The Beta Rhythm Exceeds 12 Hz
The beta rhythm exceeds 12 Hz with 2-20 microvolts asynchronous waves. Asynchronous means the neurons depolarize and hyperpolarize independently. The beta rhythm in EEG is typically defined within the frequency range of 13-30 Hz. However, some sources may use slightly different ranges. The variation in definitions can be attributed to differences in historical research, regional practices, and specific research contexts (Jadeja, 2021).
The beta rhythm is distributed across the scalp, with the highest amplitude in the frontal and precentral areas.
Beta Rhythm Generators
Whereas the sensorimotor cortex generates the sensorimotor rhythm, beta is generated in the brainstem and cortex. Ascending sensory traffic from the brainstem can override thalamic pacemakers (Andreassi, 2000), and specific cortical regions can produce localized beta activity beneath active electrodes (Thompson & Thompson, 2015). Reticular activating system graphic redrawn by minaanandag.
Kane and colleagues (2017) offered the following revised definition:
Any EEG rhythm between 14 and 30 Hz (wave duration 33–72 ms). Most characteristically recorded over the fronto-central regions of the head during wakefulness. Amplitude of fronto-central beta rhythm varies but is mostly below 30 µV. Blocking or attenuation of the beta rhythm by contralateral movement or tactile stimulation is especially obvious in electrocorticograms. Other beta rhythms are most prominent in other locations or are diffuse, and may be drug-induced (for example alcohol, barbiturates, benzodiazepines and intravenous anaesthetic agents).
Beta is also associated with the negative shift of the DC gradient (Speckmann et al., 2017). The DC gradient, only measurable by a DC-coupled EEG amplifier, measures the overall electrical gradient of cortical areas under the recording sensors. This gradient shows a slow oscillation of less than 1 second and is usually in the 0.1-0.2 Hz range. A shift of the gradient from its current state, becoming more electrically positive or negative, occurs every 5-10 seconds and sometimes quite a bit less often.
Buzsaki (2011) states that there is a progression of frequencies whose bandwidths overlap and interact with each other, from frequencies that take 15-40 seconds to complete each cycle up to those that oscillate at 200-600 cycles per second. Gunkelman (2005) called beta and gamma activity “emergent properties of bound networks.” This means that, as slower frequencies of EEG synchronize across networks, beta and gamma emerge in bursts of activity in coordination with that synchrony.
Beta activity is associated with "work" and reflects the ongoing excitatory/inhibitory cycles occurring on multiple time scales. While the work/rest cycle mentioned in relation to the alpha response and alpha blocking is one type of excitatory/inhibitory cycle on a broader scale, beta activity reflects actions that occur millisecond by millisecond and appear to be more locally generated.
Below is an example of eyes-open beta activity.
Caption: This is a 19-channel EEG recording in the eyes-open condition. This is a longitudinal bipolar montage, and the scale is 50 μV. Observe the alpha activity continuing at a much lower voltage in parietal and occipital derivations, compared to the previous eyes-closed examples, resulting from the attenuation of alpha with the opening of the eyes. There is beta activity in the 20-30 Hz range at less than 10 μV, seen mostly in frontal, central, parietal, and temporal derivations (comparisons between adjacent sensors) and somewhat slower 15-20 Hz patterns.
Kropotov (2016) describes the existence of several beta rhythms with different frequencies, various locations, and distinct functions. From this information, he states there is likely no single neuronal mechanism for generating localized beta activity. This fits the understanding that beta activity is associated with local tasks and, therefore, is mediated more by local mechanisms, with overall coordination from network systems and other rhythmic activity.
Low Beta (16-20+ Hz)
The cortex produces low beta when we solve problems like multiplication. When a child correctly answers a math problem, the 17-Hz amplitude may increase while theta and 8-10 Hz alpha amplitude simultaneously decrease. While detected between 12-15 Hz, it is less often seen above 20 Hz (Thompson & Thompson, 2015).
High Beta (20-35 Hz)
High beta is correlated with multi-tasking and optimal performance and anxiety, migraine, obsessive-compulsive disorder (OCD), rumination, and worrying. While elevations may indicate a range of disorders, they may represent the brain's compensation for elevated theta. Clinicians rarely reinforce high beta. Instead, they may inhibit high beta and theta (Demos, 2019).
Beta Spindles
Beta spindles are trains of spindle-like waveforms with frequencies lower than 20 Hz but more often fall between 22 and 25 Hz. Beta spindles may signal ADHD, especially with tantrums, anxiety, autistic spectrum disorders (ASD), epilepsy, and insomnia (Arns et al., 2015; Demos, 2019; Thompson & Thompson, 2015).
