Chapter 32A Clinical Neurophysiology
Electroencephalography and Evoked Potentials
Electroencephalography
Physiological Principles of Electroencephalography
EEG rhythms appear to be part of a complex hierarchy of cortical oscillations that are fundamental to the brain’s information processing mechanisms, including input selection and transient “binding” of distributed neuronal assemblies (Buzsaki and Draguhn, 2004). In addition to reflecting the spontaneous intrinsic activities of cortical neurons, the EEG depends on important afferent inputs from subcortical structures including the thalamus and brainstem reticular formation. Thalamic afferents, for example, probably are responsible for entraining cortical neurons to produce the rhythmic oscillations that characterize normal patterns like alpha rhythm and sleep spindles. An EEG abnormality may occur directly from disruption of cortical neural networks or indirectly from modification of subcortical inputs onto cortical neurons.
A scalp-recorded EEG represents only a limited, low-resolution view of the electrical activity of the brain. This is due in part to the pronounced voltage attenuation and “blurring” that occurs from overlying cerebrospinal fluid (CSF) and tissue layers. Relatively large areas of cortex have to be involved in similar synchronized activity for a discharge to appear on the EEG. For example, recordings obtained from arrays of microelectrodes penetrating into the cerebral cortex reveal a complex architecture of seizure initiation and propagation invisible to recordings from the scalp or even the cortical surface, with seizure-like discharges occurring in areas as small as a single cortical column (Schevon et al., 2008). Furthermore, potentials involving surfaces of gyri are more readily recorded than potentials arising in the walls and depths of sulci. Activity generated over the lateral convexities of the hemispheres records more accurately than does activity coming from interhemispherical, mesial, or basal areas. In the case of epileptiform activity, estimates are that 20% to 70% of cortical spikes do not appear on the EEG, depending on the region of cortex involved. Additionally, although the scalp-recorded EEG consists almost entirely of signals slower than approximately 40 Hz, intracranial oscillations of several hundred hertz may be recorded and, of clinical importance, have been associated with both normal physiological processes and seizure initiation (Schevon et al., 2009).
Normal Electroencephalographic Activities
In most normal adults, the waking pattern of EEG activity consists mainly of sinusoidal oscillations occurring at 8 to 12 Hz, which are most prominent over the occipital area—the alpha rhythm (Fig. 32A.1, A). Eye opening, mental activity, and drowsiness attenuate (block) the alpha rhythm. Activity faster than 12 Hz beta activity normally is present over the frontal areas and may be especially prominent in patients receiving barbiturate or benzodiazepine drugs. Activity slower than 8 Hz is divisible into delta activity (1 to 3 Hz) and theta activity (4 to 7 Hz). Adults normally may show a small amount of theta activity over the temporal regions; the percentage of intermixed theta frequencies increases after the age of 60 years. Delta activity is not present normally in adults when they are awake but appears when they fall asleep (see Fig. 32A.1, B). The amount and amplitude of slow activity (theta and delta) correlate closely with the depth of sleep. Slow frequencies are abundant in the EEGs of newborns and young children, but these disappear progressively with maturation.
Common Types of Electroencephalographic Abnormalities
Recording Techniques
The EEG recording methods in common use are summarized in the following discussion. Details can be found in the American Clinical Neurophysiology Society’s Guidelines (2006).
A typical study is about 30 to 45 minutes in duration and includes two types of “activating procedures”: hyperventilation and photic stimulation. In some patients, these techniques provoke abnormal focal or generalized alterations in activity that are of diagnostic importance and would otherwise go undetected (Fig. 32A.2). Recording during sleep and after sleep deprivation, and placement of additional electrodes at other recording sites are useful in detecting specific kinds of epileptiform potentials. The use of other maneuvers depends on the clinical question posed. For example, epileptiform activity may occasionally activate only by movement or specific sensory stimuli. Vasovagal stimulation may be important in some types of syncope.
In the past, EEG recording instruments were simple analog devices with banks of amplifiers and pen-writers. In contrast, modern EEG machines make use of digital processing and storage, and the electroencephalographer interprets the EEG from a computer display rather than from paper. Technological advances have not fundamentally changed the principles of EEG interpretation, but they have facilitated EEG reading. Early paper-based EEG systems required that all recording parameters—display gain, filter settings, and the manner in which scalp-recorded signals were combined and displayed (montages)—be fixed by the technologist at the time of recording. In contrast, digital EEG systems permit the electroencephalographer to adjust these settings at the time of interpretation. A given EEG waveform or pattern can be examined using a number of different instrument settings, including sophisticated montages (e.g., Laplacian montages), that were unavailable using traditional analog recording systems. Topographic maps can be useful to depict spatial relationships, displaying features of the EEG in a graphical manner similar to that for functional MRI (fMRI) or PET. For example, topographical maps can illustrate EEG voltage distributions over the scalp at a particular point in time (Fig. 32A.3) as well as the distributions of particular frequencies contained within the EEG. Although this flexibility does not change the interpretive strategies used to read an EEG, it does allow the electroencephalographer to apply them more effectively.
