Phenotyping Superagers Using Resting-State fMRI
L L de Godoy1,2, A Studart-Neto3, D R de Paula4
1From the Departments of Radiology and Oncology (L.L.d.G., P.A., K.T.C., C.d.C.L.) laiz.godoy@pennmedicine.upenn.edu.
Superagers, older adults with exceptional memory, show distinct brain network activity. Higher magnetic field strength (7T) improves the detection of these functional connectivity patterns for predicting superagers.
Area of Science:
- Neuroscience
- Cognitive Aging Research
- Medical Imaging
Background:
- Superagers exhibit cognitive abilities comparable to younger individuals.
- Understanding the neural basis of exceptional cognitive aging is crucial.
Purpose of the Study:
- Identify differences in brain networks between superagers and controls.
- Explore the sensitivity of 3T and 7T MRI in detecting these differences.
Main Methods:
- Analyzed resting-state fMRI data from 31 elderly participants (14 superagers, 17 controls).
- Utilized a penalized regression model for classification and calculated odds ratios (ORs) for network nodes.
- Acquired data at both 3 Tesla (3T) and 7 Tesla (7T) magnetic resonance imaging (MRI) fields.
Main Results:
- Default mode, salience, and language networks significantly differentiated superagers.
- Key superager nodes included precuneus, posterior cingulate cortex, prefrontal cortex, and insula.
- A prediction model for superagers performed better with 7T than 3T fMRI data.
Conclusions:
- Functional connectivity in specific brain networks may serve as biomarkers for superagers.
- 7T MRI offers superior sensitivity for detecting functional connectivity patterns in superagers.
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