Background: The sources of inter-subject variability in the efficacy of transcranial direct current stimulation (tDCS) remain unknown. One potential source of variations is the brain's electric field, which varies according to each individual's anatomical features.
Objective: We employed an approach that combines imaging and computational modeling to quantitatively study the extent and primary causes of inter-subject variation in tDCS electric fields.
Methods: Anatomically-accurate models of the head and brain of 24 males (age: 38.63 ± 11.24 years) were constructed from structural MRI. Finite-element method was used to computationally estimate the electric fields for tDCS of the motor cortex. Surface-based inter-subject registration of the electric field and functional MRI data was used for group level statistical analysis.
Results: We observed large differences in each individual's electric field patterns. However, group level analysis revealed that the average electric fields concentrated in the vicinity of the primary motor cortex. The variations in the electric fields in the hand motor area could be characterized by a normal distribution with a standard deviation of approximately 20% of the mean. The cerebrospinal fluid (CSF) thickness was the primary factor influencing an individual's electric field, thereby explaining 50% of the inter-individual variability, a thicker layer of CSF decreasing the electric field strength.
Conclusions: The variability in the electric fields is related to each individual's anatomical features and can only be controlled using detailed image processing. Age was found to have a slight negative effect on the electric field, which might have implications on tDCS studies on aging brains.
Keywords: Electric field; Finite-element method; Inter-subject variability; Motor cortex; tDCS.
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