Neuroanatomical predictors of transcranial direct current stimulation (tDCS)-induced modifications in neurocognitive task performance in typically developing individuals

Abstract

Transcranial direct current stimulation (tDCS) is a non-invasive neuromodulation technique gaining more attention in neurodevelopmental disorders (NDDs). Due to the phenotypic heterogeneity of NDDs, tDCS is unlikely to be equally effective in all individuals. The present study aimed to establish neuroanatomical markers in typical developing (TD) individuals that may be used for the prediction of individual responses to tDCS. 57 TD male and female children received 2mA anodal and sham tDCS, targeting the left dorsolateral prefrontal cortex (DLPFC_left), right inferior frontal gyrus, and bilateral temporo-parietal junction. Response to tDCS was assessed based on task performance differences between anodal and sham tDCS in different neurocognitive tasks (N-back, Flanker, Mooney Faces Detection, Attentional Emotional Recognition task). Measures of cortical thickness (CT) and surface area (SA) were derived from 3-Tesla structural MRI scans. Associations between neuroanatomy and task performance were assessed using a general linear model. Machine learning (ML) algorithms were employed to predict responses to tDCS. Overall, vertex-wise estimates of SA were more closely linked to differences in task performance than measures of CT. Across ML algorithms, highest accuracies were observed for the prediction of N-back task performance differences following stimulation of the DLPFC_left, where 65% of behavioural variance was explained by variability in SA. Lower accuracies were observed for all other tasks and stimulated regions. This suggests that it may be possible to predict individual responses to tDCS for some behavioural measures and target regions. In the future, these models might be extended to predict treatment outcome in individuals with NDDs.Significance statement Transcranial direct current stimulation (tDCS) is a non-invasive neuromodulation technique that has recently gained more attention in neurodevelopmental disorders (NDDs), such as autism and attention-deficit/hyperactivity disorder. However, due to the phenotypic heterogeneity of NDDs, tDCS is unlikely to be equally effective in all individuals. The present study aimed to establish neuroanatomical biomarkers in typical developing individuals that may be used for the prediction of individual responses to tDCS. Our findings suggest that it may be possible to accurately predict individual responses to tDCS for some behavioural measures using measures of neuroanatomy. In the future, our models might be extended to predict treatment outcome in individuals with clinical diagnoses, and may allow for more individualized, person-centred interventions.