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Summary Introduction to Cognitive Science midterm

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Summary of the book Cognitive Science by Friedenberg, Silverman and Spivey (4th edition). Includes chapter 1, 2, 3, 4, 5 & 9 Midterm Tilburg University, Cognitive Science and Artificial Intelligence 1st Year Includes summaries of the practicals language + memory (both articles and videos)

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Introduction to Cognitive Science -
midterm
Don’t forget to do the online quizzes and work with the flashcards. On the exam, names and dates will not be asked.

Flashcards in yellow
Names in orange

Index
Chapter 1 Introduction: Exploring Mental Space.............................................................................................................2
Representation............................................................................................................................................................2
Computation................................................................................................................................................................4
The interdisciplinary perspective.................................................................................................................................5
Chapter 3 The Psychological Approach............................................................................................................................7
What is psychology?....................................................................................................................................................7
Psychology and the scientific method.........................................................................................................................8
Intelligence tests..........................................................................................................................................................8
Mental atoms, mental molecules, and a periodic table of mind: the voluntarist movement......................................9
Structuralism: what the mind is.................................................................................................................................10
Functionalism: what the mind does..........................................................................................................................11
The whole is greater than the sum of its parts: mental physics and the Gestalt movement.....................................11
Mini minds: mechanism and psychoanalytic psychology...........................................................................................13
Mind as a black box: the behaviorist approach.........................................................................................................14
Overall evaluation of the psychological approach.....................................................................................................15
Chapter 2 The Philosophical Approach..........................................................................................................................15
The mind-body problem: what is mind?....................................................................................................................15
Monism..................................................................................................................................................................... 16
Dualism...................................................................................................................................................................... 17
Functionalism: are minds limited to brains?..............................................................................................................18
The knowledge acquisition problem: how do we acquire knowledge?.....................................................................19
The mystery of the consciousness: what is consciousness and how does it operate?...............................................20
Evaluating the emergent view of mind......................................................................................................................21
Overall evaluation of the philosophical approach.....................................................................................................24
Chapter 4 The Cognitive Approach I..............................................................................................................................24
The rise of cognitive psychology................................................................................................................................24
The cognitive approach: mind as an information processor......................................................................................25
Modularity of mind....................................................................................................................................................25
Theories of vision and pattern recognition: how do we recognize objects?..............................................................25
Theories of attention: how do we pay attention?......................................................................................................29
Evaluating the model-building approach...................................................................................................................32
Chapter 9 The Linguistic Approach................................................................................................................................32
The nature of language..............................................................................................................................................33

, Language processing.................................................................................................................................................33
Language acquisition.................................................................................................................................................36
Language deprivation................................................................................................................................................38
Language use in nonhuman animals..........................................................................................................................39
Neuroscience and linguistics: the Wernicke-Geschwind model.................................................................................40
Artificial intelligence and linguistics: natural language processing............................................................................42
Chapter 5 The Cognitive Approach II.............................................................................................................................42
Types of memory: how do we remember?................................................................................................................42
Memory models........................................................................................................................................................45
Visual imagery: how do we imagine?........................................................................................................................46
Concepts: how do we represent our knowledge of concepts?..................................................................................47
Problem solving: how do we solve problems?...........................................................................................................49
Overall evaluation of the cognitive approach............................................................................................................51
Practical 2 Language......................................................................................................................................................51
Piantadosi, Tily & Gibson (2010) Word lengths are optimized for efficient communication......................................51
Video: How Efficiency Shapes Human Language – E. Gibson.....................................................................................53
Practical 3 Memory........................................................................................................................................................54
Greenspan (2020) Pandemics and infodemics: Research on the effects of misinformation on memory....................54
Video: How reliable is your memory? – E. Loftus.......................................................................................................55
Cognition = the mental action/process of acquiring knowledge and understanding through thought, experience and
the senses. Cognition is a fundamental aspect of human intelligence that shapes how we perceive, interact with and
adapt to our environment.
 DSM 5 defines 6 key elements of cognitive function: complex attention, executive function, learning and
memory, language, perceptual-motor control and social cognition.
 5 primary cognitive skills are reading, learning, remembering, logical reasoning and paying attention.

