The quantified EEG characteristics of responders and non-responders to long-term treatment with atomoxetine in children with attention deficit hyperactivity disorders.

OBJECTIVE: The aim of our study is to examine quantitative Electroencephalogram (QEEG) differences between ADHD patients that are responders and non-responders to long-term treatment with Atomoxetine at baseline and after 6 and 12months of treatment. Patients with attention deficit hyperactivity disorder (ADHD) received atomoxetine titrated, over 7days, from 0.5 to 1.2mg/kg/day. QEEG and Swanson, Nolan, and Pelham-IV Questionnaire (SNAP-IV) scores were recorded before treatment and after therapy. METHODS: Twenty minutes of eyes closed resting EEG was recorded from 19 electrodes referenced to linked earlobes. Full frequency and narrow band spectra of two minutes of artifact-free EEG were computed as well as source localization using Variable Resolution Electrical Tomography (VARETA). Abnormalities were identified using Z-spectra relative to normative values. RESULTS: Patients were classified as responders, non-responders and partial responders based upon the SNAP-IV findings. At baseline, the responders showed increased absolute power in alpha and delta in frontal and temporal regions, whereas, non-responders showed increased absolute power in all frequency bands that was widely distributed. With treatment responders' absolute power values moved toward normal values, whereas, non-responders remained at baseline values. CONCLUSIONS: Patients with increased power in the alpha band with no evidence of alterations in the beta or theta range, might be responders to treatment with atomoxetine. Increased power in the beta band coupled with increased alpha seems to be related to non-responders and one should consider atomoxetine withdrawal, especially if there is persistence of increased alpha and beta accompanied by an increase of theta.

Identification of acute stroke using quantified brain electrical activity.

OBJECTIVES: Acute stroke is a leading cause of brain injury and death and requires rapid and accurate diagnosis. Noncontrast head computed tomography (CT) is the first line for diagnosis in the emergency department (ED). Complicating rapid triage are presenting conditions that clinically mimic stroke. There is an extensive literature reporting clinical utility of brain electrical activity in early diagnosis and management of acute stroke. However, existing technologies do not lend themselves to easily acquired rapid evaluation. This investigation used an independently derived classifier algorithm for the identification of traumatic structural brain injury based on brain electrical activity recorded from a reduced frontal montage to explore the potential clinical utility of such an approach in acute stroke assessment. METHODS: Adult patients (age 18 to 95 years) presenting with stroke-like and/or altered mental status symptoms were recruited from urban academic EDs as part of a large research study evaluating the clinical utility of quantitative brain electrical activity in acutely brain-injured patients. All patients from the parent study who had confirmed strokes, and a control group of stroke mimics (those with final ED diagnoses of migraine or syncope), were selected for this study. All stroke patients underwent head CT scans. Some patients with negative CTs had further imaging with magnetic resonance imaging (MRI). Ten minutes of electroencephalographic data were acquired on a hand-held device in development, from five frontal electrodes. Data analyses were done offline. A Structural Brain Injury Index (SBII) was derived using an independently developed binary discriminant classification algorithm whose input was specified features of brain electrical activity. The SBII was previously found to have high accuracy in the identification of traumatic brain-injured patients who were found to have brain injury on CT (CT+). This algorithm was applied to patients in this study and used to classify patients as CT+ or not CT+. Performance was assessed using sensitivity, specificity, and negative and positive predictive values (NPV, PPV). RESULTS: Forty-eight stroke patients (31 ischemic and 17 hemorrhagic) and 135 stroke mimic controls were included. Within the ischemic population, approximately half were CT- but later confirmed for stroke with MRI (CT-/MRI+). Sensitivity to stroke was 91.7%, specificity 50.4% (to stroke mimic), NPV 94.4%, and PPV 39.6%. Eighty percent of the CT-/MRI+ ischemic strokes were correctly identified at the time of the CT- scan. CONCLUSIONS: Despite a small population and the use of a classifier without the benefit of training on a stroke population, these data suggest that a rapidly acquired, easy-to-use system to assess brain electrical activity at the time of evaluation of acute stroke could be a valuable adjunct to current clinical practice.

Use of brain electrical activity for the identification of hematomas in mild traumatic brain injury.

