the injury. The amplitude systematically improved over time but remained significantly decreased at one hour, compared with baseline. In contrast, at one hour there was a concomitant enhancement of the cortical SSEP amplitude evoked from the uninjured hemisphere. Analysis of the inter-trial electroencephalogram (EEG) also revealed significant changes in low-frequency components and an increase in EEG entropy up to 30 minutes after injury, likely reflecting altered EEG reactivity to somatosensory stimuli. Injury-induced alterations in SSEPs were also observed using noninvasive epidermal electrodes, demonstrating viability of practical implementation. These results suggest cortical SSEPs recorded at just a few locations by head-mounted sensors and associated multiparametric analyses could potentially be used to rapidly detect and monitor brain injury in settings that normally present significant levels of mechanical and electrical noise.

Identification of hematomas in mild traumatic brain injury using an index of quantitative brain electrical activity

Rapid identification of traumatic intracranial hematomas following closed head injury represents a significant health care need because of the potentially life-threatening risk they present. This study demonstrates the clinical utility of an index of brain electrical activity used to identify intracranial hematomas in traumatic brain injury (TBI) presenting to the emergency department (ED). Brain electrical activity was recorded from a limited montage located on the forehead of 394 closed head injured patients who were referred for CT scans as part of their standard ED assessment. A total of 116 of these patients were found to be CT positive (CT+), of which 46 patients with traumatic intracranial hematomas (CT+) were identified for study. A total of 278 patients were found to be CT negative (CT-) and were used as controls. CT scans were subjected to quantitative measurements of volume of blood and distance of bleed from recording electrodes by blinded independent experts, implementing a validated method for hematoma measurement. Using an algorithm based on brain electrical activity developed on a large independent cohort of TBI patients and controls (TBI-Index), patients were classified as either positive or negative for structural brain injury. Sensitivity to hematomas was found to be 95.7% (95% CI = 85.2, 99.5), specificity was 43.9% (95% CI = 38.0, 49.9). There was no significant relationship between the TBI-Index and distance of the bleed from recording sites (F = 0.044, p = 0.833), or volume of blood measured F = 0.179, p = 0.674). Results of this study are a validation and extension of previously published retrospective findings in an independent population, and provide evidence that a TBI-Index for structural brain injury is a highly sensitive measure for the detection of potentially life-threatening traumatic intracranial hematomas, and could contribute to the rapid, quantitative evaluation and treatment of such patients.

Early adolescent cognitive gains are marked by increased sleep EEG coherence

Although the increases in cognitive capacities of adolescent humans are concurrent with significant cortical restructuring, functional associations between these phenomena are unclear. We examined the association between cortical development, as measured by the sleep EEG, and cognitive performance in a sample of 9/10 year olds followed up 1 to 3 years later. Our cognitive measures included a response inhibition task (Stroop), an executive control task (Trail Making), and a verbal fluency task (FAS). We correlated sleep EEG measures of power and intra-hemispheric coherence at the initial assessment with performance at that assessment. In addition we correlated the rate of change across assessments in sleep EEG measures with the rate of change in performance. We found no correlation between sleep EEG power and performance on cognitive tasks for the initial assessment. In contrast, we found a significant correlation of the rate of change in intra-hemispheric coherence for the sigma band (11 to 16 Hz) with rate of change in performance on the Stroop (r = 0.61; p<0.02) and Trail Making (r =  -0.51; p<0.02) but no association for the FAS. Thus, plastic changes in connectivity (i.e., sleep EEG coherence) were associated with improvement in complex cognitive function.

Electroencephalography and quantitative electroencephalography in mild traumatic brain injury

Mild traumatic brain injury (mTBI) causes brain injury resulting in electrophysiologic abnormalities visible in electroencephalography (EEG) recordings. Quantitative EEG (qEEG) makes use of quantitative techniques to analyze EEG characteristics such as frequency, amplitude, coherence, power, phase, and symmetry over time independently or in combination. QEEG has been evaluated for its use in making a diagnosis of mTBI and assessing prognosis, including the likelihood of progressing to the postconcussive syndrome (PCS) phase. We review the EEG and qEEG changes of mTBI described in the literature. An attempt is made to separate the findings seen during the acute, subacute, and chronic phases after mTBI. Brief mention is also made of the neurobiological correlates of qEEG using neuroimaging techniques or in histopathology. Although the literature indicates the promise of qEEG in making a diagnosis and indicating prognosis of mTBI, further study is needed to corroborate and refine these methods.