Chapter 1 Introduction: Exploring Mental Space
The human mind is difficult to study; it is not something easy to observe, measure or manipulate. In addition, the
mind is the most complex entity in the known universe.

Cognitive science = the scientific interdisciplinary (among them philosophy, psychology, linguistics, artificial
intelligence, robotics and neuroscience) study of the mind. Its primary methodology is the scientific method.
 It is not the sum of different disciplines, but rather a collaborative effort.

Computation = information processing.
 Cognitive scientists started out viewing the mind as an information processor. Information processors must
both represent information and transform information.
 A mind must incorporate some form of mental representation and processes that act on and manipulate
information.
 This perspective also compares the mind to computers, as computers are information processors.
Information is input into our minds through perception. It is stored in our memories and processed in the form of
thought. Our thoughts can then serve as the basis of outputs, such as language or physical behavior.

Representation
Representation = something that stands for something else.
 It is seen as fundamental to cognitive science.
 4 categories:

2

, 1. A concept stands for a single entity or group of entities. Single words are good examples of concepts.
 Eg. the word apple
2. Propositions are statements about the world and can be illustrated with sentences.
 Eg. Mary has black hair.
3. Rules are another form of representation that can specify the relationships between propositions.
 Eg. If it is raining, I will bring an umbrella.
4. An analogy helps us make comparisons between two similar situations.

There are 4 crucial aspects of any representation:
1. A ‘representation bearer’ (eg. human/computer) must realize a representation.
2. A representation must have content; meaning it stands for one or more objects.
 Referents = the thing(s) in the external world that a representation stands for.
3. A representation must be ‘grounded’  referent and representation come to be related.
4. A representation must be interpretable by some interpreter, either the representation bearer or somebody
else.

The fact that a representation stands for something else means it is symbolic.
 Eg. the Euro sign (€) stands for money (referent).

Human mental representations, especially linguistic ones, are said to be semantic = they have meaning.

Intentionality = directed on an object.
 A representation’s meaning is derived from the relationship between the representation and what it is about.
 Mental states and events are intentional; they refer to some actual thing or things in the world.
 Important characteristic of intentionality  appropriate causal relation = an intentional representation must
be triggered by its referent or things related to it. Activation of a representation (ie. thinking about it) should
cause behaviors/actions that are somehow related to the referent.
 Eg. the Euro sign makes you think about real life money.

Symbols can be assembled into formal logical systems = in these systems, symbols are combined into expressions.
These expressions can then be manipulated using processes. The result of a process can be a new expression.

Physical symbol system hypothesis (PSSH): a formal logical system can allow for intelligence. Since we as humans
appear to have representational and computational capacity, being able to use things that stand for things, we seem
to be intelligent.
 Critique: symbol grounding problem = the symbols that computers use have no meaning or semantic quality.
To be meaningful, symbols have to be connected to the environment in some way. People seem to have
meaning because we have bodies and can perceive things and act on them.
 Counterargument: computer systems do have the capability to designate  an expression can designate an
object if it can affect the object itself or behave in ways that depend on the object.

Types of representation
Research shows that there are numerous forms of mental representation.

Thagard (2000) proposes 4: concepts, propositions, rules and analogies.
 Concept = an idea that represents things we have grouped together (abstract ideas, eg. chair).
 Proposition = a statement or assertion typically posed in the form of a simple sentence. An essential feature
of a proposition is that it can be proved true or false. Logical conclusions are only as reliable as the premises
on which they are based. Propositions are more sophisticated representations than concepts because they
express relationships between concepts.
 Syllogism  2 premises followed by a conclusion
o Premise 1: all men like football.
o Premise 2: Charlie is a man.
o Conclusion: Charlie likes football.
 Production rule = if X, then Y (X and Y are propositions).
3

, o Antecedent = the ‘if’ part of the rule.
o Consequent = the ‘then’ part of the rule.
o In a production system, ‘if’ is the condition, ‘then’ is the action.
o Eg. If the light is red, you step on the brakes.
 Analogy = applying knowledge you already possess to new situations.
o Useful forms or representations as they allow to generalize learning.

