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B-U & T-D processing
Let 5: Bottom-Up Lec 6: Top-Down processing Reading Smith & Kosslyn
| Question | Answer |
|---|---|
| Recognition | the process of matching representations of organized sensory input to stored representations in memory |
| agnosia | condition where a person cannot readily recognize the objects around them |
| viewpoint dependence or shape constancy | an object can be viewed from an infinite combination of possible angles/distances, each of which projects a slightly different 2-dimensional image on a plane varying in size/orientation |
| template-matching models | match the whole image to a stored representation of the whole object |
| feature-matching models | extract important/discriminating features from the image & match these with known features of objects |
| recognition-by-components models | represents the 3-dimensional structure of objects by specifying their parts & their spatial relations among those parts |
| configural models | distinguish among objects that share the same basic parts & overall structure by coding each exemplar according to how it deviates from the average/phototypical object |
| excitatory connections | increase the activity of a unit |
| inhibitory connections | decrease the activity of a unit |
| geons | shapes |
| structural description | components & spatial relations of an object |
| viewpoint invariant | in the image regardless of the direction from which the object is viewed |
| visual priming | faster recognition when an object is seen for the 2nd time |
| prosopagnosia | inability to recognize different faces |
| expertise hypothesis | proposes that a specialized neural system develops that allows expert visual discrimination |
| bottom-up processing | info comes from sensory organs & is passed up the hierarchy of analysis to areas responsible for higher cognition |
| top-down processing | perception of a stimulus that originates in higher cognition and proceeds downward towards sensation & is based on earlier experiences in accordance with your knowledge, beliefs, goals, & expectations |
| brightness illusion | even with changes in illumination across an objects surface, we believe it to be all the same color |
| size illusions | assume objects maintain their "true" size across changes in apparent distance from the observer |
| word superiority | the context of surrounding letters can manipulate the perception of a target letter |
| face superiority | people are better at distinguishing faces that only differ by the type of nose that if the noses were in isolation |
| feedback | direction of info |
| probabilistic | reflects what has happened in the past & is likely to happen again |
| reverse probability | the probability that the opposite of something happens |
| Baye's theorem | uses information from previous experience to make guesses about the current environments estimates the reverse probability |
| iterative processing | processing in which info is repeatedly exchanged between visual areas, each time with more data, to refine the representation of the stimulus & extend the duration |
| bistable perception | can perceive both interpretations, but only one at a time |
| binocular rivalry | state in which individual images to each eye compete |
| aperceptive agnosia | impairment in judging basic aspects of the form/shape of objects |
| apraxia | inability to make voluntary movements even though there is no paralysis can perform actions from memory & describe what they see difficulty performing new actions on what they see |
| what are the problems with template-matching theory? | transformations don't change the object but it will no longer fit the template if the object is obstructed you won't see the whole object |
| how are stabilized retinal images used as evidence for feature matching theory? | eyes shake constantly so an image is projected on different photoreceptors (fatigue). if you record the time they shake for & time an image to the corresponding time it is constantly projected onto the same photoreceptors & you lose features of the image |
| how does the visual search experiment support the feature matching theory? | a target object is easy to recognize when surrounded by objects that are not similar to it compared to when it is surrounded by similar objects |
| Pandemonium model | visual input is received by image demon, a feature demon decodes specific features cognitive demon "shouts" after receiving certain combination of features and decision demon listens for loudest "shout" to identify input |
| caricatures exaggerate strong features of individuals & support the feature-matching model | people are quicker/more accurate at identifying them than pictures of actual individuals |
| what is a problem with the feature matching model? | different arrangements of the same features produce different objects |
| non-accidental properties | features are special/unique recognized from every viewpoint allows you to recognize geons |
| matching process of recognition-by-components model | 1. detect elementary features, edges 2. find non-accidental properties 3. determine component geons 4. match to memory |
| how does deleting non-accidental properties support recognition by components model? | deleting non-accidental properties makes it harder to identify what at object is. |
| how does object complexity support recognition by components model? | increased object complexity increases the number of geons and makes it easier to accurately identify an object |
| How does facial structure create a problem for recognition by components theory? | all faces have the same spatial arrangement so theoretically it should be harder to recognize people but is actually the opposite which creates a problem |
| What is the recognition by components theory good at? | transformations, relationships between features, explaining how we make sense of nonsense objects |
| top | refers to areas of the brain responsible for higher-level cognition |
| bottom | refers to low-level areas of brain that receive input from higher sensation |
| expectation bias | your own expectations or biases can affect the way you perceive something |
| signal detection theory | detecting some "signal" in the presence of noise/distractions demonstrates how expectations/biases affect perception |
| signal | something in the environment you are trying to detect |
| noise | things in the environment other than the signal |
| sensitivity | how easy/difficult it is to discriminate signal from noise |
| bias | your bias/tendency to say "yes" vs "no" which is determined by expectations or payoffs |
| what is the effect of changing bias | moving the threshold will change the amount of signals that are registered |
| hit | there is a signal and you correctly detect |
| miss | there is a signal but you fail to detect |
| correct rejection | there is no signal and you correctly say there was no signal |
| false alarm | there is no signal but you say that there was a signal |
| accuracy | % hits + % correct rejections |
| sensitivity depends on | how good separable signal and noise are & how good your "detector" is |
| accuracy depends on | proportion of trials with signal present/not present, bias, and sensitivity |
| context effects | when perception of an object is affected by its context/environment |
| subjective contours | when there is not an actual figure but it is perceived as one object |
| object out of context experiment | performance worse when objects are out of context |
| interactive activation model | features can excite/inhibit the letters which can excite/inhibit words. Can go in either direction |
| dorsal and ventral streams have | both bottom-up and top-down processing |
| is recognition dependent on a particular sensory modality? | no |
| what does agnosia result from? | damage to the brain |
| visual agnosia | sight is unimpaired yet recognition fails |
| what is the challenge of exemplar variation? | there are many different instances of each object category |
| what are the 4 models to overcome the challenges of recognition? | template matching, feature-matching, recognition-by-components, configural |
| for feature-matching model to be plausible neurons or populations of neurons should | show selectivity to parts of the input similar to the model |
| what is the solution to the difficulty of recognizing a 3-dimensional object with templates & features? | describing objects according to their parts & spatial relations among those parts |
| almost any object can be described by its | spatial description |
| a geons properties are | viewpoint invariant |
| what is prosopagnosia caused by? | damage to the fusiform face area which is a part of temporal lobes |
| what is required to judge subtle differences within any visual category? | expertise hypothesis |
| grouping is an | automatic process |
| grouping allows us to | see common attributes of many items at once |
| recognition may be improved if | the object is seen in expected/customary context |
| recognition may be impaired if | object is seen in context that is unexpected or inconsistent with expected/customary context |
| feedback facilitation from top layer resolves problem of recognition of imperfect input by | using stored info to guide processing |
| many top-down context effects results from | interactions between bottom-up processing & top-down knowledge |
| top-down and bottom-up processing work together to establish | best solution for object recognition |
| Necker cube | orientation of the cube changes with the direction from which it is view |
| in binocular rivalry a different monocular image is viewed in the | fovea of each eye & we alternate between the 2 images never seeing both at the same time |
| spatial processing of location relies on | the dorsal "where" pathway |
| object recognition relies on | the ventral "visual" pathway |
| apraxia is caused by damage to the | dorsal pathway |
Created by:
kzegelien2005
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