According to the U.S. Substance Abuse and Mental Health Services Administration, addiction is currently one of the most significant health and social problems in America, affecting ~12.5% of the population. Medical costs can be up to 300% higher for an untreated alcoholic than a treated alcoholic. Other costs to society have reached almost $500 billion, taking into account unemployment, lost productivity, increased crime and justice system/incarceration costs, health care system strain, increased insurance costs, child abuse/neglect and even workplace violence. It is estimated that every dollar spent on treatment saves $4–$7 in costs from drug-related crime and can help reduce the spread of infectious diseases.
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.)
I often get questions about Alzheimer’s Disease (AD) and the EEG.
Whenever a client presents with the question of dementia, all other forms of
dementia need to be ruled out before you are left with the diagnosis of AD.
There are many EEG signatures of various forms of dementia, all of which are
helpful in evaluating a client’s presentation of dementia.
Done by experts in EEG in dementia, the EEG and qEEG may be of substantial
additive value in the differential diagnosis puzzle that all cases of
dementia represent clinically.
One EEG pattern seen in dementia is the presence of periodic triphasic
slowing in the EEG, which is actually diagnostic of subacute sclerosing
panencephalitis (SSPE). SSPE is a “spongiform encephalopathy” where the
brain becomes like “Swiss cheese”, with holes scattered throughout. This
periodic triphasic finding is differentiated from MULTIFOCAL triphasics
which are diagnostic of Crutzfeld-Jacob Syndrome (CJD), which in lay terms
is a form of mad cow disease in humans.
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.
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.