Short term memory and the EEG

Gale, Anthony; Jones, Dylan M.; Smallbone, Adrian

doi:10.1038/248439a0

Cited by 8 publications

(4 citation statements)

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“…Are such physiological activities antecedent to behavioural or experiential events or merely parallel in time? I n view of our recent findings concerning EEG resting characteristics and subsequent performance in short-term recall (Gale et al, 1974), we are inclined to favour the causal view. However, any speculation concerning the relationship between EEG characteristics and experiential strategies employed in the present task, would oblige us to go well beyond the observed data.…”

Section: Discussionmentioning

confidence: 91%

“…Studies of stimulus complexity and the EEG are no exception; nevertheless, there is consistency among findings based upon visual analysis of desynchronixation (Berlyne & McDonnell, 1965), automated averaging of abundance (Gale et al, 1971) and evoked potentials (Nash & Fleming, 1970). The measure of mean dominant alpha frequency has proved useful in discriminating criterion groups based on individual differences in extraversion, imaging capacity and immediate recall (Gale et al, 1969(Gale et al, , 1974Gale, Morris et al, 1972). The final aim of this study is to measure the effects of number of elements and variety upon mean dominant alpha frequency.…”

mentioning

confidence: 99%

“…The measure of mean dominant alpha frequency has proved useful in discriminating criterion groups based on individual differences in extraversion, imaging capacity and immediate recall (Gale et al, 1969(Gale et al, , 1974Gale, Morris et al, 1972). The final aim of this study is to measure the effects of number of elements and variety upon mean dominant alpha frequency.…”

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confidence: 99%

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Stimulus Complexity, Eeg Abundance Gradients, and Detection Efficiency in a Visual Recognition Task

Gale

Spratt

Christie

et al. 1975

British J of Psychology

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Occipital EEG was monitored while subjects inspected 27 projected patterns. The number (N) and variety (V) of elements in the patterns were varied systematically. There were three levels of N (6, 12 or 24 elements) and three levels of V (circles, squares or hexagons occupying all, one half or one third of the element locations for all levels of N). Subjects were instructed that they would be required in a post-test to recognize the patterns, among patterns which had not appeared; they were also informed that the patterns had been constructed according to a set of simple rules, but the nature of these rules was not made fully explicit. The EEG was quantified by means of low-frequency analysis, yielding measures of abundance (theta, alpha and beta) and mean dominant frequency. For the recognition task, nine stimulus items were embedded among 45 items. Recognition efficiency was measured by means of the signal detection theory discrimination index (d'). The results were as follows: (i) Both N and V were inversely related to alpha abundance (P less than 0-01); (ii) the strongest relationship between stimulus parameters and the EEG held for N and EEG beta activity (13-5-19-5 Hz;P less than 0-001), where again the EEG and N were inversely related; (iii) there was a significant (P less than 0-05) direct relationship between N and theta activity; (iv) contrary to prediction, mean dominant alpha frequency decreased as N increased; (v) d' correlated significantly with a number of effects for N, i.e. subjects who exhibited greatest EEG discriminability of items during exposure of the patterns, subsequently obtained the higher detection scores in the recognition task. The work described therefore demonstrates that only only do stimulus parameters have systematic effects upon brain activity as measured by the EEG, but that such effects have functional value and reflect aspects of efficiency. The results are fully compatible with arousal theory constructs relating physiological reactivity and performance.

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Section: Discussionmentioning

confidence: 91%

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confidence: 99%

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confidence: 99%

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Stimulus Complexity, Eeg Abundance Gradients, and Detection Efficiency in a Visual Recognition Task

Gale

Spratt

Christie

et al. 1975

British J of Psychology

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“…Hinweise auf eine unterschiedliche Funktion der @Aktivität im passiven bzw. aktiven Wach-EEG (46,48), Beziehungen zu Persönlichkeitsvariablen (14, 17, 49) und dem jeweiligen hirnelektrischen Ausgangsniveau (1 0, 15,26,38) wurden von den genannten Autoren gegeben. Mulholland U. Mitarb.…”

Section: Untersuchungen üBer Struktur Und Verlauf Des Hirnelektrischeunclassified

Veränderungen der hirnelektrischen Organisation bei visuellen Such- und Diskriminationsprozessen unterschiedlichen Schwierigkeitsgrades

Zeller¹,

Bente²

1983

Klin Neurophysiol

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Effets de L’Alternance D’Une Tache Monotone et de Taches Complexes Sur la Vigilance et la Performance: Etude Exploratoire

Coblentz

Cabon

Mollard

1989

Vigilance and Performance in Automatized Systems/Vigilance Et Performance De L’Homme Dans Les Systèmes Automatisés

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Short term memory and the EEG

Cited by 8 publications

References 5 publications

Stimulus Complexity, Eeg Abundance Gradients, and Detection Efficiency in a Visual Recognition Task

Stimulus Complexity, Eeg Abundance Gradients, and Detection Efficiency in a Visual Recognition Task

Veränderungen der hirnelektrischen Organisation bei visuellen Such- und Diskriminationsprozessen unterschiedlichen Schwierigkeitsgrades

Effets de L’Alternance D’Une Tache Monotone et de Taches Complexes Sur la Vigilance et la Performance: Etude Exploratoire

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