The human brain maintains an unbroken symphony of electrical oscillations that reflect shifting cognitive states, levels of arousal, and sensory processing demands. Among these intrinsic rhythms, the alpha wave stands as the foundational electrophysiological signature of relaxed wakefulness, conscious sensory gating, and internal mental orientation. Understanding this electrocortical rhythm provides researchers and clinicians with critical insights into neural communication, attentional selection, and cerebral pathology.
Alpha Wave
1. Concise Definition
An alpha wave (frequently referred to as the alpha rhythm) is an oscillating neural voltage potential characterized by an electroencephalographic frequency band ranging strictly between 8 and 12 Hertz (cycles per second), typically exhibiting amplitudes between 20 and 100 microvolts. Prominently recorded over the posterior regions of the human scalp—predominantly the occipital, parietal, and posterior temporal cortices—this synchronized electrical potential emerges most distinctly during quiet wakefulness with closed eyes and diminishes markedly upon visual stimulation, mental calculation, or elevated cortical arousal.
Rather than merely representing an inactive or “idling” cerebral state as historic models suggested, modern cognitive neuroscience recognizes the alpha rhythm as an active, top-down inhibitory mechanism. Through this functional inhibition, the brain suppresses task-irrelevant sensory cortices, optimizing the allocation of cognitive resources toward attended internal or external streams of information.
2. Etymology & Linguistic Origin
The nomenclature derives from the classic Greek letter alpha (ἄλφα), which denotes the first position in the Greek alphabet. The terminology was introduced into physiological nomenclature by the German neuropsychiatrist Hans Berger in 1929. Berger designated these prominent electrical signals as “waves of the first order” (Alpha-Wellen), distinguishing them from the higher-frequency, lower-amplitude “waves of the second order” (Beta-Wellen) that he simultaneously observed. The term entered English medical and physiological lexicons in the early 1930s following international replication of Berger’s revolutionary findings, becoming universally standardized in systemic electrophysiology and neurology.
3. Pronunciation & Grammatical Form
In standard English phonetics, the term is pronounced as /ˈælfə weɪv/ (American English: AL-fuh wayv). Grammatically, it functions as a countable noun phrase (plural: alpha waves). It can also function attributively as a nominal adjunct, as seen in compound phrases such as alpha rhythm, alpha-band activity, alpha desynchronization, or alpha suppression. In clinical neurophysiology, practitioners often interchange “alpha wave” with “posterior basic rhythm” or “posterior dominant rhythm” when discussing baseline resting-state human electroencephalography (EEG).
4. Detailed Conceptual Explanation
Alpha waves arise from the coordinated, synchronous postsynaptic potentials of vast populations of neocortical pyramidal neurons, oriented perpendicularly to the cortical surface. When tens of thousands of these pyramidal cells undergo rhythmic, alternating depolarization and hyperpolarization in temporal unison, their extracellular electrical currents aggregate. These collective dipoles penetrate through cerebrospinal fluid, meninges, cranial bone, and the scalp, manifesting as rhythmic sinusoidal fluctuations captured by macro-electrodes in electroencephalography (EEG) or magnetic flux sensors in magnetoencephalography (MEG).
The biological pacemaker responsible for generating and pacing the alpha rhythm resides within complex thalamocortical networks. Specific reciprocal loops connecting thalamic relay cells with the reticular thalamic nucleus (nRT) and reciprocal pyramidal tracts in layer IV and V of the neocortex pace this rhythm. The reticular thalamic nucleus, comprised almost exclusively of inhibitory gamma-aminobutyric acid (GABA)-ergic neurons, acts as an endogenous master regulator. When sensory input to the thalamus declines—such as when an individual closes their eyes in an awake state—tonic hyperpolarization of thalamic relay neurons triggers bursts of oscillatory discharge at approximately 10 Hz, entraining the visual and sensory cortex into uniform, large-amplitude synchronization.
From a functional perspective, the alpha wave represents the fundamental temporal framework of conscious perception. Far from being a continuous stream, human sensory processing is parsed into temporal discrete windows governed by the phase of ongoing alpha oscillations. The peak of an alpha oscillation corresponds to a state of heightened neuronal excitability and enhanced likelihood of sensory action potentials, whereas the trough represents a phase of intense active inhibition. Consequently, incoming sensory stimuli that coincide with the inhibitory phase of the local alpha rhythm are less likely to cross the perceptual threshold, demonstrating that alpha oscillations modulate perceptual awareness in real time.
