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Lecture 5

Lecture 5.docx

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Carolyn Ensley

Lecture 5Feature NetsMcClelland and Rumelharts 1981 model of word recognition included two additionsExcitatory and inhibitory connections between detectorsTopdown connections from words to letters and letters to featuresFeature NetsSimilar feature nets may underlie our perception of objectsBeettermanThe recognition by components RBC model includes an intermediate layer that is sensitive to geons 46 basic shapes proposed as the building blocks for all threedimensional formsFeature NetsOne piece of evidence supporting the representation of geons is that perceptually degraded pictures are better recognized if geons are preservedFeature NetsThe objectsuperiority effect is analogous to the wordsuperiority effectLines are perceived more accurately if presented in the context of an objectA geon is recognize faster in a context of an object Feature NetsModels of object recognition differ on whether object recognition depends on viewpointIn the recognition by components model geons result in viewpointindependent recognitionOther proposals are viewpointdependent requiring the remembered representation to be rotated into alignment with the current viewDifferent Objects Different Recognition SystemsSome evidence suggests that certain categories of objects are perceived using specialized mechanismsIn particular the recognition of faces may involve principles different from those discussed thus far Fusiform guirsDifferent Objects Different Recognition SystemsOne source of evidence for specialized faceprocessing mechanisms comes from prosopagnosia a type of agnosia in which the visual objectrecognition deficit is specific to facesDifferent Objects Different Recognition SystemsPerception and memory for faces is also highly viewpointdependent much more so than for other objectsHere inverting faces causes a greater disruption in memory performance compared to inverting housesDifferent Objects Different Recognition SystemsThis example using an altered photograph of Margaret Thatcher also illustrates how viewpointdependent the perception of faces isUpsidedown these two pictures do not look that differentDifferent Objects Different Recognition Systems
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