Quantitative EEG (QEEG) began in the 1970s and early 80s as an attempt to extract from brain electrical activity more than what could be readily appreciated by simple, unaided visual inspection of EEG. QEEG should be viewed as an extension of, and not a replacement for, traditional EEG. Clinically, QEEG should always follow the preparation and analysis of the classic EEG. The human eye is still superior to the computer in many aspects of brain signal analysis. But the computer is superior to the eye and mind for other aspects of analysis.
What are “brainmaps”?
To assist in the estimation of EEG spectral content (one of the most difficult tasks by visual inspection), EEG data are entered into a computer, as for dEEG, and spectral content is rigorously determined by the use of techniques of mathematical signal analysis (typically by the FFT or Fast Fourier Transform algorithm). One of the early problems that was noted was how to visualize results since QEEG typically uses more channels than EEG. The solution was to map the results using colored grey scaling on schematic maps of the head.To some, such brain electrical activity mapping or simply “mapping” is taken as synonymous with QEEG. However mapping is only a display technique and only the first step. The heart of QEEG lies with the underlying computerized analytic and statistical techniques.
What else can spectral analysis measure?
A special result of spectral analysis is a measure of the coherence between two electrodes. This is referred to as “spectral coherence”. It assesses the similarity of spectral content of two electrodes over time and is usually taken to reflect a measure of “coupling” between brain regions. It is virtually impossible to estimate coherence by visual EEG inspection. Some illnesses may begin with abnormalities of cortical “coupling”. Leuchter has reported such abnormalities in Alzheimer’s Disease and Thatcher found abnormality of coherence as the best discriminator of mild closed head injury.
How do you know how abnormal a finding is?
Such spectral maps provide excellent displays of the spatial distribution of EEG spectral content and are clinically useful as such. However, evidence has shown that in some way it would be necessary to estimate when such data were outside of normal bounds for a patients age. This lead first to the need for and the development of normative databases of brain electrical activity at all ages. Second, it lead to the development of the technique of mapping, not just a patient’s brain activity, but also the degree of statistical deviancy of the patient from the normal database (in units of standard deviation of scores). Such images of deviancy are referred to as SPM (statistical or significance probability maps). Thus a neurophysiologist may look at a SPM and locate regions of possible clinical abnormality by deviant regions on the SPM. The term “encephalopathic” often refers to brains with excessive EEG slowing. A typical application would be to determine whether behavioral disturbance in an adult is due to early dementia (increased slowing) or otherwise uncomplicated depression (no increase of slowing). QEEG techniques add significant power to the search for subtle encephalopathic change. Although developed first for QEEGanalyses, the SPM technique has been widely adapted for use with other neuroimaging techniques.
Are there other applications for QEEG?
Another area where QEEG techniques have been applied is to the long latency sensory evoked potentials. EEG represents the brain’s ambient, spontaneously ongoing electrical activity. Evoked potentials (EPs) are the brain’s transient response to externally applied stimuli ?] such as light flashes, auditory clicks, and mild electrical shocks.These stimuli form, respectively, the visual evoked response or potential (VEP), auditory EP (AEP) and somatosensory EP (SEP). Since the BEG is much higher amplitude than the EP, it is necessary to apply a stimulus repetitively at random times and average the result so as to effectively remove the random background EEG and visualize the EP. This computerized technique is often referred to as “signal averaging”.
Classic Neurophysiology employs a few EP channels and evaluates the short latency response (e.g., under 30 msec). When obtained, these signals are seen to arise from specific deep brain structures and allow for assessment of structures within the brain stem and thalamus. When longer latencies (longer times from stimulation) are evaluated, signals appear to be coming from the cortical mantle. Unfortunately the complex waveform morphologies from a large set of such long latency EPs can be very difficult to analyze by unaided visual inspection. However, with the use of normative databases and the SPM technique, regions of clinically important abnormality can be delineated within the complex combined spatialtemporal information within long latency EP data sets. Many QEEG laboratories incorporate the long latency EP along with spectral analyzed EEG signals and traditional EEG as part of their routine clinical studies. Such EP data tend to be sensitive to clinical conditions where cortical dysfunction is hypothesized (e.g., dyslexia, schizophrenia, Alzheimer’s disease) although they are also often found to be abnormal in epilepsy.