Neuroplasticity Technology for Attention-deficit/Hyperactivity Disorder (ADHD)

This study evaluates the impact of computerized inhibitory control training on attention-deficit hyperactivity disorder (ADHD) symptoms and ADHD-linked neural signatures in children with ADHD. Children were randomly assigned to adaptive computerized training (n=20) or non-adaptive computerized training control (n=20) with identical stimuli and goals.

Both medication and cognitive behavioral therapy are effective treatments for many children, however, adherence to both medication and therapy regimes is low. Thus, identifying effective adjunct treatments for ADHD is imperative. Previous studies exploring computerized training programs as supplementary treatments have targeted working memory or attention. However, many lines of research point to inhibitory control (IC) playing a central role in ADHD pathophysiology. IC abnormalities in children with ADHD have been evidenced both in behavioral performance on computerized tasks as well as in the structure and function of neural systems known to support IC function. Furthermore, these IC abnormalities have been linked to symptom severity. Given findings that the most successful training interventions for children with ADHD are those that have implemented IC training along wtih working memory or attention and previous work demonstrating that IC is a central deficit for children with ADHD, it is surprising that no studies have sought to investigate programs that specifically target IC. Investigators hypothesize that training IC alone will decrease symptoms of ADHD, and information confirming this hypothesis would contribute to making training regimens for children with ADHD efficient by identifying the primary cognitive skill that requires intervention. To test this, they administer a randomized control trial of either adaptive of non-adaptive stop signal reaction time (SSRT) tasks to children with ADHD and assess effects of training on ADHD symptoms and neural activity.

Children were randomly assigned to adaptive treatment (n=20) or non-adaptive control (n=20) with identical tasks, stimuli, and goals. Children were instructed to train for 5 days a week (25m/day) for 4-weeks. All participants had between 10-20 training sessions at study completion.

Participants played a set of three modified stop-signal reaction time tasks designed by NeuroScouting, LLC at home for approximately 5 days a week (25 min/day) for 4-weeks. This condition involved real-time adaptive gameplay that increased in difficulty as performance increased.

Participants played a set of three modified stop-signal reaction time tasks designed by NeuroScouting, LLC at home for approximately 5 days a week (25 min/day) for 4-weeks. This condition had no change in difficulty (non-adaptive gameplay).

Playing computerized stop-signal reaction time tasks that had been modified to increase in difficulty as performance increased.

Playing computerized stop-signal reactions time tasks that do not change in difficulty level (non-adaptive).

Parent-report of inattention symptoms using the Swanson, Nolan, and Pelham Questionnaire (SNAP-IV). The SNAP-IV is based on a 0 to 3 rating scale (Not at All = 0, Just A Little = 1, Quite a Bit = 2, and Very Much = 3). Subscale inattention items are calculated by summing the score for the 9 inattention items and dividing by 9.

Parent-report of hyperactivity symptoms used the Swanson, Nolan, and Pelham Questionnaire (SNAP-IV). The SNAP-IV is based on a 0 to 3 rating scale (Not at All = 0, Just A Little = 1, Quite a Bit = 2, and Very Much = 3). Subscale hyperactivity items are calculated by summing the score for the 9 hyperactivity items and dividing by 9.

EEG data was collected for both eyes open and eyes closed resting state for 7 trials of 30 seconds each. For each participant, relative power in the theta band (5-8 Hz) was calculated for two regions of interest analogous to bilateral parietal electrodes in the international 10-10 system using frequency band analyses.

Teachers or other non-parental caretakers (e.g. babysitter) completed the teacher report versions of the Conners. The Conner's is based on a 0 to 3 rating scale with 0 being Not true at all, 1 = Just a little true, 2 = pretty much true, and 3 = Very much true. The teacher-report inattention score was calculated by norming and averaging ratings of the inattention domains in the Conner's Teacher Report.

Teachers or other non-parental caretakers (e.g. babysitter) completed the teacher report versions of the Conners. The Conner's is based on a 0 to 3 rating scale with 0 being Not true at all, 1 = Just a little true, 2 = pretty much true, and 3 = Very much true. The teacher-report hyperactivity score was calculated by norming and averaging ratings of the hyperactivity domains in the Conner's Teacher Report.

The N200 is a negative going component maximal over frontal scalp cites, which peaks roughly between 200 and 350 ms post stimulus onset. Each subject's ERP response on both errors of commission and correct inhibition trials of a stop-signal reaction time task were analyzed for changes in amplitude and latency.

The Developmental NEuroPSYchological Assessment (NEPSY-II) is a nationally normed neuropsychological test for children ages 3-16 years. The Inhibition scale of the NEPSY includes an 'arrows' subtest (completed at baseline) and a 'shapes' subtest (completed at 4 weeks). Performance on these tests were measured as the number of total errors on each subtest task (Naming, Inhibition, and Switching), such that individuals who make more errors show poorer self-monitoring skills.

Math ability subtests of the Woodcok Johnson (WJ-III) were administered: Match Calculation (at baseline) and Match Fluency (at 4 weeks). Normed age and grade estimates of math ability were used. Outcomes are reported using age-based Z-scores, with a mean of 0 and standard deviation of 1.

Participants completed a working memory filtering task. This was a delayed match to sample task in which participants saw a visual array of several circles on a 4x4 grid, maintained this array in working memory during a delay, and decide if the color of a single probe matched what they saw during encoding. Changes in accuracy from same load trials in which children held 1 shape versus 2 shapes in working memory were used to assess filtering of task-irrelevant information. Changes in accuracy with load from the 1-shape condition are used to assess working memory capacity.

This was a two-part modified Go/NoGo task with a training phase and testing phase. Participants completed the monetary incentive delay (MID) task during training. Shapes that had been previously rewarded or previously neutral were used as the no-go stimuli in the Go/NoGo task. Errors of commission to the previously rewarded stimuli controlling for errors of commission to the previously neutral stimuli served as the measure of inhibitory control over rewarding stimuli.

The Behavior Rating Inventory of Executive Function (BRIEF) is an assessment of executive function consisting of 86-item questionnaire completed by parents. The Global Score on the BRIEF incorporates all clinical scales of the BRIEF and is reported as a T-score with a mean of 50 and standard deviation of 10.

Inclusion Criteria: Diagnosis of inattentive or combined subtype ADHD by a licensed clinician and consistent acess to Wi-Fi at home. Exclusion Criteria: Any known genetic abnormalities, a diagnosis of autism spectrum disorder, or current use of medication for psychiatric disorders other than ADHD (e.g. depression, anxiety).

Because this is a preliminary study designed primarily to identify feasibility and presence of an effect of this kind of cognitive training on neural and behavioral outcomes in ADHD, we did not develop a data sharing plan. If researchers are interested in working with this data they are encouraged to contact the PI directly - Margaret Sheridan sheridan.margaret@unc.edu

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Meyer KN, Santillana R, Miller B, Clapp W, Way M, Bridgman-Goines K, Sheridan MA. Computer-based inhibitory control training in children with Attention-Deficit/Hyperactivity Disorder (ADHD): Evidence for behavioral and neural impact. PLoS One. 2020 Nov 30;15(11):e0241352. doi: 10.1371/journal.pone.0241352. eCollection 2020.