Journal article
Functional Characterization of Atrophy Patterns Related to Cognitive Impairment
Frontiers in neurology, Vol.11, pp.18-18
2020
DOI: 10.3389/fneur.2020.00018
PMCID: PMC6993791
PMID: 32038473
Abstract
Mild cognitive impairment (MCI) is a heterogenous syndrome considered as a risk factor for developing dementia. Previous work examining morphological brain changes in MCI has identified a temporo-parietal atrophy pattern that suggests a common neuroanatomical denominator of cognitive impairment. Using functional connectivity analyses of structurally affected regions in MCI, we aimed to investigate and characterize functional networks formed by these regions that appear to be particularly vulnerable to disease-related disruptions.
Areas of convergent atrophy in MCI were derived from a quantitative meta-analysis and encompassed left and right medial temporal (i.e., hippocampus, amygdala), as well as parietal regions (precuneus), which were defined as seed regions for connectivity analyses. Both task-based meta-analytical connectivity modeling (MACM) based on the BrainMap database and task-free resting-state functional MRI in a large cohort of older adults from the 1000BRAINS study were applied. We additionally assessed behavioral characteristics associated with the seed regions using BrainMap meta-data and investigated correlations of resting-state connectivity with age.
The left temporal seed showed stronger associations with a fronto-temporal network, whereas the right temporal atrophy cluster was more linked to cortico-striatal regions. In accordance with this, behavioral analysis indicated an emphasis of the left temporal seed on language generation, and the right temporal seed was associated with the domains of emotion and attention. Task-independent co-activation was more pronounced in the parietal seed, which demonstrated stronger connectivity with a frontoparietal network and associations with introspection and social cognition. Correlation analysis revealed both decreasing and increasing functional connectivity with higher age that may add to pathological processes but also indicates compensatory mechanisms of functional reorganization with increasing age.
Our findings provide an important pathophysiological link between morphological changes and the clinical relevance of major structural damage in MCI. Multimodal analysis of functional networks related to areas of MCI-typical atrophy may help to explain cognitive decline and behavioral alterations not tractable by a mere anatomical interpretation and therefore contribute to prognostic evaluations.
Details
- Title: Subtitle
- Functional Characterization of Atrophy Patterns Related to Cognitive Impairment
- Creators
- Gereon J Schnellbächer - Department of Neurology, RWTH Aachen University, Aachen, GermanyFelix Hoffstaedter - Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University, Düsseldorf, GermanySimon B Eickhoff - Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University, Düsseldorf, GermanySvenja Caspers - JARA-BRAIN, Jülich-Aachen Research Alliance, Jülich, GermanyThomas Nickl-Jockschat - Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa City, IA, United StatesPeter T Fox - Research Service, South Texas Veterans Administration Medical Center, San Antonio, TX, United StatesAngela R Laird - Department of Physics, Florida International University, Miami, FL, United StatesJörg B Schulz - JARA-BRAIN, Jülich-Aachen Research Alliance, Jülich, GermanyKathrin Reetz - JARA-BRAIN, Jülich-Aachen Research Alliance, Jülich, GermanyImis Dogan - JARA-BRAIN, Jülich-Aachen Research Alliance, Jülich, Germany
- Resource Type
- Journal article
- Publication Details
- Frontiers in neurology, Vol.11, pp.18-18
- DOI
- 10.3389/fneur.2020.00018
- PMID
- 32038473
- PMCID
- PMC6993791
- NLM abbreviation
- Front Neurol
- ISSN
- 1664-2295
- eISSN
- 1664-2295
- Publisher
- Switzerland
- Language
- English
- Date published
- 2020
- Academic Unit
- Psychiatry; Iowa Neuroscience Institute; Neuroscience and Pharmacology
- Record Identifier
- 9984070406702771
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