This study investigates the potential clinical utility in the emergency department (ED) of an index of brain electrical activity to identify intracranial hematomas. The relationship between this index and depth, size, and type of hematoma was explored. Ten minutes of brain electrical activity was recorded from a limited montage in 38 adult patients with traumatic hematomas (CT scan positive) and 38 mild head injured controls (CT scan negative) in the ED. The volume of blood and distance from recording electrodes were measured by blinded independent experts. Brain electrical activity data were submitted to a classification algorithm independently developed traumatic brain injury (TBI) index to identify the probability of a CT+traumatic event. There was no significant relationship between the TBI-Index and type of hematoma, or distance of the bleed from recording sites. A significant correlation was found between TBI-Index and blood volume. The sensitivity to hematomas was 100%, positive predictive value was 74.5%, and positive likelihood ratio was 2.92. The TBI-Index, derived from brain electrical activity, demonstrates high accuracy for identification of traumatic hematomas. Further, this was not influenced by distance of the bleed from the recording electrodes, blood volume, or type of hematoma. Distance and volume limitations noted with other methods, (such as that based on near-infrared spectroscopy) were not found, thus suggesting the TBI-Index to be a potentially important adjunct to acute assessment of head injury. Because of the life-threatening risk of undetected hematomas (false negatives), specificity was permitted to be lower, 66%, in exchange for extremely high sensitivity.

Time course of clinical and electrophysiological recovery after sport-related concussion.

BACKGROUND AND PURPOSE: Recent neuroimaging studies suggest that abnormalities in brain function after concussion exist beyond the point of observed clinical recovery. This study investigated the relationship between an index of brain dysfunction (traumatic brain injury [TBI] Index), concussion severity, and outcome. METHODS: EEG was collected from forehead locations in 65 male athletes with concussion within 24 hours of concussion, with follow-up at 8 and 45 days postinjury. Neurocognitive and symptom assessments were also performed and used to classify subjects in mild or moderate concussion categories. Time to return to play was recorded. RESULTS: The TBI Index was higher in the moderate than mild concussion group at injury, day 8, and day 45. The moderate group had increased symptoms and decreased cognitive performance only at the time of injury. At the time of injury, only the TBI Index was significantly associated with the length of time to return to play. CONCLUSIONS: Recovery of brain function after sport-related concussion may extend well beyond the time course of clinical recovery and be related to clinical severity. An index of brain dysfunction may be an objective indicator of injury, recovery, and readiness to return to play. The relatively small sample indicates the need for further study on the time course of physiological recovery.

Measuring brain electrical activity to track recovery from sport-related concussion.

PRIMARY OBJECTIVE: To follow recovery from concussion in a sample of athletes using an electroencephalographic (EEG) index of quantitative brain activity developed previously on an independent Emergency Department (ED) sample of head-injured subjects with traumatic brain injury. METHODS AND PROCEDURES: EEG recordings from five frontal electrode sites were obtained on 59 injured athletes and 31 controls at the time of injury and at 8 and 45 days afterward. All subjects also completed standardized clinical assessment of post-concussion symptoms, postural stability and cognitive functioning at injury and 8 and 45 days post-injury. RESULTS: Abnormalities in clinical assessment measures were observed in injured subjects only at time of injury. Statistical analysis of brain electrical activity measures with the ED-based algorithm revealed significant differences between injured athletes vs controls at the time of injury and at day 8. Measures from the two groups did not differ on day 45. CONCLUSIONS: This study demonstrated that an algorithm of brain electrical activity developed on an independent sample of ED subjects with head injury is sensitive to the effects of sport-related concussion. Using this algorithm, abnormal features of brain electrical activity were detected in athletes with concussion at the time of injury and persisted beyond the point of recovery on clinical measures.

Quantitative brain electrical activity in the initial screening of mild traumatic brain injuries.

