Neuroanatomical Predictors of Transcranial Direct Current Stimulation (tDCS)-Induced Modifications in Neurocognitive...

Area of Science:

• Neuroscience
• Neuromodulation
• Neuroimaging

Background:

• Transcranial direct current stimulation (tDCS) is a noninvasive neuromodulation technique used for neurodevelopmental disorders (NDDs).
• Individual responses to tDCS vary due to phenotypic heterogeneity in NDDs.
• Predictive neuroanatomical markers are needed to personalize tDCS efficacy.

Purpose of the Study:

• To identify neuroanatomical markers in typically developing (TD) children for predicting individual responses to tDCS.
• To investigate the relationship between cortical thickness (CT), surface area (SA), and neurocognitive task performance after tDCS.
• To utilize machine learning (ML) for predicting tDCS response based on neuroanatomy.

Main Methods:

• Fifty-seven TD children received anodal and sham tDCS targeting the left dorsolateral prefrontal cortex (DLPFCleft), right inferior frontal gyrus, and bilateral temporoparietal junction.
• Neurocognitive tasks (N-back, flanker, Mooney faces, attentional emotional recognition) assessed tDCS response.
• Structural MRI derived CT and SA; general linear models (GLM) and ML algorithms analyzed associations and predictive accuracy.

Main Results:

• Vertex-wise SA measures were more strongly associated with task performance differences than CT.
• Machine learning models achieved the highest accuracy (65% behavioral variance explained) in predicting N-back task performance differences after DLPFCleft stimulation, driven by SA variability.
• Lower prediction accuracies were observed for other tasks and stimulated regions.

Conclusions:

• Individual responses to tDCS can be predicted for specific behavioral measures and target regions using neuroanatomical markers, particularly SA.
• These predictive models hold potential for future application in tailoring tDCS treatment outcomes for individuals with NDDs.