what do we know about primary visual cortex (v1)
DESCRIPTION
What do we know about Primary Visual Cortex (V1). Xingyuan @ swarma.net 2013.6.30. Visual Neural Pathways. Retinal Photoreceptors. Retinal Photoreceptors. Rods have a high sensitivity to low levels of brightness no rods in the fovea (around) Cones - PowerPoint PPT PresentationTRANSCRIPT
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What do we know about Primary Visual Cortex (V1)
Xingyuan @swarma.net2013.6.30
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Visual Neural Pathways
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Retinal Photoreceptors
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Retinal Photoreceptors
• Rods– have a high sensitivity to low levels of brightness– no rods in the fovea (around)
• Cones– three cone types allow for the perception of color– Most cones are concentrated in and around the
fovea (center)
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S and L Cones
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LGN (Lateral geniculate nucleus)
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Retina Ganglion Cells and LGN
• the information from the two eyes remains still entirely separate in six different neuronal layers
• there is even almost a one-to-one correspondence between retinal ganglion and LGN cells
• In motion analysis, LGN ganglion cells have lower optimal temporal frequencies
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Responses of a Neuron in Cat Brain
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Center-surround receptive fields
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Center-surround receptive fields
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Difference of Gaussians
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Difference of Gaussians On GIMP
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The contrast sensitivity function
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The contrast sensitivity function
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Single-opponent cells
• Single-opponent cells are color sensitive and compute color differences– namely L-M (L for long wavelength and M for middle
wavelength, symbol “-” stands for oppo- nency) and S-(L+M) (S stands for short wavelength), thereby establishing the red-green and the blue-yellow color axes.
• These cells are parvocellular (P) neurons and are somewhat slower but have smaller receptive fields, i.e. higher spatial resolutions, than the magnocellular neurons.
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Responses of V1 Neuron in Cat Brain
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Tuning curves
From Dayan and Abbott, Theoretical Neuroscience
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Simple and Complex Cells
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Other Cells in Area V1
• edges, bars, gratings• line endings• motion• color• disparity
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Why?
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Faithful and efficient?
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Faithful and efficient?
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Faithful and efficient?
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orientation selectivity
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Competitive Learning
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Self-Organizing Map: demo
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Self-Organizing Map: MNIST
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Self-Organizing Map: WORDS
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Summary
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Thank you!
@淘幕天 _袁行远
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