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The distinct modes of vision offered by feedforward and recurrent processing Victor

The distinct modes of vision offered by feedforward and recurrent processing Victor. A.F. Lamme and Pieter R. Roelfsema. Dichotomies in the Visual System?. What are three dichotomies that Lamme identifies in the visual system?. Dichotomies in the Visual System?.

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The distinct modes of vision offered by feedforward and recurrent processing Victor

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  1. The distinct modes of vision offered byfeedforward and recurrent processing Victor A.F. Lamme and Pieter R. Roelfsema

  2. Dichotomies in the Visual System? • What are three dichotomies that Lamme identifies in the visual system?

  3. Dichotomies in the Visual System? • What are three dichotomies that Lamme identifies in the visual system? • Dorsal vs. Ventral stream

  4. Dichotomies in the Visual System? • What are three dichotomies that Lamme identifies in the visual system? • Dorsal vs. Ventral stream • Pre-attentive vs. Attentive

  5. Dichotomies in the Visual System? • What are three dichotomies that Lamme identifies in the visual system? • Dorsal vs. Ventral stream • Pre-attentive vs. Attentive • Conscious vs. Unconscious

  6. The Feed-Forward Sweep • What is the feed-forward sweep?

  7. The Feed-Forward Sweep • The feed-forward sweep is the initial response of each visual area “in turn” as information is passed to it from a “lower” area • a single spike per synapse • no time for lateral connections • no time for feedback connections

  8. The Feed-Forward Sweep • The feed-forward sweep is the initial response of each visual area “in turn” as information is passed to it from a “lower” area • Consider the latencies of the first responses in various areas

  9. The Feed-Forward Sweep • Thus the “hierarchy” of visual areas differs depending on temporal or anatomical features • Three aspects of the visual system account for this fact: • Some neurons in an area don’t receive direct connections from the next “lower” area • multiple feed-forward sweeps progressing at different rates (I.e. magno and parvo pathways) in parallel • signals arrive at cortex via routes other than the Geniculo-striate pathway (LGN to V1)

  10. The Feed-Forward Sweep • The feed-forward sweep gives rise to the “classical” receptive field properties • tuning properties exhibited in very first spikes • think of cortical neurons as “detectors” only during feed-forward sweep

  11. After the Forward Sweep • By 150 ms, virtually every visual brain area has responded to the onset of a visual stimulus • But visual cortex neurons continue to fire for hundreds of milliseconds!

  12. After the Forward Sweep • By 150 ms, virtually every visual brain area has responded to the onset of a visual stimulus • But visual cortex neurons continue to fire for hundreds of milliseconds! • What are they doing?

  13. After the Forward Sweep • By 150 ms, virtually every visual brain area has responded to the onset of a visual stimulus • But visual cortex neurons continue to fire for hundreds of milliseconds! • What are they doing? • with sufficient time (a few tens of ms) neurons begin to reflect aspects of cognition other than “detection”

  14. Extra-RF Influences • One thing they seem to be doing is helping each other figure out what aspects of the entire scene each RF contains • That is, the responses of visual neurons begin to change to reflect global rather than local features of the scene • recurrent signals sent via feedback projections are thought to mediate these later properties

  15. Extra-RF Influences • consider texture-defined boundaries • classical RF tuning properties do not allow neuron to know if RF contains figure or background • At progressively later latencies, the neuron response differently depending on whether it is encoding boundaries, surfaces, the background, etc.

  16. Recurrent Signals in Object Perception • Can a neuron represent whether or not its receptive field is on part of an attended object? • What if attention is initially directed to a different part of the object?

  17. Recurrent Signals in Object Perception • Can a neuron represent whether or not its receptive field is on part of an attended object? • What if attention is initially directed to a different part of the object? Yes, but not during the feed-forward sweep

  18. Recurrent Signals in Object Perception • curve tracing • monkey indicates whether a particular segment is on a particular curve • requires attention to scan the curve and “select” all segments that belong together • that is: make a representation of the entire curve • takes time

  19. Recurrent Signals in Object Perception • curve tracing • neuron begins to respond differently at about 200 ms • enhanced firing rate if neuron is on the attended curve

  20. Feedback Signals and the binding problem • What is the binding problem?

  21. Feedback Signals and the binding problem • What is the binding problem? • curve tracing and the binding problem: • if all neurons with RFs over the attended curve spike faster/at a specific frequency/in synchrony, this might be the binding signal

  22. Feedback Signals and the binding problem • What is the binding problem? • curve tracing and the binding problem: • if all neurons with RFs over the attended curve spike faster/at a specific frequency/in synchrony, this might be the binding signal But attention is supposed to solve the binding problem, right?

  23. Feedback Signals and the binding problem • So what’s the connection between Attention and Recurrent Signals?

  24. Feedback Signals and Attention • One theory is that attention (attentive processing) entails the establishing of recurrent “loops” • This explains why attentive processing takes time - feed-forward sweep is insufficient

  25. Feedback Signals and Attention • Instruction cues (for exaple in the Posner Cue-Target paradigm) may cause feedback signal prior to stimulus onset (thus prior to feed-forward sweep) • think of this as pre-setting the system for the upcoming stimulus

  26. Feedback Signals and Attention • We’ll consider the role of feedback signals in attention in more detail as we discuss the neuroscience of attention

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