EEG
Definition
EEG refers to electroencephalography, a technique that records oscillatory electrical activity generated by the summed output of pyramidal neurons arranged perpendicular to the scalp, and is used to measure brain rhythms across a range of frequencies. In working memory research, EEG captures modulations in theta, alpha, and beta oscillations, though detecting genuine beta activity presents methodological difficulties because beta-range signals can appear artifactually as harmonics of lower-frequency rhythms with non-sinusoidal properties. To address this, 96-electrode scalp EEG was recorded from 27 healthy adults performing a spatial working-memory task, with signals preprocessed through independent component analysis, artifact subspace reconstruction, and Morlet wavelet decomposition. An algorithm was then applied to isolate transient beta bursts that did not co-occur in time and space with more prominent lower-frequency oscillatory events, confirming that beta burst amplitude and duration decreased with memory load while peak frequency and rate increased.
Sources: Rodriguez-Larios & Haegens (2023)
Related Terms
- neural oscillations (1 shared article)
- working memory (1 shared article)
Applications
EEG and Working Memory
Working memory maintenance and manipulation produce systematic changes in oscillatory activity as measured by EEG, particularly in the theta, alpha, and beta frequency ranges. Using a 96-electrode system and a spatial working-memory task with varying cognitive load, researchers found that genuine beta bursts, isolated from lower-frequency artifact, showed reduced amplitude and duration alongside increased rate and peak frequency under higher memory demand. These results confirm that EEG-measured beta dynamics reflect functionally meaningful neural events rather than spectral byproducts of alpha or theta non-sinusoidalities.
Sources: Rodriguez-Larios & Haegens (2023)
EEG and Beta Oscillations
Beta oscillations detected in EEG signals are transient, lower in amplitude than lower-frequency rhythms, and susceptible to contamination from the harmonics of non-sinusoidal alpha and theta activity. A dedicated burst-detection algorithm, applied to single-trial EEG data transformed via Morlet wavelets, selected only those beta events forming the most prominent spectral peak after subtraction of aperiodic activity and not coinciding spatiotemporally with lower-frequency bursts. Burst parameters including amplitude, duration, rate, and peak frequency were each modulated by memory load and manipulation, establishing their independence from artifactual sources.
Sources: Rodriguez-Larios & Haegens (2023)
