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

Quantitative Electroencephalography Objectivity and Reliability in the Diagnosis and Management of Traumatic Brain Injury: A Systematic Review

Background. Persons with a history of traumatic brain injury (TBI) may exhibit short- and long-term cognitive deficits as well as psychiatric symptoms. These symptoms often reflect functional anomalies in the brain that are not detected by standard neuroimaging. In this context, quantitative electroencephalography (qEEG) is more suitable to evaluate non-normative activity in a wide range of clinical settings. Method. We searched the literature using the "Medline" and "Web of Science" online databases. The search was concluded on February 23, 2023, and revised on July 12, 2023. It returned 134 results from Medline and 4 from Web of Science. We then applied the PRISMA method, which led to the selection of 31 articles, the most recent one published in March 2023. Results. The qEEG method can detect functional anomalies in the brain occurring immediately after and even years after injury, revealing in most cases abnormal power variability and increases in slow (delta and theta) versus decreases in fast (alpha, beta, and gamma) frequency activity. Moreover, other findings show that reduced beta coherence between frontoparietal regions is associated with slower processing speed in patients with recent mild TBI (mTBI). More recently, machine learning (ML) research has developed highly reliable models and algorithms for the detection of TBI, some of which are already integrated into commercial qEEG equipment. Conclusion. Accumulating evidence indicates that the qEEG method may improve the diagnosis and management of TBI, in many cases revealing long-term functional anomalies in the brain or even neuroanatomical insults that are not revealed by standard neuroimaging. While FDA clearance has been obtained only for some of the commercially available equipment, the qEEG method allows for systematic, cost-effective, non-invasive, and reliable investigations at emergency departments. Importantly, the automated implementation of intelligent algorithms based on multimodally acquired, clinically relevant measures may play a key role in increasing diagnosis reliability.

Long-Term Changes in Brain Connectivity Reflected in Quantitative Electrophysiology of Symptomatic Former National Football League Players

Exposure to repetitive head impacts (RHI) has been associated with long-term disturbances in cognition, mood, and neurobehavioral dysregulation, and reflected in neuroimaging. Distinct patterns of changes in quantitative features of the brain electrical activity (quantitative electroencephalogram [qEEG]) have been demonstrated to be sensitive to brain changes seen in neurodegenerative disorders and in traumatic brain injuries (TBI). While these qEEG biomarkers are highly sensitive at time of injury, the long-term effects of exposure to RHI on brain electrical activity are relatively unexplored. Ten minutes of eyes closed resting EEG data were collected from a frontal and frontotemporal electrode montage (BrainScope Food and Drug Administration-cleared EEG acquisition device), as well as assessments of neuropsychiatric function and age of first exposure (AFE) to American football. A machine learning methodology was used to derive a qEEG-based algorithm to discriminate former National Football League (NFL) players (n = 87, 55.40 ± 7.98 years old) from same-age men without history of RHI (n = 68, 54.94 ± 7.63 years old), and a second algorithm to discriminate former players with AFE <12 years (n = 33) from AFE ≥12 years (n = 54). The algorithm separating NFL retirees from controls had a specificity = 80%, a sensitivity = 60%, and an area under curve (AUC) = 0.75. Within the NFL population, the algorithm separating AFE <12 from AFE ≥12 resulted in a sensitivity = 76%, a specificity = 52%, and an AUC = 0.72. The presence of a profile of EEG abnormalities in the NFL retirees and in those with younger AFE includes features associated with neurodegeneration and the disruption of neuronal transmission between regions. These results support the long-term consequences of RHI and the potential of EEG as a biomarker of persistent changes in brain function.

Sensor Level Functional Connectivity Topography Comparison Between Different References Based EEG and MEG

Sensor-level functional connectivity topography (sFCT) contributes significantly to our understanding of brain networks. sFCT can be constructed using either electroencephalography (EEG) or magnetoencephalography (MEG). Here, we compared sFCT within the EEG modality and between EEG and MEG modalities. We first used simulations to look at how different EEG references-including the Reference Electrode Standardization Technique (REST), average reference (AR), linked mastoids (LM), and left mastoid references (LR)-affect EEG-based sFCT. The results showed that REST decreased the reference effects on scalp EEG recordings, making REST-based sFCT closer to the ground truth (sFCT based on ideal recordings). For the inter-modality simulation comparisons, we compared each type of EEG-sFCT with MEG-sFCT using three metrics to quantize the differences: Relative Error (RE), Overlap Rate (OR), and Hamming Distance (HD). When two sFCTs are similar, RE and HD are low, while OR is high. Results showed that among all reference schemes, EEG-and MEG-sFCT were most similar when the EEG was REST-based and the EEG and MEG were recorded simultaneously. Next, we analyzed simultaneously recorded MEG and EEG data from publicly available face-recognition experiments using a similar procedure as in the simulations. The results showed (1) if MEG-sFCT is the standard, REST-and LM-based sFCT provided results closer to this standard in the terms of HD; (2) REST-based sFCT and MEG-sFCT had the highest similarity in terms of RE; (3) REST-based sFCT had the most overlapping edges with MEG-sFCT in terms of OR. This study thus provides new insights into the effect of different reference schemes on sFCT and the similarity between MEG and EEG in terms of sFCT.

