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Cognitive Psychology > Midterm > Flashcards

Midterm Flashcards

1
Q

Scholasticism

A

The philosophical systems and speculative tendencies of various medieval Christian thinkers, who, working against a background of fixed religious dogma, sought to solve philosophical problems with intellect, realism and nominalism. Merged classical thinking and Christian doctrine. Science still not applied to the mind.

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2
Q

Roger Bacon (1620)

A

Father of scientific method
Not focused in religion, goal was to improve life/humanity

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3
Q

Materialism

A

Belief that one type of “stuff” makes up the universe. Not liked by the Catholic Church, who thought it was anti-religious

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4
Q

Dualism

A
  • Separation of the mind and body
  • Offered some explanation of how cognition was not materialistic
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5
Q

Bell-Magendie Law (1811)

A
  • Charles Bell
  • Spine is the cause of all sensation and movement
  • Per church: physical explanation for souls
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6
Q

Law of specific nerve energies

A
  • Johannes Müller
  • The mind has access to things that are only in the nerves (not real world)
  • The contents of the mind have no qualities in common with environmental objects but serve only as arbitrary signs or markers of those objects.
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7
Q

Applying Materialism to Mental Life: 2 Interpretations

A

- Materialism + Evolution → the adaption of the brain over the lifetime of the individuals (Herbert Spencer, Herman Ebbinghaus)
- Materialism + Methods → Consciousness as a subject matter (William Wundt)

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8
Q

3 schools of Psychology in late 19th century

A

Structuralists, Wurtzberg School, Act psychology

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9
Q

Structuralists

A

- Wundt,
- Method: introspection
- Focused on breaking down mental processes into the most basic components

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10
Q

Wurtzberg School

A

- Kulpe
- Methods: mixed.
- Hypothesizes existence of special states of consciousness—“thoughts”—which cannot be reduced to the sensory content.

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11
Q

Act psychology

A

- Brentatno
- More philosophical than empirical
- The mind is a symbol system

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12
Q

William Wundt

A

- Recognized as the founder of psychology
- Voluntarism (Wundt’s experimental psychology
- Volkerpsychologie (Wundt’s non-experimental psychology)

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13
Q

Voluntarism

A

- Wundt’s experimental psychology
- Meant to indicate voluntary, active, and willful nature of the mind
- Key was Apperception

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14
Q

Apperception

A

- Active intentional process involving will
- Mechanism of creative synthesis by which psychical elements and compounds are synthesized into experience
- Key to Wundt’s Voluntarism theory

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15
Q

Volkerpsychologie

A

- Wundt’s non experimental psychology (cultural psychology)
- Precursor to social psychology cultural psychology, and personality

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16
Q

Wundt’s goal of psychology

A

To analyze experience in terms of component elements and compounds

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17
Q

Two types of experience

A

- Mediate experience: domain of natural science
- Immediate experience: domain of psychology

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18
Q

Experimental self-observation

A

- Wundt’s self described experimental methd
- Observer presented with stimulus condition and instructed to be in a state of readiness

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19
Q

Tridimensional theory of feeling

A

Wundt’s theory that all emotions take place on three separate continua: pleasant-unpleasant, tension-relaxation, excitement-depression

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20
Q

Ebbinghaus

A
  • Forgetting curve
  • Wanted to study associations as they were being formed
  • Nonsense syllables method
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21
Q

Systematic experimental introspection

A

- Observers would experience what ever stimuli or events they were supposed to experience and then provide comprehensive account of mental processes
- Pioneered by Kulpe

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22
Q

Imageless Thought

A

- Pioneered by Kulpe
- Observers reported forming images of weights when lifted them but reported there was no sensory or imaginal content present when they made judgments

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23
Q

Gestalt Psychology

A

- Koffka, Wertheimer, and Kholer
- Sought to explain perceptions in terms of gestalts rather than by analyzing their constituents.