INTRODUCTION: The incidence of emergency department (ED) visits for Traumatic Brain Injury (TBI) in the United States exceeds 1,000,000 cases/year with the vast majority classified as mild (mTBI). Using existing computed tomography (CT) decision rules for selecting patients to be referred for CT, such as the New Orleans Criteria (NOC), approximately 70% of those scanned are found to have a negative CT. This study investigates the use of quantified brain electrical activity to assess its possible role in the initial screening of ED mTBI patients as compared to NOC. METHODS: We studied 119 patients who reported to the ED with mTBI and received a CT. Using a hand-held electroencephalogram (EEG) acquisition device, we collected data from frontal leads to determine the likelihood of a positive CT. The brain electrical activity was processed off-line to generate an index (TBI-Index, biomarker). This index was previously derived using an independent population, and the value found to be sensitive for significant brain dysfunction in TBI patients. We compared this performance of the TBI-Index to the NOC for accuracy in prediction of positive CT findings. RESULTS: Both the brain electrical activity TBI-Index and the NOC had sensitivities, at 94.7% and 92.1% respectively. The specificity of the TBI-Index was more than twice that of NOC, 49.4% and 23.5% respectively. The positive predictive value, negative predictive value and the positive likelihood ratio were better with the TBI-Index. When either the TBI-Index or the NOC are positive (combining both indices) the sensitivity to detect a positive CT increases to 97%. CONCLUSION: The hand-held EEG device with a limited frontal montage is applicable to the ED environment and its performance was superior to that obtained using the New Orleans criteria. This study suggests a possible role for an index of brain function based on EEG to aid in the acute assessment of mTBI patients.

Use of brain electrical activity to quantify traumatic brain injury in the emergency department.

PRIMARY OBJECTIVE: To validate a QEEG algorithm on traumatic brain injury in an Emergency Department (ED) setting. METHODS AND PROCEDURES: EEG data were collected from 105 patients with head injury (53 CT+ and 52 CT-) and 50 ED controls. Ten minutes of eyes closed resting EEG was collected from five frontal locations. A discriminant index of the probability of belonging to the TBI CT+ group was computed. Analysis of variance was computed comparing this index across the three patient groups. Using ROC curves, the p < 0.05 confidence level was determined to compute sensitivity and specificity for the TBI CT+ population. RESULTS: CT+ patients had a mean TBI discriminant index of 80.4, CT- patients 38.9 and controls 24.5; F = 70.2, p < 0.0001. Sensitivity was 92.45% for the CT+ group and specificity was 90.00% for the control group. CONCLUSIONS: The TBI discriminant index appears to be a sensitive index of brain function. It may be used to suggest whether or not a patient presenting with altered mental status requires a CT scan. This index may aid in the triage of such patients in the ED. Such an easy to use, automated system may greatly enhance the clinical utility of EEG in the ED.

Acute effects and recovery after sport-related concussion: a neurocognitive and quantitative brain electrical activity study.

OBJECTIVE: To investigate the clinical utility and sensitivity of a portable, automatic, frontal quantitative electroencephalographic (QEEG) acquisition device currently in development in detecting abnormal brain electrical activity after sport-related concussion. DESIGN: This was a prospective, non-randomized study of 396 high school and college football players, including cohorts of 28 athletes with concussion and 28 matched controls. All subjects underwent preseason baseline testing on measures of postconcussive symptoms, postural stability, and cognitive functioning, as well as QEEG. Clinical testing and QEEG were repeated on day of injury and days 8 and 45 postinjury for the concussion and control groups. MAIN OUTCOMES AND RESULTS: The injured group reported more significant postconcussive symptoms during the first 3 days postinjury, which resolved by days 5 and 8. Injured subjects also performed poorer than controls on neurocognitive testing on the day of injury, but no differences were evident on day 8 or day 45. QEEG studies revealed significant abnormalities in electrical brain activity in the injured group on day of injury and day 8 postinjury, but not on day 45. CONCLUSIONS: Results from the current study on clinical recovery after sport-related concussion are consistent with early reports indicating a typical course of full recovery in symptoms and cognitive dysfunction within the first week of injury. QEEG results, however, suggest that the duration of physiological recovery after concussion may extend longer than observed clinical recovery. Further study is required to replicate and extend these findings in a larger clinical sample, and further demonstrate the utility of QEEG as a marker of recovery after sport-related concussion.

QEEG studies in the assessment and treatment of childhood disorders.

Quantifying EEG measures across age allows the ability to establish parameters of normalcy at any age which can be used as a reference when children exhibit developmental delays in their abilities and/or other atypical and maladaptive behaviors. A review of the current literature on the utilization of QEEG methods to serve as an aid for identifying these children as distinctively different from normal, and in some cases as distinctive from other clinical considerations has been shown to provide a sufficient sensitivity and specificity worthy of consideration as a diagnostic aid in evaluating clinical deviations in development. Furthermore, these same QEEG measures can provide a means of establishing treatment efficacy for the evident brain dysfunctions underlying these childhood disorders.

