Cognitive Psychology Exam 2 Studyguide
Difference between analog and propositional code:
● Analog code: Mental representations that preserve the perceptual characteristics of the original stimulus
○ Often called “picture-like” representations
○ Example: When you imagine your bedroom, you can "see" the spatial layout and details
● Propositional code: Mental representations that store information as abstract, language-like symbols or
relationships
○ Example: “The book is on the table” – knowledge is represented as a statement, not a visual image
○ More efficient for facts and relationships than detailed visual information
● Key difference: Analog codes retain perceptual/spatial properties, propositional codes represent meaning
and relationships abstractly
Visual imagery and Interference:
● Visual imagery interferes with visual perception
○ Hard to focus on two activities that both deal with sound
■ Imagine tree outline → cant detect blue arrow
■ Imagine sound of oboe → can detect arrow (different sensory modality)
Research findings on ambiguous figures:
● Mental imagery is an analog format; makes it difficult to accommodate for the effect of ambiguous figures
(use propositional)
● Ambiguous figures: Images that can be perceived in more than one way (rabbit/duck)
● A strong verbal code may overshadow a weak analog code
● Propositional for more complex figures; analog for simple
Spatial framework model:
● A model describing how humans represent spatial relationships in three dimensions in mental imagery:
○ People mentally encode spatial relations differently depending on axes of orientation:
■ Depth axis (front–back) → largest errors
■ Horizontal axis (left–right) → moderate errors
■ Vertical axis (up–down) → smallest errors
Reasoning: Humans are more accurate along the vertical axis because gravity provides a
strong reference; depth is hardest to judge mentally and because we won't confuse our
heads with our feet
Applications: Explains why people make systematic errors when imagining rotations or
spatial layouts
Rotation versus alignment heuristic:
● Rotation Heuristic: a figure that is slightly tilted will be remembered as being either more vertical or more
horizontal than it really is
○ People mentally rotate objects or maps to align them with a familiar orientation (e.g., north-up
maps)
○ Can lead to systematic distortions: overestimating angles or distances when objects are misaligned
from familiar axes
, ● Alignment Heuristic: a series of separate geographic structures will be remembered as being more lined up
than they really are
○ People mentally “straighten” misaligned objects or regions so they appear more aligned with
familiar grids (e.g., assuming cities line up neatly along latitude)
○ Can cause distorted distance and direction judgments
General findings of auditory imagery research:
● Pitch: characteristic of a sound stimulus that can be arranged on a scale from low to high
○ The distance between two actual sounds is correlated with the distance between two imagined
sounds
● Timbre: the sound quality of a tone
○ Timbre of an actual instrument is similar to the cognitive representation for the timbre of an
imagined instrument
● Pitch and timbre are preserved: People can recognize melodies and familiar sounds in their mind accurately
Boundary Extension:
● Concept: A memory phenomenon where people remember seeing more of a scene than was actually shown
○ Key idea: When viewing a picture, the brain automatically extrapolates beyond the edges, filling
in likely surroundings
○ Example: Seeing a close-up photo of a table, later recalling the table as larger or seeing more of
the surrounding room
Exemplar vs. Prototype Approach
● Prototype Approach: Concepts are represented by a single “average” or idealized example (the prototype)
of a category
○ New items are categorized based on similarity to this prototype
○ Example: For the category “bird,” a robin might serve as the prototype
● Exemplar Approach: Concepts are represented by all known examples of the category, not just an average
○ New items are categorized based on similarity to stored examples
○ Example: For “bird,” you compare a new bird to all birds you know (sparrow, penguin, eagle, etc.)
Collins and Loftus Model (Spreading Activation Model)
● Concept: A semantic network model of memory
● Structure:
○ Concepts are represented as nodes
○ Related concepts are connected by links
● How it works: Activation spreads from one node to related nodes
○ Example: Thinking about “dog” may activate “cat,” “pet,” and “animal”
● Strength of connection: Determines how quickly activation spreads
Parallel Distributed Processing (PDP) Approach
● Also called: Connectionist or neural network models.