Furthermore, alpha activity is not regionally uniform. Although the posterior dominant rhythm is the most readily identifiable manifestation, independent alpha-frequency rhythms exist across distinct functional cortices. For instance, the sensorimotor rhythm, or mu (µ) rhythm, oscillates within the 8–13 Hz range over the primary motor and somatosensory cortices and desynchronizes during physical movement or motor imagery. Similarly, the tau rhythm manifests in auditory cortex within the upper temporal lobes. Thus, alpha oscillations represent a generalized cortical mechanism deployed locally to regulate neural excitability across sensory modalities.
5. Historical Development
The systematic exploration of alpha waves traces back to the University of Jena in Germany, where Hans Berger recorded the first human scalp electroencephalogram in 1924, subsequently publishing his watershed paper in 1929. Utilizing primitive string galvanometers and radio tubes, Berger systematically recorded the continuous bioelectric fluctuations of the human brain. He noted that when human subjects rested tranquilly in a darkened chamber with their eyes shut, substantial 10-Hz oscillations dominated the recording. He dubbed these Alpha-Wellen and observed that the physical act of opening the eyes or engaging in complex mental arithmetic abruptly abolished this oscillation—a phenomenon he termed Alpha-Arbeit (alpha blocking), known today as alpha desynchronization.
Berger’s findings initially encountered skepticism throughout the European medical establishment, which largely viewed his bioelectric readings as artifactual signals caused by cranial muscle contractions or skin impedance fluctuations. However, in 1934, British Nobel laureate Edgar Douglas Adrian and his colleague Brian Matthews successfully replicated Berger’s observations at the University of Cambridge. In their landmark publication, Adrian and Matthews validated the cortical origin of the rhythm and coined the term “Berger rhythm” to honor the German pioneer. They demonstrated with rigorous physiological precision that the rhythm was primarily generated within the occipital lobes and reflected the functional cessation of visual processing.
The mid-twentieth century brought technical refinements through high-gain differential amplifiers, multichannel montage systems, and standardized electrode arrays such as the International 10–20 System established by Herbert Jasper in 1958. During this era, researchers systematically classified the development of the alpha rhythm across the human lifespan, establishing that the posterior dominant rhythm accelerates from an early childhood frequency of 3–4 Hz up to its characteristic adult pace of 10 Hz by approximately 8 to 10 years of age.
In the late 1960s and 1970s, the emergence of sensory biofeedback, spearheaded by researchers such as Joe Kamiya, catapulted alpha waves into mainstream public discourse and cognitive research. Kamiya demonstrated that human subjects could consciously learn to recognize and voluntarily enhance their alpha rhythm via real-time auditory or visual feedback. Although this phenomenon sparked an unscientific cultural movement asserting that alpha states represented elevated enlightenment or psychic power, it catalyzed modern empirical research into neurofeedback, attentional regulation, and non-pharmacological interventions for affective disorders.
In modern neuroscience, the advent of source-localization algorithms, simultaneous EEG-functional magnetic resonance imaging (EEG-fMRI), and high-density magnetoencephalography has replaced the classical “idling hypothesis” with the contemporary “inhibition-timing hypothesis.” Investigators such as Wolfgang Klimesch and Ole Jensen have demonstrated that alpha oscillations represent an active top-down gatekeeper rather than a passive byproduct of rest.
6. Theoretical Foundations
Theoretical frameworks explaining the alpha wave have fundamentally transformed over the past century. For decades, the dominant theoretical framework was the Cortical Idling Hypothesis, proposed by early electrophysiologists. This view held that synchronized alpha waves merely reflected a resting, passive state of cortical circuitry—a “screen-saver” mode that the brain entered when sensory inputs ceased. Because alpha power dramatically decreased whenever subjects opened their eyes, engaged in targeted visual search, or focused on complex tasks, researchers deduced that alpha synchronization signified regional metabolic quiescence.
In contrast, contemporary cognitive neuroscience operates primarily under the Inhibition-Timing Hypothesis, formulated extensively by Wolfgang Klimesch, Paul Sauseng, and Steven Hanslmayr. This model posits that synchronized alpha power reflects active, localized functional inhibition of task-irrelevant cortical areas. According to this framework, high alpha amplitude within a sensory region suppresses distracting environmental noise or irrelevant sensory channels, thereby protecting upstream working memory processes from interference. Conversely, localized alpha desynchronization (decreased amplitude) reflects the release of inhibition, enabling the underlying cortical circuits to process relevant sensory information.
