ADHD stands for Attention Deficit Hyperactivity Disorder, previously known as ADD (Attention Deficit Disorder). ADHD is not caused by poor parenting, motivation or effort, or reduced intelligence. ADHD is a medical disorder of neurobiological origin. Stereotypical views are quite damaging for anyone trying to seek help for their symptoms. ADHD seems to be genetically linked. That means if your parents or someone in your family has been diagnosed ADHD or symptoms of ADHD, there is an increased chance you or your children may have ADHD. The three most common symptoms of ADHD are inattention, hyperactivity, and impulsivity. Not everyone who has ADHD struggles with all three major symptoms. Different subtypes of ADHD include inattentive presentation, hyperactive-impulsive presentation, and combined inattentive-hyperactive-impulsive presentation.
People with ADHD may also struggle with executive functioning (tasks related to organization, planning, and working memory). Other ways to identify if someone has ADHD or is struggling with ADHD symptoms is to complete Neurocognitive Testing. This type of testing looks at the brain’s performance in multiple categories and compares the person to other people their age and gender. Someone who struggles with ADHD symptoms will usually have trouble with tests related to simple attention, complex attention, cognitive flexibility, processing speed, reaction time, and overall executive functioning. For more information on Neurocognitive Testing please visit our assessment page.
Our Approach to ADHD
We start with a Clinical Intake Interview to review background history, medical history, identify specific symptoms and their severity, review previous assessments and interventions, and identify if any other assessments are required. The next step is to complete a QEEG (Quantitative Electroencephalogram) assessment to analyze your brainwave patterns. The best way to understand brain waves is to compare them to each section of an orchestra. Every section of an orchestra needs to work together to make sure the music sounds good. Sometimes one section of the orchestra is more dominant than the other, but all sections are necessary to produce beautiful music. In the same way all brain waves are necessary to balance each other out, complement each other, and become dominant when necessary. For example, when you need to analyze and engage in higher level thinking you want your brain to be dominant in faster brain wave patterns to accomplish this task. When you are getting ready for sleep you want your brain to gradually slow down and be dominant in slower brain wave patterns.
People who have ADHD usually demonstrate an excess or dominance or slow brainwave patterns such as delta (the brainwave dominant during sleep) and theta (the brainwave associated with daydreaming, tuning out, and being internally aware). This imbalance or excess may explain why people with ADHD struggle with regulating their focus and attention. A reduction in calm and relaxed brain wave patterns (a reduction in sensorimotor rhythm) can help explain struggles with symptoms of hyperactivity. People with ADHD may have areas in the brain that communicate too quickly with one another and may explain some impulsive tendencies. Once we figure out what brain wave patterns are related to your symptoms we can design a personalized program to target and improve them. During each session we monitor your brain waves in real time and when there is greater balance of brain wave patterns we reward you with video and sound. These audio and visual rewards help train and guide your brain to have improved balance and improve your symptoms.
Research Articles on ADHD
This section is meant to highlight research that has been done in the field. The following brief summaries are resources that we have gathered for the public. For an in-depth look at each research article we recommend using the citation to find and read the original article. We hope to add additional resources when possible!
Arns, M., Feddema, I., & Kenemans, J. L. (2014). Differential effects of theta/beta and SMR neurofeedback in ADHD on sleep onset latency. Frontiers in Human Neuroscience, 8. doi:10.3389/fnhum.2014.01019
One mechanism suggested for the effects of sensorimotor rhythm (SMR) neurofeedback as well as TBR (Theta-Beta-Ratio) training is that it helps to normalize sleep and thus improves ADHD symptoms such as inattention and hyperactivity/ impulsivity. ADHD patients were compared to a control group to investigate if differences existed in sleep components including Sleep Onset Latency (SOL), Sleep Duration (DUR) and overall reported sleep problems (PSQI). They also examined if ay associations were seen between sleep=parameters and ADHD symptoms. Also, this study investigated the effects of SMR and TBR on symptoms, sleep parameters, and if they were mediated in the treatment outcomes. They found that there was a relationship between self-reported sleep problems (PSQI) and inattention in adults both with and without ADHD. TBE resulted in a small reduction of SOL. This change in SOL didn't correlate with change in ADHD symptoms, and the reduction in SOL only happened in the latter half of treatment. This effect was not specifically related to TBR neurofeedback. SMR specifically reduced the SOL, and pSQI score and these changes PSQI were strongly correlated with changes in inattention and the reduction in SOL was achieved in the first half of treatment. SMR neurofeedback may have SOL mediated through the course of treatment. TBR and SMR had similar effects of symptoms reduction in ADHD. The effects of training may have different working mechanisms in the amelioration of ADHD symptoms.
