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Lecture 8

Perception lecture 8

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University of Toronto Scarborough
Matthias Niemeier

Under certain conditions we are very good at scene perception. How come? Why is it that sometimes we have great difficulties;When? And what explains the difference? We perceive things globally , dont need to analyze every single little detail, we are able to extract salient information from photos, multiple dimensions to categorize certain aspects of a scene. Makes sense in a semantic way. Sort scenes based on global simple process. The details in one picture or other global features are very similar we have to use other local strategies to tell the differences We dont represent them at a first glance. We can use attention to zoom into details and process them one at a time Selective attention is a cognitive brain mechanism that enables one to process relevant inputs, thoughts or actions while ignoring others that are less important, irrelevant or distracting Attention is not arousal; a global state of the brain reflecting an overall level of responsiveness (also known as affect intensity in the context of emotions) Early vs late selection Early selection or early with adaptable filter system We get sensory input and then we analyze that input , some kind of a continuum back and forth connections then we have higher level analysis feed into executive functions finally through motor areas we see some kind of a response human processing in a nutshell could take the position that sensorimotor is everything humans are defined by Behaviour based on immediate stimuli and (memory) Late Selection even semantic processes can remain unattendedunconscious Semantic processes can happen unattended Attentional blink Paradigm looking for 2 targets in visual display RSVP Multi level filtering , Perceptual load Spotlight or search light model: Attention is confined to a coherent region of space and can move from one point to the next Zoom lens model attention expands from fixation grows to fill whole region...shrinks to include just cued location Problems with zoom and spotlight models
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