ADHD
Attention-Deficit/Hyperactivity Disorder: neurofeedback training, QEEG brain mapping, and evidence-based interventions for attention, focus, and executive function.
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Showing 6 of 207Adaptive P300-Based Brain-Computer Interface for Attention Training: Protocol for a Randomized Controlled Trial
Noble, Sandra-Carina, Woods, Eva, Ward, Tomas, Ringwood, John V (2023) · JMIR Research Protocols
Background The number of people with cognitive deficits and diseases, such as stroke, dementia, or attention-deficit/hyperactivity disorder, is rising due to an aging, or in the case of attention-deficit/hyperactivity disorder, a growing population. Neurofeedback training using brain-computer interfaces is emerging as a means of easy-to-use and noninvasive cognitive training and rehabilitation. A novel application of neurofeedback training using a P300-based brain-computer interface has previously shown potential to improve attention in healthy adults. Objective This study aims to accelerate attention training using iterative learning control to optimize the task difficulty in an adaptive P300 speller task. Furthermore, we hope to replicate the results of a previous study using a P300 speller for attention training, as a benchmark comparison. In addition, the effectiveness of personalizing the task difficulty during training will be compared to a nonpersonalized task difficulty adaptation. Methods In this single-blind, parallel, 3-arm randomized controlled trial, 45 healthy adults will be recruited and randomly assigned to the experimental group or 1 of 2 control groups. This study involves a single training session, where participants receive neurofeedback training through a P300 speller task. During this training, the task’s difficulty is progressively increased, which makes it more difficult for the participants to maintain their performance. This encourages the participants to improve their focus. Task difficulty is either adapted based on the participants’ performance (in the experimental group and control group 1) or chosen randomly (in control group 2). Changes in brain patterns before and after training will be analyzed to study the effectiveness of the different approaches. Participants will complete a random dot motion task before and after the training so that any transfer effects of the training to other cognitive tasks can be evaluated. Questionnaires will be used to estimate the participants’ fatigue and compare the perceived workload of the training between groups. Results This study has been approved by the Maynooth University Ethics Committee (BSRESC-2022-2474456) and is registered on ClinicalTrials.gov (NCT05576649). Participant recruitment and data collection began in October 2022, and we expect to publish the results in 2023. Conclusions This study aims to accelerate attention training using iterative learning control in an adaptive P300 speller task, making it a more attractive training option for individuals with cognitive deficits due to its ease of use and speed. The successful replication of the results from the previous study, which used a P300 speller for attention training, would provide further evidence to support the effectiveness of this training tool. Trial Registration ClinicalTrials.gov NCT05576649; https://clinicaltrials.gov/ct2/show/NCT05576649 International Registered Report Identifier (IRRID) DERR1-10.2196/46135
View Full Paper →Benefits of a 12-Week Non-Drug “Brain Fitness Program” for Patients with Attention-Deficit/Hyperactive Disorder, Post-Concussion Syndrome, or Memory Loss
Fotuhi, Majid, Khorrami, Noah D., Raji, Cyrus A. (2023) · Journal of Alzheimer's Disease Reports
Background: Non-pharmacologic interventions can potentially improve cognitive function, sleep, and/or mood in patients with attention-deficit/hyperactive disorder (ADHD), post-concussion syndrome (PCS), or memory loss. Objective: We evaluated the benefits of a brain rehabilitation program in an outpatient neurology practice that consists of targeted cognitive training, lifestyle coaching, and electroencephalography (EEG)-based neurofeedback, twice weekly (90 minutes each), for 12 weeks. Methods: 223 child and adult patients were included: 71 patients with ADHD, 88 with PCS, and 64 with memory loss (mild cognitive impairment or subjective cognitive decline). Patients underwent a complete neurocognitive evaluation, including tests for Verbal Memory, Complex Attention, Processing Speed, Executive Functioning, and Neurocognition Index. They completed questionnaires about sleep, mood, diet, exercise, anxiety levels, and depression—as well as underwent quantitative EEG—at the beginning and the end of the program. Results: Pre-post test score comparison demonstrated that all patient subgroups experienced statistically significant improvements on most measures, especially the PCS subgroup, which experienced significant score improvement on all measures tested (p≤0.0011; dz≥0.36). After completing the program, 60% to 90% of patients scored higher on cognitive tests and reported having fewer cognitive and emotional symptoms. The largest effect size for pre-post score change was improved executive functioning in all subgroups (ADHD dz= 0.86; PCS dz= 0.83; memory dz= 1.09). Conclusion: This study demonstrates that a multimodal brain rehabilitation program can have benefits for patients with ADHD, PCS, or memory loss and supports further clinical trials in this field.
