Read this article for Friday next week

1. Read this article for Friday next week [1]Chelazzi L, Miller EK, Duncan J, Desimone R. A neural basis for visual search in inferior temporal cortex. Nature 1993; 363: 345-347.

2. Test Oct. 21 Review Session Oct 19 2pm in TH201 (that’s here)

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

4. The Role of “Extrastriate” Areas • Different visual cortex regions contain cells with different tuning properties

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

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

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

8. 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

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

10. 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 • Characteristics: • a single spike per synapse • no time for lateral connections • no time for feedback connections

11. 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 • What does it mean for an area to be “lower” or “higher”

12. The Feed-Forward Sweep • Hierarchy of visual cortical areas defined anatomically Dorsal “where”/”how” Ventral “what”

13. The Feed-Forward Sweep • Hierarchy can be defined more functionaly • 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

14. The Feed-Forward Sweep • Thus the “hierarchy” of visual areas differs depending on temporal or anatomical features • aspects of the visual system account for this fact: • multiple feed-forward sweeps progressing at different rates (I.e. magno and parvo pathways) in parallel • M pathway is myelinated • P pathway is not • signals arrive at cortex via routes other than the Geniculo-striate pathway (LGN to V1) • Will be important in understanding blindsight

15. The Feed-Forward Sweep • The feed-forward sweep gives rise to the “classical” receptive field properties • tuning properties exhibited in very first spikes • Orientation tuning in V1 • Optic flow tuning in MST • think of cortical neurons as “detectors” only during feed-forward sweep

16. 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!

17. 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?

18. 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”

19. 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

20. 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 responds differently depending on whether it is encoding boundaries, surfaces, the background, etc.

21. Extra-RF Influences • How do these data contradict the notion of a “classical” receptive field?

22. Extra-RF Influences • How do these data contradict the notion of a “classical” receptive field? • Remember that for a classical receptive field (i.e. feature detector): • If the neuron’s preferred stimulus is present in the receptive field, the neuron should fire a stereotypical burst of APs • If the neuron is firing a burst of APs, its preferred stimulus must be present in the receptive field

23. Extra-RF Influences • How do these data contradict the notion of a “classical” receptive field? • Remember that for a classical receptive field (i.e. feature detector): • If the neuron’s preferred stimulus is present in the receptive field, the neuron should fire a stereotypical burst of APs • If the neuron is firing a burst of APs, its preferred stimulus must be present in the receptive field

24. 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?

25. 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

26. 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

27. 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

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

29. 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

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

31. 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

32. Feedback Signals and Attention • Instruction cues (for example 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 • What does this accomplish?

33. Feedback Signals and Attention • What does this accomplish? • Preface to attention: Two ways to think about attention • Attention improves perception, acts as a gateway to memory and consciousness • Attention is a mechanism that routes information through the brain • It is the brain actively reconfiguring itself by changing the way signals propagate through networks • It is a form of very fast, very transient plasticity

34. Feedback Signals and Attention • Put another way: • It may strike you as remarkable that a single visual stimulus should “activate” so many brain areas so rapidly • In fact it should be puzzling that a visual input doesn’t create a runaway “chain reaction” • The brain is massively interconnected • Why shouldn’t every neuron respond to a visual stimulus

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