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Changes in face and face pareidolia processing in patients with migraine: An ERP study.

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Migraine is a multifactorial brain disorder characterized by recurrent disabling headache attacks. One of the possible mechanisms in the pathogenesis of migraine may be a decrease in inhibitory cortical stimuli… Click to show full abstract

Migraine is a multifactorial brain disorder characterized by recurrent disabling headache attacks. One of the possible mechanisms in the pathogenesis of migraine may be a decrease in inhibitory cortical stimuli in the primary visual cortex due to cortical hyperexcitability. The aim of this study was to investigate the neural correlates underlying face and face pareidolia processing in terms of the event-related potential (ERP) components, N170, VPP, and N250 in migraine patients. In total, 40 patients with migraine without aura, 23 patients with migraine and aura, and 30 healthy controls were enrolled. We recorded event-related potentials (ERPs) during the presentation of the face and face pareidolia images. N170, vertex positive potential (VPP), and N250 mean amplitudes and latencies were examined. N170 was significantly greater in migraine with aura patients than in healthy controls. VPP amplitude was significantly greater in migraine without aura patients than in healthy controls. The face stimuli evoked significantly earlier VPP responses to faces (168.7 ms, SE = 1.46) than pareidolias (173.4 ms, SE = 1.41) in migraine with aura patients. We did not find a significant difference between N250 amplitude for face and face pareidolia processing. A significant difference was observed between the groups for pareidolia in terms of N170 (F(2,86) = 14,75, P < 0.001) and VPP (F(2,86) = 16.43, P < 0.001]) amplitudes. Early ERPs are a valuable tool to study the neural processing of face processing in migraine patients to demonstrate visual cortical hyperexcitability.

Keywords: patients migraine; face pareidolia; face face; pareidolia processing; face

Journal Title: Journal of neurophysiology
Year Published: 2020

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