Models of Orientation Preference
Maps
Descriptive models: iso-orientation
columns, pinwheels, ...
Neural
Networks: (Hebbian) learning from examples
Evolving Fields:
- Assume an orientation at each point (2-dimensional, 2-component
field)
- Employ some rule (see later) for evolving the field in time
- Starting from random initial conditions, most rules lead
to patterns similar to real maps,
