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Central visual pathways

Central visual pathways. NRS 495 – Neuroscience Seminar Christopher DiMattina , PhD. Retinal information p rocessing. Ganglion cell receptive fields. H ave a center-surround organization ( Kuffler 1953). Spatial frequency filtering. Contrast coding. Mach bands. Mach bands.

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Central visual pathways

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  1. Central visual pathways NRS 495 – Neuroscience Seminar Christopher DiMattina, PhD

  2. Retinal information processing NRS 495 - Grinnell College - Fall 2012

  3. Ganglion cell receptive fields • Have a center-surround organization (Kuffler 1953) NRS 495 - Grinnell College - Fall 2012

  4. Spatial frequency filtering NRS 495 - Grinnell College - Fall 2012

  5. Contrast coding NRS 495 - Grinnell College - Fall 2012

  6. Mach bands NRS 495 - Grinnell College - Fall 2012

  7. Mach bands NRS 495 - Grinnell College - Fall 2012

  8. Detecting edges NRS 495 - Grinnell College - Fall 2012

  9. From retina to cortex NRS 495 - Grinnell College - Fall 2012

  10. The visual pathway NRS 495 - Grinnell College - Fall 2012

  11. Lateral geniculate nucleus NRS 495 - Grinnell College - Fall 2012

  12. Mapping the visual field NRS 495 - Grinnell College - Fall 2012

  13. Mapping the visual field NRS 495 - Grinnell College - Fall 2012

  14. Cortical magnification NRS 495 - Grinnell College - Fall 2012

  15. Cortical magnification NRS 495 - Grinnell College - Fall 2012

  16. Orientation tuning NRS 495 - Grinnell College - Fall 2012

  17. Model of orientation tuning NRS 495 - Grinnell College - Fall 2012

  18. Types of simple cells NRS 495 - Grinnell College - Fall 2012

  19. Simple and complex cells NRS 495 - Grinnell College - Fall 2012

  20. Complex cell model NRS 495 - Grinnell College - Fall 2012

  21. Columnar organization NRS 495 - Grinnell College - Fall 2012

  22. Ocular dominance NRS 495 - Grinnell College - Fall 2012

  23. Functional maps NRS 495 - Grinnell College - Fall 2012

  24. Object representation NRS 495 - Grinnell College - Fall 2012

  25. What and where pathways NRS 495 - Grinnell College - Fall 2012

  26. What and where pathways NRS 495 - Grinnell College - Fall 2012

  27. Inferotemporal cortex NRS 495 - Grinnell College - Fall 2012

  28. Jennifer Aniston neuron NRS 495 - Grinnell College - Fall 2012

  29. Object recognition is hard NRS 495 - Grinnell College - Fall 2012

  30. Template matching NRS 495 - Grinnell College - Fall 2012

  31. Template matching is problematic NRS 495 - Grinnell College - Fall 2012

  32. Feature detection hierarchies NRS 495 - Grinnell College - Fall 2012

  33. Hierarchical organization of cortex NRS 495 - Grinnell College - Fall 2012

  34. V1 cells like edges NRS 495 - Grinnell College - Fall 2012

  35. V2 cells – more complex stimuli NRS 495 - Grinnell College - Fall 2012

  36. Some V2 neurons represent border ownership NRS 495 - Grinnell College - Fall 2012

  37. V2 cells represent illusory contours NRS 495 - Grinnell College - Fall 2012

  38. V4 cells tuned for complex shape NRS 495 - Grinnell College - Fall 2012

  39. IT cells tuned for 3-D shape NRS 495 - Grinnell College - Fall 2012

  40. Topographic organization of IT NRS 495 - Grinnell College - Fall 2012

  41. Specialization in human cortex NRS 495 - Grinnell College - Fall 2012

  42. Viewpoint dependence NRS 495 - Grinnell College - Fall 2012

  43. Viewpoint dependence NRS 495 - Grinnell College - Fall 2012

  44. A model of ventral stream NRS 495 - Grinnell College - Fall 2012

  45. Paperclip responses - Data NRS 495 - Grinnell College - Fall 2012

  46. Paperclip responses - Model NRS 495 - Grinnell College - Fall 2012

  47. Scrambled stimuli NRS 495 - Grinnell College - Fall 2012

  48. Summary • Visual system organized hierarchically • Two processing streams • Increasing feature selectivity ultimately serves object recognition • Mechanisms remain poorly understood NRS 495 - Grinnell College - Fall 2012

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