Attention with or without working memory: mnemonic reselection of attended information.

Trends Cogn Sci

Department of Psychology and Behavioral Sciences, Zhejiang University, Zhejiang, China. Electronic address:

Published: December 2023

Attention has been regarded as the 'gatekeeper' controlling what information gets selected into working memory. However, a new perspective has emerged with the discovery of attribute amnesia, a phenomenon revealing that people are frequently unable to report information they have just attended to moments ago. This report failure is thought to stem from a lack of consolidating the attended information into working memory, indicating a dissociation between attention and working memory. Building on these findings, a new concept called memory reselection is proposed to describe a secondary round of selection among the attended information. These discoveries challenge the conventional view of how attention and working memory are related and shed new light onto modeling attention and memory as dissociable processes.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.tics.2023.08.010DOI Listing

Publication Analysis

Top Keywords

working memory
20
attention working
12
memory
7
attention
5
memory mnemonic
4
mnemonic reselection
4
attended
4
reselection attended
4
attended attention
4
attention regarded
4

Similar Publications

Purpose Of The Review: Clinical trials suggest that dietary anthocyanins may enhance cognitive function. This systematic literature review and meta-analysis aimed to identify the effect of anthocyanin on cognition and mood in adults.

Recent Findings: Using a random-effects model, Hedge's g scores were calculated to estimate the effect size.

View Article and Find Full Text PDF

Aging is a multi-organ disease, yet the traditional approach has been to study each organ in isolation. Such organ-specific studies have provided invaluable information regarding its pathomechanisms. However, an overall picture of the whole-body network (WBN) during aging is still incomplete.

View Article and Find Full Text PDF

Re-locative guided search optimized self-sparse attention enabled deep learning decoder for quantum error correction.

Sci Rep

January 2025

Department of Mathematics, School of Advanced Sciences, VIT-AP University, Besides AP Secretariate, Amaravati, Andhra Pradesh, 522237, India.

Heavy hexagonal coding is a type of quantum error-correcting coding in which the edges and vertices of a low-degree graph are assigned auxiliary and physical qubits. While many topological code decoders have been presented, it is still difficult to construct the optimal decoder due to leakage errors and qubit collision. Therefore, this research proposes a Re-locative Guided Search optimized self-sparse attention-enabled convolutional Neural Network with Long Short-Term Memory (RlGS2-DCNTM) for performing effective error correction in quantum codes.

View Article and Find Full Text PDF

In this paper, the usage of a predictive surrogate model for the estimate of flow variables in the transient phase of coolant injection from the nose cone by combining the Long Short-Term Memory (LSTM) and Proper Orthogonal Decomposition (POD) technique. The velocity, pressure, and mass fraction of the counterflow jet is evaluated via this hybrid technique and the source of discrepancy of a predictive surrogate model with Full order model is explained in this study. The POD modes for the efficient prediction of the different flow variables are defined.

View Article and Find Full Text PDF

Multiple sclerosis (MS) unfavorably affects working capacity. The Comprehensive International Classification of Functioning, Disability and Health Core Set for MS (cICF-MS), issued by the World Health Organization, has not yet been extended to evaluate working capacity level (WCL). To evaluate the relative importance of cICF-MS categories in relation to WCL.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!