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Visual dysfunction and reading in special populations

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  • Full or part time
    Dr Andrew Schofield
  • Application Deadline
    Applications accepted all year round

Project Description

In recent years it has become apparent that a number of psychological and medical conditions are associated with visual dysfunction leading to reading difficulties. Such conditions include Dyslexia, Autism and Schizophrenia but other conditions have a visual component. These conditions have been linked to two somewhat disparate visual dysfunctions: magnocellular deficit and cortical hyper-excitability leading to visual stress.

The magnocellular systems within human vision is thought to be responsible for motion detection and the control of eye movements. The deficit can be measured using motion coherence tasks and by measuring sensitive to low frequency stripes, although it is likely eye movement control that impedes reading.

Cortical hyper-excitability relates to an over sensitivity to medium-thin stripes which causes poorly regulated excitation in visual cortex resulting in visual distortions and hallucinations. Text, being a stripy pattern, can cause the same distortions which can mask the text making it harder to read and also leading to tiredness and headaches.

Ostensibly the two theories are very different although the apparent co-occurrence of both sets of symptoms in a range of psychological conditions itself suggests that there may be a link.

This project will consider one or more condition and measure reading behavior, cortical hyper-excitability and magnocellular performance in that population as compared to controls in an attempt to either link the visual dysfunctions, or differentiate sub-populations within each clinical group.

Funding Notes

Strong UK/EU applicants will be considered for competitive internal funding rounds in 2018-19 with a start date of Sept 2019. EU students will not receive full financial support. I am also happy to assist good overseas applicants in their search for external funding.

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FTE Category A staff submitted: 40.80

Research output data provided by the Research Excellence Framework (REF)

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