Understanding visual snow syndrome
: a clinical characterization and functional imaging approach

Student thesis: Doctoral ThesisDoctor of Philosophy


Visual snow is a neurological condition that was first described and defined clinically a little over five years ago. The main clinical feature is an unremitting, positive visual phenomenon present in the entire visual field and characterized by uncountable tiny flickering dots. The pathophysiology of this disorder is largely unknown, making treatment of affected patients extremely challenging.

The aim of this PhD was to understand more about the biology of visual snow, first through its clinical characterization and then with the use of neuroimaging. The first objective has been addressed with a large web-based survey that involved visual snow subjects (n = 1104), who were defined according to the recently proposed diagnostic criteria. This study (chapter 2) allowed recognition of the common clinical presentation of the syndrome and of its principal comorbidities, as well as prediction of its severity.

The second aim was carried out with a multimodal structural and functional magnetic resonance imaging study, comparing twenty-four visual snow patients with an equal number of healthy volunteers (chapter 3).
Voxel based-morphometry (chapter 4) was used to study structural changes in the brain; arterial spin labelling (chapter 5) to analyse regional cerebral blood flow; functional connectivity (chapter 6) and task-based functional magnetic resonance imaging (chapter 0) to study localised brain responses at rest and in response to a ‘visual snow-like’ stimulus; finally magnetic resonance spectroscopy (chapter 0) was employed to study neurochemical properties of the brain.
The imaging data show that visual snow is characterized by subtle morphological, as well as widespread functional, changes that involve important brain networks regulating attention, salience, sensory processing and cognition.
Date of Award1 Sept 2020
Original languageEnglish
Awarding Institution
  • King's College London
SupervisorPeter Goadsby (Supervisor), Steven Williams (Supervisor) & Dominic Ffytche (Supervisor)

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