Bronzino J.D.. Berbari. E.J.. Johnson P.L.. Smith. W.M."Bioelectronics and Instruments The electrical Engineering Handbook Ed. Richard C. dorf Boca Raton CRC Press llc. 2000
Bronzino, J.D., Berbari, E.J., Johnson, P.L., Smith, W.M. “Bioelectronics and Instruments” The Electrical Engineering Handbook Ed. Richard C. Dorf Boca Raton: CRC Press LLC, 2000
15 Bioelectronics and Joseph D. Bronzino finity College/Biomedical Allience Instruments for Central Connecticut(BOACON) Edward J. Berbari Purdue University 115.1 The Electroencephalogram Philip L. Johnson Recording Techniques Frequency Analysis of the EEG University of Alabama at Nonlinear Analysis of the EEG. Topographic Mapping 115.2 The Electrocardiograph William M. smith Physiology. Instrumentation.Conclusions University of Alabama at 115.3 Pacemakers/Implantable Defibrillators Pacemakers. Implantable Cardioverter Defibrillators 115.1 The Electroencephalogram Joseph d. bronzino Electroencephalograms(EEGs)are recordings of the minute (generally less than 300 uV) electrical potential produced by the brain. Since 1924, when Hans Berger reported the measurements of rhythmic electrical activit the neuronal bases for specific behaviors and has offered great promise to reveal correlations between patha a on the human scalp, it has been suggested that these patterns of bioelectrical origin may provide clues regard logical processes and the electrical activity of specific regions of the brain. Over the years, EEG analyses have been conducted primarily in clinical settings, to detect gross organic pathologies and the epilepsies, and in research facilities to quantify the central effect of new pharmacological agents. As a result of these efforts, cortical EEG patterns have been shown to be modified by a wide variety of variables including biochemical, metabolic, circulatory, hormonal, neuroelectric, and behavioral factors. In the past, interpretation of the EEG was limited to visual inspection by a trained electroencephalographer capable of distinguishing normal activity from localized or generalized abnormalities of particular types from relatively long EEG records. This approach has left clinicians and researchers alike lost in a sea of EEG paper records. Computer technology has permitted the application of a host of methods to quantify EEG changes. With this mind, this section provides an introduction to some of the basic concepts underlying the generation of the EEG, a review of the basic approaches used in quantifying alterations in the EEG, and some insights regarding quantitative electrophysiology techniques The Language of the Brain The mass of brain tissue is composed of bundles of nerve cells(neurons) which constitute the fundamental uilding blocks of the nervous system. Figure 115. 1 is a schematic drawing of just such a cell. It consists of the cell body (or soma), the receptor zone(or dendrites), and the axon, which carries electrical signals from the soma to target sites such as muscles, glands, or other neurons. Numbering approx imately 20 billion in each human being, these tiny cells come in a variety of sizes and shapes. Although neurons are anatomically distinct units having no physical continuity between their processes, the axon ends on the as a spherical enlargement at the end of the axon to whis synapse. Under the microscope this often stands out soma and the dendrites of other cells in what is called a various names have been given, for example, boutons, c 2000 by CRC Press LLC
© 2000 by CRC Press LLC 115 Bioelectronics and Instruments 115.1 The Electroencephalogram The Language of the Brain • Historical Perspective • EEG Recording Techniques • Frequency Analysis of the EEG • Nonlinear Analysis of the EEG • Topographic Mapping 115.2 The Electrocardiograph Physiology • Instrumentation • Conclusions 115.3 Pacemakers/Implantable Defibrillators Pacemakers • Implantable Cardioverter Defibrillators 115.1 The Electroencephalogram Joseph D. Bronzino Electroencephalograms (EEGs) are recordings of the minute (generally less than 300 µV) electrical potentials produced by the brain. Since 1924, when Hans Berger reported the measurements of rhythmic electrical activity on the human scalp, it has been suggested that these patterns of bioelectrical origin may provide clues regarding the neuronal bases for specific behaviors and has offered great promise to reveal correlations between pathological processes and the electrical activity of specific regions of the brain. Over the years, EEG analyses have been conducted primarily in clinical settings, to detect gross organic pathologies and the epilepsies, and in research facilities to quantify the central effect of new pharmacological agents. As a result of these efforts, cortical EEG patterns have been shown to be modified by a wide variety of variables including biochemical, metabolic, circulatory, hormonal, neuroelectric, and behavioral factors. In the past, interpretation of the EEG was limited to visual inspection by a trained electroencephalographer capable of distinguishing normal activity from localized or generalized abnormalities of particular types from relatively long EEG records. This approach has left clinicians and researchers alike lost in a sea of EEG paper records. Computer technology has permitted the application of a host of methods to quantify EEG changes. With this in mind, this section provides an introduction to some of the basic concepts underlying the generation of the EEG, a review of the basic approaches used in quantifying alterations in the EEG, and some insights