Unsolved:Alpha wave

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Short description: Neural oscillations in the frequency range of 8–12 Hz

For the helium nucleus, see Physics:Alpha particle.
Alpha waves

Alpha waves, or the alpha rhythm, are neural oscillations in the frequency range of 8–12 Hz[1][2] likely originating from the synchronous and coherent (in phase or constructive) neocortical neuronal electrical activity possibly involving thalamic pacemaker cells. Historically, they are also called "Berger's waves" after Hans Berger, who first described them when he invented the EEG in 1924.[3]

Alpha waves are one type of brain waves detected by electrophysiological methods, e.g., electroencephalography (EEG) or magnetoencephalography (MEG), and can be quantified using power spectra and time-frequency representations of power[4] like quantitative electroencephalography (qEEG). They are predominantly recorded over parieto-occipital brain and were the earliest brain rhythm recorded in humans.[5] Alpha waves can be observed during relaxed wakefulness, especially when there is no mental activity. During the eyes-closed condition, alpha waves are prominent at parietal locations. Attentional processing or cognitive tasks attenuate (reduce) the alpha waves.[6]

Historically, alpha waves were thought to represent the brain in an idle state as they are strongest during rest and quiet wakefulness.[citation needed] More recently it was found the alpha oscillations increase in demanding task not requiring visual input. In particular, alpha oscillations increase during maintenance (retention) of visually presented information.[7][8] These findings resulted in the notion that alpha oscillations inhibit areas of the cortex not in use,[9] and they play an active role in network coordination and communication.[10] Whether they are inhibitory or play an active role in attention may link to their direction of propagation. Possibly top-down propagating waves are inhibitory whereas forward propagating waves reflect visual bottom-up attentional processes,[11] but this is still an area of active research.

Research

Origins

Human alpha rhythm has strong generators[clarification needed] in parieto-occipital areas[12][13] which can be coherent with sources in the pulvinar and lateral geniculate nucleus.[14] They are generated in other neocortical areas as well. Oscillations in the alpha band called a mu wave can be found over the primary motor cortex.[15] At multi-electrode study performed in non-human primates reported alpha oscillations widespread across neocortex.[16]

One study reported that cortical alpha leads pulvinar (thalamic) alpha, challenging prevailing theories of a thalamic pacemaker. Based on intracranial recordings in epileptic patients it was reported that alpha acts within the nervous system by propagating from cortex to thalamus.[17] It remains to be determined if these findings generalize to healthy participants.

The experimental and computational models explored by Traub RD et al. suggested cortical- a lamina- and principal neuron subtype specific origin for the visual alpha rhythm.[18]

Development

On the basis of examination of patients with congenital visual defects, it was established that the existence of an efficient and complete visual pathway is necessary for the development of normal EEG activity pattern.[19] This wave begins appearing at around four months, and is initially a frequency of 4 waves per second. The mature alpha wave, at 10 waves per second, is firmly established by age 3. Other research finds an increase in alpha frequency from about 9 Hz at the age of five to about 12 Hz in 21 year olds. This shift has been linked to changes in the optic radiation and correlates with improvement in visual perception.[13] Alpha waves can slow after neural compromise such that which occurs in hepatic encephalopathy.[20]

Sleep and possible types

Some researchers[who?] posit that there are at least two forms of alpha waves, which may have different functions in the wake-sleep cycle.

Alpha waves are present at different stages of the wake-sleep cycle.[21] The most widely researched is during the relaxed mental state, where the subject is at rest with eyes closed, but is not tired or asleep. This alpha activity is centered in the occipital lobe,[22][23] although there has been speculation that it has a thalamic origin.[24]


It has long been believed that alpha waves indicate a wakeful period during sleep. This has been attributed to studies where subjects report non-refreshing sleep and have EEG records reporting high levels of alpha intrusion into sleep. This occurrence is known as alpha wave intrusion.[25] However, it is possible that these explanations may be misleading, as they only focus on alpha waves being generated from the occipital lobe.[citation needed]

Meditation

Mindfulness meditation has been shown to increase alpha wave power in both healthy subjects and patients.[26] Practitioners of Transcendental Meditation have demonstrated a one-Hertz reduction in alpha wave frequency relative to controls.[27]