19-21 Hz or 20-23 Hz
Clients diagnosed with anxiety disorder frequently show increased power in the 19-21 Hz or 20-23 Hz range compared with 16-18 Hz. Elevations in these ranges may be associated with emotional intensity. Thompson and Thompson (2015) advise clinicians to use open-ended questions to ask clients about their mental activity and emotional state when these bands are elevated without telegraphing their expectations.
24-36 Hz
Clients who are distressed, hypervigilant, overthink, worry, and ruminate may show marked elevations in this range. A peak in this range may be associated with family or personal substance use disorder and may indicate the instrumental use of drugs to control anxiety. High-amplitude beta in this range is not always a negative indicator since it is also observed when highly intelligent individuals multi-task (Thompson & Thompson, 2015).
The movie below is a 19-channel BioTrace+ /NeXus-32 display of low beta (13-21 Hz) and high beta (22-34 Hz) activity © John S. Anderson. Brighter colors represent higher beta amplitudes. Frequency histograms are displayed for each channel.
Beta Rhythm Abnormalities
High voltage or abundant beta activity is the most common fast activity abnormality in EEGs due to pharmacologic effects. Benzodiazepines (e.g., diazepam, lorazepam) and barbiturates (e.g., phenobarbital) often cause this increase, as they are used for seizure management. This drug-induced beta activity is usually diffuse or frontally predominant and can also appear transiently during drowsiness, subsiding with deeper sleep (Libenson, 2024).
When beta activity is typical for the client based on age, state (eyes-open, eyes-closed, under task, etc.), and location, it suggests those areas are functioning as expected. If beta activity is deficient, that may mean that the site is under-functioning or under-activated for some reason. Reasons may include damage of some sort, metabolic deficits, fatigue, or other factors. An area that is consistently over-functioning may, in time, because of overuse and fatigue, end up with a lower level of functioning and, hence, less beta activity.
Higher-than-typical beta amplitude at a given location may mean the area is over-functioning or overly activated. Whether the beta amplitude is higher or lower than average, the clinician will want to understand the underlying functional neuroanatomy of the area to aid in the assessment process. For example, suppose the right posterior temporal/parietal junction that roughly underlies the area between T4 and T6 (TP8 in the 10-10 system) shows excess beta amplitude. In that case, it may be associated with heightened sensitivity to or attention to non-verbal communication, such as tone of voice, facial expression, and body language associated with angry outbursts or that may signal danger. If this area is under-activated, it may represent a self-protective “disconnection” from these same signals (Gunkelman, 2021).
Individuals who typically show excess beta activity at sleep onset and during sleep stages have a higher incidence of insomnia (Perlis et al., 2001). Meier and colleagues (2014) found a correlation between excess beta power in frontal, central, and temporal areas with delinquent behavior in adult men with concurrent ADHD symptomatology. In Rowan’s Primer of EEG (2nd ed.), Marcuse and colleagues (2016) identify excess interhemispheric beta asymmetry as an important diagnostic tool. The side with reduced relative beta power points to the pathological hemisphere. They identify brain abscesses, stroke, tumors, vascular malformations, and cortical dysplasia as associated with a focal decrease or enhancement of beta activity.
A reference to a normative database can be useful when assessing beta activity, particularly if a traumatic brain injury is suspected. Comparison with other EEG frequencies is also important, as an excess or lack of beta activity often accompanies differences from expected values for other frequencies.
Significant cerebral dysgenesis, like lissencephaly, can cause increased beta activity, typically accompanied by other EEG abnormalities and intellectual disability. In such cases, the beta activity is often slower. Increased beta activity can also appear in normal EEGs without explanation, potentially due to incomplete medication lists or residual drug effects.
Reductions in beta activity frequency (18-30 Hz) often indicate diffuse cortical injury, such as post-anoxic episodes, or the effects of sedative medications. Severe cortical injuries may show an absence of beta activity, though some patients naturally exhibit less beta activity as a normal variant. Low amplifier gains can obscure normal fast activity in EEG traces with high-voltage slow activity.
A true asymmetry in fast activity between brain regions is a significant abnormality, suggesting potential cortical damage. Fast waves are generated at the cortical level, reflecting the activity of circuits near the scalp surface rather than deeper or more medial regions of the brain. Asymmetry in fast activity often indicates cortical damage, with the area of lower voltage marking the abnormality, such as in the case of a cortical stroke where beta activity is reduced. Rarely, an abnormal cortical area may show increased fast activity.
Spindling Excessive Beta (SEB)
Spindling excessive beta (SEB) refers to a specific pattern observed in electroencephalogram (EEG) recordings characterized by high-frequency beta waves (13-30 Hz) that display a spindle-like appearance. These beta spindles often exceed 20 μV in amplitude and can occur in both frontal and central regions of the brain. SEB is distinguished from typical beta activity by its spindling morphology and higher amplitude (Arns et al., 2015; Krepel et al., 2021). Beta spindle graphic retrieved from ADDYSSEY.
