Your Test
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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.
Extra-RF Influences
• How do these data contradict the notion of a “classical” receptive field?
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
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
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?
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
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
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
Feedback Signals and the binding problem
• What is the binding problem?
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
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?
Feedback Signals and the binding problem
• So what’s the connection between Attention and Recurrent Signals?
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
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
Feedback Signals and Attention
• We’ll consider the role of feedback signals in attention in more detail as we discuss the neuroscience of attention