In Experimental neurology
While the treatment of Attention Deficit Hyperactivity Disorder (ADHD) is dominated by pharmacological agents, transcranial electrical stimulation (tES) is gaining attention as an alternative method for treatment. Most current meta-analyses have suggested that tES can improve cognitive functions that are otherwise impaired in ADHD, such as inhibition and working memory, as well as alleviated clinical symptoms. Here we review some of the promising findings in the field of tES. At the same time, we highlight two factors, which hinder the effective application of tES in treating ADHD: 1) the heterogeneity of tES protocols used in different studies; 2) patient profiles influencing responses to tES. We highlight potential solutions for overcoming such limitations, including the use of active machine learning, and provide simulated data to demonstrate how these solutions could also improve the understanding, diagnosis, and treatment of ADHD.
Lipka Renée, Ahlers Eike, Reed Thomas L, Karstens Malin I, Nguyen Vu, Bajbouj Malek, Cohen Kadosh Roi
ADHD, Bayesian optimization, Heterogeneity, NIBS, Personalization, tES