Clinical EEG and Neuroscience

Two major trends have been dominant in health care in recent years. First, there is a growing consensus that standardization of health care procedures and methods can result in improved effectiveness and safety of treatments. Second, there is increased interest in “personalized medicine,” which refers to the tailoring of treatments to individual patients. Here I discuss how these trends apply to the field of quantitative EEG (qEEG), where de-artifacted resting state EEGs of individuals are compared with a normative database in order to assess clinically meaningful deviations, which can be used for diagnostic procedures, to guide personalized treatment protocols, and to assess treatment effectiveness. Standardized and automated de-artifacting procedures are increasingly being used in scientific research and in clinical practice. The advantages of these procedures over manual de-artifacting will be discussed. The results of a systematic comparison between 2 commonly used qEEG databases show that these databases produce very comparable results, illustrating not only the validity and reliability of both databases but also the opportunity to move forward to a standardized use of qEEG in clinical practice. Finally, the standardization of qEEG interpretation as both a diagnostic and treatment selection tool provides an example of how qEEG can merge both personalized medicine and standardization in the treatment of psychological disorders.

For patients with psychiatric disorders, current diagnostic and treatment approaches are far from optimal. The clinical interview drives the standard approach—matching symptoms to diagnostic criteria—and results in standardized pharmacological and behavioral treatments, often, with inadequate outcome; but now, recent imaging advances can correlate behavioral assessments with brain function and measure them against normative databases to provide data critical for the reevaluation of patient diagnosis and treatment. This article addresses the data that support a redefinition of our current paradigm. We believe a neurobehavioral approach provides for more personalized treatment approaches unbound from classically defined diagnostic biases.

In part 1 of this article, we describe an approach and methodology that bridges 2 worlds: the internal, subjective experience of emotions and thoughts, and the external world of brain electrical activity. Using a novel event-related brain activation imaging method, we demonstrate that within single trials, short-term mental processes, on the order of 100 ms, can be clearly related to observed brain activation in controlled experiments. We use an ipsative assessment validation process that combines self-report with real-time EEG recordings to provide a combined picture of both the mental and the brain activity, during short-term reactions, emotions, and decisions regarding controlled information. Part 2 provides a detailed description of the emerging emotional decision-making model.

In this report, we integrate the principles described in part 1 and describe an operational model for emotional decision making that incorporates brain activation data along with subjective experience correlates. This model takes the form of a state machine that carries out transitions between a finite set of 16 possible states of emotional and decision-making response. By considering a 4 × 4 grid of possible states based on left and right activation, in primary (sensation) and secondary (perception/comprehension) response, the range of responses is completely specified. The transition probabilities within this repertoire of possible response states can be used to characterize an individual (or any system) in terms of its likelihood to respond in a particular fashion. The possible value of this model in psychiatry, psychology, and counseling is introduced and discussed.

Concussion is a common brain injury. The American Academy of Neurology provides a definition of concussion: “Concussion is a traumatically, or biomechanically, induced alteration of brain function. Emphasis is placed on a pathophysiological process, or functional disruption, as opposed to anatomic, structural, or tissue injury.”. The incidence of mild traumatic brain injury (mTBI) is estimated at 200 per 100 000. The Centers for Disease Control and Prevention (CDC) estimates 3.8 million sport and recreational mTBIs occurring in the United States each year. A more recent CDC assessment estimates 2.5 million concussion injuries in high school sports alone. The controlled environment and opportunity for direct surveillance and observation has made the sports arena the scientific “wet lab” for the study of mTBI natural history, short- and long-term consequences and opportunities to intervene. Quantitative EEG methods have been utilized in the assessment and management of mTBI and lends to provide a cost-effective procedure that has the sensitivities needed to identify pathology where routine visual inspection of the EEG has failed.

