Download - 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.

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?


• LGN cells converge on “simple” cells in V1 imparting orientation (and location) specificity


• 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


• 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?


• Edges are important because they are the boundaries between objects and the background or objects and other objects


• 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!


• Boundaries between objects can be defined by color rather than brightness


• Boundaries between objects can be defined by texture


• Boundaries between objects can be defined by motion