regarding quantitative electrophysiology techniques. The Language of the Brain The mass of brain tissue is composed of bundles of nerve cells (neurons) which constitute the fundamental building blocks of the nervous system. Figure 115.1 is a schematic drawing of just such a cell. It consists of three major components: the cell body (or soma), the receptor zone (or dendrites), and the axon, which carries electrical signals from the soma to target sites such as muscles, glands, or other neurons. Numbering approximately 20 billion in each human being, these tiny cells come in a variety of sizes and shapes. Although neurons are anatomically distinct units having no physical continuity between their processes, the axon ends on the soma and the dendrites of other cells in what is called a synapse. Under the microscope this often stands out as a spherical enlargement at the end of the axon to which various names have been given, for example, boutons, Joseph D. Bronzino Trinity College/Biomedical Allience for Central Connecticut (BOACON) Edward J. Berbari Purdue University Philip L. Johnson University of Alabama at Birmingham William M. Smith University of Alabama at Birmingham
end-plate, or synaptic terminals. This ending does not actually make physical contact with the soma or dendrite but is separated by a narrow cleft(gap)of approximately Axonal Terminals cleft. Each of these synaptic endings contains a large num ber of submicroscopic spherical structures(synaptic vesi in be detected only under an electron Dendrite microscope. These synaptic vesicles, in turn, are essentially is released into the synaptic cleft on excitation. Axon When an individual neuron is excited, an electrical sig- nal is transmitted along its axon to many tiny branching, diverging fibers near its far end. These axonal terminals Axonal nd as synapse on a large number of other neurons. when an electrical pulse arrives at the synapse, it triggers the FIGURE 115.1 Basic structure of the neuron lease of a tiny amount of transmitter substance which crosses the synaptic cleft thereby altering the membrane potential of the receiving neuron. If the change is above a certain threshold value, the neuron is activated and generates an action potential of its own which propagated along its axon, and the process is repeated. Neurons are involved in every conceivable action taken by the body, whether it is to control its own internal nvironment or to respond to changes in the external world. As a result, they are responsible for such essential ons as: Accepting and converting sensory information into a form that can be processed within the nervous system by other neurons. Processing and analyzing this information so that an"integrated portrait"of the incoming data can be obtained Translating the final outcome or decision"of this analysis process into appropriate electrical or chemical form needed to stimulate glands or activate muscles. Evolution has played a role in the development of these unique neurons and in the arrangement and development of interconnections between nerve cells in the various parts of the brain. Since the brain is a most complex organ, it contains numerous regions designed for specific tasks. One might, in fact, consider it to be a collection of organs arranged together to act in the harmony of activity we recognize as the individuals state of consciousness or as life itself. Over the years, anatomists and physiologists have identified and named most pathways(tracts), most groups of neurons(nuclei), and most of the major parts of the human brain. Such attention to detail is certainly not necessary here. It will serve our purpose to simply provide a broad overview of the organization of the brain and speak of three general regions: the brainstem, cerebellum, and the cerebral cortex. The brainstem, or old brain, is really an extension and elaboration of the spinal chord. This section of the brain evolved first and is the location of all the centers that control the regulatory systems, such as respiration, necessary for physical survival of the organism. In addition, all sensory pathways find their way into the brainstem, thereby permitting the integration of complex input patterns to take place within its domain Above the brainstem is a spherical mass of neuronal tissue called the cerebellum. This remarkable structure is a complex monitor and modifier of body movements. The cerebellum does not initiate movements, but only modifies motor control activate er areas. Cerebellar operation is not only dependent on evolutionary development but relies heavily on actual use and patterns of learned motor behavior acquired throughout life. It is for this reason that the movements of a gymnast are smooth and seemingly effortless The most conspicuous part of all in the human brain is the cerebral cortex. Compared to most mammals, it is so large in man that it becomes a covering that surrounds and hides most of the other regions of the brain. Wrinkled and folded, the cerebral tissue is literally pressed into the limited space allocated to it. although it has been possible to ascertain that certain cortical areas such as visual cortex, the sensory projection area, and the motor strip are associated with specific functions, the overall operation of this complex structure is still c2000 by CRC Press LLC
