Identification of cognitive load-dependent activation patterns using working memory task-based fMRI at various levels of difficulty Article Swipe
Seyedeh Naghmeh Miri Ashtiani
,
Mohammad Reza Daliri
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1038/s41598-023-43837-w
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1038/s41598-023-43837-w
Working memory, which is regarded as the foundation of cognitive processes, is a system that stores, processes, and manipulates information in short intervals of time that are actually needed for daily functioning. This study aimed to assess the brain activity of healthy controls (HC) while performing the N-back task, which is one of the most popularly used tests for evaluating working memory along with functional magnetic resonance imaging (fMRI). In this regard, we collected fMRI data from right-handed individuals in a 3.0 T scanner during the Persian version of the visual variant N-back task performance with three levels of complexity varied throughout the experiment (1, 2, and 3-back conditions) to increase the cognitive demands. The statistical parametric mapping (SPM12) software was used to analyze fMRI data for the identification of cognitive load-dependent activation patterns based on contrast images obtained from different levels of task difficulty. Our findings showed that as cognitive complexity increased, the number of significant activation clusters and cluster extent increased in several areas distributed in the cerebellum, frontoparietal lobes, insula, SMA, and lenticular nucleus, the majority of which are recognized for their role in working memory. Furthermore, deactivation patterns during 1-, 2-, and 3-back vs. 0-back contrasts revealed significant clusters in brain regions that are mostly described as being part of the default mode network (DMN). Based on previous research, our results supported the recognized involvement of the mentioned cortical and subcortical areas in various types or levels of N-back tasks. This study found that altering activation patterns by increasing task difficulty could aid in evaluating the various stages of cognitive dysfunction in many brain diseases such as multiple sclerosis (MS) and Alzheimer's disease by comparing controls in future studies to apply early appropriate treatment strategies.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1038/s41598-023-43837-w
- https://www.nature.com/articles/s41598-023-43837-w.pdf
- OA Status
- gold
- Cited By
- 20
- References
- 32
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4387215636
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4387215636Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1038/s41598-023-43837-wDigital Object Identifier
- Title
-
Identification of cognitive load-dependent activation patterns using working memory task-based fMRI at various levels of difficultyWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-09-30Full publication date if available
- Authors
-
Seyedeh Naghmeh Miri Ashtiani, Mohammad Reza DaliriList of authors in order
- Landing page
-
https://doi.org/10.1038/s41598-023-43837-wPublisher landing page
- PDF URL
-
https://www.nature.com/articles/s41598-023-43837-w.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://www.nature.com/articles/s41598-023-43837-w.pdfDirect OA link when available
- Concepts
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Working memory, Cognition, n-back, Functional magnetic resonance imaging, Default mode network, Task (project management), Effects of sleep deprivation on cognitive performance, Elementary cognitive task, Cognitive psychology, Computer science, Psychology, Neuroscience, Management, EconomicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
20Total citation count in OpenAlex
- Citations by year (recent)
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2025: 13, 2024: 6, 2023: 1Per-year citation counts (last 5 years)
- References (count)
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32Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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