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• See me if you have to complain about something

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