Scalp EEG-based discrimination of cognitive deficits after traumatic brain injury using event-related Tsallis entropy analysis

Traumatic brain injury (TBI) is the leading cause of death and disability in children and adolescents in the U.S. This is a pilot study, which explores the discrimination of chronic TBI from normal controls using scalp EEG during a memory task. Tsallis entropies are computed for responses during an old-new memory recognition task. A support vector machine model is constructed to discriminate between normal and moderate/severe TBI individuals using Tsallis entropies as features. Numerical analyses of 30 records (15 normal and 15 TBI) show a maximum discrimination accuracy of 93% (p-value = 7.8557E-5) using four features. These results suggest the potential of scalp EEG as an efficacious method for noninvasive diagnosis of TBI.

Deletion of Rictor in neural progenitor cells reveals contributions of mTORC2 signaling to tuberous sclerosis complex

Tuberous sclerosis complex (TSC) is a multisystem genetic disorder with severe neurologic manifestations, including epilepsy, autism, anxiety and attention deficit hyperactivity disorder. TSC is caused by the loss of either the TSC1 or TSC2 genes that normally regulate the mammalian target of rapamycin (mTOR) kinase. mTOR exists within two distinct complexes, mTOR complex 1 (mTORC1) and mTOR complex 2 (mTORC2). Loss of either TSC gene leads to increased mTORC1 but decreased mTORC2 signaling. As the contribution of decreased mTORC2 signaling to neural development and homeostasis has not been well studied, we generated a conditional knockout (CKO) of Rictor, a key component of mTORC2. mTORC2 signaling is impaired in the brain, whereas mTORC1 signaling is unchanged. Rictor CKO mice have small brains and bodies, normal lifespan and are fertile. Cortical layering is normal, but neurons are smaller than those in control brains. Seizures were not observed, although excessive slow activity was seen on electroencephalography. Rictor CKO mice are hyperactive and have reduced anxiety-like behavior. Finally, there is decreased white matter and increased levels of monoamine neurotransmitters in the cerebral cortex. Loss of mTORC2 signaling in the cortex independent of mTORC1 can disrupt normal brain development and function and may contribute to some of the neurologic manifestations seen in TSC.

Clinical electrophysiologic assessments and mild traumatic brain injury: state-of-the-science and implications for clinical practice

Conventional and quantitative electroencephalography (EEG and qEEG, respectively) may enhance clinical diagnosis and treatment planning provided to persons with mild traumatic brain injury (mTBI) and postconcussive symptoms. Effective and appropriate use of EEG and qEEG in this context requires expert-level knowledge of these technologies, mTBI, and the differential diagnosis for postconcussive symptoms. A practical and brief review from the perspective of a clinician-scientist engaged principally in the care and study of persons with mTBI therefore may be of use and value to other clinicians and scientists interested in these matters. Toward that end, this article offers an overview of the current applications of conventional EEG and qEEG to the study and clinical evaluation of persons with mTBI. The clinical case definition of TBI, the differential diagnosis of post-injury neuropsychiatric disturbances, and the typical course of recovery following mTBI are reviewed. With this background and context, the strengths and limitations of the literature describing EEG and qEEG studies in this population are considered. The implications of this review on the applications of these electrophysiologic assessments to the clinical evaluation of persons with mTBI and postconcussive symptoms are then considered. Finally, suggestions are offered regarding the design of future studies using these technologies in this population. Although this review may be of interest and value to professionals engaged in clinical or research electrophysiology in their daily work, it is intended to serve more immediately the needs of clinicians less familiar with these types of clinical electrophysiologic assessments.

Influence of phosphatidylserine on cognitive performance and cortical activity after induced stress

The aim of this study was to investigate the effect of phosphatidylserine (PS) on cognition and cortical activity after mental stress. After familiarization, 16 healthy subjects completed cognitive tasks after induced stress in a test-re-test design (T1 and T2). Directly after T1, subjects were assigned double-blind to either PS or placebo groups followed by T2 after 42 days. At T1 and T2, cortical activity was measured at baseline and immediately after stress with cognitive tasks using electro-encephalography (EEG). EEG was recorded at 17 electrode positions and fast Fourier transforms (FFT) determined power at Theta, Alpha-1, Alpha-2, Beta-1 and Beta-2. Statistics were calculated using ANOVA (group x trial x time). The main finding of the study was that chronic supplementation of phosphatidylserine significantly decreases Beta-1 power in right hemispheric frontal brain regions (F8; P < 0.05) before and after induced stress. The results for Beta-1 power in the PS group were connected to a more relaxed state compared to the controls.

