scholarly journals Working memory reconstructions using alpha-band activity are disrupted by sensory input.

2017 ◽  
Vol 17 (10) ◽  
pp. 334
Author(s):  
Tom Bullock ◽  
Mary MacLean ◽  
Barry Giesbrecht
2020 ◽  
Vol 20 (11) ◽  
pp. 1248
Author(s):  
Gisella Diaz ◽  
Edward Vogel ◽  
Edward Awh

2020 ◽  
pp. 1-27 ◽  
Author(s):  
Sisi Wang ◽  
Emma E. Megla ◽  
Geoffrey F. Woodman

Human alpha-band activity (8–12 Hz) has been proposed to index a variety of mechanisms during visual processing. Here, we distinguished between an account in which alpha suppression indexes selective attention versus an account in which it indexes subsequent working memory storage. We manipulated two aspects of the visual stimuli that perceptual attention is believed to mitigate before working memory storage: the potential interference from distractors and the size of the focus of attention. We found that the magnitude of alpha-band suppression tracked both of these aspects of the visual arrays. Thus, alpha-band activity after stimulus onset is clearly related to how the visual system deploys perceptual attention and appears to be distinct from mechanisms that store target representations in working memory.


2017 ◽  
Vol 17 (10) ◽  
pp. 332
Author(s):  
David Sutterer ◽  
Joshua Foster ◽  
Kirsten Adam ◽  
Edward Vogel ◽  
Edward Awh

2017 ◽  
Vol 27 (20) ◽  
pp. 3216-3223.e6 ◽  
Author(s):  
Joshua J. Foster ◽  
Emma M. Bsales ◽  
Russell J. Jaffe ◽  
Edward Awh

2018 ◽  
Vol 18 (10) ◽  
pp. 108
Author(s):  
Laura Rodriguez ◽  
Asal Nouri ◽  
Edward Ester

2017 ◽  
Vol 17 (10) ◽  
pp. 337
Author(s):  
Eren Gunseli ◽  
Joshua Foster ◽  
David Sutterer ◽  
Edward Vogel ◽  
Edward Awh

2020 ◽  
Author(s):  
Nikita Novikov ◽  
Boris Gutkin

Working memory (WM) is the brain's ability to retain information that is not directly available from the sensory systems. WM retention is accompanied by sustained firing rate modulation and changes of the large-scale oscillatory profile. Among other changes, beta-band activity elevates in task-related regions, presumably stabilizing WM retention. Alpha-band activity, in turn, is stronger in task-irrelevant regions, serving to protect WM trace from distracting information. Although a large body of experimental evidence links neural oscillations to WM functions, theoretical understanding of their interrelations is still incomplete. In this study, we used a computational approach to explore a potential role of beta and alpha oscillations in control of WM stability. First, we examined a single bistable module that served as a discrete object representation and was resonant in the beta-band in the active state. We demonstrated that beta-band input produced differentially stronger excitatory effect on the module in the active state compared to the background state, while this difference decreased with the input frequency. We then considered a system of two competing modules, selective for a stimulus and for a distractor, respectively. We simulated a task, in which a stimulus was loaded into the first module, then an identical oscillatory input to both modules was turned on, after which a distractor was presented to the second module. We showed that beta-band input prevented loading of high-amplitude distractors and erasure of the stimulus from WM. On the contrary, alpha-band input promoted loading of low-amplitude distractors and the stimulus erasure. In summary, we demonstrated that stability of WM trace could be controlled by global oscillatory input in a frequency-dependent manner via controlling the level of competition between stimulus-encoding and distractor-encoding circuits. Such control is possible due to difference in the resonant and non-linear properties between the background and the active states.


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