Resting-State Alpha-Band Oscillations in Migraine
Author(s) -
Louise O’Hare,
Federica Menchinelli,
Simon Durrant
Publication year - 2018
Publication title -
perception
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.619
H-Index - 91
eISSN - 1468-4233
pISSN - 0301-0066
DOI - 10.1177/0301006618755639
Subject(s) - migraine , resting state fmri , stimulus (psychology) , psychology , alpha (finance) , perception , noise (video) , audiology , neuroscience , communication , developmental psychology , cognitive psychology , medicine , artificial intelligence , computer science , construct validity , psychiatry , image (mathematics) , psychometrics
Migraine groups show differences in motion perception compared with controls, when tested in between migraine attacks (interictally). This is thought to be due to an increased susceptibility to stimulus degradation (multiplicative internal noise). Fluctuations in alpha-band oscillations are thought to regulate visual perception, and so differences could provide a mechanism for the increased multiplicative noise seen in migraine. The aim of this article was to characterise resting-state alpha-band oscillations (between 8 and 12 Hz) in the visual areas of the brain in migraine and control groups. Alpha-band activity in the resting state (with eyes closed) was recorded before and after a visual psychophysics task to estimate equivalent noise, specifically a contrast detection task. The lower alpha-band (8 to 10 Hz) resting-state alpha-band power was increased in the migraine compared with the control group, which may provide a mechanism for increased multiplicative noise. In agreement with previous research, there were no differences found in the additive (baseline) internal noise, estimated using an equivalent noise task in the same observers. As fluctuations in alpha-band oscillations control the timing of perceptual processing, increased lower alpha-band (8 to 10 Hz) power could explain the behavioural differences in migraine compared with control groups, particularly on tasks relying on temporal integration.
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