Intelligence and EEG current density using low-resolution electromagnetic tomography (LORETA)

The purpose of this study was to compare EEG current source densities in high IQ subjects vs. low IQ subjects. Resting eyes closed EEG was recorded from 19 scalp locations with a linked ears reference from 442 subjects ages 5 to 52 years. The Wechsler Intelligence Test was administered and subjects were divided into low IQ (< or =90), middle IQ (>90 to <120) and high IQ (> or =120) groups. Low-resolution electromagnetic tomographic current densities (LORETA) from 2,394 cortical gray matter voxels were computed from 1-30 Hz based on each subject's EEG. Differences in current densities using t tests, multivariate analyses of covariance, and regression analyses were used to evaluate the relationships between IQ and current density in Brodmann area groupings of cortical gray matter voxels. Frontal, temporal, parietal, and occipital regions of interest (ROIs) consistently exhibited a direct relationship between LORETA current density and IQ. Maximal t test differences were present at 4 Hz, 9 Hz, 13 Hz, 18 Hz, and 30 Hz with different anatomical regions showing different maxima. Linear regression fits from low to high IQ groups were statistically significant (P < 0.0001). Intelligence is directly related to a general level of arousal and to the synchrony of neural populations driven by thalamo-cortical resonances. A traveling frame model of sequential microstates is hypothesized to explain the results.

Longitudinal changes in neuroanatomy and neural activity in early schizophrenia

Although there is substantial evidence indicating that patients with first-episode schizophrenia exhibit both anatomical and electrophysiological abnormalities, there has been little research investigating the relationship between these two indices. We acquired structural magnetic resonance images and resting electroencephalographic recordings from 19 patients with schizophrenia, both at the time of their first presentation to mental health services and 2-3 years subsequently. Patients' grey matter images were parcellated into four brain lobes, and slow-wave, alpha- and beta-electroencephalographic power was calculated in four corresponding cortical regions. Although grey matter volume decreased longitudinally, particularly fronto-parietally, electroencephalographic power increased in the slow-wave and beta-frequency bands. These results suggest that first-episode schizophrenia may be associated with abnormally elevated levels of neural synchrony.

Brain maturation in adolescence: concurrent changes in neuroanatomy and neurophysiology

Adolescence to early adulthood is a period of dramatic transformation in the healthy human brain. However, the relationship between the concurrent structural and functional changes remains unclear. We investigated the impact of age on both neuroanatomy and neurophysiology in the same healthy subjects (n = 138) aged 10 to 30 years using magnetic resonance imaging (MRI) and resting electroencephalography (EEG) recordings. MRI data were segmented into gray and white matter images and parcellated into large-scale regions of interest. Absolute EEG power was quantified for each lobe for the slow-wave, alpha and beta frequency bands. Gray matter volume was found to decrease across the age bracket in the frontal and parietal cortices, with the greatest change occurring in adolescence. EEG activity, particularly in the slow-wave band, showed a similar curvilinear decline to gray matter volume in corresponding cortical regions. An inverse pattern of curvilinearly increasing white matter volume was observed in the parietal lobe. We suggest that the reduction in gray matter primarily reflects a reduction of neuropil, and that the corresponding elimination of active synapses is responsible for the observed reduction in EEG power.