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24
Q

Behaviorism

A

- Goal to predict behavior or show how classical and operational conditions can account for behavior
- Methods cannot be subjective, introspection as a method in invalid
- Pioneered by Watson

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25
Q

Neobehavioraism

A
  • These psychologists were interested in theory, focusing their research on learning and motivation
  • Neobehaviorism (muscle twitch psych)-reflex is a functional relation
  • Hull, Skinner, Tolman
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26
Q

Introspection Method Goal

A

To find the basic units of mental life underlying consciousness

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27
Q

Cognitive Method Goal

A

To figure out which representations and which processes the mind uses

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28
Q

What was Behaviorism unable to account for?

A

Ethology and Language

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29
Q

Cognition Movement

A

- The goal is to account for behavior, but the focus is on mental life as unconscious
- Method: Explanation = processes that manipulate internal representations

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30
Q

Principles of Cognition

A

-Symbols replace S-R/conditioning as the unit of thought
- Mental life is unconscious
- Intervening variables could exist
- Existence of hypothetical constructs (e.g. strategy, mental images)

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31
Q

What was Cognition unable to account for?

A

How can we avoid “tricking” ourselves if we are allowed to make up what a mental representation is?

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32
Q

Four positions on cognition

A

1. Study computation without the brain
2. Study computation but leave out cognition
3. Start with mapping theory
4. Brain is involved in construct development

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33
Q

Informational description

A

- Related to 4th position on cognition
- Mental events can be described in terms of “input” “operation” and “output”

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34
Q

Recursive decomposition

A

- Related to 4th position on cognition
- You can decompose each even into a more basic event, but at some point you hit a primitive that is not further reducible at a functional level

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35
Q

How did cognitive psychologists respond to the issue of “made up” constructs

A
  • Neural constraints
    -Formal models
  • Evolution
  • Behavioral measures
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36
Q

Two types of long-term memory

A

Type - enduring representation
Token - duplicate of the representation you create to manipulate in your mind

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37
Q

Information Theory

A
  • Quantitative approach to psychology
  • Was meant to be a way of thinking of human information processing that was going to constrain theory
  • Logarithmic relationship between information and reaction time
  • Way of measuring information irrespective of content
  • Valuable as one way of describing the environment
  • Mapping theory
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38
Q

Donders Subtraction Technique

A

Perception and motor time = time required for simple task
Discrimination time = time for discrimination task minus simple task
Choice time = time for choice task minus discrimination time.

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39
Q

Miller’s Law

A

The number of objects an average human can hold in short term memory is 7 + 2

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40
Q

Key Features of Cognitive Strategy

A
  • Develop alternate methods of processing
    • e.g. search (serial: exhaustive, serial: self-terminating, parallel)
  • Derive signature predictions of each models
  • Obtain data that allow comparison
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41
Q

Mental Chronometry

A
  • Discrete stimulus = Task C - Task A
  • Response Selection = Task B - Task C
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42
Q

Sternberg’s Additive Factors

A

Use positive sets to as base stimuli
Subject responds if a number is in the set
Step 1: Specify a model
Step 2: Identify the stages with different IV and DVs

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43
Q

Independence problem in additive factors

A

Method assumes that each step of the model is independent

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44
Q

Signal Detection Theory

A

Testing how far a patient falls from the line between hit rate and false alarm rate

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45
Q

Types of Cognitive Methods

A
  • EEG
  • Single Cell Recording
  • fMRI
  • Testing patients with lesions to the brain
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46
Q

Single Cell Recording

A
  • Records the activity of a single neuron in an animal
  • Method: place a wire through a hole made in skull
  • Benefits: precise temporal information and location of information (after repeated testing)
  • Issues: highly invasive-not done on humans
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47
Q

