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Postoperative facial nerve (FN) dysfunction is associated with a significant impact on the quality of life of patients and can result in psychological stress and disorders such as depression and social isolation. Preoperative prediction of FN outcomes can play a critical role in vestibular schwannomas (VSs) patient care. Several studies have developed machine learning (ML)-based models in predicting FN outcomes following resection of VS.

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Background/objectives: The auditory middle-latency responses (AMLRs) assess central sensory processing beyond the brainstem and serve as a measure of sensory gating. They have clinical relevance in the diagnosis of neurological conditions. In this study, magnitude and habituation of the AMLRs were tested for sensitivity and specificity in classifying dizzy patients with vestibular migraine (VM) and post-concussive syndrome.

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Background: Trigeminal neuralgia is a disease characterized by severe facial pain that significantly reduces patients quality of life. Trigeminal neuralgia is subcategorized as idiopathic, classic or secondary. Magnetic resonance imaging is the basis for classification, but neurophysiological tests are also used.

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Introduction: Vestibular migraine (VM), particularly its chronic variant, poses a diagnostic challenge. Patients suffering from VM may not have the characteristic headaches associated with the dizziness. In these cases, a marker for migraine pathology in general could help appropriately diagnose certain types of dizziness as migrainous despite these patients not meeting current diagnostic criteria for VM.

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Integrating vestibular and visual cues for verticality perception.

Exp Brain Res

January 2025

School of Psychological Sciences, Birkbeck University of London, Malet St, London, WC1E 7HX, UK.

Verticality is the perception of what's upright relative to gravity. The vestibular system provides information about the head's orientation relative to gravity, while visual cues influence the perception of external objects' alignment with the vertical. According to Bayesian integration, the perception of verticality depends on the relative reliability of visual and vestibular cues.

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