Feature Integration Theory

Front 1

What is the Binding Problem?

Back 1

Selective Attention Problem of how it is we are able to have stable representation of the world full of integrated objects whilst avoiding confusing these features (colours, size, motion, etc) with other objects

Front 2

What defines the binding problem?

Back 2

1) Many Stimuli in visual scene

2) Specialised modules process visual scene: much evidence for this
Dorsal Pathway: motion
Ventral Pathway: Colour Shape

Parietal Lobe combines these

Large amount of space taken up by specialised modules --> how do receptor fields not conflict with one another
i.e. activated red feature and motion feature: how do we not confuse reality (i.e. moving green object and red stationary object) with imagination (moving red object)

Front 3

1) What does FIT stand for?

2) Who created the theory?

Back 3

1) Feature Integration Theory

2) Treisman and Gelade (1980)

Front 4

Briefly describe FIT

Back 4

Objects: several features (colour, shape, size, etc)

Features perceived by Specialised Modules : FEATURE MAPS.
Feature maps analyse specific features: automatically, parallel and pre-attentively (unconscious perception)

Information: "Flags" features in visual field & implicit information on spatial location

Feature maps then combine to create MASTER MAP: requires attention --> allows object perception and representation

Front 5

What are the assumptions of FIT?

Back 5

1) Features are free-floating until bound by object representation

2) Object representation occurs AFTER conscious attention allocated to feature maps

Front 6

What is the main support for FIT?

Back 6

1) Visual Search: e.g. Neisser

2) Illusionary conjunction: Treisman & Schmidt (1997??)

Front 7

Explain Visual Search tasks

Back 7

Feature Search: target differs from distractor by one feature

Conjunction: Target shares two, or more features with distractors

Front 8

Explain the assumptions of FIT on visual Search Tasks

Back 8

Feature: Easy and Fast, can be done without conscious attention, flag information from feature allows it to "pop out" of visual scene. Can be done in parallel
Display size does not impact on the performance.
e.g. Hubel & Weisel (1987?)

Conjunction: Harder and slower, cannot be done without conscious attention, needs to bind features to spatial location to be able to process similarities and differences and needs to be done serially
e.g. Neisser (1964; 1967)

Front 9

Explain Illusionary Conjunctions

Back 9

Brief presentation impairs the binding of features which in turn impairs the perception of visual scene (i.e. causes illusions)