Biomarkers

Area of Science:

• Neuroscience
• Biomedical Engineering
• Gerontology

Background:

• Transcranial direct current stimulation (tDCS) shows promise for mitigating age-related cognitive decline.
• Individual tDCS responses are influenced by anatomical variations, as indicated by finite element method (FEM) modeling.
• Current head segmentation tools are not optimized for older adult anatomy, leading to inaccurate tDCS current distribution predictions.

Purpose of the Study:

• To create the largest dataset of manually segmented T1-weighted images from cognitively healthy older adults.
• To investigate the impact of corrected older adult anatomy on tDCS current distribution.
• To identify key anatomical predictors of tDCS current density in the aging brain.

Main Methods:

• Segmentation of heads into 11 tissue types.
• Modification of the ROAST tool to accommodate 11 tissues for tDCS modeling (2mA, F4 anode, F3 cathode).
• Calculation of median current densities (J) in the Superior Frontal Gyrus (SFG), Inferior Frontal Gyrus (IFG), and Middle Frontal Gyrus (MFG) using multiple linear regression.

Main Results:

• Regression models explained significant variance in current density (43.2-49.4%) across ROIs.
• Fat and cortical bone volumes were significant negative predictors of current density.
• Higher brain-to-intracranial volume positively correlated with current density.

Conclusions:

• Anatomical variability, especially fat and cortical bone, significantly influences tDCS current distribution in older adults.
• Fat's insulating properties and cortical bone's resistive properties reduce current density.
• Brain atrophy, indicated by lower brain-to-intracranial volume, leads to current shunting within CSF, reducing current density in the brain.