Alpha Rhythms

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Ensembles of synchronously active cortical neurons generate electromagnetic field potentials that can be measured by electroencephalography (EEG) or magnetoencephalog-raphy (MEG). The alpha frequency band is defined to be between 8 and 13 Hz (Berger, 1929; Adrian & Mathews, 1934). The classical alpha rhythm is prominent at electrodes overlying the occipital (visual) cortex and to a lesser extent over the posterior temporal and parietal areas. Alpha rhythm occurs in a condition of relaxed wakefulness with eyes closed, and it is depressed upon eye opening. The alpha rhythm disappears gradually during drowsiness, and different types of alpha activity appear in rapid eye movement (REM) sleep (Cantero, Atienza, & Salas, 2002).

Blind children do not develop the alpha rhythm. The alpha frequency matures and reaches the approximate average values of 8 Hz at age 3, 9 Hz at age 9, and 10 Hz at age 15. The interindividual variability is quite large. About 6— 10% of healthy subjects have "low-voltage alpha activity," below 20 mV. In general, alpha amplitude is higher in children than in adults. Consistent amplitude asymmetries exceeding 2:1 are usually considered to be abnormal. Alpha variant rhythms with frequency of half or double the normal frequency may occur in some healthy subjects (Markand, 1990).

Alpha rhythm peak frequency correlates with cerebral blood flow and metabolism (Sulg, 1984), and low frequency is found in metabolic, infectious, and degenerative disorders, such as dementia of the Alzheimer type. Unilateral slowing or loss of alpha rhythm occurs in the presence of traumatic, neoplastic, infectious, or vascular lesions of one occipital lobe. Abnormal "alpha coma pattern" occurs in some comatose patients. The outcome is variable, depending on the underlying condition, but it is most often poor.

Other physiological rhythms within the alpha frequency band are the mu rhythm (9-11 Hz) recorded over the sensorimotor cortex (Niedermeyer, 1999) and the tau rhythm (Hari, 1999). Mu may be the only routinely recorded alphaband rhythm in EEG of infants and small children. In order to see the proper alpha rhythm, passive eye closure or recording in darkness should by attempted.

Subdural and intracortical recordings, as well as source localization studies, have shown that the alpha rhythm has multiple generators within the cerebral cortex (Williamson, Kaufmann, Lu, Wang, & Karron, 1997). Although early studies suggested that the alpha rhythm was driven by feedback inhibition of thalamic relé cells (Andersen & Anders-son, 1968), more recent studies suggest that both cortico-cortical and thalamo-cortical connections are of importance. It has been suggested that both intrinsic membrane ion channel properties and local neuron network properties determine rhythmic behavior (Lopes da Silva, 1991).

The coherence-function has become a popular tool because it reveals information about functional connectivity between different parts of the brain during various tasks and states (Gevins, Leong, Smith, Le, & Du, 1995). Volume conduction and the EEG-reference montage must be considered during interpretation. Event-related desynchro-nization (ERD) of central and occipital alpha rhythms represent activation of those cortical areas that are active in vision, motor preparation or selective attention (Pfurts-cheller, Stancák, & Neuper, 1996). Event-related alpha-oscillations in visual and auditory cortex following visual and auditory stimuli respectively have been described (Basar, Basar-Eroglu, Karakas, & Schürmann, 1999).

Conflicting results have been published regarding the possible relationship between alpha frequency and cognitive performance (Markand, 1990; Klimesch, 1999). A recent study found no correlation between alpha peak frequency and intelligence dimensions (Posthuma, Neale, Boomsma, & de Geus, 2001). Some evidence suggest that slow (8-10 Hz) and fast (11-12 Hz) alphas reflect functionally different processes (Verstraeten & Cluydts, 2002). Biofeedback treatment aimed at alpha enhancement may relieve anxiety (Moore, 2000). The existence of a relationship between depression and frontal alpha asymmetry has been challenged recently (Debener et al., 2000).

Considerable progress has been made toward a better understanding of the basic mechanisms behind alpha rhythms and brain function during recent years. Some data regarding alpha coherence seem to challenge the concept that cognitive events only are associated with gamma (30100 Hz) activity (Nunez, Wingeier, & Silberstein, 2001). High-resolution EEG and MEG recording combined with mathematical methods and individual magnetic resonance brain imaging are exciting tools for future brain function research.

