Event-related desynchronization (ERD) during visual processing

doi:10.1016/0167-8760(89)90041-X

International Journal of Psychophysiology

Volume 16, Issues 2–3, May 1994, Pages 147-153

https://doi.org/10.1016/0167-8760(89)90041-X Get rights and content

Abstract

Event-related desynchronization (ERD) is the short-lasting attenuation or blocking of rhythms within the alpha (beta) band. ERD is found during but also before visual stimulation. Two different types of ERD can be differentiated: one short-lasting, localized to occipital areas and involving upper alpha components; the other longer lasting, more widespread, most prominent over parietal areas and maximal for lower alpha components. The former most likely reflects primary visual processing and feature extraction, the latter is more related to cognitive processing and mechanisms of attention.

References (24)

A. Aranibar et al.
On and off effects in the background EEG activity during one-second photic stimulation
Electroenceph. Clin. Neurophysiol.
(1978)
W. Klimesch et al.
Event-related desynchronization, ERD-mapping and hemispheric differences for words and numbers
Int. J. Psychophysiol.
(1990)
F.H. Lopes da Silva et al.
Relative contributions of intracortical and thalamo-cortical processes in the generation of alpha rhythms, revealed by partial coherence analysis
Electroenceph. Clin. Neurophysiol.
(1980)
F.H. Lopes da Silva
Neural mechanisms underlying brain waves: from neural membranes to networks
Electroenceph. Clin. Neurophysiol.
(1991)
G. Pfurtscheller et al.
Clinical relevance of long-latency SEPs and VEPs during coma and emergence from coma
Electroenceph. Clin. Neurophysiol.
(1985)
R. Cooper et al.
Comparison of subcortical, cortical and scalp activity using chronically indwelling electrodes in man
Electroenceph. Clin. Neurophysiol.
(1965)
G. Pfurtscheller
Event-related synchronization (ERS): an electrophysiological correlate of cortical areas at rest
Electroenceph. Clin. Neurophysiol.
(1992)
G. Pfurtscheller et al.
Amplitude of evoked potentials and degree of event-related desynchronization (ERD) during photic stimulation
Electroenceph. Clin. Neurophysiol.
(1979)
G. Chatrian et al.
The blocking of the rolandic wicket rhythm and some central changes related to movement
Electroenceph. Clin. Neurophysiol.
(1959)
G. Pfurtscheller et al.
Patterns of cortical activation during planning of voluntary movement
Electroenceph. Clin. Neurophysiol.
(1989)

C. Barber

Evoked Potentials

(1980)

H. Berger

Über das Elektroencephalogramm des Menschen II

J. Psychol. Neurol.

(1930)

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Event-related desynchronization (ERD) during visual processing

Abstract

Electroenceph. Clin. Neurophysiol.

Int. J. Psychophysiol.

Electroenceph. Clin. Neurophysiol.

Electroenceph. Clin. Neurophysiol.

Electroenceph. Clin. Neurophysiol.

Electroenceph. Clin. Neurophysiol.

Electroenceph. Clin. Neurophysiol.

Electroenceph. Clin. Neurophysiol.

Electroenceph. Clin. Neurophysiol.

Electroenceph. Clin. Neurophysiol.

Evoked Potentials

Über das Elektroencephalogramm des Menschen II

J. Psychol. Neurol.