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Steady state visually evoked potential

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In neurology and neuroscience research, steady state visually evoked potentials (SSVEPs) are signals that are natural responses to visual stimulation at specific frequencies. When the retina is excited by a visual stimulus ranging from 3.5 Hz to 75 Hz,[1] the brain generates electrical activity at the same (or multiples of) frequency of the visual stimulus.

SSVEPs are typically measured using electroencephalography. SSVEPs are useful in research because of the excellent signal-to-noise ratio[2] and relative immunity to artifacts.[3] SSVEPs also provide a means to characterize preferred frequencies of neocortical dynamic processes. SSVEPs are generated by stationary localized sources and distributed sources that exhibit characteristics of wave phenomena.

SSVEPs have been widely used in vision, cognitive neuroscience (e.g., visual attention, binocular rivalry, working memory, alpha range), and clinical neuroscience (e.g., aging and neurodegenerative disorders, schizophrenia, epilepsy) research.[4][5][6] They are also used for brain-computer-interfaces.[7]

See also[edit]


  1. ^ Beverina F, Palmas G, Silvoni S, Piccione F, Giove S (2003). "User adaptive BCIs: SSVEP and P300 based interfaces". PsychNol. J. 1: 331–54.
  2. ^ D. Regan, Human Brain Electrophysiology: Evoked Potentials and Evoked Magnetic Fields in Science and Medicine, Elsevier, New York, NY, USA, 1989.
  3. ^ K. E. Misulis, Spehlmann's Evoked Potential Primer, Butterworth-Heinemann, Boston, Mass, USA, 1994.
  4. ^ Norcia, Anthony M.; Appelbaum, L. Gregory; Ales, Justin M.; Cottereau, Benoit R.; Rossion, Bruno (2015-05-05). "The steady-state visual evoked potential in vision research: A review". Journal of Vision. 15 (6): 4. doi:10.1167/15.6.4. ISSN 1534-7362. PMC 4581566. PMID 26024451.
  5. ^ Kritzman, Lior; Eidelman-Rothman, Moran; Keil, Andreas; Freche, Dominik; Sheppes, Gal; Levit-Binnun, Nava (2022-03-23). "Steady-state visual evoked potentials differentiate between internally and externally directed attention". NeuroImage. 254: 119133. doi:10.1016/j.neuroimage.2022.119133. PMID 35339684.
  6. ^ Vialatte, François-Benoît; Maurice, Monique; Dauwels, Justin; Cichocki, Andrzej (2010). "Steady-state visually evoked potentials: Focus on essential paradigms and future perspectives". Progress in Neurobiology. 90 (4): 418–438. doi:10.1016/j.pneurobio.2009.11.005. PMID 19963032. S2CID 2233024.
  7. ^ Yijun Wang; Xiaorong Gao; Bo Hong; Chuan Jia; Shangkai Gao (2008). "Brain-Computer Interfaces Based on Visual Evoked Potentials". IEEE Engineering in Medicine and Biology Magazine. 27 (5): 64–71. doi:10.1109/MEMB.2008.923958. ISSN 0739-5175. PMID 18799392. S2CID 18467802.