Alpha wave intrusion

Alpha wave intrusion occurs when the alpha waves appear with non-REM sleep when delta activity is expected. It is hypothesized to be associated with fibromyalgia with increased phasic alpha sleep activity correlated with clinical manifestations of fibromyalgia, such as longer pain duration.[28]

Despite this, alpha wave intrusion has not been significantly linked to any major sleep disorder, including chronic fatigue syndrome, and major depression. However, it is common in chronic fatigued patients, and may amplify the effects of other sleep disorders.[29]

Mistake prediction

Following this lapse-of-attention line of thought, a recent study indicates that alpha waves may be used to predict mistakes. In it, MEGs measured increases of up to 25% in alpha brain wave activity before mistakes occurred. This study used common sense: alpha waves indicate idleness, and mistakes are often made when a person is doing something automatically, or "on auto-pilot", and not paying attention to the task they are performing. After the mistake was noticed by the subject, there was a decrease in alpha waves as the subject began paying more attention. This study hopes to promote the use of wireless EEG technology on employees in high-risk fields, such as air traffic controlling, to monitor alpha wave activity and gauge the attention level of the employee.[30]

Processing of visual information in memory

A study has shown that the appearance of an alpha rhythm with open eyes can be a predictor of visual information processing in working memory.[31] It was shown that the moment of appearance of alpha activity depends on the type of stimulus in memory and the number of visual characteristics (color, shape, etc.) that it needs to keep in memory. The authors suggest that the appearance of the alpha rhythm with open eyes may indicate a temporary shutdown of visual information processing in the primary visual cortex at the moments when the subject analyzes the image in visual memory. At these moments, information is processed in the association areas of the visual cortex (hV4, V3v, VO1, VO2 areas).[32]

Visual learning

One study suggests that a "visual flicker paradigm to entrain individuals at their own brain rhythm (i.e. peak alpha frequency)" can result in substantially faster perceptual visual learning, maintained the day following training.

In particular, the entrainment substantially accelerated learning in a discrimination task to detect targets embedded in background clutter or to identify radial vs. concentric Glass patterns embedded in noise compared to entrainment that does not match an individual's alpha frequency.[33][additional citation(s) needed]

History

The sample of human EEG with prominent alpha-rhythm in occipital sites
The sample of human EEG with prominent alpha-rhythm in occipital sites

Berger took a cue from Ukrainian physiologist Vladimir Pravdich-Neminsky, who used a string galvanometer to create a photograph of the electrical activity of a dog's brain. Using similar techniques, Berger confirmed the existence of electrical activity in the human brain. He first did this by presenting a stimulus to hospital patients with skull damage and measuring the electrical activity in their brains. Later he ceased the stimulus method and began measuring the natural rhythmic electrical cycles in the brain. The first natural rhythm he documented was what would become known as the alpha wave. Berger was very thorough and meticulous in his data-gathering, but despite his brilliance, he did not feel confident enough to publish his discoveries until at least five years after he had made them. In 1929, he published his first findings on alpha waves in the journal Archiv für Psychiatrie. He was originally met with derision for his EEG technique and his subsequent alpha and beta wave discoveries. His technique and findings did not gain widespread acceptance in the psychological community until 1937, when he gained the approval of the famous physiologist Lord Adrian, who took a particular interest in alpha waves.[34]


Alpha wave biofeedback has gained interest for having some successes in humans for seizure suppression and for treatment of depression.[35]

Alpha waves again gained interest in regards to an engineering approach to the science fiction challenge of psychokinesis, i.e. control of movement of a physical object using energy emanating from a human brain. In 1988, EEG alpha rhythm was used in a brain–computer interface experiment of control of a movement of a physical object, a robot.[36][37] It was the first experiment to demonstrate control of a physical object, a robot, using EEG.[38][39]