Routine and quantitative EEG in mild traumatic brain injury

This article reviews the pathophysiology of mild traumatic brain injury, and the findings from EEG and quantitative EEG (QEEG) testing after such an injury. Research on the clinical presentation and pathophysiology of mild traumatic brain injury is reviewed with an emphasis on details that may pertain to EEG or QEEG and their interpretation. Research reports on EEG and QEEG in mild traumatic brain injury are reviewed in this setting, and conclusions are drawn about general diagnostic results that can be determined using these tests. QEEG strengths and weaknesses are reviewed in the context of factors used to determine the clinical usefulness of proposed diagnostic tests. Clinical signs, symptoms, and the pathophysiologic axonal injury and cytotoxicity tend to clear over weeks or months after a mild head injury. Loss of consciousness might be similar to a non-convulsive seizure and accompanied subsequently by postictal-like symptoms. EEG shows slowing of the posterior dominant rhythm and increased diffuse theta slowing, which may revert to normal within hours or may clear more slowly over many weeks. There are no clear EEG or QEEG features unique to mild traumatic brain injury. Late after head injury, the correspondence is poor between electrophysiologic findings and clinical symptoms. Complicating factors are reviewed for the proposed commercial uses of QEEG as a diagnostic test for brain injury after concussion or mild traumatic brain injury. The pathophysiology, clinical symptoms and electrophysiological features tend to clear over time after mild traumatic brain injury. There are no proven pathognomonic signatures useful for identifying head injury as the cause of signs and symptoms, especially late after the injury.

EEG and postural correlates of mild traumatic brain injury in athletes

Mild traumatic brain injury (MTBI), or concussion, is one of the least understood injuries facing the neuroscience and sports medicine community today. The notion of transient dysfunction and rapid symptom resolution is misleading since symptom resolution is not indicative of injury resolution. Our working hypothesis is that there are residual postural and EEG abnormalities in concussed individuals that could be reliably assessed using appropriate research methodology. This paper presents combined postural and electroencephalographic (EEG) findings suggesting the persistent functional deficits in athletes suffering from MTBI. Twelve concussed athletes and twelve normal controls participated in the study. There was a decrease in EEG power in all bandwidths studied in concussed subjects, especially in standing postures. This was accompanied by sustained postural instability especially under the no vision testing condition. Overall, this study demonstrated the presence of long-term functional abnormalities in individuals suffering from mild traumatic brain injury.

EEG Correlates of Methylphenidate Response in ADHD: Association With Cognitive and Behavioral Measures

The authors examined the association between EEG correlates of medication response and concomitant cognitive and behavioral changes among children with attention-deficit hyperactivity disorder (ADHD). Subjects were 36 children with ADHD, aged 8 to 12 years. EEG activity was recorded from nine active electrodes during placebo and medication conditions. Medication administration resulted in increased alpha activity in central and parietal regions during both the baseline and cognitive activation conditions. Children who were medication responders exhibited increased frontal beta activity whereas nonresponders showed decreased beta activity in the same region. Increased frontal beta activity was significantly correlated with medication-related improvement in performance on Conners'Continuous Performance Test and parent behavior ratings in attention and hyperactivity. Decreased right frontal theta activity was associated with improvements in parent-rated attention, but not in CPT performance. Stimulant medication increases beta activity in children with ADHD, particularly in frontal regions. Increased cortical arousal and activation in the frontal cortex is strongly associated with sustained attention and response inhibition and with parent-rated attention and hyperactivity/impulsivity.

The usefulness of quantitative EEG (QEEG) and neurotherapy in the assessment and treatment of post-concussion syndrome

Mild traumatic brain injury (TBI) is associated with damage to frontal, temporal and parietal lobes. Post-concussion syndrome has been used to describe a range of residual symptoms that persist 12 months or more after the injury, often despite a lack of evidence of brain abnormalities on MRI and CT scans. The core deficits of post-concussion syndrome are similar to those of ADHD and mood disorders, and sufferers often report memory, socialization problems and frequent headaches. While cognitive rehabilitation and psychological support are widely used, neither has been shown to be effective in redressing the core deficits of post-concussion syndrome. On the other hand, quantitative EEG has been shown to be highly sensitive (96%) in identifying post-concussion syndrome, and neurotherapy has been shown in a number of studies to be effective in significantly improving or redressing the symptoms of post-concussion syndrome, as well as improving similar symptoms in non-TBI patients.

The neurophysiology of brain injury

OBJECTIVE

This article reviews the mechanisms and pathophysiology of traumatic brain injury (TBI).

METHODS

Research on the pathophysiology of diffuse and focal TBI is reviewed with an emphasis on damage that occurs at the cellular level. The mechanisms of injury are discussed in detail including the factors and time course associated with mild to severe diffuse injury as well as the pathophysiology of focal injuries. Examples of electrophysiologic procedures consistent with recent theory and research evidence are presented.

