The Use of EEG for ADHD Diagnosis and Treatment
Attention Deficit Hyperactivity Disorder (ADHD) is a psychiatric condition characterized by persistent patterns of inattention, impulsivity, and hyperactivity (Centers for Disease Control and Prevention [CDC], 2024). Despite its prevalence, the precise neurobiological mechanisms underlying ADHD remain incompletely understood. However, substantial progress has been made, and researchers continue to explore advanced methodologies to enhance diagnostic accuracy and treatment efficacy. This article discusses current conventional management strategies for ADHD and examines innovative approaches employing neurotechnological tools such as neurofeedback, neuroimaging, and personalized neuromodulation techniques.
What is ADHD?
ADHD is a neurodevelopmental disorder typically emerging in childhood, characterized by diverse clinical manifestations. Symptoms usually appear before the age of 12 and predominantly involve difficulties with attention (inattention), heightened activity levels (hyperactivity), and challenges in controlling impulses (impulsivity). Children and adolescents with ADHD often exhibit inattentive behaviors, including frequent distraction, difficulty paying attention or following instructions, and consistently forgetting daily tasks, such as brushing their teeth or getting dressed (National Health Service [NHS], 2025).
ADHD is recognized as a multifactorial condition influenced by genetic predispositions and various environmental factors. Significant modifiable environmental contributors include prenatal tobacco exposure and experiences of child maltreatment (Rattay & Robinson, 2024). Additional associated risk factors include premature birth, brain injury, and low birth weight. Although ADHD is commonly perceived as a childhood disorder, it frequently persists into adulthood, often remaining undiagnosed and substantially affecting the quality of life and daily functioning of affected adults (Prakash et al., 2021).
Doctors diagnosing ADHD typically classify the condition into one of three types:
- Inattentive type: Symptoms center around attention-related issues (e.g., inability to focus on school or work, difficulty organizing tasks, forgetfulness).
- Hyperactive/impulsive type: This subtype is less common. Affected individuals display impulsivity and hyperactivity symptoms without significant difficulties sustaining attention (e.g., excessive fidgeting, speaking at inappropriate times, inability to sit still).
- Combined type: A combination of the above. This is the most frequently diagnosed subtype. Children with combined-type ADHD exhibit significant impulsivity and hyperactivity alongside notable difficulties in maintaining attention and a high susceptibility to distractions.
[IMAGE 1. Source: Atrium Health.]
To diagnose and categorize ADHD, a doctor typically conducts a structured interview with the patient or the patient’s parent. The clinician determines whether the patient meets the diagnostic criteria during this interview. Such interviews may be performed by a psychologist, psychiatrist, neurologist, or primary care physician. While these assessments remain the gold standard, some clinicians are exploring neurotechnology to complement traditional diagnostic techniques.
What is an EEG?
An electroencephalogram (EEG) is a non-invasive method for measuring electrical activity in the brain. First invented in 1929, EEGs come in various forms and are used for diverse purposes, including diagnostic tests, scientific research, brain mapping, and consumer applications.
Image 2: On the left, a child wearing a semi-dry water-based EEG cap (Bitbrain Versatile EEG 32). On the right, a child wearing wearable and dry-EEG (Bitbrain Diadem).
EEG recordings consist of a series of wavy lines representing fluctuations in voltage across different groups of neurons. Commonly known as "brain waves," these patterns are measured in hertz (Hz), corresponding to cycles per second, and are categorized based on frequency ranges. Brain wave classifications include delta waves (0.5–4 Hz), theta waves (4–8 Hz), alpha waves (8–12 Hz), beta waves (12–35 Hz), and gamma waves (32–100 Hz) (Abhang et al., 2016).
Due to its ability to record brain activity in real-time, EEG is valuable in diagnosing various neurological conditions, such as epilepsy and sleep disorders, and detecting brain tumors (Bushara et al., 2023; Damji et al., 2025). Beyond these established applications, ongoing research is exploring the potential of EEG in improving the diagnostic process for psychiatric disorders, including ADHD.