Complementing this functional architecture is the Gating-by-Inhibition Model developed by Ole Jensen and colleagues. This theoretical paradigm articulates that the human brain does not possess infinite computational bandwidth to process every environmental input simultaneously. To optimize behavior, the prefrontal cortex and executive control networks orchestrate selective gating by down-regulating cortical excitability in non-priority networks using targeted bursts of alpha-frequency inhibition. For example, during a visuospatial working memory task requiring attention to the right visual hemifield, alpha oscillations selectively decrease in the contralateral (left) occipital cortex to facilitate visual perception, while simultaneously increasing in the ipsilateral (right) occipital cortex to suppress distracting stimuli from the left hemifield.
Finally, the Perceptual Framing or Pulsed-Inhibition Theory posits that alpha waves operate as discrete temporal cycles that parse continuous sensory reality into micro-snapshots. Under this theory, each 100-millisecond cycle of an alpha oscillation contains an excitable phase window followed by an inhibitory phase window. Sensory signals arriving during the excitable phase trigger coherent downstream neuronal cascades and conscious perception, whereas signals arriving during the inhibitory phase fall beneath the perceptual threshold or suffer delayed reaction times. This cyclical modulation underpins subjective time perception and sensory integration.
7. Key Components, Types & Dimensions
The alpha phenomenon encompasses several distinct electrophysiological variants, dimensions, and topography across human brain tissue:
- Posterior Dominant Alpha Rhythm: The classic occipital-parietal rhythm, prominent during quiet wakefulness with closed eyes, responding promptly to the “Berger effect” (eye opening and visual fixation).
- Rolandic Mu (µ) Rhythm: An 8–13 Hz oscillation located bilaterally over the central sensorimotor strip (electrodes C3, Cz, C4). It desynchronizes upon real, planned, or imagined motor actions and reflects motor cortex readiness.
- Temporal Tau (τ) Rhythm: A localized 8–10 Hz rhythm originating within the superior temporal auditory cortex, which attenuates in response to sound processing, acoustic stimuli, or auditory imagery.
- Frontal Midline Alpha: Oscillatory dynamics recorded over frontal regions associated with affective processing, emotional regulation, and working memory retention.
- Frontal Alpha Asymmetry (FAA): The dimensional ratio of alpha power between the left and right dorsolateral prefrontal cortices, widely used as an electrophysiological correlate of approach-avoidance motivation and depressive vulnerability.
- Alpha Peak Frequency (APF): The precise spectral frequency (e.g., 9.8 Hz vs. 11.2 Hz) where individual alpha power is maximized; functions as a stable biological trait correlated with cognitive processing speed and working memory capacity.
- Alpha Phase-Locking and Coherence: The degree to which distant cortical sites synchronize their alpha oscillations in time, reflecting long-range functional connectivity and coordinated neural information routing.
8. Examples & Illustrative Cases
To conceptualize the alpha wave across naturalistic scenarios and empirical studies, consider the following real-world and clinical illustrations:
Example 1: The Classic Eye-Closure Paradox. A participant in a cognitive electrophysiology laboratory sits reclined in an acoustically isolated room. With their eyes wide open, their occipital EEG traces exhibit low-amplitude, high-frequency irregular fluctuations (predominantly beta and gamma activity). The moment the participant closes their eyes, the baseline waveform transforms into continuous, highly regular sinusoidal bursts registering at 10 Hz with an amplitude reaching 60 microvolts. The participant is entirely awake, relaxed, and mentally tranquil. The moment they open their eyes or are asked to calculate “73 minus 17,” the high-amplitude sinusoidal train flattens into desynchronized fast waves within 200 milliseconds.
Example 2: Visual Hemifield Cued Attention. An athlete undergoes an attentional cuing experiment where a directional arrow indicates that an upcoming target will appear on the far-left side of a computer display. MEG sensors record a sharp decrease in alpha power over the athlete’s right occipital cortex (contralateral to the target), preparing the relevant visual pathways for fast target identification. Simultaneously, high-amplitude alpha bursts flood the left occipital cortex (ipsilateral), intentionally suppressing sensory capture from the irrelevant right visual field. This bilateral asymmetry directly improves the athlete’s reaction time and spatial accuracy.
