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Functional Brain Connectivity Using fMRI in Aging and Alzheimer’s Disease

Overview of attention for article published in Neuropsychology Review, February 2014
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Title
Functional Brain Connectivity Using fMRI in Aging and Alzheimer’s Disease
Published in
Neuropsychology Review, February 2014
DOI 10.1007/s11065-014-9249-6
Pubmed ID
Authors

Emily L. Dennis, Paul M. Thompson

Abstract

Normal aging and Alzheimer's disease (AD) cause profound changes in the brain's structure and function. AD in particular is accompanied by widespread cortical neuronal loss, and loss of connections between brain systems. This degeneration of neural pathways disrupts the functional coherence of brain activation. Recent innovations in brain imaging have detected characteristic disruptions in functional networks. Here we review studies examining changes in functional connectivity, measured through fMRI (functional magnetic resonance imaging), starting with healthy aging and then Alzheimer's disease. We cover studies that employ the three primary methods to analyze functional connectivity--seed-based, ICA (independent components analysis), and graph theory. At the end we include a brief discussion of other methodologies, such as EEG (electroencephalography), MEG (magnetoencephalography), and PET (positron emission tomography). We also describe multi-modal studies that combine rsfMRI (resting state fMRI) with PET imaging, as well as studies examining the effects of medications. Overall, connectivity and network integrity appear to decrease in healthy aging, but this decrease is accelerated in AD, with specific systems hit hardest, such as the default mode network (DMN). Functional connectivity is a relatively new topic of research, but it holds great promise in revealing how brain network dynamics change across the lifespan and in disease.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 677 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Finland 2 <1%
Germany 2 <1%
Netherlands 1 <1%
Chile 1 <1%
Korea, Republic of 1 <1%
Ireland 1 <1%
Colombia 1 <1%
Austria 1 <1%
Australia 1 <1%
Other 6 <1%
Unknown 660 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 148 22%
Researcher 103 15%
Student > Master 90 13%
Student > Bachelor 53 8%
Student > Doctoral Student 36 5%
Other 103 15%
Unknown 144 21%
Readers by discipline Count As %
Neuroscience 141 21%
Psychology 105 16%
Medicine and Dentistry 76 11%
Engineering 40 6%
Agricultural and Biological Sciences 36 5%
Other 73 11%
Unknown 206 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 February 2016.
All research outputs
#17,726,563
of 22,763,032 outputs
Outputs from Neuropsychology Review
#375
of 454 outputs
Outputs of similar age
#157,286
of 225,081 outputs
Outputs of similar age from Neuropsychology Review
#10
of 10 outputs
Altmetric has tracked 22,763,032 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 454 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.1. This one is in the 12th percentile – i.e., 12% of its peers scored the same or lower than it.
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