Dementia is a collective term describing a decline in mental ability severe enough to interfere with daily life, resulting from various diseases and conditions that cause brain cells to fail. Evaluating a patient presenting with cognitive impairment requires tools capable of assessing the brain’s function, not just its physical structure. The electroencephalogram, or EEG, is a non-invasive procedure that records the electrical activity generated by the brain’s neurons. This method provides functional data that complements clinical assessments and other neuroimaging techniques, offering valuable insights for clinicians evaluating patients with suspected cognitive impairment.
Understanding the Electroencephalogram
The electroencephalogram captures synchronized electrical potentials generated by neurons in the cerebral cortex. The procedure involves placing electrodes onto the scalp, which detect subtle voltage fluctuations. These fluctuations are recorded as wavy lines representing different brain rhythms, categorized by their frequency in Hertz (Hz).
These brain waves correspond to different states of consciousness. Alpha waves (8 to 12 Hz) are dominant when a person is awake but relaxed. Faster beta waves (13 to 30 Hz) are associated with active thinking and concentration.
Slower patterns include theta waves (4 to 8 Hz), common during sleep or deep relaxation, and delta waves (below 4 Hz), characteristic of deep sleep. In a clinical setting, abnormalities in the frequency, amplitude, or location of these waves signal underlying neurological dysfunction.
How EEG Data Supports Dementia Diagnosis
EEG provides a functional assessment of brain network activity, which is crucial because dementia involves a gradual disruption of neuronal communication. This disruption is often detected as a generalized slowing of brain rhythms, offering a perspective distinct from the structural changes seen in Magnetic Resonance Imaging (MRI).
EEG is important for differential diagnosis, helping to distinguish progressive neurodegeneration from reversible causes of cognitive change. Acute conditions like delirium, metabolic encephalopathy, or toxic states often produce a severe, diffuse slowing of the background rhythm. This pronounced slowing is typically much greater than the subtle, gradual changes seen in early Alzheimer’s disease.
The EEG also helps rule out non-dementia conditions that mimic cognitive impairment, such as non-convulsive status epilepticus. In these cases, the EEG reveals epileptiform discharges requiring distinct medical treatment. Specific wave patterns, like triphasic waves, suggest a metabolic or toxic encephalopathy rather than a neurodegenerative dementia.
Characteristic EEG Patterns Linked to Cognitive Decline
Analysis of EEG tracings focuses on changes in the posterior dominant rhythm (PDR) and abnormal wave forms. In Alzheimer’s disease (AD), the primary change is a progressive, generalized slowing of the PDR. The dominant frequency shifts from the normal alpha range (8–12 Hz) down into the theta range (4–8 Hz).
This slowing is quantified by an increase in the relative power of slower theta and delta waves, alongside a reduction in faster alpha and beta activity. In early AD, the dominant frequency may be around 8.3 Hz, correlating with the severity of cognitive decline as the disease progresses.
Dementia with Lewy Bodies (DLB) exhibits a more pronounced and variable pattern of slowing than AD. The mean dominant frequency in DLB often falls significantly lower, typically between 6.7 to 7.5 Hz. A supportive finding for DLB is the presence of Frontal Intermittent Rhythmic Delta Activity (FIRDA).
FIRDA appears as rhythmic bursts of delta waves over the frontal regions. Other dementias show distinct patterns; vascular dementia may present with focal or asymmetric slowing, suggesting localized brain injury. Conversely, a normal or near-normal EEG tracing in early stages can suggest Frontotemporal Dementia (FTD), differentiating it from the typically abnormal EEGs of AD and DLB.
Integrating EEG into the Diagnostic Process
EEG functions as an adjunct tool within the comprehensive diagnostic workup for dementia, providing crucial information about electrical function. Structural imaging techniques like MRI and CT scans visualize the brain’s anatomy, revealing atrophy or structural damage like stroke lesions. Functional imaging, such as Positron Emission Tomography (PET), measures metabolic activity, often detecting reduced glucose uptake.
The EEG offers high temporal resolution, providing a real-time measure of neuronal communication that these other modalities cannot capture. Combining EEG functional data with structural or metabolic data improves diagnostic accuracy compared to using any single modality alone.
The advantages of EEG include its non-invasive nature, lower cost compared to other neuroimaging, and wider availability in diverse clinical settings. This makes it a practical option for initial screening or for distinguishing neurodegenerative processes from functional disorders like psychiatric conditions or epilepsy.
Integrating structural integrity, metabolic function, and electrical activity better equips clinicians to arrive at an accurate diagnosis.