scholarly journals Accessing long-term memory representations during visual change detection

2010 ◽  
Vol 39 (3) ◽  
pp. 433-446 ◽  
Author(s):  
Melissa R. Beck ◽  
Amanda E. van Lamsweerde
2020 ◽  
pp. 311-332
Author(s):  
Nicole Hakim ◽  
Edward Awh ◽  
Edward K. Vogel

Visual working memory allows us to maintain information in mind for use in ongoing cognition. Research on visual working memory often characterizes it within the context of its interaction with long-term memory (LTM). These embedded-processes models describe memory representations as existing in three potential states: inactivated LTM, including all representations stored in LTM; activated LTM, latent representations that can quickly be brought into an active state due to contextual priming or recency; and the focus of attention, an active but sharply limited state in which only a small number of items can be represented simultaneously. This chapter extends the embedded-processes framework of working memory. It proposes that working memory should be defined operationally based on neural activity. By defining working memory in this way, the important theoretical distinction between working memory and LTM is maintained, while still acknowledging that they operate together. It is additionally proposed that active working memory should be further subdivided into at least two subcomponent processes that index item-based storage and currently prioritized spatial locations. This fractionation of working memory is based on recent research that has found that the maintenance of information distinctly relies on item-based representations as well as prioritization of spatial locations. It is hoped that this updated framework of the definition of working memory within the embedded-processes model provides further traction for understanding how we maintain information in mind.


2018 ◽  
Vol 89 (4) ◽  
pp. 409-415
Author(s):  
Tomoe Masuoka ◽  
Megumi Nishiyama ◽  
Takafumi Terasawa

2016 ◽  
Vol 20 (4) ◽  
pp. 687-688 ◽  
Author(s):  
PHILLIP HAMRICK ◽  
MICHAEL T. ULLMAN

Cunnings (Cunnings) offers an interpretation of L2-L1 sentence processing differences in terms of memory principles. We applaud such cross-domain approaches, which seem likely to significantly elucidate the neurocognition of language. Cunnings attributes sentence processing differences between (adult) high proficiency L2 and L1 speakers to an increased susceptibility to similarity-based retrieval interference, rather than to qualitative L2-L1 processing differences (cf. Clahsen & Felser, 2006). On his account, both L1 and L2 sentence processing depend upon a ‘bipartite’ working memory, which involves maintaining items active by focusing attention on long-term memory representations (Cowan, 2001).


2012 ◽  
Vol 19 (2) ◽  
pp. 258-263 ◽  
Author(s):  
Stephen Darling ◽  
Richard J. Allen ◽  
Jelena Havelka ◽  
Aileen Campbell ◽  
Emma Rattray

2013 ◽  
Vol 21 (6) ◽  
pp. 682-685
Author(s):  
Kao-Wei Chua ◽  
Daniel N. Bub ◽  
Michael E. J. Masson ◽  
Isabel Gauthier

2021 ◽  
Author(s):  
Benjamin Goecke ◽  
Klaus Oberauer

In tests of working memory with verbal or spatial materials repeating the same memory sets across trials leads to improved memory performance. This well-established “Hebb repetition effect” could not be shown for visual materials. This absence of the Hebb effect can be explained in two ways: Either persons fail to acquire a long-term memory representation of the repeated memory sets, or they acquire such long-term memory representations, but fail to use them during the working memory task. In two experiments, (N1 = 18 and N2 = 30), we aimed to decide between these two possibilities by manipulating the long-term memory knowledge of some of the memory sets used in a change-detection task. Before the change-detection test, participants learned three arrays of colors to criterion. The subsequent change-detection test contained both previously learned and new color arrays. Change detection performance was better on previously learned compared to new arrays, showing that long-term memory is used in change detection.


2003 ◽  
Vol 26 (6) ◽  
pp. 756-756 ◽  
Author(s):  
Jennifer D. Ryan ◽  
Neal J. Cohen

Ruchkin et al. ascribe a pivotal role to long-term memory representations and binding within working memory. Here we focus on the interaction of working memory and long-term memory in supporting on-line representations of experience available to guide on-going processing, and we distinguish the role of frontal-lobe systems from what the hippocampus contributes to relational long-term memory binding.


2018 ◽  
Vol 30 (2) ◽  
pp. 223-237 ◽  
Author(s):  
Natalie Biderman ◽  
Roy Luria ◽  
Andrei R. Teodorescu ◽  
Ron Hajaj ◽  
Yonatan Goshen-Gottstein

How detailed are long-term-memory representations compared with working memory representations? Recent research has found an equal fidelity bound for both memory systems, suggesting a novel general constraint on memory. Here, we assessed the replicability of this discovery. Participants (total N = 72) were presented with colored real-life objects and were asked to recall the colors using a continuous color wheel. Deviations from study colors were modeled to generate two estimates of color memory: the variability of remembered colors—fidelity—and the probability of forgetting the color. Estimating model parameters using both maximum-likelihood estimation and Bayesian hierarchical modeling, we found that working memory had better fidelity than long-term memory (Experiments 1 and 2). Furthermore, within each system, fidelity worsened as a function of time-correlated mechanisms (Experiments 2 and 3). We conclude that fidelity is subject to decline across and within memory systems. Thus, the justification for a general fidelity constraint in memory does not seem to be valid.


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