RESULTS

Acceleration/deceleration (A/D) forces rarely cause shearing of nervous tissue, but instead, initiate a pathophysiologic process with a well defined temporal progression. The injury foci are considered to be diffuse trauma to white matter with damage occurring at the superficial layers of the brain, and extending inward as A/D forces increase. Focal injuries result in primary injuries to neurons and the surrounding cerebrovasculature, with secondary damage occurring due to ischemia and a cytotoxic cascade. A subset of electrophysiologic procedures consistent with current TBI research is briefly reviewed.

CONCLUSIONS

The pathophysiology of TBI occurs over time, in a pattern consistent with the physics of injury. The development of electrophysiologic procedures designed to detect specific patterns of change related to TBI may be of most use to the neurophysiologist.

SIGNIFICANCE

This article provides an up-to-date review of the mechanisms and pathophysiology of TBI and attempts to address misconceptions in the existing literature.

Quantitative EEG and the Frye and Daubert standards of admissibility

The 70-year-old Frye standards of "general acceptance" were replaced by the Supreme Court's 1993 Daubert criteria of the scientific method, which established the standards for admissibility of evidence in Federal Court. The four Daubert criteria were: 1- Hypothesis testing, 2- Estimates of error rates, 3- Peer reviewed publication and 4- General acceptance (Daubert v. Merrell Dow Pharmaceuticals, 61 U.S.LW 4805 (U.S. June 29, 1993)). The present paper starts with the Daubert four factors and then matches them, step by step, to the scientific peer reviewed literature of quantitative EEG (QEEG) in relation to different clinical evaluations. This process shows how the peer reviewed science of the Digital EEG and the Quantitative EEG (QEEG) meet all of the Daubert standards of scientific knowledge. Furthermore, the science and technical aspects of QEEG in measuring the effects of neurological and psychiatric dysfunction also match the recent Supreme Court standards of "technical" and "other specialized" knowledge (General Electric Co v. Joiner, 1997, Kumho Tire Company, Ltd. v. Carmichael, 1999). Finally, it is shown that QEEG scientific knowledge and QEEG "technical" and "other specialized" knowledge meet the trilogy standards of the Supreme Court rulings in support of QEEG's admissibility as a clinically valid method in the evaluation of the nature and extent of neurological and psychiatric disorders.

Neurophysiological and behavioral concomitants of mild brain injury in collegiate athletes

OBJECTIVES

There is still limited understanding regarding the effect of mild brain injury (MBI) on normal functioning of the human brain with respect to motor control and coordination. To our knowledge, no research exists on how both the accuracy of force production and underlying neurophysiological concomitants are interactively affected by MBI. The aim of this study is to provide empirical evidence that there are at least transient functional changes in the brain associated with motor control and coordination in collegiate athletes suffering from MBI as reflected in alterations of force trajectory patterns and electroencephalogram (EEG) potentials both in time and frequency domains.

METHODS

Comparisons of the performance and concomitant EEG waveforms both in time and frequency domains of 6 collegiate athletes with MBI and 6 normal subjects in a series of isometric force production tasks were made. The traditional averaging techniques to obtain the slow-wave movement-related potentials (MRP) and Morlet wavelet transform to obtain EEG time-frequency (TF) profiles associated with task performance were used. Subjects performed isometric force production tasks when the level of nominal force was experimentally manipulated. EEG recordings from the frontal-central areas were analyzed with respect to the accuracy of force production during the ramp phase.

RESULTS

Behaviorally, the accuracy of force trajectory performance was considerably impaired in MBI subjects even when the amount of task force was only increased from 25 to 50% maximum voluntary contraction (MVC) within a given subject. Electro-cortically, impaired performance in MBI subjects was associated with alterations in EEG waveforms, amplitude of MRP and TF profiles of EEG.

CONCLUSIONS

Both behavioral and electro-cortical data of control subjects generally were comparable with those from subjects with MBI when small amounts of force were regulated. However, differences become apparent as the amount of task force production was increased. Overall our findings identify the presence of transient functional changes in the brain associated with motor control and coordination in subjects suffering from MBI.

Estimation of the EEG power spectrum using MRI T(2) relaxation time in traumatic brain injury

OBJECTIVES

To study the relationship between magnetic resonance imaging (MRI) T(2) relaxation time and the power spectrum of the electroencephalogram (EEG) in long-term follow up of traumatic brain injury.

