Application-specific memory performance of a heterogeneous reconfigurable architecture

2010 ◽  
Author(s):  
Sean Whitty ◽  
Henning Sahlbach ◽  
Brady Hurlburt ◽  
Rolf Ernst ◽  
Wolfram Putzke-Roming
Keyword(s):  
Memory Performance ◽  
Reconfigurable Architecture ◽  
Specific Memory ◽  
Application Specific

The Manipulation and Measurement of Task-specific Memory Self-Efficacy in Younger and Older Adults

1997 ◽  
Vol 21 (2) ◽  
pp. 209-227 ◽  
Author(s):  
Maria Gardiner ◽  
Mary A. Luszcz ◽  
Janet Bryan
Keyword(s):  
Older Adults ◽  
Free Recall ◽  
Self Efficacy ◽  
Task Difficulty ◽  
Memory Performance ◽  
Recall Trial ◽  
Domain Specific ◽  
Specific Memory ◽  
Younger Age ◽  
Before And After

Task-specific memory self-efficacy (TSMSE) was experimentally manipulated through provision of information about task difficulty, to determine its effect on free recall for 56 older (age 63-86) and 56 younger (age 16-25) adults. The implications of using prediction-based measures of TSMSE were addressed. After completing one recall trial of a list of 20 words, half the participants were told a second list comprised more difficult words; the others were told the second list would be similar to the first they had received. Free recall and TSMSE were measured before and after this manipulation. The manipulation reduced TSMSE for participants expecting a harder list of words, but not differently for younger compared with older adults. Younger and older adults’ recall declined at the second recall trial, but there was no difference between those expecting a harder list and those expecting a similar list. Recall was predicted by domain-specific memory self-efficacy as well as a traditional measure of TSMSE. The study demonstrated the malleability of memory self-efficacy, but called into question assertions about its salience as a mediator of older adults’ poorer memory performance.

scholarly journals Brain Connectivity Alterations During Sleep by Closed-Loop Transcranial Neurostimulation Predict Meta-memory Sensitivity

2021 ◽  
pp. 1-41
Author(s):  
Ryan J. Hubbard ◽  
Iman Zadeh ◽  
Aaron P. Jones ◽  
Bradley Robert ◽  
Natalie B. Bryant ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Brain Stimulation ◽  
Closed Loop ◽  
Brain Connectivity ◽  
Memory Performance ◽  
Machine Learning Techniques ◽  
Beta Band ◽  
Graph Theoretic ◽  
Specific Memory ◽  
Up States

Abstract Meta-memory involves the ability to correctly judge the accuracy of our memories. The retrieval of memories can be improved using transcranial electrical brain stimulation (tES) during sleep, but evidence for improvements to meta-memory sensitivity is limited. Applying tES can enhance sleepdependent memory consolidation, which along with meta-memory requires the coordination of activity across distributed neural systems, suggesting that examining functional connectivity is important for understanding these processes. Nevertheless, little research has examined how functional connectivity modulations relate to overnight changes in meta-memory sensitivity. Here, we developed a closed-loop short-duration tES method, time-locked to up-states of ongoing slow-wave oscillations, to cue specific memory replays in humans. We measured electroencephalographic (EEG) coherence changes following stimulation pulses, and characterized network alterations with graph theoretic metrics. Using machine learning techniques, we show that pulsed tES elicited network changes in multiple frequency bands, including increased connectivity in the Theta band and increased efficiency in the Spindle band. Additionally, stimulation-induced changes in Beta band path length were predictive of overnight changes in meta-memory sensitivity. These findings add new insights into the growing literature investigating increases in memory performance through brain stimulation during sleep, and highlight the importance of examining functional connectivity to explain its effects.

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