© 2000 by CRC Press LLC end-plate, or synaptic terminals. This ending does not actually make physical contact with the soma or dendrite but is separated by a narrow cleft (gap) of approximately 100 to 200 Å (10–9 m) wide. This is known as the synaptic cleft. Each of these synaptic endings contains a large number of submicroscopic spherical structures (synaptic vesicles) that can be detected only under an electron microscope. These synaptic vesicles, in turn, are essentially “chemical carriers” containing transmitter substance that is released into the synaptic cleft on excitation. When an individual neuron is excited, an electrical signal is transmitted along its axon to many tiny branching, diverging fibers near its far end. These axonal terminals end as synapse on a large number of other neurons. When an electrical pulse arrives at the synapse, it triggers the release of a tiny amount of transmitter substance which crosses the synaptic cleft thereby altering the membrane potential of the receiving neuron. If the change is above a certain threshold value, the neuron is activated and generates an action potential of its own which is propagated along its axon, and the process is repeated. Neurons are involved in every conceivable action taken by the body, whether it is to control its own internal environment or to respond to changes in the external world. As a result, they are responsible for such essential functions as: • Accepting and converting sensory information into a form that can be processed within the nervous system by other neurons. • Processing and analyzing this information so that an “integrated portrait” of the incoming data can be obtained. • Translating the final outcome or “decision” of this analysis process into appropriate electrical or chemical form needed to stimulate glands or activate muscles. Evolution has played a role in the development of these unique neurons and in the arrangement and development of interconnections between nerve cells in the various parts of the brain. Since the brain is a most complex organ, it contains numerous regions designed for specific tasks. One might, in fact, consider it to be a collection of organs arranged together to act in the harmony of activity we recognize as the individual’s state of consciousness or as life itself. Over the years, anatomists and physiologists have identified and named most pathways (tracts), most groups of neurons (nuclei), and most of the major parts of the human brain. Such attention to detail is certainly not necessary here. It will serve our purpose to simply provide a broad overview of the organization of the brain and speak of three general regions: the brainstem, cerebellum, and the cerebral cortex. The brainstem, or old brain, is really an extension and elaboration of the spinal chord. This section of the brain evolved first and is the location of all the centers that control the regulatory systems, such as respiration, necessary for physical survival of the organism. In addition, all sensory pathways find their way into the brainstem, thereby permitting the integration of complex input patterns to take place within its domain. Above the brainstem is a spherical mass of neuronal tissue called the cerebellum. This remarkable structure is a complex monitor and modifier of body movements. The cerebellum does not initiate movements, but only modifies motor control activated in other areas. Cerebellar operation is not only dependent on evolutionary development, but relies heavily on actual use and patterns of learned motor behavior acquired throughout life. It is for this reason that the movements of a gymnast are smooth and seemingly effortless. The most conspicuous part of all in the human brain is the cerebral cortex. Compared to most mammals, it is so large in man that it becomes a covering that surrounds and hides most of the other regions of the brain. Wrinkled and folded, the cerebral tissue is literally pressed into the limited space allocated to it. Although it has been possible to ascertain that certain cortical areas such as visual cortex, the sensory projection area, and the motor strip are associated with specific functions, the overall operation of this complex structure is still FIGURE 115.1 Basic structure of the neuron
Parietal Lobe Frontal Occipital Temporal Lobe Cerebellum Brainstem FIGURE 115.2 Major divisions of the cerebral cortex. not completely understood. However, for the sake of convenience, it has been arbitrarily divided( based primarily on anatomical considerations) into the following areas: frontal lobe, parietal lobe, temporal lobe, and occipital lobe( Fig. 115.2). Each of these segments of the cortex, which is the source of intellectual and imaginative capacities, includes millions of neurons and a host of interconnections. It is generally agreed that brain function is based on the organization of the activity of large numbers of neurons into coherent patterns. Since the primary mode of activity of these nerve cells is clectrical in nature, it is not surprising that a composite of this activity can be detected in the form of electrical signals Of extreme interest, then, are the actual oscillations, rhythms, and patterns seen in the cryptic flow of electrical energy oming from the brain itself, i. e, in the EEG Historical Perspective In 1875, Caton published the initial account of the recording of the spontaneous electrical activity of the brain from the cerebral cortex of an experimental animal. The amplitude of these electrical oscillations was so lot that is, on the order of microvolts, that Catons discovery is all the more amazing because it was made 50 years before suitable electronic amplifiers became available. In 1924, Hans Berger, of the University of Jena in Austria, arried out the first human EEG