Question Examples
• If you were a neurosurgeon and you needed to take out part of the cortex of a patient, which technique would you use to identify the function of that part and why.
• What is the most important drawback to the fMRI technique
• What does the Stroop Effect tell us about how the brain works?
Visual Pathways
• visual hemifields project contralaterally– exception: bilateral
representation of fovea!• Optic nerve splits at optic
chiasm
• about 90 % of fibers project to cortex via LGN
• about 10 % project through superior colliculus and pulvinar– but that’s still a lot of fibers!
Note: this will be important when we talk about visuospatial attention
Visual Pathways
• Lateral Geniculate Nucleus maintains segregation:
– of M and P cells (mango and parvo)
– of left and right eyes
P cells project to layers 3 - 6
M cells project to layers 1 and 2
Visual Pathways
• Primary visual cortex receives input from LGN
– also known as “striate” because it appears striped on some micrographs
– also known as V1
– also known as Brodmann Area 17
Visual Pathways
W. W. Norton
• Primary cortex maintains distinct pathways – functional segregation
• M and P pathways synapse in different layers
How does the visual system represent visual information?
How does the visual system represent features of scenes?
• Vision is analytical - the system breaks down the scene into distinct kinds of features and represents them in functionally segregated pathways
• but…
• the spike timing matters too!
Visual Neuron Responses
• Unit recordings in LGN reveal a centre/surround receptive field
• many arrangements exist, but the “classical” RF has an excitatory centre and an inhibitory surround
• these receptive fields tend to be circular - they are not orientation specific
How could the outputs of such cells be transformed into a cell with orientation specificity?
Visual Neuron Responses
• LGN cells converge on “simple” cells in V1 imparting orientation (and location) specificity
Visual Neuron Responses
• V1 maintains a map of orientations across the retina because each small area on the retina has a corresponding cortical module that contains cells with the entire range of orientation tunings
Visual Neuron Responses
• LGN cells converge on simple cells in V1 imparting orientation specificity
• Thus we begin to see how a simple representation - the orientation of a line in the visual scene - can be maintained in the visual system– increase in spike rate of specific neurons indicates presence of a line
with a specific orientation at a specific location on the retina
– Why should this matter?
Visual Neuron Responses
• Edges are important because they are the boundaries between objects and the background or objects and other objects
Visual Neuron Responses
• This conceptualization of the visual system was “static” - it did not take into account the possibility that visual cells might change their response selectivity over time
– Logic went like this: if the cell is firing, its preferred line/edge must be present and…
– if the preferred line/edge is present, the cell must be firing
• We will encounter examples in which neither of these are true!
• Representing boundaries must be more complicated than simple edge detection!
Visual Neuron Responses
• Boundaries between objects can be defined by color rather than brightness
Visual Neuron Responses
• Boundaries between objects can be defined by texture
Visual Neuron Responses
• Boundaries between objects can be defined by motion