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Working Memory

Working Memory

Working memory refers to a combination of components, including short-term memory and attention, that allow an individual to hold information temporarily as we perform cognitive tasks. It is an essential cognitive function that enables the execution of complex tasks such as problem-solving, comprehension, and reasoning. Unlike short-term memory, which simply involves the storage of information for a brief period, working memory involves the active manipulation and processing of this...

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Related Experiment Video

Updated: Dec 5, 2025

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

Published on: May 7, 2014

Age differences in predicting working memory performance from network-based functional connectivity.

Rachel N Pläschke¹, Kaustubh R Patil¹, Edna C Cieslik¹

¹Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.

Cortex; a Journal Devoted to the Study of the Nervous System and Behavior

|October 16, 2020

Summary

This summary is machine-generated.

Working memory capacity (WMC) becomes less predictable from brain network connectivity in older adults, suggesting age-related neural reorganization. Brain network integrity is linked to individual WMC performance in aging.

Keywords:

Aging Brain networks Machine learning Performance prediction Relevance vector machine Resting-state fMRI Working memory

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Working Memory Training for Older Participants: A Control Group Training Regimen and Initial Intellectual Functioning Assessment

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Published on: September 20, 2020

Area of Science:

Neuroscience
Cognitive Psychology
Aging Research

Background:

Working memory capacity (WMC) declines with normal aging.
The impact of aging on the relationship between WMC and functional brain network connectivity is not well understood.

Purpose of the Study:

To investigate how age influences the predictability of WMC from resting-state functional connectivity (RSFC) within brain networks.
To explore age-specific effects on the association between WMC and brain network integrity.

Main Methods:

Used fMRI-based RSFC data from young and old adults.
Applied relevance vector machine and cross-validation to predict WMC from connectivity in eight functional brain networks and the connectome.
Examined age-specific prediction performance and differences in predictive power based on WMC levels in older adults.

Main Results:

In young adults, WMC was generally unpredictable from RSFC in key cognitive networks.
In older adults, all examined brain networks significantly predicted WMC.
Both WM-related and unrelated networks showed differential predictability in older adults with low versus high WMC.

Conclusions:

Within-network functional coupling during rest is specifically related to individual WMC performance in older age, indicating neural reorganization.
Findings suggest decreased network segregation, impaired network integrity, or compensatory reorganization contribute to WMC-RSFC associations in aging.
Multivariate pattern regression offers insights into age-related brain reorganization by linking cognitive capacity to brain network integrity.