recordings using electrical metal strips pasted to the scalps of his subjects as electrodes and a sensitive galvanometer as the recording instrument. Berger was able to measure the irregula relatively small electrical potentials (i.e. 50 to 100 uV) coming from the brain. By studying the successive positions of the moving element of the galvanometer recorded on a continuous roll of paper, he was able to observe the resultant patterns in these brain waves as they varied with time. From 1924 to 1938, Berger laid the foundation for many of the present applications of electroencephalography. He was the first to use the word electroencephalogram in describing these brain potentials in man. Berger noted that these brain waves were although these brain waves were slow(i. e, exhibited a synchronized patter of high amplitude and low frequency, <3 Hz)in sleep and states of depressed function, they were faster(i.e, exhibited a desynchronized pattern of low amplitude and high frequency, 15-25 Hz)during waking behavior. He suggested, quite correctly, that the brain's activity changed in a consistent and recognizable fashion when the general status of the subject changed as from relaxation to alertness. Berger also concluded that these brain waves could be greatly affected by certain pathological conditions after noting the marked increase in the amplitude of these brain waves brought about by convulsive seizures. However, in spite of the insights provided by these studies, Berger's original paper published in 1929 did not excite much attention. In essence, the efforts of this most remarkable pioneer were largely ignored until similar investigations were carried out and verified by British investigators It was not until 1934 when Adrian and Matthews published their classic paper verifying Berger's findings that the reality of human brain waves was accepted and EEG studies were put on a firmly established basis One of their primary contributions was the identification of certain rhythms in the EEG, regular oscillations at approximately 10-12 Hz in the occipital lobes of the cerebral cortex. They found that this alpha rhythm in the EEG would disappear when the brain displayed any type of attention or alertness or focused on objects in ne visual field. The physiological basis for these results, the"arousing influence "of external stimuli on the e 2000 by CRC Press LLC
© 2000 by CRC Press LLC not completely understood.However, for the sake of convenience, it has been arbitrarily divided (based primarily on anatomical considerations) into the following areas: frontal lobe, parietal lobe, temporal lobe, and occipital lobe (Fig. 115.2). Each of these segments of the cortex, which is the source of intellectual and imaginative capacities, includes millions of neurons and a host of interconnections. It is generally agreed that brain function is based on the organization of the activity of large numbers of neurons into coherent patterns. Since the primary mode of activity of these nerve cells is electrical in nature, it is not surprising that a composite of this activity can be detected in the form of electrical signals. Of extreme interest, then, are the actual oscillations, rhythms, and patterns seen in the cryptic flow of electrical energy coming from the brain itself, i.e., in the EEG. Historical Perspective In 1875, Caton published the initial account of the recording of the spontaneous electrical activity of the brain from the cerebral cortex of an experimental animal. The amplitude of these electrical oscillations was so low, that is, on the order of microvolts, that Caton’s discovery is all the more amazing because it was made 50 years before suitable electronic amplifiers became available. In 1924, Hans Berger, of the University of Jena in Austria, carried out the first human EEG recordings using electrical metal strips pasted to the scalps of his subjects as electrodes and a sensitive galvanometer as the recording instrument. Berger was able to measure the irregular, relatively small electrical potentials (i.e., 50 to 100 mV) coming from the brain. By studying the successive positions of the moving element of the galvanometer recorded on a continuous roll of paper, he was able to observe the resultant patterns in these brain waves as they varied with time. From 1924 to 1938, Berger laid the foundation for many of the present applications of electroencephalography. He was the first to use the word electroencephalogram in describing these brain potentials in man. Berger noted that these brain waves were not entirely random, but instead displayed certain periodicities and regularities. For example, he observed that although these brain waves were slow (i.e., exhibited a synchronized patter of high amplitude and low frequency, <3 Hz) in sleep and states of depressed function, they were faster (i.e., exhibited a desynchronized pattern of low amplitude and high frequency, 15–25 Hz) during waking behavior. He suggested, quite correctly, that the brain’s activity changed in a consistent and recognizable fashion when the general status of the subject changed, as from relaxation to alertness. Berger also concluded that these brain waves could be greatly affected by certain pathological conditions after noting the marked increase in the amplitude of these brain waves brought about by convulsive seizures. However, in spite of the insights provided by these studies, Berger’s original paper published in 1929 did not excite much attention. In essence, the efforts of this most remarkable pioneer were largely ignored until similar investigations were carried out and verified by British investigators. It was not until 1934 when Adrian and Matthews published their classic paper verifying Berger’s findings that the reality of human brain waves was accepted and EEG studies were put on a firmly established basis. One of their primary contributions was the identification of certain rhythms in the EEG, regular oscillations at approximately 10–12 Hz in the occipital lobes of the cerebral cortex. They found that this alpha rhythm in the EEG would disappear when the brain displayed any type of attention or alertness or focused on objects in the visual field. The physiological basis for these results, the “arousing influence” of external stimuli on the FIGURE 115.2 Major divisions of the cerebral cortex