Quantitative electroencephalography (QEEG)-electrical neuroimaging has been underutilized in general neurology practice. Recent advances in computer technology have made this electrophysiological testing relatively inexpensive as well as precise in identifying brain areas with electrical dysfunction related to either traumatic injury or neurodegenerative process. In this article, the author presents 2 cases that can be frequently encountered in every general neurological practice: case of early dementia and traumatic brain injury. The clinical usefulness of QEEG is demonstrated by showing evidence of electrical abnormalities and networks dysfunctions (including an elevation of frontal/temporal delta and theta powers as well as abnormalities in functional connectivity). In addition, the correlation of QEEG and findings from structural imaging technique—magnetic resonance imaging diffusion tensor imaging and another functional imaging—positron emission tomography is presented.

This brief article is an overview of my personal experience over the past almost 10 years of the clinical use of EEG and quantitative EEG (qEEG) functional neuroimaging in a busy pediatric neurology practice. The concomitant use of surface EEG and functional electromagnetic EEG neuroimaging/qEEG in clinical practice provides significant additional clinical and neurophysiologic information. The qEEG is a noninvasive, inexpensive, portable technique with high temporal resolution (milliseconds) and improving spatial resolution (down to 3 mm³) and is an appropriate and validated tool for investigation of abnormal brain dynamics and connectivity of neuronal networks in clinical disorders of the brain. This article describes the daily applicability and utility of this modality in assisting diagnosis and clinical management of patients with a wide variety of presenting symptoms, including headaches, tics, autism spectrum disorder, inattention, sleep dysregulation, anxiety, and depression. The ease of data acquisition and analysis in clinical practices, coupled with skilled interpretation and clinical application, makes this tool one of the most valuable clinical tools to complement a thorough history and examination process.

Children with attention deficit hyperactivity disorder (ADHD) have high theta and low beta activity in the frontal lobe. The higher the theta/beta ratio, the lower the level of central nervous system (CNS) cortical arousal. However, there is seldom evidence between electroencephalograms (EEGs) and the patient’s intentionality to regulate the cortical activity of executive attention tasks. We investigated whether children with ADHD intended to improve their performance in executive attention tasks and whether that increased their brain activity. Fifty-one children with ADHD (ADHD) and 51 typical developing (TD) children were investigated using focused attention (FA) and search attention (SA) tasks and a simultaneous EEG. The children were then regrouped as faster (ADHD-F, TD-F) and slower (ADHD-S, TD-S) depending on reaction time (RT). Quantitative EEGs of frontal lobe theta and beta activity at frontal F3, F4, and Fz were used. Twenty-eight (54.9%) ADHD children were regrouped as ADHD-S and 14 (27.5%) as TD-S. The ADHD-S group, however, had poorer FA and SA performance than the other 3 groups did: fewer correct answers, more frequent impulsive and missing errors, and higher RT variations. There were no significant differences in theta activity, but the TD-S group had higher beta activity than the ADHD-S group did. We conclude that the ADHD-F and ADHD-S groups had different attention processes. beta activity did not increase in the ADHD-S group, and their executive attention performance in the FA and SA tests was poor. It seems ADHD-S had poor meta-intention function. The frontal beta activity might be a feasible training target of neurofeedback in ADHD-S patients.

The clinical use of the quantitative EEG (QEEG) from the pioneering work of John has received a new impetus thanks to new neuroimaging techniques and the possibility of using a number of normative databases both of normal subjects and of subjects with definite pathologies. In this direction, the term personalized medicine is becoming more and more common, a medical procedure that separates patients into different groups based on their predicted response to the quantitative EEG. This has allowed the study of single subjects and to customize health care, with decisions and treatments tailored to each individual patient, as well as improvement of knowledge of the pathophysiological mechanisms of specific diseases. This review article will present the most recent evidence in the field of developmental neuropsychiatric disorders obtained from the application of quantitative EEG both in clinical group studies (attention deficit hyperactivity disorder, developmental dyslexia, oppositional defiant disorder) and in individual case studies not yet published.