qEEG Artifacting

The qEEG represents the statistical manipulation of the raw EEG, so an understanding of these manipulations should precede any discussion of the qEEGs clinical indications for protocols. Without such knowledge any given finding may be misinterpreted.

Following the careful recording of the EEG, the quantitative analysis is begun with the sampling of the data to be used in the analysis by the Fourier transform. The Fourier analysis assumes there are no transients (epileptic discharges, episodic voltage changes etc.) or state changes (light sleep, drug effect, mental task, etc.), so these must be avoided when selecting data for analysis in qEEG for eyes closed resting database comparison. There are some eyes open and task databases available more recently (Hudspeth, Sterman, Duffy etc.)

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Why do a qEEG for Neurotherapy?

There are many in the field of Neurotherapy who do not perform qEEGs prior to designing a clinical intervention. These people are currently practicing well within the standard of practice for this rapidly evolving field. Many within this group have standard protocols which are used on all clients, with various alterations to respond to the client’s reported experiences during the treatment.

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Patterns seen in the qEEG and their indicated interventions

Diffuse slowing, with slower alpha

The ascending reticular activating system stimulates the diffuse thalamic projection system and sets the general arousal level of the brain. With an increase in the CNS arousal level, there is an increase in the mean frequency of alpha and a decreased slowing. With decreases in arousal there is a slowing of the alpha, as well as eventually an increase in diffusely distributed slowing ( a mixture of diffuse lower voltage delta and theta, usually with a weak vertex prominence in linked ear montages).

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EEG Biofeedback as a Treatment for Substance Use Disorders: Review, Rating of Efficacy, and Recommendations for Further Research. Part 2

P300 Abnormalities in Cocaine, Methamphetamine, Heroin Addiction, and Alcoholism

The P300 component of the ERP, occurring 300–600 ms post-stimulus, is the most widely used ERP in psychiatry and other clinical applications (Polich et al. 1994; Polich and Herbst 2000; Pritchard 1981, 1986; Pritchard et al. 2004). The amplitude of the P300 reflects the allocation of attentional resources, while the latency is considered to reflect stimulus evaluation and classification time (Katayama and Polich 1998; Polich and Herbst 2000). The P300 is usually obtained in an oddball paradigm, wherein two stimuli are presented in a random order, one of them frequent (standard) and another one rare (target) (Polich 1990). A modification of the oddball task has been used where a third, also rare stimulus (distracter), is presented along with standard and target stimuli. It was reported that these infrequent distracters elicit a frontocentral P300, so called P3a, whereas the rare targets elicit a parietal P300, so called P3b (Katayama and Polich 1996, 1998). The P3a is recorded at the anterior scalp locations and has been interpreted as reflecting frontal lobe activity (Gaeta et al. 2003; Knight 1984). Though the P300 response in general is thought to represent ‘‘context updating/closure,’’ in a three-stimuli oddball task the P3a is interpreted as ‘‘orienting,’’ and the P3b is viewed as an index of the ability to maintain sustained attention to target (Na¨a¨ta¨nen 1990). The anterior P3a indexes the contextual salience of the rare stimuli, whereas the posterior P3b is indexing task-relevance of the stimuli (Gaeta et al. 2003).

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EEG Biofeedback as a Treatment for Substance Use Disorders: Review, Rating of Efficacy, and Recommendations for Further Research. Part 1

T. M. Sokhadze – email: tato.sokhadze@louisville.edu
Department of Psychiatry and Behavioral Sciences, University of Louisville School of Medicine, Louisville, KY, USA

R. L. Cannon – email: rcannon2@utk.edu
Department of Psychology, The University of Tennessee, Knoxville, TN 37996, USA

D. L. Trudeau – email: trude003@maroon.tc.umn.edu
Department of Family and Community Health, School of Health Sciences, University of Minnesota, Minneapolis, MN, USA

Abstract

Electroencephalographic (EEG) biofeedback has been employed in substance use disorder (SUD) over the last three decades. The SUD is a complex series of disorders with frequent comorbidities and EEG abnormalities of several types. EEG biofeedback has been employed in conjunction with other therapies and may be useful in enhancing certain outcomes of therapy. Based on published clinical studies and employing efficacy criteria adapted by the Association for Applied Psychophysiology and Biofeedback and the International Society for Neurofeedback and Research, alpha theta training—either alone for alcoholism or in combination with beta training for stimulant and mixed substance abuse and combined with residential treatment programs, is probably efficacious. Considerations of further research design taking these factors into account are discussed and descriptions of contemporary research are given.

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EEG Findings in Traumatic Brain Injury

This brief summary will discuss the various EEG findings seen in head injury when it results in a brain injury, though any given head injury may or may not result in traumatic brain injury.  When an injury is incurred by the brain there are a few varieties of findings seen in the EEG, ranging from spectral changes associated with either white or gray matter damage, to the changes in “connectivity”, seen as changes in coherence or correlation measured across the cortex, or between more distant functionally related areas.

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Introduction to Phenotypes

Identifying subtypes of specific disorders is an attractive exercise, as it expands our understanding of the individual’s response to therapy, but it remains attached to the approach based on the Diagnostic and Statistical Manual of Mental Disorders (DSM), which is rooted in behavior and frequently does not predict therapeutic response by any individual within the DSM grouping. Phenotypes are an intermediate step between genetics and behavior. These proposed electroencephalography (EEG) phenotypes are semistable states of neurophysiological function. The author proposes a framework allowing one to describe much of the observed EEG variance with a small number of phenotypical categories. These groupings cut across the DSM categories, and unlike the DSM, the phenotypes predict the individual’s response to therapy, for neurofeedback as well as for medication.

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