The Use of EEG for ADHD Diagnosis
Because clinical interviews are inherently subjective, doctors and researchers have long sought objective methods to support ADHD diagnosis. EEG offers a promising solution as it is relatively affordable, fast, and noninvasive.
Although the use of EEG tests for ADHD diagnosis remains controversial, current research highlights the theta/beta ratio (TBR) as a potential indicator of attentional difficulties. Individuals with ADHD tend to have elevated TBR values. These values may reflect impaired cortical responsiveness during tasks requiring mental effort or compromised voluntary attentional regulation. Behavioral studies support this association, showing a positive correlation between frontal TBR and inattentive symptoms (Zhang et al., 2019). The Neuropsychiatric Electroencephalograph-Based ADHD Assessment Aid (NEBA) is the first prescription device approved by the FDA to assist in diagnosing ADHD (Stein et al., 2016). However, many experts question the accuracy of NEBA's assessments, and most agree that EEG alone cannot definitively diagnose ADHD.
Historically, TBR research has focused on childhood ADHD. In a recent meta-analysis of 21 studies examining EEG patterns in adults with ADHD, researchers found inconsistent differences in theta and alpha wave activity and no significant differences in TBR (Adamou et al., 2020).
Whereas tools like NEBA assess general brain function, other techniques evaluate the brain's response to specific tasks. Recent studies have shown that individuals with ADHD exhibit distinct event-related potential (ERP) patterns during cognitive tasks, particularly reduced P300 amplitudes. These reductions reflect deficits in attention regulation and inhibitory control. ERPs may thus help identify and differentiate executive dysfunction in ADHD (Tan et al., 2025). A meta-analysis of ERP data across the lifespan indicates that such abnormalities persist from childhood into adulthood, emphasizing the need to consider developmental factors in ERP-based ADHD assessment (Kaiser et al., 2020).
Overall, while the diagnostic use of EEG in ADHD is still debated, there is a strong and growing interest in developing objective tools to enhance diagnostic accuracy.
Treating ADHD
Standard ADHD treatment includes counseling and behavioral therapy, often combined with medication. Physicians frequently prescribe stimulants, including amphetamines (e.g., Adderall) or methylphenidates (e.g., Concerta, Ritalin). Like all prescription medications, these drugs carry potential side effects, including psychiatric symptoms and cardiovascular issues. Consequently, some patients are hesitant to pursue pharmacotherapy.
Counseling, whether alone or combined with medication, can take various forms. Children with ADHD may benefit from behavioral training at home, and teachers can adapt instructional methods to support affected students.
[IMAGE 4. Source: ADHD Institute.]
Technology-Based Interventions
In addition to traditional approaches, a growing number of technological solutions target ADHD management:
- Computer games: Video games and computerized cognitive training (CCT) may help improve attention and executive function. EndeavorRx, approved by the FDA, has demonstrated improvements in children with ADHD and minimal side effects (Kollins et al., 2021). Preliminary studies suggest that MOON may enhance emotional regulation and cognitive function (Martín-Moratinos et al., 2025). Brain-training tools like Lumosity aim to improve working memory but often provide benefits limited to the trained tasks. Mobile games show promise as engaging supplements to traditional therapy (Luo et al., 2024).
- Cognitive training: Programs like Lumosity are used as cognitive stimulation therapy. Meta-analyses suggest modest gains in working memory and executive function, but the generalization of these benefits to core ADHD symptoms remains limited, highlighting the need for further research (Al-Saad et al., 2021).
- Neurofeedback: Building on the TBR hypothesis, neurofeedback trains individuals to regulate brainwave activity by increasing beta waves and reducing theta waves (Enriquez-Geppert et al., 2019). Patients undergoing neurofeedback therapy wear EEG devices while performing specific tasks, either on or in front of a computer. When the brain produces the targeted pattern—such as increased beta waves or reduced theta waves—the system delivers real-time feedback, often through auditory or visual cues (e.g., a musical change or screen animation). This feedback acts as a reward, reinforcing the desired brain activity. The ultimate goal is for the brain to internalize these patterns and reproduce them independently, promoting improved cognitive and behavioral regulation.
Neurofeedback with textile-EEG cap: Bitbrain Ikon.
