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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.
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Test Oct. 21
Review Session Oct 19 2pm in TH201 (that’s here)
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The distinct modes of vision offered by feedforward and
recurrent processing
Victor A.F. Lamme and Pieter R. Roelfsema
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The Role of “Extrastriate” Areas
• Different visual cortex regions contain cells with different tuning properties
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Dichotomies in the Visual System?
• What are three dichotomies that Lamme identifies in the visual system?
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Dichotomies in the Visual System?
• What are three dichotomies that Lamme identifies in the visual system?
• Dorsal vs. Ventral stream
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Dichotomies in the Visual System?
• What are three dichotomies that Lamme identifies in the visual system?
• Dorsal vs. Ventral stream
• Pre-attentive vs. Attentive
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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
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The Feed-Forward Sweep
• What is the feed-forward sweep?
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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
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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”
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The Feed-Forward Sweep
• Hierarchy of visual cortical areas defined anatomically
Dorsal “where”/”how”
Ventral “what”
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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
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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
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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
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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!
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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?
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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”
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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
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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.
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Extra-RF Influences
• How do these data contradict the notion of a “classical” receptive field?
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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
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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
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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?
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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
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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
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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
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Feedback Signals and the binding problem
• What is the binding problem?
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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
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Feedback Signals and the binding problem
• So what’s the connection between Attention and Recurrent Signals?
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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
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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?
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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
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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
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Feedback Signals and Attention
• We’ll consider the role of feedback signals in attention in more detail as we discuss the neuroscience of attention