Example 3: Deep Mindfulness Meditation. An experienced meditator engages in open-monitoring or focused-attention Buddhist meditation. Quantitative EEG (qEEG) recordings demonstrate an expansion of high-amplitude alpha oscillations beyond the typical posterior boundaries, spreading anteriorly across central and prefrontal networks. This widespread alpha synchronization reflects deep relaxation coupled with heightened internal alertness and diminished reactivity to extraneous external noises.
9. Measurement & Assessment
The observation and quantitative analysis of alpha waves depend upon rigorous recording protocols and mathematical signal processing paradigms:
In standard clinical and research environments, alpha activity is recorded via non-invasive scalp EEG using the International 10–20 System or higher-density montages (such as 64- or 128-channel caps). Electrodes placed at occipital (O1, O2, Oz), parietal (P3, P4, Pz), and central (C3, C4, Cz) coordinates are particularly critical. To assess the health and vitality of the rhythm, neurophysiologists inspect the signal using both bipolar montages (evaluating voltage differences between adjacent electrodes) and referential montages (measuring voltage against an inactive reference, such as linked earlobes or the mastoids).
Signal analysis historically relied on visual qualitative inspection of paper traces. Modern electrophysiology converts continuous analog voltage signals into digital records, employing mathematical algorithms to quantify spectral properties:
- Fast Fourier Transform (FFT): Computes the power spectral density (PSD) of the signal, expressing alpha amplitude in microvolts squared per Hertz (µV²/Hz) within the 8–12 Hz window.
- Event-Related Desynchronization (ERD) / Event-Related Synchronization (ERS): Measures the percentage decrease (ERD) or increase (ERS) in alpha power relative to a pre-stimulus baseline interval, delineating the exact temporal dynamics of cognitive operations.
- Time-Frequency Analysis (Wavelet Decomposition): Provides simultaneous high-resolution temporal and spectral data, tracing how alpha phase and power fluctuate millisecond-by-millisecond during perceptual tasks.
- Source Localization (e.g., LORETA or Beamforming): Mathematical modeling that resolves the “inverse problem” of EEG, projecting surface-recorded alpha currents back onto three-dimensional anatomical structural magnetic resonance imaging (MRI) reconstructions to isolate specific cortical generators.
10. Applications & Practical Significance
The study of alpha oscillations holds wide-ranging relevance across clinical diagnosis, neurotechnology, psychology, and occupational performance:
Clinical Diagnostics and Neurology: In clinical neurology, the posterior dominant rhythm serves as a vital index of cerebral health. A slowing of the background alpha peak frequency below 8 Hz (drifting into the theta band) is an early biomarker of metabolic encephalopathy, generalized toxic states, traumatic brain injury, or neurodegenerative conditions like Alzheimer’s disease. In contrast, “Alpha Coma”—a rare clinical syndrome where widespread, unreactive alpha-frequency patterns dominate the EEG of a comatose patient following severe cardiorespiratory arrest or pontine damage—carries an ominous, grave neurological prognosis.
Neurofeedback and Psychiatric Interventions: In psychological therapy, quantitative EEG profiles frequently reveal disturbances in Frontal Alpha Asymmetry (FAA). Elevated right frontal alpha power (reflecting relative hypoactivation of the left dorsolateral prefrontal cortex) correlates strongly with major depressive disorder, anhedonia, and anxiety disorders. Clinicians utilize alpha neurofeedback to train patients to self-regulate regional cortical activation, normalizing hemispheric asymmetries and alleviating depressive symptoms without pharmacological intervention.
Brain-Computer Interfaces (BCI): The sensory-motor mu variant of the alpha rhythm forms the backbone of motor imagery-based Brain-Computer Interfaces. Because imagined motor execution (e.g., visualizing moving the right hand) induces robust contralateral alpha/mu desynchronization over electrode C3, neuroprosthetic software can translate this drop in electrical power into real-time digital commands, enabling paralyzed individuals to maneuver motorized wheelchairs, prosthetic limbs, or robotic cursors.