How Different EEG References Influence Sensor Level Functional Connectivity Graphs

Highlights: Hamming Distance is applied to distinguish the difference of functional connectivity networkThe orientations of sources are testified to influence the scalp Functional Connectivity Graph (FCG) from different references significantlyREST, the reference electrode standardization technique, is proved to have an overall stable and excellent performance in variable situations. The choice of an electroencephalograph (EEG) reference is a practical issue for the study of brain functional connectivity. To study how EEG reference influence functional connectivity estimation (FCE), this study compares the differences of FCE resulting from the different references such as REST (the reference electrode standardization technique), average reference (AR), linked mastoids (LM), and left mastoid references (LR). Simulations involve two parts. One is based on 300 dipolar pairs, which are located on the superficial cortex with a radial source direction. The other part is based on 20 dipolar pairs. In each pair, the dipoles have various orientation combinations. The relative error (RE) and Hamming distance (HD) between functional connectivity matrices of ideal recordings and that of recordings obtained with different references, are metrics to compare the differences of the scalp functional connectivity graph (FCG) derived from those two kinds of recordings. Lower RE and HD values imply more similarity between the two FCGs. Using the ideal recording (IR) as a standard, the results show that AR, LM and LR perform well only in specific conditions, i.e., AR performs stable when there is no upward component in sources' orientation. LR achieves desirable results when the sources' locations are away from left ear. LM achieves an indistinct difference with IR, i.e., when the distribution of source locations is symmetric along the line linking the two ears. However, REST not only achieves excellent performance for superficial and radial dipolar sources, but also achieves a stable and robust performance with variable source locations and orientations. Benefitting from the stable and robust performance of REST vs. other reference methods, REST might best recover the real FCG of EEG. Thus, REST based FCG may be a good candidate to compare the FCG of EEG based on different references from different labs.

Non-linear Analysis of Scalp EEG by Using Bispectra: The Effect of the Reference Choice

Bispectral analysis is a signal processing technique that makes it possible to capture the non-linear and non-Gaussian properties of the EEG signals. It has found various applications in EEG research and clinical practice, including the assessment of anesthetic depth, the identification of epileptic seizures, and more recently, the evaluation of non-linear cross-frequency brain functional connectivity. However, the validity and reliability of the indices drawn from bispectral analysis of EEG signals are potentially biased by the use of a non-neutral EEG reference. The present study aims at investigating the effects of the reference choice on the analysis of the non-linear features of EEG signals through bicoherence, as well as on the estimation of cross-frequency EEG connectivity through two different non-linear measures, i.e., the cross-bicoherence and the antisymmetric cross-bicoherence. To this end, four commonly used reference schemes were considered: the vertex electrode (Cz), the digitally linked mastoids, the average reference, and the Reference Electrode Standardization Technique (REST). The reference effects were assessed both in simulations and in a real EEG experiment. The simulations allowed to investigated: (i) the effects of the electrode density on the performance of the above references in the estimation of bispectral measures; and (ii) the effects of the head model accuracy in the performance of the REST. For real data, the EEG signals recorded from 10 subjects during eyes open resting state were examined, and the distortions induced by the reference choice in the patterns of alpha-beta bicoherence, cross-bicoherence, and antisymmetric cross-bicoherence were assessed. The results showed significant differences in the findings depending on the chosen reference, with the REST providing superior performance than all the other references in approximating the ideal neutral reference. In conclusion, this study highlights the importance of considering the effects of the reference choice in the interpretation and comparison of the results of bispectral analysis of scalp EEG.

Neuroimaging Measures to Assess the Effectiveness of a Two-Day Marathon Group of Individuals with Early Developmental Trauma: A Pilot Study

Group therapy can be effective with individuals with developmental trauma who re-experience intense physiological traumatic distress and struggle with terror and despair. This modality can address the long-term ramifications of developmental trauma, including problems with perceptions, trust, emotional regulation, and loss of sense of self. Neuroimaging techniques can be combined with group therapy interventions as a way to empirically validate the effectiveness of group psychotherapy on brain structures and networks impacted by trauma. The neuroscience explaining overpowering traumatic responses and related emotions will be reviewed. Results of a pilot study combining group therapy with neuroimaging are presented.