See also

Brain waves

References

  1. ↑ Shaw, John C.; Shaw, John Crosley (2003). The brain's alpha rhythms and the mind : a review of classical and modern studies of the alpha rhythm component of the electroencephalogram with commentaries on associated neuroscience and neuropsychology. Amsterdam Heidelberg: Elsevier. ISBN 978-0-444-51397-7. 
  2. ↑ Schomer, Donald L., ed (2011). Niedermeyer's electroencephalography: basic principles, clinical applications, and related fields (6th ed.). Philadelphia, Pa. London: Wolters Kluwer, Lippincott Williams & Wilkins. ISBN 978-0-7817-8942-4. 
  3. ↑ "The inventor of electroencephalography (EEG): Hans Berger (1873-1941)". Child's Nervous System 37 (9): 2723–2724. September 2021. doi:10.1007/s00381-020-04564-z. PMID 32140776. 
  4. ↑ Percival, Donald B.; Walden, Andrew T. (2002). Spectral analysis for physical applications: multitaper and conventional univariate techniques (Digital printing ed.). Cambridge: Cambridge Univ. Pr. ISBN 978-0-521-43541-3. 
  5. ↑ "Über das Elektrenkephalogramm des Menschen" (in de). Archiv für Psychiatrie und Nervenkrankheiten 87 (1): 527–570. 1929-12-01. doi:10.1007/BF01797193. ISSN 1433-8491. https://doi.org/10.1007/BF01797193. 
  6. ↑ Amin, Hafeez Ullah; Malik, Aamir Saeed (2017). "1.2.3 Alpha Waves (8-13Hz)" (in EN). Designing EEG Experiments for Studying the Brain. Elsevier (published 2017-05-25). pp. 3–4. ISBN 9780128111413. https://www.brainmaster.com/tfc/index_files/Publications/2017%20Malik%20-Designing-EEG-Experiments-for-Studying-the-Brain.pdf?srsltid=AfmBOorBWDVPKUgZn7Zv4L3FF2o5fWgdkBdTJnZwqd52q80hOAjTo-b7. Retrieved 2025-01-09. "Alpha waves can be observed spontaneously in normal adults during wakefulness and in relaxed state, especially when there is no mental activity. During the eyes-closed condition, alpha waves are prominent at parietal locations. Attentional processing or cognitive tasks attenuate the alpha waves. Alpha waves are subdivided into lower alpha and upper alpha. It has been observed that alpha activity changes with load during retention of working memory. In addition, individual alpha peak frequency is an indicator of general intelligence factor (also known as g factor)." 
  7. ↑ Klimesch, W.; Doppelmayr, M.; Schwaiger, J.; Auinger, P.; Winkler, Th. (March 1999). "'Paradoxical' alpha synchronization in a memory task" (in en). Cognitive Brain Research 7 (4): 493–501. doi:10.1016/S0926-6410(98)00056-1. https://linkinghub.elsevier.com/retrieve/pii/S0926641098000561. 
  8. ↑ Jensen, O. (2002-08-01). "Oscillations in the Alpha Band (9-12 Hz) Increase with Memory Load during Retention in a Short-term Memory Task". Cerebral Cortex 12 (8): 877–882. doi:10.1093/cercor/12.8.877. https://academic.oup.com/cercor/article-lookup/doi/10.1093/cercor/12.8.877. 
  9. ↑ "Shaping functional architecture by oscillatory alpha activity: gating by inhibition". Frontiers in Human Neuroscience 4 (186): 186. 2010. doi:10.3389/fnhum.2010.00186. PMID 21119777. 
  10. ↑ "New vistas for alpha-frequency band oscillations". Trends in Neurosciences 30 (4): 150–158. April 2007. doi:10.1016/j.tins.2007.02.001. PMID 17307258. 
  11. ↑ "Distinct roles of forward and backward alpha-band waves in spatial visual attention". eLife 12. March 2023. doi:10.7554/elife.85035. PMID 36876909. 
  12. ↑ Salmelin, R.; Hari, R. (October 1994). "Characterization of spontaneous MEG rhythms in healthy adults" (in en). Electroencephalography and Clinical Neurophysiology 91 (4): 237–248. doi:10.1016/0013-4694(94)90187-2. PMID 7523073. https://linkinghub.elsevier.com/retrieve/pii/0013469494901872. 