METHODS

Nineteen channel quantitative electroencephalograms or qEEG, tests of cognitive function and quantitative MRI T(2) relaxation times (qMRI) were measured in 18 mild to severe closed head injured outpatients 2 months to 4.6 years after injury and 11 normal controls. MRI T(2) and the Laplacian of T(2) were then correlated with the power spectrum of the scalp electrical potentials and current source densities of the qEEG.

RESULTS

qEEG and qMRI T(2) were related by a frequency tuning with maxima in the alpha (8-12Hz) and the lower EEG frequencies (0.5-5Hz), which varied as a function of spatial location. The Laplacian of T(2) acted like a spatial-temporal "lens" by increasing the spatial-temporal resolution of correlation between 3-dimensional T(2) and the ear referenced alert but resting spontaneous qEEG.

CONCLUSIONS

The severity of traumatic brain injury can be modeled by a linear transfer function that relates the molecular qMRI to qEEG resonant frequencies.

The current status of electrophysiologic procedures for the assessment of mild traumatic brain injury

DESIGN

This review examines studies that used spontaneous electroencephalography (EEG), evoked potentials (EP), event-related potentials (ERP), and magnetoencephalography (MEG) to detect brain dysfunction in mild traumatic brain injured (MTBI) subjects.

CONCLUSIONS

The following conclusions are offered: (1) standard clinical EEG is not useful; however, newer analytical procedures may be proven valuable; (2) consistent with current theory of MTBI, cognitive ERPs seem to be more sensitive to injury than EPs; (3) development of an assessment battery that may include EEG, EPs, ERPs, and neuropsychologic testing is advocated.

Spatial-temporal structures of human alpha rhythms: theory, microcurrent sources, multiscale measurements, and global binding of local networks

A theoretical framework supporting experimental measures of dynamic properties of human EEG is proposed with emphasis on distinct alpha rhythms. Robust relationships between measured dynamics and cognitive or behavioral conditions are reviewed, and proposed physiological bases for EEG at cellular levels are considered. Classical EEG data are interpreted in the context of a conceptual framework that distinguishes between locally and globally dominated dynamic processes, as estimated with coherence or other measures of phase synchronization. Macroscopic (scalp) potentials generated by cortical current sources are described at three spatial scales, taking advantage of the columnar structure of neocortex. New EEG data demonstrate that both globally coherent and locally dominated behavior can occur within the alpha band, depending on narrow band frequency, spatial measurement scale, and brain state. Quasi-stable alpha phase structures consistent with global standing waves are observed. At the same time, alpha and theta phase locking between cortical regions during mental calculations is demonstrated, consistent with neural network formation. The brain-binding problem is considered in the context of EEG dynamic behavior that generally exhibits both of these local and global aspects. But specific experimental designs and data analysis methods may severely bias physiological interpretations in either local or global directions.

A history and review of quantitative electroencephalography in traumatic brain injury

The electroencephalogram (EEG) is a physiologic measure of cerebral function that has been used by some to assess coma and prognosticate survival and global outcome after traumatic brain injury (TBI). Surface recordings of the brain's electrical activity reveal distinct patterns that indicate injury severity, depth of unconsciousness, and patient survival. The data produced with traditional qualitative studies, however, does not allow resolution and quantification of the wave frequency spectrum present in the brain. As a result, conventional EEG typically has only been used for gross and qualitative analyses and is not practical for use in long-term patient monitoring or as a sophisticated prognostic tool. One area of investigation that is working to address the limitations of conventional EEG has been the development and implementation of Fourier Transform (FT) EEG which resolves and quantifies frequency bands present in the brain. When FT analysis is applied to EEG, it provides concurrent and continuous monitoring, resolution, and quantification of all frequencies emitted. This review discusses the history and significance of conventional EEG and provides a review of how FT-EEG, commonly referred to as Quantitative EEG (QEEG), is being used in the clinical setting. The specific applications and significance of QEEG methods regarding treatment of patients with TBI are discussed in detail. The advantages, disadvantages, and future directions of QEEG in TBI are also discussed.