Rules bring up the question what knowledge really is:
 Declarative knowledge = used to represent facts  verbal communication (eg. telling the capital of Cuba).
 Procedural knowledge = refers to skills  action (eg. showing you can skate).
 It is important that information-processing systems have some way of representing actions if they are to help
an organism/computer perform those actions. Rules are just one way of representing procedural knowledge.

Computation
Representations by themselves are of little use unless something can be done with them. In the cognitive science
view, the mind performs computations on representations. We should think of mental operations as falling into
broad categories. These categories can be defined by the type of operation that is performed or by the type of
information acted on  sensation, perception, attention, memory, language, mathematical reasoning, logical
reasoning, decision making, problem solving, etc.

The Tri-Level Hypothesis
Any given information process can be described at several different levels.

The Tri-Level Hypothesis states that biological or artificial information-processing events can be evaluated on at least
3 different levels:
1. Computational level
 One is concerned with two tasks:
o Specification and clarification of the problem.
o The purpose/reason for the process.
 Adaptiveness = the idea that biological mental processes are learned or have evolved
to enable the organism to solve a problem it faces.
2. Algorithmic level/programming level
 Inquiring about the way in which an information process is carried out  need for an
algorithm/formal procedure/system that acts on informational representations.
o Algorithms can be carried out regardless of a representation’s meaning; algorithms act on
the form, not the meaning of the symbols they transform.
o Algorithms are formal and well defined. Each step is known. An example is a mathematical
formula.
 The type of description of the transformed data, the steps taken and the order of the steps is put
together at this level.
3. Implementational level/hardware level
 Formulates the most specific and concrete types of description.
 What is the information processor made of?
o Eg. the hardware of a computer is the screen, keyboard, etc. (physical stuff).
o Eg. biological condition is the brain and the neurons

We need the algorithmic level to tell us how a particular system performs a computation, as not all computational
systems solve a problem in the same way.

Critique on this system:
 It seems to be fundamentally simplistic since the levels clearly interact with one another and each level can
be further subdivided into its own sublevels.

Differing views of representation and computation
4

,There are 3 views on representation and computation: formal systems notion, connectionist/network approach and
dynamical perspective.
The view on computation just explained sees computation as being based on the formal systems notion. In this view,
a computer is a formal symbol manipulator:
 A system is formal if it is syntactic or rule governed.
 Syntax = refers to the set of rules that govern any symbol system.
 The rules of language and mathematics are formal systems because they specify which types of allowable
changes can be made to symbols.
 Formal systems also operate on representations independent of the content of those representations. A
process can be applied to a symbol regardless of its meaning or semantic content.
 A symbol is a type of representation and can assume a wide variety of forms and can undergo a wide variety
of manipulations. Manipulations implies that computation is an active, physical process that takes place over
time.

Another approach as to what computation is, is the connectionist/network approach:
Classical view Connectionist view/network approach
Knowledge is represented locally in the form Knowledge is represented as a pattern of neural activation, or a
of symbols. pattern of synaptic strengths that is distributed throughout a
network and is more global than a single symbol.
Processing occurs in discrete sequential Processing occurs in parallel through the simultaneous activation
stages. of many elements in the network.

Third view of representation is the dynamical perspective:
 The mind is constantly changing as it adapts to new information.
 A representation formed when we first learn a concept is altered each time we think about that concept or
experience information that is in some way related to it.

The interdisciplinary perspective
Metaphor: five men feeling different parts of an elephant do not guess what creature it is. The elephant is the mind
and the blind men are researchers in different disciplines in cognitive science. To understand the whole, results of
each discipline need to be compared in interaction with one another.

