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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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Updated: Dec 20, 2025

Developing Neuroimaging Phenotypes of the Default Mode Network in PTSD: Integrating the Resting State, Working Memory, and Structural Connectivity
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Brain Network Modularity During a Sustained Working-Memory Task.

Marta Moraschi1,2, Daniele Mascali1,2, Silvia Tommasin3

  • 1Centro Fermi-Museo Storico della Fisica e Centro di Studi e Ricerche Enrico Fermi, Rome, Italy.

Frontiers in Physiology
|May 28, 2020
PubMed
Summary
This summary is machine-generated.

Brain networks dynamically reorganize during working memory tasks. Graph analysis reveals task-specific shifts in network topology, highlighting both segregation and integration for efficient cognitive processing.

Keywords:
brain segregationconnectivity dynamicsfunctional connectivitymodularitytopologyworking memory

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Area of Science:

  • Neuroscience
  • Cognitive Neuroscience
  • Systems Neuroscience

Background:

  • Spontaneous brain activity, measured by blood oxygenation level-dependent (BOLD) signals, exhibits synchronized oscillations within distinct brain networks.
  • These networks are dynamically modulated by task performance, though the precise nature of these modulations remains under investigation.
  • Initial hypotheses suggested competitive interactions between the default mode network (DMN) and task-positive networks (TPNs), but recent findings indicate a coexistence of cooperative and competitive dynamics.

Purpose of the Study:

  • To investigate the functional relevance of topological reorganization in brain networks during a steady-state working memory (WM) task.
  • To assess how graph analysis can elucidate changes in brain network structure associated with cognitive demands.

Main Methods:

  • Utilized graph analysis techniques to examine the topological properties of brain networks.
  • Analyzed functional magnetic resonance imaging (fMRI) data, specifically the BOLD signal, during the execution of an auditory working memory task.

Main Results:

  • Auditory working memory task performance was linked to alterations in the topological configurations of key brain regions within frontoparietal, ventral attention, and dorsal attention networks.
  • Observed segregation of ventral attention network regions alongside an overall increase in brain-wide network integration.
  • Demonstrated that successful task completion necessitates enhanced integration across components of all involved brain networks.

Conclusions:

  • Working memory tasks induce significant topological reconfigurations in brain networks, involving both segregation and integration.
  • The interplay between network segregation and integration is crucial for efficient cognitive function during demanding tasks.
  • Graph analysis provides a valuable framework for understanding the dynamic structural changes in brain networks underlying cognitive processes.