Source-domain spectral EEG analysis of sports-related concussion via Measure Projection Analysis

Here, we investigated EEG-based source-level spectral differences between adolescents with sports-related concussions and healthy age matched controls. We transformed resting state EEG collected in both groups to the source domain using Independent Component Analysis (ICA) and computed the component process power spectra. For group-level analysis in the source domain, we used a probabilistic framework, Measure Projection Analysis (MPA), that has advantages over parametric k-means clustering of brain sources. MPA revealed that some frontal brain sources in the concussed group had significantly more power in the beta band (p<;0.005) and significantly less delta (p<;0.01) and theta band power (p<;0.05) than the healthy control group. These results suggest that a shift in spectral profile toward higher frequencies in some frontal brain regions might distinguish individuals with concussion from healthy controls.

Impact of the reference choice on scalp EEG connectivity estimation

OBJECTIVE

Several scalp EEG functional connectivity studies, mostly clinical, seem to overlook the reference electrode impact. The subsequent interpretation of brain connectivity is thus often biased by the choice of a non-neutral reference. This study aims at systematically investigating these effects.

APPROACH

As EEG reference, we examined the vertex electrode (Cz), the digitally linked mastoids (DLM), the average reference (AVE), and the reference electrode standardization technique (REST). As a connectivity metric, we used the imaginary part of the coherency. We tested simulated and real data (eyes-open resting state) by evaluating the influence of electrode density, the effect of head model accuracy in the REST transformation, and the impact on the characterization of the topology of functional networks from graph analysis.

MAIN RESULTS

Simulations demonstrated that REST significantly reduced the distortion of connectivity patterns when compared to AVE, Cz, and DLM references. Moreover, the availability of high-density EEG systems and an accurate knowledge of the head model are crucial elements to improve REST performance, with the individual realistic head model being preferable to the standard realistic head model. For real data, a systematic change of the spatial pattern of functional connectivity depending on the chosen reference was also observed. The distortion of connectivity patterns was larger for the Cz reference, and progressively decreased when using the DLM, the AVE, and the REST. Strikingly, we also showed that network attributes derived from graph analysis, i.e. node degree and local efficiency, are significantly influenced by the EEG reference choice.

SIGNIFICANCE

Overall, this study highlights that significant differences arise in scalp EEG functional connectivity and graph network properties, in dependence on the chosen reference. We hope that our study will convey the message that caution should be used when interpreting and comparing results obtained from different laboratories using different reference schemes.

Treating Postconcussion Syndrome with LORETA Z-Score Neurofeedback and Heart Rate Variability Biofeedback: Neuroanatomical/Neurophysiological Rationale, Methods, and Case Examples

Media attention has highlighted the critical problem of concussion injuries in sport and the challenge of treating and rehabilitating individuals with traumatic brain injury. The authors present a framework for the treatment of traumatic brain injury, using low-resolution electromagnetic tomography Z-score based neurofeedback and heart rate–variability biofeedback. The article advocates a comprehensive assessment process including the use of a 19-channel quantitative electroencephalogram, a heart rate variability baseline, and symptom severity questionnaires for attention deficit/hyperactivity disorder, depression, and anxiety. The initial medical assessment, neuropsychological assessment, and evoked potential studies also have potential for a more precise assessment of deficits in brain activation patterns, which assists the targeting of neurofeedback training.

Traumatic brain injury detection using electrophysiological methods

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.

Multimodal Analysis: New Approaches to the Concussion Conundrum

Sports-related concussions are complex injuries with biomechanical and biochemical etiology that present with central and autonomic nervous system dysfunction. Current methods for assessing concussions and basing return-to-play decisions rely on symptom resolution, rating scales, and neuropsychological testing, all of which are indirect measures of injury severity and detect functional capabilities but do not directly measure injury location or severity. In addition, these downstream measures are susceptible to false negatives because compensatory mechanism, such as unmasking and redundancies in brain circuitry can return functional capabilities before injury resolution. The multifactorial nature of concussion necessitates rapid, inexpensive, and easily applied multimodal analysis methods that can offer greater sensitivity and specificity. This article discusses how new approaches utilizing electrophysiology (e.g., QEEG, ERP, ECG, HRV), quantified balance measures, and biochemistry are necessary to advance the science of concussion assessment, treatment, recovery projections, and return-to-play decisions. These additional assessment tools offer a more direct window into the severity and location of the injury, real-time measures of brain function, and the ability to measure the multiple body systems negatively affected by concussion.