In addition to facilitating the standard interpretation of EEGs, mathematical techniques can also be used to reveal features that may not be apparent to visual inspection of raw EEG waveforms. For example, averaging techniques, useful in improving the signal-to-noise ratios of spikes and sharp waves, can reveal field distributions and timing relationships that are not otherwise appreciable. Dipole source localization methods have been used to characterize both interictal spikes and ictal discharges in patients with epilepsy and may contribute to localization of the seizure focus (Ebersole, 2000). Such methods are based on a number of critical assumptions that, if applied without recognition of their limitations, can result in anatomically and physiologically erroneous conclusions (Emerson et al., 1995), so caution is warranted in their use.
For patients undergoing long-term EEG recordings as part of the diagnosis or management of epilepsy, a time-locked digitally recorded video image of the patient is recorded simultaneously with the EEG. EEG data are often processed by software that can automatically detect most seizure activity. Similar systems are finding increased use in intensive care units (ICU), where EEG monitoring has become increasingly important in the management of patients with nonconvulsive seizure activity, threatened or impending cerebral ischemia, severe head trauma, and metabolic coma (Drislane et al., 2008; Friedman et al., 2009). In this setting, compressed spectrograms, which graphically summarize the frequencies present in several hours of EEG on a single screen, can help the electroencephalographer to rapidly pinpoint important changes in the EEG and sometimes spot patterns or trends that otherwise might go unnoticed (Fig. 32A.4) (Scheuer, 2002). It is important to emphasize that fully automated robust systems analogous to those employed for cardiac monitoring are not now available for EEG, and while various automated methods can be very useful, their proper use in clinical practice should be as adjuncts to standard EEG recording and interpretation. False positives and negatives are commonplace; indeed, the very data reduction that makes such methods useful also makes them unsuitable for stand-alone application.
Clinical Uses of Electroencephalography
Epilepsy
Nonetheless, interpretation of interictal findings always requires caution. Correlating most epileptiform discharges with the frequency and likelihood of recurrence of epileptic seizures is poor (Selvitelli et al., 2010). Furthermore, a substantial number of patients with unquestionable epilepsy have consistently normal interictal EEGs. The most convincing proof that a patient’s episodic symptoms are epileptic is obtained by recording an electrographical seizure discharge during a typical behavioral attack. Although ictal EEG tracings greatly increase the sensitivity of the study in assessing the pathophysiology of specific behavioral episodes, the clinician must still be aware of limitations inherent in such recordings. (Videos showing actual EEG recordings obtained during seizures [Videos 32A.1 to 32A.3] are available at www.expertconsult.com.)
The type of epileptiform activity on EEG is helpful in classifying a patient’s seizure type correctly and sometimes in identifying a specific epileptic syndrome (see Chapter 67). Clinically, generalized tonic-clonic seizures may be generalized from the outset or may be secondary to spread from a focus. Lapses of awareness with automatisms may be a manifestation either of a generalized nonconvulsive form of epilepsy (absence seizures) or of focal epileptogenic dysfunction (temporal lobe epilepsy). The initial clinical features of a seizure may be uncertain because of postictal amnesia or nocturnal occurrence. In these and similar situations, the EEG can provide information crucial to the correct diagnosis and appropriate therapy.
In generalized seizures of nonfocal origin, the EEG typically shows bilaterally synchronous diffuse bursts of spikes and spike-and-wave discharges (Fig. 32A.5). All generalized EEG epileptiform patterns share certain common features, although the exact expression of the spike-wave activity varies depending on whether the patient has pure absence, tonic-clonic, myoclonic, or atonic-astatic seizures. The EEG also may distinguish between primary and secondary generalized epilepsy. In the former instance, no cerebral disease is demonstrable, whereas in the latter, evidence can be found for diffuse brain damage. Typically, primary (idiopathic) generalized epilepsy is associated with normal or near-normal EEG background rhythms, whereas secondary (symptomatic) epilepsy is associated with some degree of generalized slow-wave activity.
Consistently focal epileptiform activity is the signature of partial (focal) epilepsy (Fig. 32A.6). With the exception of the benign focal epilepsies of childhood, focal epileptiform activity results from neuronal dysfunction caused by demonstrable brain disease. The waveform of focal epileptiform discharges is largely independent of localization, but a reasonable correlation exists between spike location and the type of ictal behavior. Anterior temporal spikes usually are associated with complex partial seizures, rolandic spikes with simple motor or sensory seizures, and occipital spikes with primitive visual hallucinations or diminished visual function as an initial feature.
In addition to distinguishing epileptiform from nonepileptiform abnormalities, EEG analysis sometimes identifies specific electroclinical syndromes. Such syndromes include hypsarrhythmia associated with infantile spasms (West syndrome) (Fig. 32A.7); 3-Hz spike-and-wave activity associated with typical absence attacks (petit mal epilepsy) (Fig. 32A.8); generalized multiple spikes and waves (polyspike-wave pattern) associated with myoclonic epilepsy, including so-called juvenile myoclonic epilepsy of Janz (see Fig. 32A.5, B); generalized sharp and slow waves (slow spike-and-wave pattern) associated with Lennox-Gastaut syndrome (Fig. 32A.9); central-midtemporal spikes associated with benign rolandic epilepsy (Fig. 32A.10); and periodic lateralized epileptiform discharges (PLEDs) associated with acute destructive cerebral lesions such as hemorrhagic cerebral infarction, a rapidly growing malignancy, or herpes simplex encephalitis (Fig. 32A.11) (Pohlmann-Eden et al., 1996). PLEDs may also reappear in patients with chronic structural lesions in the context of new metabolic derangements.