scholarly journals Correlated Individual Differences in the Estimated Precision of Working Memory and Long-Term Memory: Commentary on the Study by Biderman, Luria, Teodorescu, Hajaj, and Goshen-Gottstein (2019)

2020 ◽  
Vol 31 (3) ◽  
pp. 345-348 ◽  
Author(s):  
Weizhen Xie ◽  
Hyung-Bum Park ◽  
Kareem A. Zaghloul ◽  
Weiwei Zhang
Author(s):  
Stoo Sepp ◽  
Steven J. Howard ◽  
Sharon Tindall-Ford ◽  
Shirley Agostinho ◽  
Fred Paas

In 1956, Miller first reported on a capacity limitation in the amount of information the human brain can process, which was thought to be seven plus or minus two items. The system of memory used to process information for immediate use was coined “working memory” by Miller, Galanter, and Pribram in 1960. In 1968, Atkinson and Shiffrin proposed their multistore model of memory, which theorized that the memory system was separated into short-term memory, long-term memory, and the sensory register, the latter of which temporarily holds and forwards information from sensory inputs to short term-memory for processing. Baddeley and Hitch built upon the concept of multiple stores, leading to the development of the multicomponent model of working memory in 1974, which described two stores devoted to the processing of visuospatial and auditory information, both coordinated by a central executive system. Later, Cowan’s theorizing focused on attentional factors in the effortful and effortless activation and maintenance of information in working memory. In 1988, Cowan published his model—the scope and control of attention model. In contrast, since the early 2000s Engle has investigated working memory capacity through the lens of his individual differences model, which does not seek to quantify capacity in the same way as Miller or Cowan. Instead, this model describes working memory capacity as the interplay between primary memory (working memory), the control of attention, and secondary memory (long-term memory). This affords the opportunity to focus on individual differences in working memory capacity and extend theorizing beyond storage to the manipulation of complex information. These models and advancements have made significant contributions to understandings of learning and cognition, informing educational research and practice in particular. Emerging areas of inquiry include investigating use of gestures to support working memory processing, leveraging working memory measures as a means to target instructional strategies for individual learners, and working memory training. Given that working memory is still debated, and not yet fully understood, researchers continue to investigate its nature, its role in learning and development, and its implications for educational curricula, pedagogy, and practice.


2021 ◽  
pp. 1-18
Author(s):  
Qi Lin ◽  
Kwangsun Yoo ◽  
Xilin Shen ◽  
Todd R. Constable ◽  
Marvin M. Chun

Abstract What is the neural basis of individual differences in the ability to hold information in long-term memory (LTM)? Here, we first characterize two whole-brain functional connectivity networks based on fMRI data acquired during an n-back task that robustly predict individual differences in two important forms of LTM, recognition and recollection. We then focus on the recognition memory model and contrast it with a working memory model. Although functional connectivity during the n-back task also predicts working memory performance and the two networks have some shared components, they are also largely distinct from each other: The recognition memory model performance remains robust when we control for working memory, and vice versa. Functional connectivity only within regions traditionally associated with LTM formation, such as the medial temporal lobe and those that show univariate subsequent memory effect, have little predictive power for both forms of LTM. Interestingly, the interactions between these regions and other brain regions play a more substantial role in predicting recollection memory than recognition memory. These results demonstrate that individual differences in LTM are dependent on the configuration of a whole-brain functional network including but not limited to regions associated with LTM during encoding and that such a network is separable from what supports the retention of information in working memory.


2003 ◽  
Vol 26 (6) ◽  
pp. 742-742
Author(s):  
Janice M. Keenan ◽  
Jukka Hyönä ◽  
Johanna K. Kaakinen

Ruchkin et al.'s view of working memory as activated long-term memory is more compatible with language processing than models such as Baddeley's, but it raises questions about individual differences in working memory and the validity of domain-general capacity estimates. Does it make sense to refer to someone as having low working memory capacity if capacity depends on particular knowledge structures tapped by the task?


2016 ◽  
Vol 39 ◽  
Author(s):  
Mary C. Potter

AbstractRapid serial visual presentation (RSVP) of words or pictured scenes provides evidence for a large-capacity conceptual short-term memory (CSTM) that momentarily provides rich associated material from long-term memory, permitting rapid chunking (Potter 1993; 2009; 2012). In perception of scenes as well as language comprehension, we make use of knowledge that briefly exceeds the supposed limits of working memory.


Author(s):  
Ian Neath ◽  
Jean Saint-Aubin ◽  
Tamra J. Bireta ◽  
Andrew J. Gabel ◽  
Chelsea G. Hudson ◽  
...  

2007 ◽  
Author(s):  
Nathan S. Rose ◽  
Joel Myerson ◽  
Henry L. Roediger ◽  
Sandra Hale

2020 ◽  
Author(s):  
Sam Verschooren ◽  
Yoav Kessler ◽  
Tobias Egner

An influential view of working memory (WM) holds that its’ contents are controlled by a selective gating mechanism that allows for relevant perceptual information to enter WM when opened, but shields WM contents from interference when closed. In support of this idea, prior studies using the reference-back paradigm have established behavioral costs for opening and closing the gate between perception and WM. WM also frequently requires input from long-term memory (LTM), but it is currently unknown whether a similar gate controls the selection of LTM representations into WM, and how WM gating of perceptual vs. LTM sources of information relate to each other. To address these key theoretical questions, we devised a novel version of the reference-back paradigm, where participants switched between gating perceptual and LTM information into WM. We observed clear evidence for gate opening and closing costs in both cases. Moreover, the pattern of costs associated with gating and source-switching indicated that perceptual and LTM information is gated into WM via a single gate, and rely on a shared source-selection mechanism. These findings extend current models of WM gating to encompass LTM information, and outline a new functional WM architecture.


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