Obsessive compulsive disorder and the efficacy of qEEG-guided neurofeedback treatment: a case series

While neurofeedback (NF) has been extensively studied in the treatment of many disorders, there have been only three published reports, by D.C. Hammond, on its clinical effects in the treatment of obsessive compulsive disorder (OCD). In this paper the efficacy of qEEG-guided NF for subjects with OCD was studied as a case series. The goal was to examine the clinical course of the OCD symptoms and assess the efficacy of qEEG guided NF training on clinical outcome measures. Thirty-six drug resistant subjects with OCD were assigned to 9-84 sessions of QEEG-guided NF treatment. Daily sessions lasted 60 minutes where 2 sessions with half-hour applications with a 30 minute rest given between sessions were conducted per day. Thirty-three out of 36 subjects who received NF training showed clinical improvement according to the Yale-Brown obsessive-compulsive scale (Y-BOCS). The Minnesota multiphasic inventory (MMPI) was administered before and after treatment to 17 of the subjects. The MMPI results showed significant improvements not only in OCD measures, but all of the MMPI scores showed a general decrease. Finally, according to the physicians' evaluation of the subjects using the clinical global impression scale (CGI), 33 of the 36 subjects were rated as improved. Thirty-six of the subjects were followed for an average of 26 months after completing the study. According to follow-up interviews conducted with them and/or their family members 19 of the subjects maintained the improvements in their OCD symptoms. This study provides good evidence for the efficacy of NF treatment in OCD. The results of this study encourage further controlled research in this area.

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.

A preliminary investigation of motor evoked potential abnormalities following sport-related concussion

BACKGROUND

Assessment of concussion is primarily based on self-reported symptoms, neurological examination and neuropsychological testing. The neurophysiologic sequelae and the integrity of the corticomotor pathways could be obtained by evaluating motor evoked potentials (MEPs).

OBJECTIVES

To compare MEPs obtained through transcranial magnetic stimulation (TMS) in acutely concussed and non-concussed collegiate athletes.

METHODS

Eighteen collegiate athletes (12 males, six females, aged 20.4 +/- 1.3 years) including nine subjects with acute concussion (<or=24 hours) matched to nine control subjects. TMS was applied over the motor cortex and MEP responses were recorded from the contralateral upper extremity. MEP thresholds (%), latencies (milliseconds per metre) and amplitudes were assessed. Central motor conduction time (CMCT) was calculated from MEP, M response and F wave latencies. Testing was performed on days 1, 3, 5 and 10 post-concussion.

RESULTS

Ulnar MEP amplitudes were significantly different between post-concussion days 3 and 5 (F(3,48) = 3.13, p = 0.041) with smaller amplitudes recorded on day 3 (0.28 +/- 0.10 ms m(-1)). Median MEP latencies were significantly longer (F(3,48) = 4.53, p = 0.023) 10 days post-concussion (27.1 +/- 1.4 ms m(-1)) compared to day 1 (25.7 +/- 1.5 ms m(-1)). No significant differences for motor thresholds or CMCTs were observed (p > 0.05).

CONCLUSION

MEP abnormalities among acutely concussed collegiate athletes provide direct electrophysiologic evidence for the immediate effects of concussion.

The effect of reference choices on the spatio-temporal analysis of brain evoked potentials: the use of infinite reference

Reference is a very virtual issue in EEG and ERP. Understanding the difference of various references will make the applications more confident. In this work, somatosensory evoked potential (SEP) with stimulation on the right hand was studied. The SEP spatio-temporal analysis was conducted comparatively on six references, left mastoid (contralateral mastoid reference, CM), right mastoid (ipsilateral mastoid reference, IM), linked mastoids (LM), average reference (AR), vertex reference (Cz) and the infinity reference (IR) newly proposed in 2001. Among the six, CM is the one used in actual recordings, and the other five are obtained by off-line re-referencing. The comparison is conducted on four selected components (P30 ms, P40 ms, N90 ms and P230 ms) in both temporal and spatial aspects. The results show that references may have a distinct influence on the amplitudes of the scalp potentials, with relative error at some electrodes larger than 500%, and for some electrodes it may even change the polarity. Pair-wise multiple comparison (Tukey test) shows that the differences of peak values among various references are very significant (P<0.001) between Cz and IR\CM\IM\LM, and significant (P<0.01) between Cz and AR for component N90 ms; very significant (P<0.001) between Cz and IR\CM\IM\LM\AR, significant between IMLM and AR (P<0.01), CM and AR (P<0.05) for component P230 ms. The amplitude value order is CM/IM> or =LM>IR>AR>Cz. The two-ways (the six references vs. the four Peaks) repeated measures ANOVA test shows the effect of different references depends on various components; there is a statistically significant interaction between reference and the peak (P=<0.001). While for the spatial map of the potential amplitude, references will not affect the amplitude map shape if the color-bar is selected automatically, but if a fixed color-bar is chosen for data of various references, they may show some differences. These results mean a common reference is important for producing a comparable result between labs. As IR is theoretically a constant reference, we recommend it as the common choice in the future.