EEG

A
  • Pros
    • Noninvasive
    • Can be used in little kids
    • Temporal resolution is great
    • Can look at interaction of processes
    • Inexpensive
  • Cons
    • Most confident about cortical results
    • You need a lot of trials
    • Real possibility of carryover effects
    • Using the same stimulus set
    • Not very interpretable to people outside of the field
48
Q

fMRI

A
  • Pros
    • Spatial and temporal resolution are good
    • You can do an anatomical span
  • Cons
    • Cost
    • Things messing up the signal
    • So much data that you can do shady data processes or fool yourself
49
Q

Four Methods of Using Neurological Data

A
  1. Single Cell
  2. Use before theory development to guess what is happening
  3. Look at brain to confirm theory
  4. Use brain data to add validity to a psych theory
50
Q

Evolutionary Psychology

A

Initially intended to analyze cognitive abilities in tandem with likely selective pressures and reverse engineer development

51
Q

Task analysis

A
  • David Marr
  • Cash register analogy- take something you can’t see the insides of and look at output-deduce what function is from behavior
  • Evolutionary psych aims to look at output and deduce how it is key to survival
52
Q

Franz Brenatno

A
  • Founded Act psychology, molar psychology that called for a larger unit of analysis in looking at consciousness
  • Foreshadowed American functional psychology and Gestalt psychology
  • Originated idea of “Experimentium Crucis”
53
Q

Experimentium Crucis

A
  • Proposed by Brentano
  • Science best served by a few grand experiments testing big questions
54
Q

Oswald Kulpe

A
  • Structuralist, Wertzberg School
  • Came up with systematic experimental introspection, imageless thoughts, and mental sets
55
Q

Survival Memory Effect

A
  • Implant bias judgment- word test then memory test
  • 1 group makes word judgements based in likeability, the other makes judgements based on use in wilderness survival (on a grassland), one makes judgment about survival in a new city
  • Increased memory occurs in grassland condition
  • Nairne
56
Q

Criticisms of Evolutionary Psych

A
  • Post-hoc explanation of findings - finding causal explanations for phenomenon
  • Swiss Army knife phenomena not good because assumes one does not impact others
  • People who apply evolution to psych are not biologists
  • Once you get to technology and culture, things get much more complicated
57
Q

Driving force behind mathematical psychology

A

William Estes

58
Q

Purpose of computational modeling of psych

A
  • Reduce and order data
  • Qualitative data → quantitative data (Scaling theory)
  • Quantify qualitative models
  • From the world we abstract a model, from the model we derive a prediction, from the prediction we interpret data.
59
Q

Model fitting

A
  • Metric that includes the quality of the fit and the ratio of free paramaters to data accounted for
  • Not additive
  • What you need to do is model comparison
60
Q

Diffusion model

A
  • Model of choice for reaction time
  • Stimulus encoding process- each count of time (millisecond) is information accumulating
61
Q

Why is it better to compare mathematical models rather than just make them?

A
  • Comparing models forces specificity
  • Makes models more concrete and makes sure you know what is going
62
Q

Advantages of computational models

A
  • If you are modeling something complex, very difficult to keep in your head
  • Computational models are explicit
  • Computational models force you to be specific
63
Q

Criticisms of computational models

A
  • Frequently not clear what central features of a model are just by looking at the model
  • Once models get complicated, very difficult to assign meaning definitively
  • Number of free parameters is an unresolved issue
64
Q

Intentionally

A

How representations come to bear meaning

65
Q

Grounded representations

A

Representations that are perceptual or motor

66
Q

Who investigated the functional role of representations?