REFERENCES

Andersen, P., & Andersson, S. (1968). Physiological basis of the alpha rhythm. New York: Appleton-Century-Croft. Adrian, E. D., & Mathews, B. H. C. The Berger rhythm: Potential changes from the occipital lobes in man. Brain, 57, 354-385. Basar, E., Basar-Eroglu, C., Karakas, S., & Schurmann, M. (1999). Are cognitive processes manifested in event-related gamma, alpha, theta and delta oscillations in the EEG? Neuroscience Letters, 259, 165-168. Berger, H. (1929). Uber das elektroenkephalogramm des Menschen. Archives of Psychiatry Nervenkr, 87, 527-570. Cantero, J. L., Atienza, M., & Salas, R. M. (2002). Spectral features of EEG alpha activity in human REM sleep: Two variants with different functional roles? Sleep, 23, 746-750. Debener, S., Beauducel, A., Nessler, D., Brocke, B., Heilemann, H., & Kayser, J. (2000). Is resting anterior EEG alpha asymmetry a trait marker for depression? Findings for healthy adults and clinically depressed patients. Neuropsychobiology, 41, 31-37. Gevins, A., Leong, H., Smith, M. E., Le, J., & Du, R. (1995). Mapping cognitive brain function with modern high-resolution electroencephalography. Trends in Neurosciences, 18, 429-436. Hari, R. (1999). Magnetoencephalography as a tool of clinical neurophysiology. In E. Niedermeyer & F. H. da Silva (Eds.), Electroencephalography: Basic principles, clinical applications and related fields (4th ed., pp. 1107-1134). Baltimore: Williams & Wilkins.

Klimesch, W. (1999). EEG alpha and theta oscillations reflect cognitive and memory performance: A review and analysis. Brain Research Reviews, 169-195. Lopes da Silva, F. (1991). Neural mechanisms underlying brain waves: From neural membranes to networks. Electroen-cephalography and Clinical Neurophysiology, 7, 81-93. Markand, O. N. (1990). Alpha rhythms. Journal of Clinical Neuro-

physiology, 7, 163-189. Moore, N. C. (2000). A review of EEG biofeedback treatment of anxiety disorders. Clinical Electroencephalography, 31, 1-6. Niedermeyer, E. (1999). The normal EEG in the waking adult. In E. Niedermeyer & F. H. da Silva (Eds.), Electroencephalogra-phy: Basic principles, clinical applications and related fields (4th ed., pp. 149-173). Baltimore: Williams & Wilkins. Nunez, P. L., Wingeier, B. M., & Silberstein, R. B. (2001). Spatial-temporal structures of human alpha rhythms: Theory, micro-current sources, multiscale measurements, and lobal binding of local networks. Human Brain Mapping, 13, 125-164. Pfurtscheller, G., Stancak, Jr., A., & Neuper, C. H. (1996). Event-related synchronization (ERS) in the alpha band—An electrophysiological correlate of cortical idling: Areview. International Journal of Psychophysiology, 24, 39-46.

Posthuma, D., Neale, M. C., Boomsma, D. I., & de Geus, E. J. C. (2001). Are smarter brains running faster? Heritability of alpha peak frequency, IQ, and their interrelation. Behaviour Genetics, 31, 567-579.

Sulg, I. (1984). Quantitative EEG as a measure of brain dysfunction. In G. Pfurtscheller, E. H. Jonkman, & F. H. Lopes da Silva (Eds.), Progress in neurobiology: Vol. 62. Brain ischemia: Quantitative EEG and imaging techniques (pp. 65-84). Amsterdam: Elsevier.

Verstraeten, E., & Cluydts, R. (2002). Attentional switching-related human EEG alpha oscillations. Neuroreport, 13, 681684.

Williamson, S. J., Kaufmann, L., Lu, Z. L., Wang, J. Z., & Karron, D. (1997). Study of human occipital alpha rhythm: The alphon hypothesis and alpha suppression. International Journal of Psychophysiology, 26, 63-76.

Trond Sand

Trondheim University Hospital, Norway

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