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XVII
Abstract
Semi-automatic Identification of Retinotopic Visual Areas
PURPOSE: A tool was implemented to identify retinotopic visual areas in a simple, semi-
automatic, and objective way from fMRI data.
BACKGROUND: Viewing a flickering, rotating wedge visual stimulus creates traveling
waves in the visual cortex that can be measured with fMRI. The fMRI signals can be used to
identify the retinotopic visual areas. The traveling waves are easier to visualize on a flattened
representation than a 3-dimensional representation. Therefore, 2D images representing com-
putationally flattened cortex are typically used to segregate the retinotopic visual areas.
METHODS: A general approach for fitting a two-dimensional parameterized model (atlas) to
a measured fMRI signal has been developed. The atlas represents an expected pattern of activ-
ity that can be found in most subjects; in this case, the organization of retinotopic visual areas.
To identify the visual areas, the atlas is coarsely aligned with the measured signal. Then, the
atlas is deformed to fit the measured data by minimizing an energy function using a custom
hierarchical optimization technique. The deformation is based on a spline representation of the
displacement field.
RESULTS: The visual areas from the deformed atlas can be overlaid onto the measurements.
Thus, the retinotopic visual areas can be objectively and semi-automatically identified based
on standard traveling wave data. The visual areas found by the program are similar to those
generated by an experienced human operator.
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