View Full Paper →Brainmarker-I Differentially Predicts Remission to Various Attention-Deficit/Hyperactivity Disorder Treatments: A Discovery, Transfer, and Blinded Validation Study
Voetterl, Helena, van Wingen, Guido, Michelini, Giorgia, Griffiths, Kristi R., Gordon, Evian, DeBeus, Roger, Korgaonkar, Mayuresh S., Loo, Sandra K., Palmer, Donna, Breteler, Rien, Denys, Damiaan, Arnold, L. Eugene, du Jour, Paul, van Ruth, Rosalinde, Jansen, Jeanine, van Dijk, Hanneke, Arns, Martijn (2023) · Biological Psychiatry. Cognitive Neuroscience and Neuroimaging
BACKGROUND: Attention-deficit/hyperactivity disorder is characterized by neurobiological heterogeneity, possibly explaining why not all patients benefit from a given treatment. As a means to select the right treatment (stratification), biomarkers may aid in personalizing treatment prescription, thereby increasing remission rates. METHODS: The biomarker in this study was developed in a heterogeneous clinical sample (N = 4249) and first applied to two large transfer datasets, a priori stratifying young males (<18 years) with a higher individual alpha peak frequency (iAPF) to methylphenidate (N = 336) and those with a lower iAPF to multimodal neurofeedback complemented with sleep coaching (N = 136). Blinded, out-of-sample validations were conducted in two independent samples. In addition, the association between iAPF and response to guanfacine and atomoxetine was explored. RESULTS: Retrospective stratification in the transfer datasets resulted in a predicted gain in normalized remission of 17% to 30%. Blinded out-of-sample validations for methylphenidate (n = 41) and multimodal neurofeedback (n = 71) corroborated these findings, yielding a predicted gain in stratified normalized remission of 36% and 29%, respectively. CONCLUSIONS: This study introduces a clinically interpretable and actionable biomarker based on the iAPF assessed during resting-state electroencephalography. Our findings suggest that acknowledging neurobiological heterogeneity can inform stratification of patients to their individual best treatment and enhance remission rates.
View Full Paper →Neural and behavioral adaptations to frontal theta neurofeedback training: A proof of concept study
Kerick, Scott E., Asbee, Justin, Spangler, Derek P., Brooks, Justin B., Garcia, Javier O., Parsons, Thomas D., Bannerjee, Nilanjan, Robucci, Ryan (2023) · PloS One
Previous neurofeedback research has shown training-related frontal theta increases and performance improvements on some executive tasks in real feedback versus sham control groups. However, typical sham control groups receive false or non-contingent feedback, making it difficult to know whether observed differences between groups are associated with accurate contingent feedback or other cognitive mechanisms (motivation, control strategies, attentional engagement, fatigue, etc.). To address this question, we investigated differences between two frontal theta training groups, each receiving accurate contingent feedback, but with different top-down goals: (1) increase and (2) alternate increase/decrease. We hypothesized that the increase group would exhibit greater increases in frontal theta compared to the alternate group, which would exhibit lower frontal theta during down- versus up-modulation blocks over sessions. We also hypothesized that the alternate group would exhibit greater performance improvements on a Go-NoGo shooting task requiring alterations in behavioral activation and inhibition, as the alternate group would be trained with greater task specificity, suggesting that receiving accurate contingent feedback may be the more salient learning mechanism underlying frontal theta neurofeedback training gains. Thirty young healthy volunteers were randomly assigned to increase or alternate groups. Training consisted of an orientation session, five neurofeedback training sessions (six blocks of six 30-s trials of FCz theta modulation (4-7 Hz) separated by 10-s rest intervals), and six Go-NoGo testing sessions (four blocks of 90 trials in both Low and High time-stress conditions). Multilevel modeling revealed greater frontal theta increases in the alternate group over training sessions. Further, Go-NoGo task performance increased at a greater rate in the increase group (accuracy and reaction time, but not commission errors). Overall, these results reject our hypotheses and suggest that changes in frontal theta and performance outcomes were not explained by reinforcement learning afforded by accurate contingent feedback. We discuss our findings in terms of alternative conceptual and methodological considerations, as well as limitations of this research.