  13. ↑ 13.0 13.1 Caffarra, Sendy; Kanopka, Klint; Kruper, John; Richie-Halford, Adam; Roy, Ethan; Rokem, Ariel; Yeatman, Jason D. (2023). "Development of the Alpha Rhythm Is Linked to Visual White Matter Pathways and Visual Detection Performance". The Journal of Neuroscience 44 (6): e0684232023. doi:10.1523/jneurosci.0684-23.2023. ISSN 0270-6474. PMID 38124006. 
  14. ↑ Lopes da Silva, F.H; Vos, J.E; Mooibroek, J; van Rotterdam, A (December 1980). "Relative contributions of intracortical and thalamo-cortical processes in the generation of alpha rhythms, revealed by partial coherence analysis" (in en). Electroencephalography and Clinical Neurophysiology 50 (5–6): 449–456. doi:10.1016/0013-4694(80)90011-5. PMID 6160987. https://linkinghub.elsevier.com/retrieve/pii/0013469480900115. 
  15. ↑ Pfurtscheller, G; Neuper, Ch; Andrew, C; Edlinger, G (June 1997). "Foot and hand area mu rhythms" (in en). International Journal of Psychophysiology 26 (1–3): 121–135. doi:10.1016/S0167-8760(97)00760-5. PMID 9202999. https://linkinghub.elsevier.com/retrieve/pii/S0167876097007605. 
  16. ↑ Hoffman, Steven J.; Dotson, Nicholas M.; Lima, Vinicius; Gray, Charles M. (2024-06-06). "The Primate Cortical LFP Exhibits Multiple Spectral and Temporal Gradients and Widespread Task-Dependence During Visual Short-Term Memory" (in en). Journal of Neurophysiology. doi:10.1152/jn.00264.2023. ISSN 0022-3077. PMID 38842507. 
  17. ↑ "The generation and propagation of the human alpha rhythm". Proceedings of the National Academy of Sciences of the United States of America 116 (47): 23772–23782. November 2019. doi:10.1073/pnas.1913092116. PMID 31685634. Bibcode: 2019PNAS..11623772H. 
  18. ↑ "Layer 4 pyramidal neuron dendritic bursting underlies a post-stimulus visual cortical alpha rhythm". Communications Biology 3 (1): 230. May 2020. doi:10.1038/s42003-020-0947-8. PMID 32393746. 
  19. ↑ "Origin of the alpha rhythm based on computer analysis of EEG activity in patients with congenital visual defects.". The Computer-aided Scientific Research. (Wrocław Scientific Society): 313–318. 2007. doi:10.5281/ZENODO.10624700. ISBN 978-83-7374-050-1. https://zenodo.org/doi/10.5281/zenodo.10624700. 
  20. ↑ Baumgarten, Thomas J.; Neugebauer, Julia; Oeltzschner, Georg; Füllenbach, Nur-Deniz; Kircheis, Gerald; Häussinger, Dieter; Lange, Joachim; Wittsack, Hans-Jörg et al. (2018). "Connecting occipital alpha band peak frequency, visual temporal resolution, and occipital GABA levels in healthy participants and hepatic encephalopathy patients" (in en). NeuroImage: Clinical 20: 347–356. doi:10.1016/j.nicl.2018.08.013. PMID 30109194. 
  21. ↑ "Cortical source localization of sleep-stage specific oscillatory activity". Scientific Reports 10 (1): 6976. April 2020. doi:10.1038/s41598-020-63933-5. PMID 32332806. Bibcode: 2020NatSR..10.6976B. 
  22. ↑ "Alpha Synchrony and the Neurofeedback Control of Spatial Attention". Neuron 105 (3): 577–587.e5. February 2020. doi:10.1016/j.neuron.2019.11.001. PMID 31812515. 
  23. ↑ "Decoding Object-Based Auditory Attention from Source-Reconstructed MEG Alpha Oscillations". The Journal of Neuroscience 41 (41): 8603–8617. October 2021. doi:10.1523/JNEUROSCI.0583-21.2021. PMID 34429378. 
