Akira Yasumura

Neurobehavioral and hemodynamic evaluation of Stroop and reverse Stroop interference in children with attention-deficit/hyperactivity disorder

Failure of executive function (EF) is a core symptom of attention-deficit/hyperactivity disorder (ADHD). However, various results have been reported and sufficient evidence is lacking. In the present study, we evaluated the characteristics of children with ADHD using the Stroop task (ST) and reverse Stroop task (RST) that reflects the inhibition function of EF. We compared children with ADHD, typically developing children (TDC), and children with autism spectrum disorder (ASD), which is more difficult to discriminate from ADHD. A total of 10 children diagnosed with ADHD, 15 TDC, and 11 children diagnosed with ASD, all matched by age, sex, language ability, and intelligence quotient, participated in this study. While each subject performed computer-based ST and RST with a touch panel, changes in oxygenated hemoglobin (oxy-Hb) were measured in the prefrontal cortex (PFC) by near-infrared spectroscopy (NIRS) to correlate test performance with neural activity. Behavioral performance significantly differed among 3 groups during RST but not during ST. The ADHD group showed greater color interference than the TDC group. In addition, there was a negative correlation between right lateral PFC (LPFC) activity and the severity of attention deficit. Children with ADHD exhibit several problems associated with inhibition of color, and this symptom is affected by low activities of the right LPFC. In addition, it is suggested that low hemodynamic activities in this area are correlated with ADHD.

Increased Prefrontal Oxygenation Related to Distractor-Resistant Working Memory in Children with Attention-Deficit/ Hyperactivity Disorder (ADHD)

This study aimed at investigating the effect of distraction on working memory and its underlying neural mechanisms in children with attention-deficit/hyperactivity disorder (ADHD). To this end, we studied hemodynamic activity in the prefrontal cortex using near-infrared spectroscopy while 16 children with ADHD and 10 typically developing (TD) children performed a working memory task. This task had two conditions: one involved a distraction during the memory delay interval, whereas the other had no systematic distraction. The ADHD patients showed significantly poorer behavioral performance compared with the TD group, particularly under the distraction. The ADHD group exhibited significantly higher level of prefrontal activation than did TD children. The activity level was positively correlated with the severity of ADHD symptoms. These results suggest that the impairment in the inhibition of distraction is responsible for the working memory deficits observed in ADHD children. Inefficient processing in the prefrontal cortex appears to underlie such deficits.

Relationship between Neural Activity and Executive Function: An NIRS Study.

Objective. This study examined the relationship between neural activity and executive function (EF) by near-infrared spectroscopy (NIRS). In addition, an oral reading span test (RST) was used to explore this association. Methods. Fifteen adults participated in the study. We used the RST and simple reading as the two tasks. Results. The RST score and cortical hemodynamic response in the left inferior frontal gyrus were significantly correlated. Conclusion. Based on the oral RST performance assessment and NIRS examination, the present findings suggest a relationship between EF and cortical activation.

Changes in negative and positive EEG shifts during slow cortical potential training in children with attention-deficit/hyperactivity disorder: a preliminary investigation.

We examined the effects of self-regulation of slow cortical potentials (SCP) in nine children with attention-deficit/hyperactivity disorder (ADHD) by focusing on the changes in electroencephalographic (EEG) shifts during SCP sessions. In SCP training, individuals learn to increase and decrease their cortical excitabilities (enhancement of negative and positive cortical shifts). To examine the efficiency of SCP training, we conducted an attention task and measured contingent negative variation, which relates to the attention maintenance ability. Moreover, to assess training effects at the behavioral level, the Japanese ADHD rating scale (SNAP-J) was completed by the parents. In SCP training, we analyzed changes in EEG shifts during 16 training sessions by calculating the peak amplitudes of positive and negative shifts. The results of EEG data showed that peak amplitudes increased in sessions 11 and 12 for negative shifts and in sessions 9 and 13 for positive shifts. Moreover, we found an enhancement of contingent negative variation amplitude in the attention task before and after training, suggesting that the ability of these children to maintain attention could be modified by SCP training. However, significant behavioral improvements were not observed on the Japanese ADHD rating scale. It has been proposed that the number of additional training sessions may affect both physiological and behavioral improvements. Our present results, however, suggest the possibility that even low numbers of training sessions, such as 16, can bring about physiological improvement, whereas greater numbers of training sessions may be needed to have an influence on behavioral changes.

Predictive factors of success in neurofeedback training for children with ADHD

ABSTRACT Introduction: Neurofeedback (NF) training aims the enhancement of self-regulation over brain activities. While it is largely recognized as an effective treatment for attention deficit hyperactivity disorder (ADHD), the existence of non-learners has also been reported. The present study explored pre-training assessment indices that could predict learners prior to NF training. Methods: Twenty-two children with ADHD participated in slow cortical potential (SCP) NF training and completed pre- and post-training assessments. Participants were classified into learners or non-learners based on their progress in the SCP regulation, and pre-training indices that differentiate the two groups were examined by decision tree analysis. Results and Discussion: The learner rate in NF training was 45.5%. Learners were predicted by pre-training cognitive and neurophysiological measures regarding Stroop tasks, which suggested relatively intact executive function as their characteristics. Given that NF training is not universally effective for children with ADHD, further studies are necessary to establish application criteria.

Executive Function in Children with Attention Deficit/ Hyperactivity Disorder

In recent years, deficit in executive function has been noted as a core symptom of attention deficit hyperactivity disorder (ADHD). Previously, with the aim of quantitatively assessing the characteristics of children with ADHD from the view‐ point of inhibition among executive functions, we have considered behavioral and frontal brain functions with regard to inhibition vis a vis color word interference. In this study we also undertook additional collections of data at a number of facilities and investigated usefulness as a differential diagnosis aid. A total of 38 ADHD children and 46 typical developing children, matched in terms of age, gender, dominant arm and non-verbal intelligence, were the subject of analysis in this study. Utilising a Reverse Stroop Task (RST), we measured prefrontal area activity during task performance with near-infrared spectroscopy (OEG-16). Results were: 1) Behavioral results: in the RST, the ADHD children recorded a higher rate of interfer‐ ence than the TD children. 2) Brain activity: as regards brain activity during the RST, right lateral prefrontal activity was significantly lower in the ADHD children than in the TD children. These results suggest that RST results and changes in brain activity during task performance allow quantitative assessment of the clinical symptom of ADHD.

Applied Machine Learning Method to Predict Children With ADHD Using Prefrontal Cortex Activity: A Multicenter Study in Japan:

Objective: To establish valid, objective biomarkers for ADHD using machine learning. Method: Machine learning was used to predict disorder severity from new brain function data, using a support vector machine (SVM). A multicenter approach was used to collect data for machine learning training, including behavioral and physiological indicators, age, and reverse Stroop task (RST) data from 108 children with ADHD and 108 typically developing (TD) children. Near-infrared spectroscopy (NIRS) was used to quantify change in prefrontal cortex oxygenated hemoglobin during RST. Verification data were from 62 children with ADHD and 37 TD children from six facilities in Japan. Results: The SVM general performance results showed sensitivity of 88.71%, specificity of 83.78%, and an overall discrimination rate of 86.25%. Conclusion: A SVM using an objective index from RST may be useful as an auxiliary biomarker for diagnosis for children with ADHD.