View Full Paper →A comparison between classical and new proposed feature selection methods for attention level recognition in disordered children
Rady, Radwa Magdy, Moussa, Nancy Diaa, El Salmawy, Doaa Hanafy, M Rizk, M R, Alim, Onsy Abdel (2022) · Alexandria Engineering Journal
Lack of attention is a chronic behavior in ADHD (Attention Deficit Hyperactivity Disorder) and ASD (Autism Spectrum Disorder). Our goal is to develop a reliable method for the detection of inattention with high accuracy and low time consumption to be used in real time neurofeedback. The new applied methods for inattention in children are EMD (Empirical Mode Decomposition) with difference time series (Dt) and MRA (Multi Resolution Analysis). EMD is a method of breaking down a signal into ‘modes’ (IMFs) representing its different frequency components. Furthermore, MRA strikes balance between temporal and frequency resolution through localizing the EEG signal in frequency domain of interest (beta range) by wavelet decomposition or EMD and then retains time domain information using FD. As the results demonstrate, in intermediate and severe level cases of inattention, EMD_Dt technique is the most accurate. In mild level cases of inattention MRA (wavelet + FD) technique performance is better than EMD_Dt. However, the time consumption of the MRA (wavelet + FD) technique is fifteen times larger than EMD_Dt technique. EMD_Dt is the best technique as it requires less processing time which is the most important factor in neurofeedback, furthermore, clinician concerned more with severe and intermediate level of inattention to be treated.
View Full Paper →Characterizing the ASD–ADHD phenotype: measurement structure and invariance in a clinical sample
Krakowski, Aneta D., Cost, Katherine Tombeau, Szatmari, Peter, Anagnostou, Evdokia, Crosbie, Jennifer, Schachar, Russell, Duku, Eric, Georgiades, Stelios, Ayub, Muhammad, Kelley, Elizabeth, Nicolson, Rob, Pullenayegum, Eleanor, Barnett‐Tapia, Carolina (2022) · Journal of Child Psychology and Psychiatry
Background: Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD) have considerable overlap, supporting the need for a dimensional framework that examines neurodevelopmental domains which cross traditional diagnostic boundaries. In the following study, we use factor analysis to deconstruct the ASD–ADHD phenotype into its underlying phenotypic domains and test for measurement invariance across adaptive functioning, age, gender and ASD/ADHD clinical diagnoses. Methods: Participants included children and youth (aged 3–20 years) with a clinical diagnosis of ASD (n = 727) or ADHD (n = 770) for a total of 1,497 participants. Parents of these children completed the Social Communication Questionnaire (SCQ), a measure of autism symptoms, and the Strengths and Weaknesses of ADHD and Normal Behaviour (SWAN) questionnaire, a measure of ADHD symptoms. An exploratory factor analysis (EFA) was performed on combined SCQ and SWAN items. This was followed by a confirmatory factor analysis (CFA) and tests of measurement invariance. Results: EFA revealed a four-factor solution (inattention, hyperactivity/impulsivity, social-communication, and restricted, repetitive, behaviours and interests (RRBI)) and a CFA confirmed good model fit. This solution also showed good model fit across subgroups of interest. Conclusions: Our study shows that a combined ASD–ADHD phenotype is characterized by two latent ASD domains (social communication and RRBIs) and two latent ADHD domains (inattention and hyperactivity/impulsivity). We established measurement invariance of the derived measurement model across adaptive functioning, age, gender and ASD/ADHD diagnoses
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