SEB appears to be a transdiagnostic EEG feature, meaning it is observed across various psychiatric disorders and is not limited to a single diagnosis (Arns et al., 2015; Krepel et al., 2021). SEB has been associated with a range of psychiatric and neurological conditions, making it a critical biomarker in clinical neurophysiology. Its clinical importance is primarily seen in sleep disorders, Attention-Deficit Hyperactivity Disorder, medication resistance, and epilepsy.
Sleep Disorders
SEB is often linked with sleep disturbances, particularly insomnia. Insomnia complaints are more prevalent in individuals with frontal SEB patterns (Arns et al., 2015). Studies indicate that individuals with SEB may experience difficulties in maintaining sleep, leading to chronic insomnia (Swatzyna et al., 2022). SEB may be a marker of hypoarousal or sub-vigil states.
Attention-Deficit/Hyperactivity Disorder (ADHD)
There is a notable association between SEB and ADHD. Patients exhibiting SEB often report symptoms of inattention, hyperactivity, and impulsivity. Children with excess beta activity in their EEGs are a small subset of ADHD children, similar to other ADHD children but more prone to temper tantrums and moodiness (Clarke et al., 2001). This association suggests that SEB can be used as an objective marker for ADHD diagnosis and management (Swatzyna et al., 2022).
Medication Resistance
SEB is frequently observed in patients who have failed multiple medication trials for various psychiatric conditions. This resistance to medication highlights the need for alternative therapeutic approaches for individuals exhibiting SEB (Swatzyna et al., 2022).
Epilepsy
Beta spindles can co-occur with seizure disorders, although patients with a history of seizures were excluded from some SEB studies to isolate its effects in other conditions. The presence of SEB in epilepsy patients can complicate the clinical picture, necessitating careful EEG interpretation (Swatzyna et al., 2022).
Mechanisms and Hypotheses
SEB might reflect a sub-vigil state, which is an intermediate state between wakefulness and sleep. This state can lead to cognitive impairments and behavioral disturbances observed in conditions like ADHD and insomnia (Swatzyna et al., 2022). Benzodiazepines and other substances affecting GABAergic transmission can induce SEB, suggesting a neurochemical basis for its occurrence. This insight provides avenues for pharmacological interventions targeting the GABA system (Swatzyna et al., 2022).
Treatment Implications
Recognizing SEB in patients can influence treatment strategies. For instance, behavioral interventions targeting sleep hygiene may benefit those with SEB-related insomnia. Similarly, neurofeedback and other non-pharmacological treatments might offer alternative approaches for ADHD patients exhibiting SEB, especially those resistant to conventional medications (Swatzyna et al., 2022).
Conclusion
SEB is a distinctive EEG pattern with significant clinical implications across various psychiatric and neurological disorders. Its presence can aid in the diagnosis, understanding, and treatment of conditions such as insomnia, ADHD, and medication-resistant psychiatric disorders. Continued research into SEB will further elucidate its mechanisms and optimize therapeutic strategies.
Summary
The beta rhythm, typically defined within the 13-30 Hz range, is characterized by asynchronous waves with amplitudes between 2-20 microvolts. Asynchronous in this context means that neurons depolarize and hyperpolarize independently. The brainstem and cortex generate the beta rhythm, with the highest amplitude in the frontal and precentral areas. Beta activity reflects ongoing excitatory and inhibitory cycles, correlates with tasks and states such as attention, problem-solving, and anxiety, and is sensitive to pharmacological influences. Beta abnormalities can indicate various clinical conditions, including insomnia, ADHD, and epilepsy.
Spindling Excessive Beta (SEB) is a distinct EEG pattern characterized by high-frequency beta waves (13-30 Hz) with a spindle-like appearance, often exceeding 20 μV in amplitude. SEB is a transdiagnostic feature associated with psychiatric and neurological conditions such as insomnia, ADHD, medication resistance, and epilepsy. SEB is thought to reflect sub-vigil states, which are intermediate between wakefulness and sleep, potentially leading to cognitive impairments and behavioral disturbances. Recognizing SEB can influence treatment strategies, including behavioral interventions for sleep and neurofeedback for ADHD. Continued research is essential further to elucidate the mechanisms and therapeutic approaches for SEB.
