week 13 (recognition + attention) Flashcards

(24 cards)

1
Q

question: which gestalt rule dominates?

A
  • committee model
    ⤷ loudest member wins but not permanently
  • ambiguous figures -> many diff. interpretations
  • accidental viewpoints -> producing regularity that’s not real
    ⤷ ex. illusion of holding the tower of pisa
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2
Q

question: how to separate figure from ground in figure ground? (5)

A
  • surroundedness
    ⤷ if one region is entirely surrounded by another, surrounded area = figure
  • size
    ⤷ smaller region = figure
  • symmetry
    ⤷ symmetrical region = figure
  • parallelism
    ⤷ parallel contours = figure
  • relative motion
    ⤷ how details move relative to an edge helps differentiate
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3
Q

explain: bayesian approach for making inferences about object recognition

A
  • bayes theorem = allows calculation for prob. that the world is in a particular state given a particular observation
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4
Q

explain: changes in cells of what pathway (diff. between V2, V4)

A
  • V2 = sensitive to contours and borders
  • V4 = sensitive to more complex attributes

**cells along what pathway have a progressive change
⤷ anterior = more sensitive to complex stim.

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5
Q

explain: subtraction method

A
  • compare activity measured in 2 conditions
    ⤷ one with and one without mental process of interest
  • look at diff. between images to see diff. in regions of brain
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6
Q

explain: fMRI experiment for object-decoding

A
  • train participant by presenting many images
    ⤷ record brain responses
  • test by presenting new image
    ⤷ researches see brain activity and try to guess what the object is
  • shows that info about object identity is in that region
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7
Q

explain: computation model for visual processing

A
  • pandemonium model
    ⤷ demons = neurons
  • sig. detected
  • feature demons extract features
  • cognitive demons look for specific features
  • decision demons pool info and choose the loudest one to make the decision
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8
Q

explain: geon concept (limitations?)

A
  • suggested geons = basic building blocks of objects

LIMITATIONS
- doesn’t explain how we can recognize specific individual objects we are familiar with
⤷ ex. if cup = cylinder + handle why can’t cup be a geon?
- some objects can be hard to break into geons (complex)
- doesn’t explain recog. after brain injuries

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9
Q

question: how can computers be taught to recognize things?

A
  • DNN extract features
  • info = pooled
  • operations create new image for DNN to extract
  • keep going to make more categories
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10
Q

explain: face inversion effect

A
  • harder to recog. which faces have been modified if face is inverted
  • harder to ID faces when inverted
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11
Q

question: do we use feature-by-feature analysis for faces?

A
  • no
    ⤷ too slow
  • use holistic processing
    ⤷ process the face as a single thing
    ⤷ similar to gestalt

**holistic needs upright, normal contrast images

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12
Q

explain: prosopagnosia

A
  • person cannot ID faces
  • can be congenital or acquired
    ⤷ acquired = damage to temporal lobe (esp. FFA)
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13
Q

define: attention

A
  • mechanism to restrict input to a subset of things
  • dev. to deal with all the input
    ⤷ bc perceiving it all would be too much

**no single locus in the nervous system
⤷ has broad areas instead

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14
Q

name + explain: types of attention (5)

A
  1. external or internal
    - internal = thoughts
    - external = ext. stim. (ex. music)
  2. overt or covert
    - O = orienting senses to thing you’re focusing on
    - C = secretly paying attention
  3. divided
    - focus on more than 1 thing
    - bad at this
  4. sustained
    - long time focused on one thing
  5. selective
    - paying att. to one among many stim.
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15
Q

explain: visual search experiments

A
  • measure time it takes for observer to say yes or no
    ⤷ when asked if target is present
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16
Q

question: what impacts the efficiency of a visual search experiment?

A
  • increasing set size = decreases efficiency
  • changing task (easiest to hardest)
    ⤷ feature search > conjunction search > spatial configuration
17
Q

define: salient feature

A
  • stands out visually from neighbour
  • ex. colour, orientation
18
Q

explain: serial self-terminating search

A
  • searching objects one by one
  • terminate when find the target
  • inefficient when target and distracts share a lot of features
    ⤷ less salient features
19
Q

compare: guided search vs conjunction vs serial

A

GUIDED
- attention restricted to a subset of possible items on based on info about basic features

CONJUNCTION
- search for target defined by the presence of 2+ attributes

SERIAL
- checking each item until find target

guided faster than conjunction faster than serial

20
Q

question: what are ways to improve efficiency of vis. search? (2)

A
  • priming
    ⤷ stim. that makes it easier to resp. to a subsequent stim.
    ⤷ ex. finding one monkey makes finding the other monkeys easier
  • scene-based guidance
    ⤷ info of understanding scene helps find specific objects
    ⤷ ex. using anchoring objects
21
Q

explain: binding problem in visual searches

A
  • hard to tie diff. attributes of vis. stim.
    ⤷ handled by diff. circuits
  • possible explanation = feature integration theory (treisman)
    ⤷ basic features can be processed together but other properties need attention
    ⤷ ex. binding needs attention
22
Q

define: illusory conjunction

A
  • incorrect grouping of features from 2 or more objects
  • both features present but not together
23
Q

question: what happens to vis attention when lesions in parietal lobe? (2)

A

**parietal lobe = association cortex

  1. contralateral neglect
    - inability to attend in contralesional visual field
    ⤷ ex. lesion in R -> ignore L field
  2. extinction
    - inability to exp. a stim. to one side of the point of fixation in the presence of another stim.
    ⤷ ex. lesion in R -> can’t attend to smth on the L if there’
    - can’t attend contralaterally if there something in the ipsilateral field
24
Q

question: what happens if both parietal cortexes are damaged?

A
  • “blind”
    ⤷ can’t attend to anything
    ⤷ parietal = association cortex
  • can still see but can’t pay attention to anything -> can’t perceive anything