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Knowledge. The Brain. Course Overview. Acquisition (perception). Use. ch. 3: Vision . How are objects recognized?. -It looks easy but it’s not. ch.4: Attention. Object Recognition. Visual System Recognizes: Object Identities (man, woman, child, oar, lake) Spatial Layout of Scene

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course overview

Knowledge

The Brain

Course Overview

Acquisition

(perception)

Use

ch. 3: Vision. How are objects recognized?

-It looks easy but it’s not

ch.4: Attention.

slide4
Visual System Recognizes:
    • Object Identities (man, woman, child, oar, lake)
    • Spatial Layout of Scene
    • Properties of Surfaces(color, texture, etc.)
  • Are these real psychological dimensions? (What about Small vs. big? Alive vs. Inanimate? Tool vs. Non-tool? soft vs. hard? )
  • - Are these dimensions processed independently by the mind/brain? (after all, our subjective experience is that of an integrated scene)
slide5

Specific Disorders suggest functionally

independent types of visual analysis

  • 1. Visual Agnosia:(object identity)
    • loss of ability to recognize objects
    • preserved ability to navigate, reach
    • Bilateral damage to occipital/temporal
    • Prosopagnosia (specific to face recognition)
  • 2. Balint’s Syndrome:(spatial layout)
    • inability to navigate, reach
    • preserved ability to recognize objects
    • damage to parietal areas
  • 3. Cerebral Achromatopsia (color)
    • inability to discriminate colors
    • distinct from color blindness--Color blindness results from abnormalities in the photoreceptors of the eye. But cerebral achromatopsia results from damage to posterior visual areas in the brain
slide6

fMRI studies have confirmed the anatomical

Segregation of these functions

  • 1. Object recognition:(lateral occipital cortex)
    • face recognition (medio-temporal)
  • 2. spatial layout and spatial attention
    • parietal areas
  • 3. Color
    • medio-temporal
slide8

1. The visual system must carry out “image segmentation”, but

object boundaries are not easily determined

slide9

3. Objects may occlude each other

or they may be superimposed on

each other.

slide10

2. Objects may appear anywhere on retina in any size

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Perhaps the brain is able to represent these objects in a way that is “translationally

invariant” and “size invariant”.

slide11

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4. Same object category (‘e’) may have different shapes

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slide14

5. Object may be abnormally oriented

Words: Moderate Effects

Letters & Digits: Small Effects

slide15

How is object recognition accomplished?

Simplest idea: “Template Model”:

Store in brain a copy of what every possible input will look like.

Match observed object to the proper image in memory

slide16

Template Theory

Perceptual

Representation

Memory Representations

slide17

Problems with Template Theory:

(1) Massive numbers of templates are required (remember all those E’s?).

(2) Predicts no transfer to novel views of the same object

(unlikely for different retinal positions)

(3) Objects are often obstructed (remember the baby?)

slide18

Feature Analysis Theory

A fixed set of elementary properties are analyzed

Independently and in parallel across visual field.

Possible examples

Free line endings:

+45deg. -10deg.

Line Orientations:

Different Sizes:

Curvature:

Colors:

slide19

A Simple Version of Feature Theory

E

Perceptual

Representation

Memory

Representation

3 Horizontal lines

1 Vertical line

4 Right angles

3 Horizontal lines 1 Vertical line 4 Right angles

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2 Horizontal lines 1 Vertical line 3 Right angles

evidence that features are really basic elements of visual processing
Evidence that Features are really basic elements of visual processing
  • Physiological Evidence
    • Individual neurons respond preferentially to different kinds of simple visual features
      • simple cells--respond best to lines or angles of a specific orientation and retinal position
      • complex cells--fire maximally to lines or angles without respect to location. They often also have preference for stimuli moving in certain directions…
      • hypercomplex cells--fire maximally have even more complicated sets of requirements for maximal firing. (e.g. corners, notches….etc.)
slide21

Adaptation Effects are indicators of

  • elementary visual features...
    • Your eyes are always moving, even when “fixated”(microsaccades)
    • An image completely still on the retina will slowly fade from view, because
    • individual feature detectors become habituated (fatigued) with prolonged, sustained stimulation.
    • Retinal stabilization procedure allows direct demonstration of this
    • phenomenon.
slide23

More Evidence for Features...

In a Visual Search Task:

(1)Targets defined by a single feature are easy to detect(the red item; the square)

(2) Targets defined by a combination of features are difficult to detect (the red square).

Let’s try it out

slide24

Call out “now!” when

you see the horizontal line.

slide26

TypicalResults for “Feature Search”

“No”

Reaction

Time

(msec)

“Yes”

2 4 6 10 20 30

# of items in display

These results suggests parallel analysis and detection of simple visual features.

conjunction search
Conjunction Search
  • Combination of features (e.g., red AND horizontal)
  • Spatial arrangements of features (e.g. black above white)

When targets are defined by:

slide28

Call out “Now!” when you find the black

square above the white square:

slide29

Treisman’sResults for

“Conjunction Search”

“No”

Reaction

Time

(msec)

“Yes”

2 4 6 10 20 30

# of items in display

When higher order analysis or integration of multiple features is required, search is much harder, and reaction time rises with number of distractors.

slide30

Detecting absence of a feature

Look for circle missing the free line

ending

among

slide32

Detecting presence of a feature

Look for circle with the free line

ending

among

slide34

How do we make an object

out of a pile of features?

word recognition a case study
Word Recognition: A Case Study
  • Frequency Effects
  • Word Frequency: Frequent words are recognized more easily
  • Repetition Priming:Words seen recently are perceived more easily
  • Context Effects
  • Word Superiority: Individual letters are easiest to identify when they are part of a word (work vs. orwk)
  • Well-formedness: Individual letters are recognized more easily as part of “word-like” stimuli than in a random strings of letters (lipe vs. lpei).
w o r d
w o r d

An item will appear

slide37
k

An letter will appear

slide38

Guess = 1/5 correct

WORD

WORK

WORM

WORE

WORN

Guess = 1/26

correct

Word superiority

WORD

_ _ _ _

D

_

slide39

K

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WORD

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RWOD

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This “forced-choice” procedure controls for the effects of guessing, and confirms the validity of the word superiority effect.

slide40

K

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D

WORD

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ZORD

XXXX

K

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D

D

XXXX

interactive activation model explains the word superiority effect
Interactive Activation Model explains the word superiority effect
  • Letters in words benefit from bottom-up and top-down activation
  • But letters alone receive only bottom-up activation.
slide42

WORD

WORK

K

XXXX

D

WORD

K

D

features

K

XXXX

D

K

D

D

features

slide45

A simple “feature net” model of word recognition

TORQUE vs.

•baseline activation: in the absence of direct stimulation. This is sensitive to recency and frequency of stimulation.

•activation level: how active is a particular detector at a given moment

•response threshold: how much excitatory input does a detector require before it “fires” and sends excitatory input further downstream.

slide46

CQRN

CQRN

slide48

Interactive Activation Model (IAM):

(McClelland & Rumelhart)

Previous models posed a bottom-up flow of information (from features to letters to words).

IAM also poses a top-down flows of information

In addition, detectors at the same level interact with each other.

Another important aspect of this theory is the presence of inhibitory connections between detectors that are inconsistent with each other...

interactive activation model explains the word superiority effect1
Interactive Activation Model explains the word superiority effect
  • Letters in words benefit from bottom-up and top-down activation
  • But letters alone receive only bottom-up activation.
slide51

WORD

WORK

K

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WORD

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D

features

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features