Sleep Medicine: Alpha oscillations play a distinctive role in the architecture of sleep. The normal transition from waking rest to Stage 1 non-rapid eye movement (NREM) sleep is defined by the progressive breakdown and fragmentation of the posterior alpha rhythm, which is replaced by diffuse theta activity. The abnormal intrusion of alpha rhythms during deeper Stage 3 slow-wave sleep—termed “Alpha-Delta sleep”—is a hallmark of non-restorative sleep syndromes, chronic fatigue syndrome, and fibromyalgia, frequently corresponding to chronic pain and morning exhaustion.
11. Research & Empirical Evidence
Extensive neuroscientific literature documents the functional properties of alpha waves across both human and animal models:
A landmark investigation by Wolfgang Klimesch and colleagues demonstrated that Individual Alpha Frequency (IAF) is a genetically heritable trait positively correlated with cognitive performance. Subjects with naturally higher resting alpha peak frequencies (e.g., 11 Hz) demonstrate significantly faster cognitive processing speeds, superior working memory retention, and quicker visual reaction times compared to individuals whose peak frequencies rest closer to 8.5 Hz. Moreover, resting IAF exhibits a steady decline during healthy aging, paralleling physiological reductions in white matter integrity and processing speed.
Pioneering neuroimaging research combining EEG with functional magnetic resonance imaging (fMRI) has corroborated the inhibitory function of alpha waves. Studies led by Laufs, Goldman, and colleagues demonstrated that spontaneous fluctuations in posterior alpha power correlate negatively with the blood-oxygen-level-dependent (BOLD) signal in the primary visual cortex (V1). When alpha power surges, metabolic oxygen consumption in visual networks drops, confirming that high-amplitude alpha represents regional cortical deactivation rather than computational processing.
In cognitive neuroscience, research by Ole Jensen, Paul Sauseng, and colleagues on phase-amplitude coupling (PAC) revealed that high-frequency gamma waves (which underpin localized information processing and memory binding) are nested within the phase of slower alpha oscillations. This mechanistic coupling indicates that the phase of an alpha wave directly governs the timing of local neural firing, structuring the transmission of sensory information into precise temporal packets across downstream hierarchical brain networks.
12. Cultural & Cross-Cultural Considerations
While the biophysical architecture of thalamocortical networks is a universal biological feature of human neuroanatomy, the behavioral engagement and scientific study of alpha rhythms vary markedly across socio-cultural traditions, particularly concerning contemplative practices and clinical norms:
Cross-cultural electrophysiological research on contemplative traditions has revealed substantial differences in resting-state alpha dynamics. Research conducted on Tibetan Buddhist monks, Zen practitioners, and Indian yogic meditators has shown that decades of structured mental training induce distinct alpha modifications. Unlike non-meditating Western control cohorts who display rapid alpha desynchronization in response to startling acoustic stimuli, advanced Zen practitioners frequently demonstrate an unusual immunity to habituation or, alternatively, maintain robust alpha rhythms that do not suppress despite sharp auditory clicks. This phenomenon highlights how cross-cultural traditions of attentional cultivation alter basic neurophysiological sensory processing.
Furthermore, cross-cultural comparative studies in psychiatric populations require careful normative calibration. The quantitative normative EEG databases used to diagnose psychiatric abnormalities—often compiled using predominantly North American or Western European cohorts—must be culturally and environmentally contextualized. Differences in socioeconomic stress levels, dietary patterns, sleep hygiene, and baseline caffeine consumption can subtly influence alpha peak frequency and absolute power, demanding that baseline metrics be standardized across diverse demographic populations to prevent diagnostic misclassification.
13. Criticisms, Debates & Limitations
Despite a century of continuous empirical study, several theoretical and methodological controversies surround alpha oscillations:
The Idling vs. Active Inhibition Debate: While the active inhibition hypothesis currently enjoys substantial empirical consensus, debates persist regarding whether all alpha rhythms represent inhibitory gating. Some cognitive scientists argue that certain forms of alpha activity—particularly in prefrontal, memory-associated structures—might play an active role in long-range inter-areal communication and phase-dependent information transfer, rather than serving solely as a localized suppression mechanism.
Commercial Neurofeedback and the “Alpha Wellness” Myth: Commercial wellness industries, pseudoscientific self-help programs, and consumer-grade EEG headbands frequently oversimplify alpha dynamics. Marketing campaigns often claim that inducing an “alpha state” automatically leads to enhanced creativity, psychological bliss, and stress eradication. Academic neuroscientists criticize these claims, highlighting that alpha elevation is not universally beneficial; excessive, uncontrolled alpha synchronization in frontal regions can lead to cognitive disengagement, spatial neglect, impaired decision-making, and depressive symptoms.