Albrecht, B., Sandersleben, H. U., Gevensleben, H., & Rothenberger, A. (2015). Pathophysiology of ADHD and associated problems—starting points for NF interventions? Frontiers in Human Neuroscience, 9. doi:10.3389/fnhum.2015.00359
This article covers the basics of neurofeedback. ADHD is characterized by hyperactivity, impulsivity, and inattention. This disorder is heterogeneous and often comorbid of associated problems from other psychiatric disorders are prevalent. ADHD can be accompanied by cognitive and motivational problems as well as abnormalities in the resting-state, associated with impaired brain activity in neuronal networks. Multimodal treatments should be utilized with comprising (NF). NF provides brain activity feedback using visual or auditory signals, which allow the participant to gain control over neuronal processes. NF can be used to improve underlying neuronal deficits or establish self-regulatory skills that can help compensate for behavioral difficulties. Most often ODD/ conduct or tic disorders are prevalent as comorbid disorders.
Arns, M., Conners, C. K., & Kraemer, H. C. (2012). A decade of EEG theta/beta ratio research in ADHD: A meta-analysis. Journal of Attention Disorders, http://dx. doi.org/10.1177/1087054712460087
EEG studies often cite that Theta/Beta ratio (TBR) is a specific measure which is characteristic of ADHD. This meta-analysis covers the literature on Theta/Beta Ratio in ADHD. This study analyzed TBR during Eyes Open at location Cz. Individuals between the ages of 6-18 were measured both with and without ADHD. This study identified 1253 individuals with ADHD and 517 without, over nine studies. They found that the mean effect size for 6-14-year-olds were 0.75 and for 6-18-year-olds were 0.62. Heterogeneity is significant within these populations. The Effect Sizes are misleading and may be an overestimation. Throughout the developmental span, TBR tends to decrease. Although excessive TBR is not a reliable diagnostic measure of ADHD; a significant subgroup of ADHD patients were found to have large TBR measures in the study. Thus, excess theta and TBR can potentially be used as a prognostic measure rather than a diagnostic measure.
Gevensleben, H., Moll, G. H., Rothenberger, A., & Heinrich, H. (2014). Neurofeedback in attention-deficit/hyperactivity disorder - different models, different ways of application. Frontiers in Human Neuroscience, 8. doi:10.3389/fnhum.2014.00846
Neurofeedback for ADHD has multiple protocols including TBR training and training of slow cortical potentials (SCPs). In this article, mechanisms of action are questioned. Frameworks for NF models namely, conditioning-and-repair model and the skill acquisition model are also discussed at length. This underlying model impacts NF application as well as selection and evaluation strategies. Empirical data is presented. It is hypothesized that different models may hold true depending on the process and behaviors to be addressed by the nF protocol. SCP may relate to skill acquisition model.
Snyder, S. M., & Hall, J. R. (2006). A Meta-analysis of Quantitative EEG Power Associated With Attention-Deficit Hyperactivity Disorder. Journal of Clinical Neurophysiology, 23(5), 441-456. doi:10.1097/01.wnp.0000221363.12503.78
This meta-analysis is utilized to demonstrate the utility of QEEG theta/beta ratios in the present in ADHD vs. the normal populations. Individuals had to have met criteria from the DSM-IV for diagnosis of ADHD. 9 studies with N=1498) were observed and the theta/beta ratio was summarized. The Effect size found was 3.08 for ADHD versus controls. This encompassed a control group of children adolescents and adults. This indicates that there may be up between 94-98% specificity of using theta/beta ratios for identifying ADHD. Controlled group studies were often limited in the sense that measured among the general population the specificity may be lower. 29/32 studies found in the literature demonstrated results consistent with the meta-analysis. The results are supported by the observation that TBR follows age-related changes in ADHD symptom presentation. TBR is a well-observed trait in ADHD compared to normal controls. Theta/beta ratio may rise with other condition, a study covering differential diagnosis would be required to determine generalization to this protocol to clinical applications. Standardization of QEEG technique is also needed for controlling the mental state, drowsiness, and mediation of participants.