Defense and Veterans Head Injury Program: background and overview

Traumatic brain injury (TBI) is the principal cause of death and disability for young Americans, with an estimated societal cost of over $39 billion per year. The Defense and Veterans Head Injury Program (DVHIP) represents a close collaboration among the Departments of Defense (DoD) and Veterans Affairs (DVA), the Brain Injury Association (BIA), and the International Brain Injury Association (IBIA). Its principal mission is to ensure that military and veteran patients with head injury receive TBI-specific evaluation, treatment, rehabilitation, and follow-up, while at the same time addressing the readiness mission of the military and helping to define optimal care for victims of TBI nationwide. Defense and Veterans Head Injury Program activities can be grouped into three broad classes: (1) TBI education, community service, and primary prevention projects; (2) combined TBI clinical treatment, rehabilitation, and clinical research projects; and (3) clinically linked TBI laboratory research projects. It is thus based on a prudent integration of clinical care and follow-up with programmatic clinical and clinically related laboratory research, TBI prevention, and education. This previously nonexistent clinical infrastructure now offers a valuable base for ongoing TBI clinical research.

Exploratory investigation into mild brain injury and discriminant analysis with high frequency bands (32-64 Hz)

QEEG variables (five activation, two relationship variables, 19 locations and five bands up to 64 Hertz) were collected under eyes closed condition (under both 32 and 64 Hertz conditions) on 91 subjects, consisting of 32 mild brain-injured subjects (no loss of consciousness greater than 20 minutes) and 52 normals over the age of 14. An additional seven subjects who were unconscious greater than 20 minutes were available for analysis. Previous discriminant function analysis developed by Thatcher et al. was employed on the eyes closed 32 Hertz condition to ascertain its robustness for time periods greater than 1 year and for significant periods of unconsciousness. A separate discriminant for subjects was developed, employing only frontal high frequency coherence figures. The Thatcher discriminant could reliably (79%) identify all subjects up to 43 years post accident. The high frequency discriminant effectively identified 87% of the brain injured across all time periods (without significant loss of consciousness) and 100% of subjects within 1 year of accident. The combination of the discriminants resulted in a 100% accuracy rate for the 39 brain injured subjects for which discriminate values were available.

Electrophysiology in neuropsychiatric research: a network perspective

A growing number of anatomic and physiologic studies have shown that parallel sensory and motor information processing occurs in multiple cortical areas. These findings challenge the traditional model of brain processing, which states that the brain is a collection of physically discrete processing modules that pass information to each other by neuronal impulses in a stepwise manner. New concepts based on neural network models suggest that the brain is a dynamically shifting collection of interpenetrating, distributed, and transient neural networks. Neither of these models is necessarily mutually exclusive, but each gives different perspectives on the brain that might be complementary. Each model has its own research methodology, with functional magnetic resonance imaging supporting notions of modular processing, and electrophysiology (eg, electroencephalography) emphasizing the network model. These two technologies might be combined fruitfully in the near future to provide us with a better understanding of the brain. However, this common enterprise can succeed only when the inherent limitations and advantages of both models and technologies are known. After a general introduction about electrophysiology as a research tool and its relation to the network model, several practical examples are given on the generation of pathophysiologic models and disease classification, intermediate phenotyping for genetic investigations, and pharmacodynamic modeling. Finally, proposals are made about how to integrate electrophysiology and neuroimaging methods.

Biophysical linkage between MRI and EEG coherence in closed head injury

Using conventional MRI procedures, nuclear magnetic resonance (NMR) of brain water proton (1H) T2 relaxation times and EEG coherence were obtained from two independent groups of closed head injured (CHI) patients and a group of normal control subjects. Statistically significant intercorrelations were observed between 1H T2 relaxation times of the cortical gray and white matter and EEG coherence. The analyses showed that lengthened 1H T2 relaxation times of the cortical gray and white matter were related to: (1) decreased EEG coherence between short interelectrode distances (e.g., 7 cm) and increased EEG coherence between long interelectrode distances (e.g., 28 cm), (2) differences in EEG frequency in which T2 relaxation time was most strongly related to the gray matter in the delta and theta frequencies in CHI patients, and (3) increased T2 relaxation time and decreased short-distance EEG coherence were related to reduced cognitive function. The results were interpreted in terms of reduced integrity of protein/lipid neural membranes and the efficiency and effectiveness of short- and long-distance neural synchronization following traumatic brain injury.