Glossary
beta asymmetry: an uneven distribution of beta wave activity between the two brain hemispheres. This asymmetry can be observed as differences in the amplitude or power of beta waves recorded over corresponding regions on either side of the brain. Beta asymmetry may indicate underlying neurological or psychiatric conditions, such as localized brain damage, epilepsy, or mood disorders.
beta rhythm: 12-38-Hz activity associated with arousal and attention generated by brainstem mesencephalic reticular stimulation that depolarizes neurons in both the thalamus and cortex. The beta rhythm can be divided into multiple ranges: beta 1 (12-15 Hz), beta 2 (15-18 Hz), beta 3 (18-25 Hz), and beta 4 (25-38 Hz).
beta spindles: trains of spindle-like waveforms with frequencies that can be lower than 20 Hz but more often fall between 22 and 25 Hz. They may signal ADHD, especially with tantrums, anxiety, autistic spectrum disorders (ASD), epilepsy, and insomnia.
cerebral dysgenesis: brain malformations caused by abnormal brain development during prenatal growth. This condition can involve a range of structural anomalies, including issues with forming the cerebral cortex, improper organization of neural connections, and other developmental irregularities. These abnormalities can lead to various neurological deficits, intellectual disabilities, and epilepsy. Cerebral dysgenesis can result from genetic mutations, environmental factors, or both, impacting the brain's normal developmental processes. high beta: 20-35 Hz rhythm correlated with multi-tasking and optimal performance and anxiety, migraine, obsessive-compulsive disorder (OCD), rumination, and worry. lissencephaly: an abnormality meaning "smooth brain," is a rare brain malformation characterized by the absence or underdevelopment of the brain's normal convolutions (gyri) and grooves (sulci). This condition results from defective neuronal migration during embryonic development. Individuals with lissencephaly often have severe intellectual disabilities, developmental delays, seizures, and other neurological impairments. The severity of symptoms can vary, but the condition is typically associated with significant functional impairments. Lissencephaly can be caused by genetic mutations or other factors affecting brain development during pregnancy. low beta: 16-20+ Hz rhythm associated with successful problem-solving.
spindling excessive beta (SEB): an EEG pattern characterized by high-frequency beta waves (13-30 Hz) with a spindle-like appearance, often exceeding 20 μV in amplitude. It is associated with various psychiatric and neurological conditions, including ADHD, insomnia, and medication-resistant psychiatric disorders.
sub-vigil states: intermediate states between wakefulness and sleep, characterized by reduced sensory and cognitive activity. These states can lead to cognitive impairments and behavioral disturbances, often observed in conditions like ADHD and insomnia.
References
Angelakis, E., Lubar, J. F., Stathopoulou, S., & Kounios, J. (2004). Peak alpha frequency: an electroencephalographic measure of cognitive preparedness. Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology, 115(4), 887–897. https://doi.org/10.1016/j.clinph.2003.11.034 Arns, M., Heinrich, H., Ros, T., Rothenberger, A., & Strehl, U. (2015). Editorial: Neurofeedback in ADHD. Frontiers in Human Neuroscience, 9, 602. https://doi.org/10.3389/fnhum.2015.00602
Arns, M., Swatzyna, R., Gunkelman, J., & Olbrich, S. (2015). Sleep maintenance, spindling excessive beta and impulse control: an RDoC arousal and regulatory systems approach? Neuropsychiatric Electrophysiology, 1, 1-11. https://doi.org/10.1186/S40810-015-0005-9
Clarke, A., Barry, R., McCarthy, R., & Selikowitz, M. (2001). Excess beta activity in children with attention-deficit/hyperactivity disorder: an atypical electrophysiological group. Psychiatry Research, 103, 205-218. https://doi.org/10.1016/S0165-1781(01)00277-3
Demos, J. N. (2019). Getting started with neurofeedback (2nd ed.). W. W. Norton & Company.
Kane, N., Acharya, J., Benickzy, S., Caboclo, L., Finnigan, S., Kaplan, P. W., Shibasaki, H., Pressler, R., & van Putten, M. J. A. M. (2017). A revised glossary of terms most commonly used by clinical electroencephalographers and updated proposal for the report format of the EEG findings. Revision 2017. Clinical Neurophysiology Practice, 2, 170–185. https://doi.org/10.1016/j.cnp.2017.07.002
Libenson, M. H. (2024). Practical approach to electroencephalography. Elsevier.
Swatzyna, R. J., Arns, M., Tarnow, J. D., Turner, R. P., Barr, E., MacInerney, E. K., Hoffman, A. M., & Boutros, N. N. (2022). Isolated epileptiform activity in children and adolescents: Prevalence, relevance, and implications for treatment. European Child & Adolescent Psychiatry, 31(4), 545–552. https://doi.org/10.1007/s00787-020-01597-2
Thompson, M., & Thompson, L. (2015). The neurofeedback book: An introduction to basic concepts in applied psychophysiology (2nd ed.). Association for Applied Psychophysiology and Biofeedback.
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