Examining working memory task acquisition in a disrupted neural network
Abstract
There is mounting literature that examines brain activation during tasks of working memory in individuals with neurological disorders such as traumatic brain injury. These studies represent a foundation for understanding the functional brain changes that occur after moderate and severe traumatic brain injury, but the focus on topographical brain-'activation' differences ignores potential alterations in how nodes communicate within a distributed neural network. The present study makes use of the most recently developed connectivity modelling (extended-unified structural equation model) to examine performance during a well-established working-memory task (the n-back) in individuals sustaining moderate and severe traumatic brain injury. The goal is to use the findings observed in topographical activation analysis as the basis for second-level effective connectivity modelling. Findings reveal important between-group differences in within-hemisphere connectivity during task acquisition, with the control sample demonstrating rapid within-left hemisphere connectivity increases and the traumatic brain injury sample demonstrating consistently elevated within-right hemisphere connectivity. These findings also point to important maturational effects from 'early' to 'late' during task performance, including diminished right prefrontal cortex involvement and an anterior to posterior shift in connectivity with increased task exposure. We anticipate that this approach to functional imaging data analysis represents an important future direction for understanding how neural plasticity is expressed in brain disorders.
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Brain connectivity maps have been used to identify systematic differences between subgroups and conditions in both clinical and non-clinical populations.
“Brain connectivity maps have been used to identify systematic differences between subgroups and conditions in both clinical and non-clinical populations (e.g., [5], [13]).”
From Organizing Heterogeneous Samples Using Community Detection of GIMME-Derived Resting State Functional Networks (2014) · cites this paper as [5]
The degree of similarity to expect and variability in connection weights has been informed by previous research that used individual-level connectivity maps to examine a priori defined subgroups.
“The degree of similarity to expect as well as the variability in connection weights has been informed by previous research that used individual-level connectivity maps to examine a priori defined subgroups (e.g., [5])”
From Organizing Heterogeneous Samples Using Community Detection of GIMME-Derived Resting State Functional Networks (2014) · cites this paper as [5]
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- Authors
- Hillary, F. G., Medaglia, J. D., Gates, K., Molenaar, P. C., Slocomb, J., Peechatka, A., & Good, D. C.
- Affiliations
- Pennsylvania State University (US)
- Penn State Milton S. Hershey Medical Center (US)
- Venue
- Brain
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-05
- Volume
- 134
- Issue
- 5
- Pages
- 1555-1570
- ISSN
- 0006-8950 (ISSN-L)
- 1460-2156
- OpenAlex
- W2107337758
- Cited by
- 74
- References
- 46
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 2 · 2023: 1 · 2022: 2 · 2021: 6 · 2020: 1 · 2019: 5 · 2018: 5 · 2017: 8 · 2016: 6 · 2015: 6 · 2014: 11 · 2013: 8 · 2012: 9
- FWCI
- 4.86
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Brain (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Epidemiology › Traumatic Brain Injury Research
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- working memory, traumatic brain injury, n-back task, effective connectivity, right prefrontal cortex, neuroplasticity, task acquisition
- MeSH terms
- Adult, Brain Injuries, Brain Mapping, Cerebral Cortex, Female, Humans, Functional Laterality, Magnetic Resonance Imaging, Male, Memory Disorders, Memory, Short-Term, Middle Aged, Models, Neurological, Nerve Net, Neuropsychological Tests, Reaction Time, Time Factors
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