An electroencephalogram, commonly known as an EEG, is a non-invasive test that measures the electrical activity of the brain. It involves placing small, flat metal discs called electrodes on the scalp, which detect electrical signals generated by brain cells. These signals are then amplified and displayed as wavy lines, or brain wave patterns, on a computer screen or printed paper. EEG helps identify irregularities that indicate various brain disorders, including those resulting from a stroke.
Understanding Electroencephalography
Electroencephalography records the synchronized electrical impulses produced by neurons within the brain. Brain waves are categorized by frequency (Hertz, Hz) and amplitude. Different types of brain waves correspond to various states of consciousness and mental activity.
Alpha waves (8-13 Hz) are observed when a person is in a relaxed, awake state, while beta waves (greater than 13 Hz) are prominent during intense mental activity. Slower waves, such as theta (3.5-7.5 Hz) and delta (3 Hz or less), are associated with sleep in adults; their presence during wakefulness can signal brain dysfunction. The EEG procedure is painless and safe, with electrodes only recording activity without producing any sensation.
How Stroke Affects EEG Readings
A stroke, which disrupts normal blood flow to the brain, significantly alters its electrical activity, resulting in detectable changes on an EEG. A common abnormality is focal slowing, where brain waves in the affected area become slower, shifting into theta and delta frequencies. This slowing can be continuous or intermittent, with continuous slowing indicating a more severe underlying structural issue like an infarct or hemorrhage.
Another common finding is asymmetry in brain wave activity between the two hemispheres, with the affected side showing reduced or disorganized patterns compared to the healthy side. In severe cases, there is a suppression of brain activity, indicating significant brain dysfunction. Specific patterns like Periodic Lateralized Epileptiform Discharges (PLEDs) also appear, seen in acute unilateral lesions such as cerebral infarctions.
The Role of EEG in Acute Stroke Assessment
In the immediate aftermath of a suspected stroke, EEG is not the primary diagnostic tool; neuroimaging techniques like CT or MRI are preferred for rapid and precise diagnosis. However, EEG serves as a valuable supplementary tool for identifying complications that occur after a stroke. It is effective in detecting epileptic activity, such as seizures, which occur after a stroke and mimic stroke symptoms or worsen outcomes.
EEG’s utility extends to assessing the general severity and extent of brain dysfunction, especially when neuroimaging is delayed or unavailable. Its portability allows for continuous bedside monitoring in critical care settings, providing real-time information on brain activity. Despite these advantages, EEG has limitations: its changes are not exclusive to stroke and are caused by other brain conditions, and it does not pinpoint the exact location or type of stroke with the precision of imaging scans. Additionally, abnormalities on an EEG may not appear immediately after an acute stroke.
EEG in Monitoring and Recovery After Stroke
Beyond the acute phase, EEG plays a role in the ongoing monitoring of stroke patients and in assessing their potential for recovery. It is used to detect the development of post-stroke epilepsy, especially in patients who experience altered consciousness or other signs suggestive of seizures. Studies indicate that epileptiform activity and regional slowing on an early EEG (within 7 days of stroke) are associated with an increased risk of developing post-stroke epilepsy.
EEG also offers insights into brain plasticity and the recovery process, although this area is explored in research settings. The persistence or resolution of abnormal brain wave patterns over time can indicate improvement or worsening of neurological outcomes. For instance, certain EEG measures, such as the Delta-to-Alpha Ratio (DAR) and brain symmetry, have shown promise in predicting motor recovery and overall functional outcomes months after a stroke.