cortex,was not formulated until 1949 when Moruzzi and Magoun demonstrated the existence of widely spread pathways through the central reticular core of the brainstem capable of exerting a diffuse activating influence on the cerebral cortex. This reticular activating system has been called the brain s response selector because it alerts the cortex to focus on certain incoming information while ignoring other. It is for this reason that a sleeping mother will immediately be awakened by her crying baby or the smell of smoke, and yet ignore the traffic outside her window or the television still playing in the next room. An in-depth discussion of these early studies is beyond the scope of this presentation; however, for the interested reader an excellent historical review of this early era in brain research has been recorded in a fascinating text by Brazier [1968 EEG Recording TechI eques Scalp recordings of spontaneous neuronal activity in the brain, identified as the EeG, allow measurement of potential changes over time between a signal electrode and a reference electrode[ Kondraski, 1986]. Compared to other biopotentials, such as the electrocardiogram, the EEG is extremely difficult for an untrained observer to interpret. As might be expected, partially as a result of the spatial mapping of functions onto different regions of the brain, correspondingly different waveforms are visible, depending on electrode placement. Recognizing that some standardizati vas necessary for comparison of research as well as clinical EEG records, the International Federation in Electroencephalography and Clinical Neurophysiology adopted the 10-20 electrode placement system, [Jasper, 1958]. Additional electrodes to monitor extracerebral contaminants of the EEG such as eye movement, EKG, and muscle activity are essential. The acquisition of EEG for quantitative analysis should also require the ability to view the EEG during collection on a polygraph or high-resolution video display Since amplification, filtering, and digitization determine the frequency characteristics of the EEG and the source of potential artifacts, the acquisition parameters must be chosen with an understanding of their effects on signal acquisition and subsequent analysis. Amplification, for example, increases the amplitude range(volts) of the analog-to-digital (A/D)converter. The resolution of the A/D converter is determined by the smallest plitude of steps that can be sampled. This is calculated by dividing the voltage range of the A/D converter by 2 to the power of the number of bits of the A/D converter. For example, an A/D converter with a range of +5 V with 12-bit resolution can resolve samples as small as #2. 4 mV. Appropriate matching of amplification and A/D converter sensitivity permits resolution of the smallest signal while preventing clipping of the largest ignal amplitudes. The bandwidth of the filters and the rate of digitization determine the frequency components of interest that are passed, while other frequencies outside the band of interest that may represent potential artifacts, such as aliasing, are rejected. A filter's characteristics are determined by the rate of the amplitude decrease at the bandwidths upper and lower edges. Proper digital representation of the analog signal depends on the rate of data sampling, which is governed by the Nyquist theorem that states that data sampling should be at least twice the highest frequency of interest. In addition to the information available from spontaneous electrical activity of the EEG, the brains electrical response to sensory stimulation can contribute data as to the status of cortical and subcortical regions activate by sensory input. Due to the relatively small amplitude of a stimulus-evoked potential as compared to the spontaneous EEG potentials, the technique of signal averaging is used to enhance the stimulus-evoked respo Stimulus averaging takes advantage of the fact that the brains electrical response is time-locked to the onset of the stimulus and the nonevoked background potentials are randomly distributed in time. Consequently, the average of multiple stimulus responses will result in the enhancement of the time-locked activity, while the averaged random background activity will approach zero. The result is an evoked response that consists of a lumber of discrete and replicable peaks that occur, depending upon the stimulus and the recording parameters, at predicted latencies from the onset of stimulation. The spatial localization of maximum peak amplitudes has been associated with cortical generators in y sensory cortex. Instrumentation required for EEG recordings can be simple or elaborate[Kondraski, 1986].(Note: Although the discussion presented in this section is for a single-channel system it can be extended to simultaneous multichannel recordings simply by multiplying the hardware by the number of channels required In cases that do not require true simultaneous recordings, special electrode selector panels can minimize hardware require- ments)Any EEG system consists of electrodes, amplifiers(with appropriate filters)and a recording device c2000 by CRC Press LLC