A

Arthur Markman

67
Q

Four types of representation

A
  1. Spatial Representation
  2. Feature Model
  3. Semantic Network
  4. Structured Representation
68
Q

Pros of Spatial Representation

A
  • One dimension of space for what we are trying to represent
  • Uses continuous units
  • Relationally obvious
  • Can change things or add mechanisms to a spacial model
  • Can stretch or compress
  • Simplicity of model is best aspect
69
Q

Cons of Spatial Representation

A
  • No direct access to to features that made judgment
  • Model is useful when speed is prioritized over detail
  • All dimensions play and equal role unless specified
70
Q

Pros of Feature Representation

A
  • Uses discrete unites
  • Features stay determined
  • Example: Cold/Flu with symptoms represented as (+) or (-) for presence or absence.
71
Q

Cons of Feature Representation

A
  • Not clear about what factors should be added
  • Compromise between spatial and semantic network
72
Q

Pros of Semantic Network

A
  • Very good at relationships among concepts and associations
  • Example: Network analysis
  • Good at relations where they are explicit
73
Q

Cons of Semantic Network

A
  • People also don’t describe objects with hierarchy in mind
  • Power (too powerful)
  • 1 node per concept does not allow for wrong information or lack of info (must know everything about everything in concept)
    -Does not allow for slow separation of representativeness (assimilation-accommodation)
74
Q

Semantic Network: Marking Passing

A
  • Tried to deal with choosing features
  • Only specify as needed
  • At base-only relevant to one representation
  • Efficiency os also considered
  • Made when we were concerned about brain space
75
Q

Semantic Network: Spreading Activation

A
  • Weights are added to connections
  • Labels are lost
  • Activation is graded in representations
  • Example: Network analysis
76
Q

Pros of Interactive application model

A

Deals with multiple constraints simultaneously

77
Q

Pros of cascading model

A
  • As some parts become active, they reach down and start inhibiting other representation
  • Uses top down processing to constrain likelihood of lower process of representation
78
Q

Structured representation

A
  • Rich information about how how parts of representation relate and work as a part of the whole representation
  • Takes an argument and varies kinds of arguments or relationships
  • Come from AI and computer intelligence
  • Restricts the scope of a represational element
  • Three type examples: Schemas, Frames, Scripts
79
Q

Schemas

A

A cognitive framework or concept that helps organize and interpret information.

80
Q

Script

A

A form of memory structure that evolve over multiple exposure to the same set of stimuli and/or repeated enactment of a particular behavior.

81
Q

Parallel Processing Models

A

A set of system in which memories are stored and retrieved in a system consisting of a large number of simple computational elements, all working at the same time and all contributing to the outcome.

82
Q

Distributed Models

A
  • In distributed models you have to look at contributing units to understand a pattern
  • Uses “neuron like” elements
  • Good at pattern completion (e.g. memory is a pattern completion tool)
  • Assign default for missing features
  • Output gets corrective feedback and slowly changes
83
Q

Weaknesses of Distributive Models

A
  • Catastrophic interference
  • Not good at sequential modeling
  • Cannot explain rule based behavior
  • Neuron like elements oversell the connection to biology/neruo
  • Computational power is debated
  • Hard to understand
84
Q

4 Common Types of Categorization

A
  1. Classical/rule based view
  2. Prototype view
  3. Exemplar view
  4. Category/boundary view
85
Q

Classical/rule based view

A
  • Category is an object
  • Concept is a mental representation of category/necessary and sufficient features
  • Example: Trunk, big ears, tusks = Elephant
86
Q

Prototype View

A
  • Categorization is the central tendency of all the different members of the category
  • Concept = a representation that has all the features that are typical of the concept
  • Computationally efficient but less practical
  • “Typical” object is represented and compared with other prototypes
87
Q

Exemplar View

A
  • Structure/process trade off
  • New stimuli were saved amongst all seen examples
  • Can be used to make a prototype
  • See at encoding → store each exemplar → derive prototype if needed
88
Q

Category/Boundary view

A
  • The distance from a boundary explains the the similarity/typicality of a result
  • The distance from a boundary explains the the similarity/typicality of a result
  • Compliment to prototype view but looks at periphery rather than the category itself
89
Q

Issues with Similarity Model

A
  • Dependent of self selected features (we identify what seems important)
  • Sometimes certain features have outsized importance
  • Rules matter, and exceptions exist
90
Q