The neurophysiology of attention-deficit/hyperactivity disorder.

Recent reviews of the neurobiology of Attention-Deficit/Hyperactivity Disorder (AD/HD) have concluded that there is no single pathophysiological profile underlying this disorder. Certainly, dysfunctions in the frontal/subcortical pathways that control attention and motor behavior are implicated. However, no diagnostic criteria or behavioral/neuroimaging techniques allow a clear discrimination among subtypes within this disorder, especially when problems with learning are also considered. Two major Quantitative EEG (QEEG) subtypes have been found to characterize AD/HD. Here we review the major findings in the neurophysiology of AD/HD, focusing on QEEG, and briefly present our previous findings using a source localization technique called Variable Resolution Electromagnetic Tomography (VARETA). These two techniques represent a possible objective method to identify specific patterns corresponding to EEG-defined subtypes of AD/HD. We then propose a model representing the distribution of the neural generators in these two major AD/HD subtypes, localized within basal ganglia and right anterior cortical regions, and hippocampal, para-hippocampal and temporal cortical regions, respectively. A comprehensive review of neurochemical, genetic, neuroimaging, pharmacological and neuropsychological evidence in support of this model is then presented. These results indicate the value of the neurophysiological model of AD/HD and support the involvement of different neuroanatomical systems, particularly the dopaminergic pathways.

The role of quantitative electroencephalography in child and adolescent psychiatric disorders.

This article presents a critical review of quantitative electroencephalographic (qEEG) research and issues relevant to its clinical application. Included is a summary of methodologic issues necessary for a reliable implementation of qEEG within clinical settings and a brief discussion of controversial issues surrounding this implementation. The main body of the article includes a summary of qEEG findings that involves adults with various neurologic and psychiatric disorders, which is followed by an in-depth presentation of qEEG research that involves children and adolescents with neurologic and psychiatric disorders. A concluding section presents a qEEG-based neurophysiologic model of attention deficit disorder.

Patient State Index: titration of delivery and recovery from propofol, alfentanil, and nitrous oxide anesthesia.

BACKGROUND: The Patient State Index (PSI) uses derived quantitative electroencephalogram features in a multivariate algorithm that varies as a function of hypnotic state. Data are recorded from two anterior, one midline central, and one midline posterior scalp locations. PSI has been demonstrated to have a significant relation to level of hypnosis during intravenous propofol, inhalation, and nitrous oxide-narcotic anesthesia. This multisite study evaluated the utility of PSI monitoring as an adjunct to standard anesthetic practice for guiding the delivery of propofol and alfentanil to accelerate emergence from anesthesia. METHODS: Three hundred six patients were enrolled in this multicenter prospective randomized clinical study. Using continuous monitoring throughout the period of propofol-alfentanil-nitrous oxide anesthesia delivery, PSI guidance was compared with use of standard practice guidelines (both before [historic controls] and after exposure to the PSA 4000 monitor [Physiometrix, Inc., N. Billerica, MA; standard practice controls]). Anesthesia was always administered with the aim of providing hemodynamic stability, with rapid recovery. RESULTS: No significant differences were found for demographic variables or for site. The PSI group received significantly less propofol than the standard practice control group (11.9 microg x kg(-1) x min(-1); P < 0.01) and historic control group (18.2 microg x kg(-1) x min(-1); P < 0.001). Verbal response time, emergence time, extubation time, and eligibility for operating room discharge time were all significantly shorter for the PSI group compared with the historic control (3.3-3.8 min; P < 0.001) and standard practice control (1.4-1.5 min; P < 0.05 or P < 0.01) groups. No significant differences in the number of unwanted somatic events or hemodynamic instability and no incidences of reported awareness were found. CONCLUSIONS: Patient State Index-directed titration of propofol delivery resulted in faster emergence and recovery from propofol-alfentanil-nitrous oxide anesthesia, with modest decrease in the amount of propofol delivered, without increasing the number of unwanted events.

Subtyping of psychiatric disorders: implications for drug development.

Psychiatric diagnosis suffers from being based on phenomenology and not on pathophysiology. Data are presented showing that psychiatric patients reveal consistent quantitative electroencephalographic abnormalities, such that they can be separated from normals and from each other. Clustering these pathophysiological groupings reveals an underlying variability, which permits useful subtyping. Data are presented relating subtyping to pharmacological treatment.