Beauregard, M., & Lévesque, J. (2006). Functional Magnetic Resonance Imaging Investigation of the Effects of Neurofeedback Training on the Neural Basis of Selective Attention and Response Inhibition in Children with Attention-Deficit/Hyperactivity Disorder. Applied Psychophysiology and Biofeedback, 31(1), 3-20. doi:10.1007/s10484-006-9001-y
Two fMRI experiments were conducted to measure the effects of neurofeedback training (NFT) in ADHD children on neural areas of selective attention and response inhibition. 15 children were randomly assigned to the experimental (Neurofeedback) group while five were randomly assigned to the control (CON) group. The experiment group trained to increase Beta (15-18 Hz) and decrease Theta (4-7Hz). The fMRI was conducted one week before beginning NFT and at the end of NFT. Significant activation was seen for the experimental group in areas associated with attention. No changes in activation were seen in the control group. This suggests that NFT can help continually normalize brain systems as well as functional areas associated with selective attention and response inhibition.
Steiner, N. J., Frenette, E. C., Rene, K. M., Brennan, R. T., & Perrin, E. C. (2014). In-School Neurofeedback Training for ADHD: Sustained Improvements From a Randomized Control Trial. Pediatrics, 133(3), 483-492. doi:10.1542/peds.2013-2059
This study attempted to conduct a randomized control trial in which they evaluated sustained improvements after six months of 40 neurofeedback sessions which occurred in school. Individuals received either neurofeedback or Cognitive Training (CT). Participants were between 7-11 years old with diagnosed ADHD. 104 children were randomly assigned to receive either neurofeedback, CT, or a control condition. Neurofeedback participants maintained significant gains on inattention, executive functioning, and hyperactivity.
Bakhshayesh, A. R., Hänsch, S., Wyschkon, A., Rezai, M. J., & Esser, G. (2011). Neurofeedback in ADHD: A single-blind randomized controlled trial. European Child & Adolescent Psychiatry, 20(9), 481-491. doi:10.1007/s00787-011-0208-y
This study looks at using biofeedback with EEG neurofeedback in a single-blind randomized control trial design to evaluate the efficacy of neurofeedback. EMG biofeedback (BF) and theta/beta ratio reduction training were used in this study. 35 children with ADHD are randomly assigned to either therapy group (18) or control group (17) treatment for both groups utilize 30 sessions. Teachers and parents completed behavior rating scales as well as psychometric measures. Training reduced theta/beta ratios. Parents reported a reduction in ADHD symptoms and inattention. Improvements in NF groups were higher than BF groups. NF groups also improved on psychometric measures; the NF group showed a reduction inattention symptoms and reaction time on neuropsychological tests.
Meisel, V., Servera, M., Garcia-Banda, G., Cardo, E., & Moreno, I. (2013). Neurofeedback and standard pharmacological intervention in ADHD: A randomized controlled trial with six-month follow-up. Biological Psychology,94(1), 12-21. doi:10.1016/j.biopsych.2013.04.015
One of the first studies which utilized a randomized control trial compares Neurofeedback to stimulant medication for the amelioration of ADHD symptoms. In this study, 23 children (11 boys and 12 girls) between the ages of (7-14 years old) were randomly assigned either 40 sessions of theta/beta training or received methylphenidate. They utilized behavioral rating scales completed by parents and educators pre and post treatments. This was tested at both two and six-month follow-ups. Though similar significant reductions were reported in both treatment conditions for both functional and primary ADHD symptoms, only the Neurofeedback group had demonstrated significant academic improvements.