  24. ↑ "Tobacco smoking produces widespread dominant brain wave alpha frequency increases". International Journal of Psychophysiology 74 (3): 192–198. December 2009. doi:10.1016/j.ijpsycho.2009.08.011. PMID 19765621. 
  25. ↑ "ASDA report on EEG arousals: scoring rules and examples". Sleep 15 (2): 173–184. 1992. doi:10.1093/sleep/15.2.173. 
  26. ↑ "A systematic review of the neurophysiology of mindfulness on EEG oscillations". Neuroscience and Biobehavioral Reviews 57: 401–410. October 2015. doi:10.1016/j.neubiorev.2015.09.018. PMID 26441373. http://roar.uel.ac.uk/4509/1/A%20systematic%20review%20of%20the%20neurophysiology%20of.pdf. 
  27. ↑ "Meditation states and traits: EEG, ERP, and neuroimaging studies". Psychological Bulletin 132 (2): 180–211. March 2006. doi:10.1037/0033-2909.132.2.180. PMID 16536641. 
  28. ↑ "Alpha sleep characteristics in fibromyalgia". Arthritis and Rheumatism 44 (1): 222–230. January 2001. doi:10.1002/1529-0131(200101)44:1<222::AID-ANR29>3.0.CO;2-K. PMID 11212164. 
  29. ↑ "Alpha-delta sleep in patients with a chief complaint of chronic fatigue". Southern Medical Journal 87 (4): 465–470. April 1994. doi:10.1097/00007611-199404000-00008. PMID 8153772. 
  30. ↑ "Brain Wave Patterns Can Predict Blunders, New Study Finds". UC Davis News and Information. University of California, Davis campus. 23 March 2009. http://www.news.ucdavis.edu/search/news_detail.lasso?id=9031. 
  31. ↑ Kozlovskiy, Stanislav; Rogachev, Anton (December 2021). "Appearance of alpha rhythm as a predictor of visual information processing in working memory". Perception (Sage) 50 (1): 50. doi:10.1177/03010066211059887. PMID 34989647. https://journals.sagepub.com/doi/10.1177/03010066211059887. 
  32. ↑ "How Areas of Ventral Visual Stream Interact when We Memorize Color and Shape Information". Advances in Cognitive Research, Artificial Intelligence and Neuroinformatics. Advances in Intelligent Systems and Computing. 1358. Springer. 2021. pp. 95–100. doi:10.1007/978-3-030-71637-0_10. ISBN 978-3-030-71636-3. 
  33. ↑ "Learning at your brain's rhythm: individualized entrainment boosts learning for perceptual decisions". Cerebral Cortex 33 (9): 5382–5394. April 2023. doi:10.1093/cercor/bhac426. PMID 36352510. 
  34. ↑ "Hans Berger (1873-1941)". Journal of Neurology 249 (8): 1130–1131. August 2002. doi:10.1007/s00415-002-0872-4. PMID 12420722. 
  35. ↑ "Train Your Brain-Mental exercises with neurofeedback may ease symptoms of attention-deficit disorder, epilepsy and depression--and even boost cognition in healthy brains.". Scientific American. 2006. https://www.scientificamerican.com/article/train-your-brain-2007-06. 
  36. ↑ "Using EEG alpha rhythm to control a mobile robot". Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society. New Orleans: IEEE. 1988. pp. 1515–1516. doi:10.1109/IEMBS.1988.95357. ISBN 0-7803-0785-2. 
  37. ↑ "Mobile robot trajectory control: From fixed rails to direct bioelectric control". Proc. IEEE Workshop on Intelligent Motion Control. Istanbul. 1990. pp. 63–67. doi:10.1109/IMC.1990.687362. 
  38. ↑ "Augmentation of sensorimotor functions with neural prostheses.". Opera Medica and Physiologica 2 (3): 211–227. 2016. https://operamedphys.org/sites/default/files/pdf/OMP_2016_03_0035.pdf. 
  39. ↑ "Brain-Machine Interfaces: From Basic Science to Neuroprostheses and Neurorehabilitation". Physiological Reviews 97 (2): 767–837. April 2017. doi:10.1152/physrev.00027.2016. PMID 28275048. 

Further reading

de:Elektroenzephalografie#Alpha-Wellen



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