Methodological Limitations of Scalp Recordings: Non-invasive scalp EEG suffers from severe volume conduction constraints. Macro-electrodes collect the summation of electrical signals that have diffused through biological tissue, making it notoriously difficult to disentangle true functional cortical connectivity from passive signal smearing. Furthermore, deep brain structures (such as the hippocampus, amygdala, and basal ganglia) generate oscillatory activity that cannot be easily detected by surface alpha montages, necessitating caution when interpreting whole-brain neural dynamics from scalp data alone.
14. Related Terms & Distinctions
To ensure precise scientific taxonomy, the alpha wave must be carefully demarcated from neighboring electrophysiological rhythms and cognitive concepts:
- Beta Wave (13–30 Hz): A faster, lower-amplitude rhythm characteristic of active, alert, focused mental engagement, motor execution, and analytical problem-solving. While alpha diminishes with sensory stimulation, beta power frequently rises.
- Theta Wave (4–8 Hz): A slower frequency band prominent during drowsiness, light sleep (Stage 1 NREM), deep meditation, and hippocampal memory encoding. Slowing of the alpha rhythm into the theta band during waking rest indicates cerebral pathology or extreme fatigue.
- Gamma Wave (>30 Hz): Very fast, low-amplitude oscillations associated with active cross-modal sensory binding, conscious perception, and localized neuronal computation. Gamma bursts are frequently phase-locked to underlying alpha waves.
- Mu Rhythm (8–13 Hz): A morphological and functional sub-type of alpha activity specific to the motor cortex. Although sharing the exact frequency profile of occipital alpha waves, the mu rhythm is modulated by motor planning and physical movement rather than visual processing or eye closure.
- Delta Wave (0.5–4 Hz): The slowest, highest-voltage rhythm, dominant during Stage 3 slow-wave sleep. Delta activity observed in waking adults reflects structural lesions, encephalopathy, or severe cortical injury.
15. Summary / Key Takeaways
The alpha wave represents the cornerstone of modern electrophysiology and cognitive neuroscience. Discovered by Hans Berger in 1929, this 8–12 Hz oscillating electrical rhythm originates from complex reciprocal loops between the thalamus and the cerebral cortex. Primarily recorded over the posterior scalp during relaxed wakefulness with closed eyes, alpha waves undergo instantaneous desynchronization upon visual fixation or cognitive engagement.
Modern neuroscientific paradigms have discarded the outdated view of the alpha wave as a passive “screen-saver” rhythm, instead establishing the Inhibition-Timing Hypothesis. Under this framework, synchronized alpha power operates as an active, top-down gatekeeper that selectively suppresses irrelevant brain areas to shield conscious attention from sensory distractions. Through applications spanning clinical diagnostics, neurofeedback, sleep medicine, and brain-computer interfaces, deciphering the mechanics of the alpha wave remains integral to unraveling how the human brain orchestrates attention, consciousness, and perceptual reality.
References
- Adrian, E. D., & Matthews, B. H. C. (1934). The Berger rhythm: Potential changes from the occipital lobes in man. Brain, 57(4), 355–385. https://doi.org/10.1093/brain/57.4.355
- Berger, H. (1929). Über das Elektrenkephalogramm des Menschen. Archiv für Psychiatrie und Nervenkrankheiten, 87(1), 527–570. https://doi.org/10.1007/BF01797193
- Jensen, O., & Mazaheri, A. (2010). Shaping functional architecture by oscillatory alpha activity: Gating by inhibition. Frontiers in Human Neuroscience, 4, 186. https://doi.org/10.3389/fnhum.2010.00186
- Klimesch, W. (2012). Alpha-band oscillations, attention, and controlled access to stored information. Trends in Cognitive Sciences, 16(12), 606–617. https://doi.org/10.1016/j.tics.2012.10.007
- Klimesch, W., Sauseng, P., & Hanslmayr, S. (2007). EEG alpha oscillations: The inhibition–timing hypothesis. Brain Research Reviews, 53(1), 63–88. https://doi.org/10.1016/j.brainresrev.2006.06.003