Visual snow syndrome is a persistent visual disturbance characterized by rapid flickering dots in the entire visual field. Hypothesized to arise from reduced inhibition of sensory cortex, visual snow has recently been linked to potentiation (enhancement) of the P100, an event-related potential (ERP) component associated with early visual processing. Here, we investigate whether this potentiation in visual snow is specific to visual responses, by comparing ERPs linked to early, bottom-up perceptual versus late, top-down cognitive processes. Specifically, we examined two components, the N170 and P300, associated respectively with rapid face categorization and attentional orienting towards targets. We predicted that if visual snow predominantly reflects diminished inhibition of perceptual areas, there should be stronger potentiation for the earlier perceptual N170 component. ERPs associated with the N170 (Face > House) and P300 (Target > Nontarget) were recorded in a 22 year-old male with a 2-year history of visual snow symptoms and a set of age- and gender-matched controls. Although N170 and P300 responses in all participants showed appropriate face- and target-selectivity, respectively, the visual snow patient demonstrated consistent potentiation relative to controls, particularly for the early N170 response. Bootstrapped estimates of mean amplitude computed within participants similarly revealed larger and more variable ERP amplitudes in the visual snow patient, especially for the N170 component. These results support an early perceptual locus of ERP potentiation in visual snow, further supporting the idea that this condition arises from diminished inhibition of sensory cortices.
| Identifer | oai:union.ndltd.org:CLAREMONT/oai:scholarship.claremont.edu:cmc_theses-2892 |
| Date | 01 January 2018 |
| Creators | Lai, Daniel |
| Publisher | Scholarship @ Claremont |
| Source Sets | Claremont Colleges |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | CMC Senior Theses |
| Rights | © 2018 Daniel Lai, default |
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