Cognitive markers for efficacy of neurofeedback for attention-deficit hyperactivity disorder - personalized medicine using computational psychiatry in a randomized clinical trial.

Background: Exploring whether cognitive components (identified by baseline cognitive testing and computational modeling) moderate clinical outcome of neurofeedback (NF) for attention-deficit hyperactivity disorder (ADHD).

Method: 142 children (aged 7-10) with ADHD were randomly assigned to either NF ( n = 84) or control treatment ( n = 58) in a double-blind clinical trial (NCT02251743). The NF group received live, self-controlled downtraining of electroencephalographic theta/beta ratio power. The control group received identical-appearing reinforcement from prerecorded electroencephalograms from other children. 133 (78 NF, 55 control) children had cognitive processing measured at baseline with the Integrated Visual and Auditory Continuous Performance Test (IVA2-CPT) and were included in this analysis. A diffusion decision model applied to the IVA2-CPT data quantified two latent cognitive components deficient in ADHD: drift rate and drift bias , indexing efficiency and context sensitivity of cognitive processes involving information integration. We explored whether these cognitive components moderated the improvement in parent- and teacher-rated inattention symptoms from baseline to treatment end (primary clinical outcome).

Results: Baseline cognitive components reflecting information integration ( drift rate, drift bias ) moderated the improvement in inattention due to NF vs. control treatment ( p = 0.006 ). Specifically, those with either the most or least severe deficits in these components showed more improvement in parent- and teacher-rated inattention when assigned to NF (Cohen's d = 0.59) than when assigned to control (Cohen's d = -0.21).

Conclusions: Pre-treatment cognitive testing with computational modeling identified children who benefitted more from neurofeedback than control treatment for ADHD.