Monastra, V. J., Monastra, D. M., & George, S. (2002). The effects of stimulant therapy, EEG biofeedback, and parenting style on the primary symptoms of attention-deficit/hyperactivity disorder. Applied Psychophysiology and Biofeedback, 27(4), 231-249. doi:10.1023/a:1021018700609
100 children ages 6-19 who had ADHD, inattentive, or combined participated in this study which aimed to examine the effects of Ritalin, EEG biofeedback, and parenting styles on ADHD symptoms. All patients participated in the 1-year multimodal program that included Ritalin, parent counseling, and academic support at school. 51 of the participants received EEG biofeedback as well. In the post-treatment assessments, individuals were assessed with both stimulant and stimulants. Individual completed T.O.V.A and ADDES scales. Those who had received EEG biofeedback sustained the gains when tested without Ritalin.
Monastra, V. J., Lubar, J. F., Linden, M., Vandeusen, P., Green, G., Wing, W., . . . Fenger, T. N. (1999). Assessing attention-deficit hyperactivity disorder via quantitative electroencephalography: An initial validation study. Neuropsychology, 13(3), 424-433. doi:10.1037//0894-4188.8.131.524
Analysis of EEG output at the prefrontal location (Cz) was conducted on 482 individuals between the ages of 6-30 years old. The study attempted to test that cortical slowing in a prefrontal region can help differentiate patients with attention deficit hyperactivity disorder (ADHD) from nonclinical control groups. Participants were divided into 3 groups (ADHD, Inattentive; ADHD, Combined; and control group) on the basis of results of the standardized clinical interview, behavioral rating scales, and a CPT continuous performance task. Overall, a relation between theta/beta ratios being evaluated in ADHD patients were found.
Arns, M., Heinrich, H., & Strehl, U. (2014). Evaluation of neurofeedback in ADHD: The long and winding road. Biological Psychology, 95, 108-115. doi:10.1016/j.biopsych.2013.11.013
Prevalence is reported to be 3-7 % for ADHD in school age children. Three subtypes: predominantly inattentive, predominantly hyperactive-impulsive and combined type. Core symptoms of ADHD consist of inattention, impulsivity, and hyperactivity. Limitations exist for medication and behavior therapy. Neurofeedback helps teach or improve self-regulation of brain activity. Principles of classical conditioning and operant conditioning can be applied to help individuals gain self-regulatory skills. SMR treatments conducted by Sterman found improvements in sleep quality. Lubar employed A-B-A designs to find that symptoms of ADHD increased when training protocols were reversed. Protocol training, specifically training Theta/Beta (4-8 Hz/13-21 Hz) led to improvements in cognitive measures (attention and IQ). Studies since then have found that Theta/Beta ratio (TBR) training has comparable results to stimulant medication. Semi-active control conditions find that neurofeedback useful for inattention and impulsivity. Randomized control trials find that these effects are consistency at follow-up and a reduction in hyperactivity and impulsivity is also seen. 40 sessions lead to stronger results. Methylphenidate has not been shown to be more effective than neurofeedback in several studies. Low sample sizes may lead to further issues. It is difficult to eliminate all the other effects involved with Neurofeedback, but they can be controlled by using randomization in studies. Studies which randomized trials often fail to utilize proper Neurofeedback and make serious errors in the administration of Neurofeedback. For example utilizing thresholds that are too high. Many randomized studies do not consider the effects of generalization or apply any learning strategies to aid this process. There should be a focus on specific protocol investigation. A multidimensional approach should be taken to work with neurofeedback. Newer modalities of Neurofeedback, LORETA, and sLORETA show increased promise when dealing with complex disorders.
Ghaziri, J., Tucholka, A., Larue, V., Blanchette-Sylvestre, M., Reyburn, G., Gilbert, G., . . . Beauregard, M. (2013). Neurofeedback Training Induces Changes in White and Gray Matter. Clinical EEG and Neuroscience, 44(4), 265-272. doi:10.1177/1550059413476031
In this study, Health university students were randomly assigned to the experimental group, sham group or control group. Participants in the experimental group trained to enhance beta waves at F4 and P4. Attentional performance and MRI data were recorded one week before training and one week after training. Higher scores on auditory and visual sustained attention were present in experiment group. Gray matter volume increases were detected in cerebral structures involved in this type of attention. This study constitutes the first empirical demonstration that neurofeedback training leads to microstructural changes in white and gray matter.