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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: Apr 20, 2026

Disruption of Frontal Lobe Neural Synchrony During Cognitive Control by Alcohol Intoxication

Disruption of Frontal Lobe Neural Synchrony During Cognitive Control by Alcohol Intoxication

Published on: February 6, 2019

Dynamic shifts in brain network activation during supracapacity working memory task performance.

Jared X Van Snellenberg¹, Mark Slifstein, Christina Read

¹Department of Psychiatry, Columbia University College of Physicians and Surgeons, New York, New York; Division of Translational Imaging, New York State Psychiatric Institute, New York, New York.

Human Brain Mapping

|November 26, 2014

Summary

This summary is machine-generated.

Brain networks show dynamic responses when working memory (WM) capacity is exceeded. Specific activation patterns predict performance, indicating adaptive neural strategies under cognitive load.

Keywords:

cognition magnetic resonance imaging memory, short-term prefrontal cortex task performance and analysis

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Published on: March 21, 2019

Area of Science:

Neuroscience
Cognitive Psychology
Neuroimaging

Background:

Understanding how brain networks support working memory (WM) and cognitive control is crucial.
Limited knowledge exists on neural network responses when cognitive capabilities are overtaxed.

Purpose of the Study:

Investigate brain network responses to exceeding WM capacity.
Examine how neural activity supports task performance under high cognitive load.

Main Methods:

Used functional magnetic resonance imaging (fMRI) with fine-grained memory load manipulation within a single trial.
Analyzed correct trials to assess neural responses to exceeding WM capacity.

Main Results:

Observed a nonmonotonic (inverted-U) WM load response in the classic WM network, peaking later in individuals with higher WM capacity.
Identified increased activity in medial prefrontal cortex, posterior cingulate/precuneus, and lateral temporal/parietal regions at highest loads.
Found that inverted-U patterns correlated with poorer performance, while early/late activation patterns predicted better performance. Increased fusiform gyrus and occipital lobe activation at high loads also predicted better performance.

Conclusions:

Demonstrated dynamic, behaviorally relevant changes in brain network activation with increasing WM load.
Results challenge current models of WM and cognitive control, highlighting adaptive neural strategies.
Neural network responses to exceeding WM capacity are complex and predictive of cognitive performance.