Rule X Model

A
  • Derived by Nosofsky
  • People are lazy and just do what is easiest
  • They are likely to made a general rule and memorize exceptions
  • Perceptual categorization is really important for experts
91
Q

Role based categorization

A
  • Also called categorization expansion
  • Categorization is based on relationship with other categories
  • Focused placed on extrinsic rather than intrinsic factors
92
Q

Frames

A
  • Schema that helps organize a situation
  • Helps attend to relevant features
93
Q

Propositions

A
  • Ways of storing complex information in schemas
  • Can predict connections between words
94
Q

4 main cues for connecting propositions

A
  • Similarity (about the same thing)
  • Connectivity (key word connecting the sentences)
  • Causality (one thing causes another)
  • Setting (things happening in same place)
95
Q

How does the human brain tend to identify objects?

A

Shape

96
Q

Inverse projection problem

A

Three dimensional space can project an infinite number of 2 dimensional images on the retina

97
Q

Viewpoint independence

A

We are pretty good at identifying objects from different viewpoints

98
Q

4 Types of Model Features

A
  1. Primitive elements
  2. Reference frame
  3. Relations of primitive elements
  4. Parts vs. whole
99
Q

How do we know what things are from different perspectives?

A

4 types of model feature theories

100
Q

Primitive Elements

A
  • Vertices/lines or geometric solids
  • We are better identifying things with vertices intact than lines intact
101
Q

Reference Frame

A
  • Viewer centered
  • Object centered
  • Hybrid
102
Q

Relations of primitive elements

A
  • Coordinates in space
  • Relative relations like above/below
  • Sometimes called categorical
103
Q

Parts vs. whole

A
  • Analytic vs. holistic
  • Analytic: different parts of elephant together = elephant
  • Holistic: face = face (parts don’t look like anything on their own - knowing this is a face depends on spatial relationship of objects).
104
Q

View Based Model

A
  • Vertices
  • Viewer-centered
  • Coordinates in space
  • Holistic
105
Q

3D Matching Models

A
  • Lines, gemetrics solids
  • Hybrids
  • Coordinates in space
  • Analytic
  • Matching what is out in world into back projection
106
Q

Structural Description Models

A
  • Geometric solids
  • Object centered, viewer centered, hybrid
  • Relative relations like above/below
  • Analytic
107
Q

Biederman’s Model

A
  • Addresses viewpoint independence by introducing geons
  • Too effective
  • Can ID shape from obstructed view but too well
108
Q

Why is it difficult to compare models of object recognition?

A

Any object can be recognized if you have enough 2D representations of it

109
Q

Tarr’s viewer centered experiments

A
  • Used geons to show that the model expected better reconciling of viewpoint independence than was true
  • Found that people could not really ID objects in space if not trained on them
110
Q

Geons

A

Shapes of different rotations that could form different common objects

111
Q

Categorical verus coordinate change in object recognition

A

Studies suggest we are more sensitive to categorical change in objects

112
Q

Two viewpoints in visual object recognition

A
  • Psychological reality and the brain
  • Brain as a model system
113
Q

Problems with DCNN

A
  • Need more varied training that is more similar to how humans are trained visually
  • Don’t compare to human data but rather how we see neurophysiology respond
  • Do not account for cortical Specialization
114
Q

Deep convolution neural networks (DCNN)

A
  • Receive images as an input and use them to train a classifier
  • The network employs a special mathematical operation called a “convolution” instead of matrix multiplication
  • The architecture of a convolutional network typically consists of four types of layers: convolution, pooling, activation, and fully connected.
115
Q

Flow Diagram of Attention

A
  • Broadbent
  • Post WWII examining control tower operators attention (1950’s)
116
Q

Is Taxonomy effective in the study of attention?

A

No

117
Q
A

Cognitive Psychology (1 decks)

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