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.

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.

A comparative study of different references for EEG spectral mapping: the issue of the neutral reference and the use of the infinity reference

Based on EEG data recorded from 11 subjects with eyes open and the left mastoid (M) reference, three data sets were generated by re-referencing to the conventional linked mastoids (L), average (A) and the new 'infinity' (I) reference provided by the reference electrode standardization technique (REST, Yao 2001 Physiol. Meas. 22 693-711). The EEG power in the alpha frequency band with the four different references was calculated and compared with respect to the total energy and spatial amplitude weight centre (AWC) coordinates, to compare the effects of different references on power mapping in the frequency domain. Compared with the I reference, the AWCs of the EEG with the M reference show significant shifts to the right, frontal and superficial positions, the L reference significant shifts to frontal and superficial positions, and the A reference shifts the AWC significantly to a deeper position. Furthermore, the power maps of the M and L references have larger total power than the I reference, while that of the A reference has the smallest total power. These results confirm that different choices of reference electrodes result in systematic changes in the distribution of EEG frequency power, and in order to reduce the effect of such systematic shifts on the explanation of EEG mappings, a common reference is necessary for EEG research. We recommend the I reference for objective use in cross-laboratory studies and clinical practices, as it is far from all the other electrodes and can act as a neutral reference.

Advances in quantitative electroencephalogram analysis methods

Quantitative electroencephalogram (qEEG) plays a significant role in EEG-based clinical diagnosis and studies of brain function. In past decades, various qEEG methods have been extensively studied. This article provides a detailed review of the advances in this field. qEEG methods are generally classified into linear and nonlinear approaches. The traditional qEEG approach is based on spectrum analysis, which hypothesizes that the EEG is a stationary process. EEG signals are nonstationary and nonlinear, especially in some pathological conditions. Various time-frequency representations and time-dependent measures have been proposed to address those transient and irregular events in EEG. With regard to the nonlinearity of EEG, higher order statistics and chaotic measures have been put forward. In characterizing the interactions across the cerebral cortex, an information theory-based measure such as mutual information is applied. To improve the spatial resolution, qEEG analysis has also been combined with medical imaging technology (e.g., CT, MR, and PET). With these advances, qEEG plays a very important role in basic research and clinical studies of brain injury, neurological disorders, epilepsy, sleep studies and consciousness, and brain function.

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.

Electronic medical devices: a primer for pathologists

CONTEXT

Electronic medical devices (EMDs) with downloadable memories, such as implantable cardiac pacemakers, defibrillators, drug pumps, insulin pumps, and glucose monitors, are now an integral part of routine medical practice in the United States, and functional organ replacements, such as the artificial heart, pancreas, and retina, will most likely become commonplace in the near future. Often, EMDs end up in the hands of the pathologist as a surgical specimen or at autopsy. No established guidelines for systematic examination and reporting or comprehensive reviews of EMDs currently exist for the pathologist.

OBJECTIVE

To provide pathologists with a general overview of EMDs, including a brief history; epidemiology; essential technical aspects, indications, contraindications, and complications of selected devices; potential applications in pathology; relevant government regulations; and suggested examination and reporting guidelines.

DATA SOURCES

Articles indexed on PubMed of the National Library of Medicine, various medical and history of medicine textbooks, US Food and Drug Administration publications and product information, and specifications provided by device manufacturers.

STUDY SELECTION

Studies were selected on the basis of relevance to the study objectives.

DATA EXTRACTION

Descriptive data were selected by the author.

DATA SYNTHESIS

Suggested examination and reporting guidelines for EMDs received as surgical specimens and retrieved at autopsy.

CONCLUSIONS

Electronic medical devices received as surgical specimens and retrieved at autopsy are increasing in number and level of sophistication. They should be systematically examined and reported, should have electronic memories downloaded when indicated, will help pathologists answer more questions with greater certainty, and should become an integral part of the formal knowledge base, research focus, training, and practice of pathology.

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.