© 2000 by CRC Press LLC cortex, was not formulated until 1949 when Moruzzi and Magoun demonstrated the existence of widely spread pathways through the central reticular core of the brainstem capable of exerting a diffuse activating influence on the cerebral cortex. This reticular activating system has been called the brain’s response selector because it alerts the cortex to focus on certain incoming information while ignoring other. It is for this reason that a sleeping mother will immediately be awakened by her crying baby or the smell of smoke, and yet ignore the traffic outside her window or the television still playing in the next room. An in-depth discussion of these early studies is beyond the scope of this presentation; however, for the interested reader an excellent historical review of this early era in brain research has been recorded in a fascinating text by Brazier [1968]. EEG Recording Techniques Scalp recordings of spontaneous neuronal activity in the brain, identified as the EEG, allow measurement of potential changes over time between a signal electrode and a reference electrode [Kondraski, 1986]. Compared to other biopotentials, such as the electrocardiogram, the EEG is extremely difficult for an untrained observer to interpret. As might be expected, partially as a result of the spatial mapping of functions onto different regions of the brain, correspondingly different waveforms are visible, depending on electrode placement. Recognizing that some standardization was necessary for comparison of research as well as clinical EEG records, the International Federation in Electroencephalography and Clinical Neurophysiology adopted the 10–20 electrode placement system, [Jasper, 1958]. Additional electrodes to monitor extracerebral contaminants of the EEG such as eye movement, EKG, and muscle activity are essential. The acquisition of EEG for quantitative analysis should also require the ability to view the EEG during collection on a polygraph or high-resolution video display. Since amplification, filtering, and digitization determine the frequency characteristics of the EEG and the source of potential artifacts, the acquisition parameters must be chosen with an understanding of their effects on signal acquisition and subsequent analysis. Amplification, for example, increases the amplitude range (volts) of the analog-to-digital (A/D) converter. The resolution of the A/D converter is determined by the smallest amplitude of steps that can be sampled. This is calculated by dividing the voltage range of the A/D converter by 2 to the power of the number of bits of the A/D converter. For example, an A/D converter with a range of ±5 V with 12-bit resolution can resolve samples as small as ±2.4 mV. Appropriate matching of amplification and A/D converter sensitivity permits resolution of the smallest signal while preventing clipping of the largest signal amplitudes. The bandwidth of the filters and the rate of digitization determine the frequency components of interest that are passed, while other frequencies outside the band of interest that may represent potential artifacts, such as aliasing, are rejected. A filter’s characteristics are determined by the rate of the amplitude decrease at the bandwidth’s upper and lower edges. Proper digital representation of the analog signal depends on the rate of data sampling, which is governed by the Nyquist theorem that states that data sampling should be at least twice the highest frequency of interest. In addition to the information available from spontaneous electrical activity of the EEG, the brain’s electrical response to sensory stimulation can contribute data as to the status of cortical and subcortical regions activated by sensory input. Due to the relatively small amplitude of a stimulus-evoked potential as compared to the spontaneous EEG potentials, the technique of signal averaging is used to enhance the stimulus-evoked response. Stimulus averaging takes advantage of the fact that the brain’s electrical response is time-locked to the onset of the stimulus and the nonevoked background potentials are randomly distributed in time. Consequently, the average of multiple stimulus responses will result in the enhancement of the time-locked activity, while the averaged random background activity will approach zero. The result is an evoked response that consists of a number of discrete and replicable peaks that occur, depending upon the stimulus and the recording parameters, at predicted latencies from the onset of stimulation. The spatial localization of maximum peak amplitudes has been associated with cortical generators in primary sensory cortex. Instrumentation required for EEG recordings can be simple or elaborate [Kondraski, 1986]. (Note: Although the discussion presented in this section is for a single-channel system it can be extended to simultaneous multichannel recordings simply by multiplying the hardware by the number of channels required. In cases that do not require true simultaneous recordings, special electrode selector panels can minimize hardware requirements.) Any EEG system consists of electrodes, amplifiers (with appropriate filters) and a recording device