The philosophical approach [chapter 2]
Philosophy is the oldest of all the disciplines in cognitive science. Philosophers of mind narrow their focus to specific
problems concerning the nature and characteristics of mind:
 What is mind?
 How do we come to know things?
 How is mental knowledge organized?

The primary method of philosophical inquiry is reasoning:
 Deductive reasoning = involves the application of the rules of logic to statements about the world
o General  particular
o Eg. College students study 3 hours every night. Mary will study 3 hours every night.
 Inductive reasoning = observations about specific instances are used to draw general conclusions.
o Particular  general
o Eg. Daisy the dog has four legs. Therefore, all dogs have four legs.

Interdisciplinary crossroads: science and philosophy
New trend in philosophy going away from ‘armchair’ philosophy  experimental philosophy = uses empirical
methods, typically in the form of surveys that assess people’s understanding of constructed scenarios, to help answer
philosophical questions.

The psychological approach [chapter 3]


5

, Psychology is a relatively young discipline and it was the first discipline in which the scientific method was applied
exclusively to the study of mental phenomena  mind and behavior. They attempt to understand not just internal
mental phenomena, but also the external behaviors that these internal phenomena can give rise to.
The cognitive approach [chapter 4 + 5]
Cognitive psychology came into being in the 1960s, in part, as a backlash against the behaviorist movement and its
emphasis on behavior (and its neglect of mental computations). Cognitive psychologists placed renewed emphasis on
the study of internal mental operations. They adopted the computer as a metaphor for mind and described mental
functioning in terms of representation and computation. They believed that the mind, like a computer, could be
understood in terms of information processing.

Inherent early on in the cognitive approach was the idea of modularity. Modules are functionally independent units
that receive inputs from other modules, perform a specific processing task and pass the results of their computation
onto other modules. The influence of the modular approach can be seen in the use of process models or flow
diagrams. These depict a given mental activity via the use of boxes and arrows, where boxes depict modules, and
arrows depict the flow of information among them.

Techniques used are experimental method and computational modeling:
 Computational modeling involves carrying out a formal (typically software-based) implementation of a
proposed cognitive process.
 Researchers can run the modeling process so as to simulate how the process might operate in a human mind.
 They can then alter various parameters of the model or change its structure in an effort to achieve results as
close as possible to those obtained in human experiments.
 The model can also produce new results that then inspire new experiments.

The neuroscience approach [chapter 6]
The brain has been studied for years, but it is only recently that we see tremendous advances in our understanding of
the brain, especially in terms of how neuronal processes can account for cognitive phenomena.
Neuroscience = the study of the brain and endocrine system and how these account for mental states and behavior.

Cognitive neuroscience = the attempt to explain cognitive processes in terms of underlying brain mechanisms.

Neuroscience provides a description of mental events at the implemental level. It attempts to describe the biological
‘hardware’ on which mental ‘software’ supposedly runs. However, it is not always clear which level provides the best
explanation for any given cognitive process. Many of recent developments in neuroscience are the result of
developments of new technologies  EEG, MEG, fMRI, etc.

The network approach [chapter 7]
This approach is at least partially derived from neuroscience. The mind is seen as a collection of computing units.
These units are connected to one another and mutually influence one another’s activity via their connections,
although each of the units is believed to perform a relatively simple computation. In these networks, the connectivity
among many units can give rise to representational and computational complexity. In the field of network science,
researchers focus on the structure and function of networks.

The evolutionary approach [chapter 8, will be skipped]
The theory of natural selection proposed by Darwin in 1859 revolutionized our way of thinking about biology. Natural
selection holds that adaptive features enable the animals that possess them to survive and pass these features to
future generations. The environment is seen as selecting from among a variety of traits those that serve a functional
purpose. The field of evolutionary psychology applies the theory of natural selection to account for human mental
processes. It attempts to elucidate the selection forces that acted on our ancestors and how those forces gave rise to
the cognitive structures we now possess.

Modular approach:
 The proposed modules would be individual mechanisms in the brain that carry out various distinct cognitive
abilities that were successful at solving certain problems, thus helping our ancestors contribute their genes
to the next generation.
6

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