● Basic Principles:
○ Knowledge is represented as patterns of activation across many units (nodes)
Difference between analog and propositional code:
● Analog code: Mental representations that preserve the perceptual characteristics of the original stimulus
○ Often called “picture-like” representations
○ Example: When you imagine your bedroom, you can "see" the spatial layout and details
● Propositional code: Mental representations that store information as abstract, language-like symbols or
relationships
○ Example: “The book is on the table” – knowledge is represented as a statement, not a visual image
○ More efficient for facts and relationships than detailed visual information
● Key difference: Analog codes retain perceptual/spatial properties, propositional codes represent meaning
and relationships abstractly
Visual imagery and Interference:
● Visual imagery interferes with visual perception
○ Hard to focus on two activities that both deal with sound
■ Imagine tree outline → cant detect blue arrow
■ Imagine sound of oboe → can detect arrow (different sensory modality)
Research findings on ambiguous figures:
● Mental imagery is an analog format; makes it difficult to accommodate for the effect of ambiguous figures
(use propositional)
● Ambiguous figures: Images that can be perceived in more than one way (rabbit/duck)
● A strong verbal code may overshadow a weak analog code
● Propositional for more complex figures; analog for simple
Spatial framework model:
● A model describing how humans represent spatial relationships in three dimensions in mental imagery:
○ People mentally encode spatial relations differently depending on axes of orientation:
■ Depth axis (front–back) → largest errors
■ Horizontal axis (left–right) → moderate errors
■ Vertical axis (up–down) → smallest errors
Reasoning: Humans are more accurate along the vertical axis because gravity provides a
strong reference; depth is hardest to judge mentally and because we won't confuse our
heads with our feet
Applications: Explains why people make systematic errors when imagining rotations or
spatial layouts
Rotation versus alignment heuristic:
● Rotation Heuristic: a figure that is slightly tilted will be remembered as being either more vertical or more
horizontal than it really is
○ People mentally rotate objects or maps to align them with a familiar orientation (e.g., north-up
maps)
○ Can lead to systematic distortions: overestimating angles or distances when objects are misaligned
from familiar axes
, ● Alignment Heuristic: a series of separate geographic structures will be remembered as being more lined up
than they really are
○ People mentally “straighten” misaligned objects or regions so they appear more aligned with
familiar grids (e.g., assuming cities line up neatly along latitude)
○ Can cause distorted distance and direction judgments
General findings of auditory imagery research:
● Pitch: characteristic of a sound stimulus that can be arranged on a scale from low to high
○ The distance between two actual sounds is correlated with the distance between two imagined
sounds
● Timbre: the sound quality of a tone
○ Timbre of an actual instrument is similar to the cognitive representation for the timbre of an
imagined instrument
● Pitch and timbre are preserved: People can recognize melodies and familiar sounds in their mind accurately
Boundary Extension:
● Concept: A memory phenomenon where people remember seeing more of a scene than was actually shown
○ Key idea: When viewing a picture, the brain automatically extrapolates beyond the edges, filling
in likely surroundings
○ Example: Seeing a close-up photo of a table, later recalling the table as larger or seeing more of
the surrounding room
Exemplar vs. Prototype Approach
● Prototype Approach: Concepts are represented by a single “average” or idealized example (the prototype)
of a category
○ New items are categorized based on similarity to this prototype
○ Example: For the category “bird,” a robin might serve as the prototype
● Exemplar Approach: Concepts are represented by all known examples of the category, not just an average
○ New items are categorized based on similarity to stored examples
○ Example: For “bird,” you compare a new bird to all birds you know (sparrow, penguin, eagle, etc.)
Collins and Loftus Model (Spreading Activation Model)
● Concept: A semantic network model of memory
● Structure:
○ Concepts are represented as nodes
○ Related concepts are connected by links
● How it works: Activation spreads from one node to related nodes
○ Example: Thinking about “dog” may activate “cat,” “pet,” and “animal”
● Strength of connection: Determines how quickly activation spreads
Parallel Distributed Processing (PDP) Approach
● Also called: Connectionist or neural network models.
● Basic Principles:
○ Knowledge is represented as patterns of activation across many units (nodes)