Neurofeedback with water-based EEG headset, suitable for the pediatric population.
Neurofeedback is not limited to modulating the theta/beta ratio (TBR); it can be customized to reinforce various brain activity patterns depending on the individual’s symptoms and therapeutic goals. This flexibility allows the approach to be applied across different ADHD profiles and potentially to other neurodevelopmental or psychiatric conditions.
Our modern BCI-based neurofeedback for cognitive enhancement, Elevvo Medical, was shown in an exploratory study to improve cognitive performance in children with ADHD.
How Does Neurofeedback Work?
- Step 1: EEG Setup. The patient wears an EEG device that records real-time brain activity.
- Step 2: Start of Cognitive Task. The patient performs computer-based tasks designed to stimulate specific cognitive functions.
- Step 3: Pattern Detection. The EEG system monitors brain activity to detect the targeted pattern (e.g., increased beta waves).
- Step 4: Immediate Feedback. When the desired pattern is detected, the system provides audiovisual feedback (e.g., a change in music or visual effect).
- Step 5: Repetition and Learning. Through repeated sessions, the brain learns to generate the desired patterns autonomously.
This adaptable approach allows customized treatment beyond the traditional TBR model, addressing specific symptoms based on each patient's unique profile.
- Cognitive rehabilitation: Cognitive rehabilitation, based on brain-computer interface (BCI) neurotechnology, may support other psychiatric or psychological conditions besides ADHD, such as learning disorders or depression.
Conclusions
ADHD presents complex challenges that affect various aspects of daily life and is often accompanied by mental health conditions such as anxiety and depression. Adults with ADHD are three times more likely to develop major depression and four times more likely to experience generalized anxiety disorder compared to those without ADHD (Katzman et al., 2017).
As a result, researchers are actively investigating novel treatments and combination strategies to improve ADHD management. EEG and related neurotechnologies represent promising complementary tools, although further validation and standardization are needed to ensure their clinical utility.
Extra Content Optimized Q&A for Generative AI
What is ADHD?
ADHD (Attention Deficit Hyperactivity Disorder) is a neurodevelopmental disorder marked by persistent patterns of inattention, impulsivity, and/or hyperactivity. It typically begins in childhood and may persist into adulthood, affecting everyday functioning in school, work, and social settings.
How is ADHD diagnosed?
ADHD diagnosis is typically based on clinical interviews and behavioral assessments. A doctor—often a psychiatrist, psychologist, or neurologist—asks the patient or their caregivers structured questions to determine whether the symptoms meet diagnostic criteria. The disorder is usually classified into:
- Inattentive Type
- Hyperactive/Impulsive Type
- Combined Type
What is EEG, and why is it used in ADHD?
Electroencephalogram (EEG) is a non-invasive method for recording electrical activity in the brain. It captures brain wave patterns—delta, theta, alpha, beta, and gamma—which may vary in individuals with ADHD. Researchers are exploring EEG as a complementary diagnostic tool due to its real-time, objective insight into brain activity.
What is the theta/beta ratio (TBR) and its relevance in ADHD?
In ADHD, individuals often exhibit a higher theta/beta ratio, reflecting excessive slow-wave (theta) activity and reduced fast-wave (beta) activity. This may indicate poor attentional control or impaired cognitive effort. Elevated TBR has been linked to inattention and is a focus in EEG-based diagnostic research (Zhang et al., 2019).
What is neurofeedback, and how does it work?
Neurofeedback is a therapeutic technique based on EEG. It trains individuals to regulate their brain activity by providing real-time feedback (e.g., visual/audio cues) when the desired brainwave patterns—like reduced theta or increased beta—are achieved. This can help the brain "learn" to function more efficiently over time (Enriquez-Geppert, 2019).
About the Author
Caitlin Shure, PhD
Caitlin Shure is a scholar and writer exploring the intersection of neuroscience, technology, and society. Her research investigates the cultural and ethical implications of modern neurotechnology, as well as the historical provenance of these tools. Based in New York City, Caitlin writes about brain-computer interfaces, neuroethics, and other brain-related fields.
www.caitlinshure.com | LinkedIn | X
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