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COGNITIVE PSYCHOLOGY AND

COGNITIVE NEUROSCIENCE

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Contents

CHAPTERS..............................................................................................................................4

01 Cognitive Psychology and the Brain................................................................................................ 4

02 Problem Solving from an Evolutionary Perspective........................................................................ 8

03 Evolutionary Perspective on Social Cognitions............................................................................. 25

04 Behavioral and Neuroscience Methods.......................................................................................... 33

05 Motivation and Emotion................................................................................................................. 47

06 Memory.......................................................................................................................................... 57

07 Memory and Language................................................................................................................... 66

08 Imagery........................................................................................................................................... 73

09 Comprehension............................................................................................................................... 81

10 Neuroscience of Comprehension.................................................................................................... 94

11 Situation Models and Inferencing................................................................................................ 109

12 Knowledge.................................................................................................................................... 125

13 Decision Making and Reasoning.................................................................................................. 146

14 Present and Future of Research.................................................................................................... 168

ABOUT THE BOOK............................................................................................................... 177

History & Document Notes............................................................................................................... 177

Authors & Image Credits.................................................................................................................. 178

GNU Free Documentation License................................................................................................... 179

Chapter 1

1 COGNITIVE PSYCHOLOGY AND THE BRAIN

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Introduction

magine a young man, Knut, sitting at his desk, with his tired eyes staring at a monitor, surfing

Iaround, trying to find some worthy articles for his psychology homework. A cigarette rests between

the middle and index fingers of his left hand. Without looking, he stretches out his free hand and grabs

a cup of coffee located on the right of his keyboard. While sipping some of the cheap discounter blend,

he suddenly asks himself: "What is happening here?"

Around the beginning of the 20th century, psychologists would have said, "Take a look into

yourself, Knut, analyse what you're thinking and doing," as analytical introspection was the method of

that time.

A few years later, J.B. Watson published his book Psychology from the Standpoint of a

Behaviorist, from which began the era of behaviourism. Behaviourists claimed that it was impossible to

study the inner life of people scientifically. Their approach to psychology, which they assumed to be

more scientific, focussed only on the study and experimental analysis of behaviour. The right answer to

Knut's question would have been: "You are sitting in front of your computer, reading and drinking

coffee, because of your environment and how it influences you." Behaviorism was the primary means

for American psychology for about the next 50 years. One of the primary critiques and downfalls of

behaviorism was Noam Chomsky's 1959 critique of B.F. Skinner's "Verbal behaviour". Skinner, an

influential behaviourist, attempted to explain language on the basis of behaviour alone. Chomsky

showed that this was impossible, and by doing so, influenced enough psychologists to end the

dominance of behaviorism in American psychology.

As more researchers were once again concerned with processes inside the head, cognitive

psychology arose on the landscape of science. Their central claim was that cognition was information

processing of the brain. Cognitive psychology did not dispose the methods of behaviourism, but rather

widened their horizon by adding levels between input and output.

Modern technology and new methods enabled researchers to combine examinations of public

actions (latencies in reaction time, number of recalls) with physiological measurements (EEG and

event-related potentials, fMRI). Such methods, in addition to others, are used by cognitive science to

collect evidence for certain features of mental activity. From this, references and correlations between

action and cognition could be made.

These correlations were inspiration and thenceforwards the main challenge for cognitive

psychologists. To answer Knut's question the cognitive psychologist would probably first examining

Knut’s brain in that specific situation. So let's try this!

Knut has a problem, he really needs to do his homework. To solve this problem, he has to perform

loads of cognition. The light is gleaming into his eyes, transducing it from his retina into nerve signals

by sensory cells. The information is passed on through the optic nerve, crosses the brain at the lateral

geniculate nucleus to arrive at the central visual cortex. On its journey, the signals get computed over

complex nets of neurons; the contrast of the picture gets enhanced; irrelevant information gets filtered

4 | Cognitive Psychology and Neuroscience

Cognitive Psychology and the Brain

out; patterns are recognized; stains and lines on the screen become words; words get meaning, the

meaning is put into context, analyzed on its relevance for Knut's problem, maybe stored in some part of

memory. At the same time an appetite for coffee is creeping from Knut's hypothalamus, a region in the

brain responsible for controlling the needs of an organism. The appetite, encoded in patterns of neural

information, makes its way to the motor cortex where it is passed on to the muscles into Knut's arm.

A lot more could be said about this, and Knut's question remains unanswered, but this should be

enough to point out the complexity of cognition and the brain's importance. In this chapter, we are

going to dig deeper into the question of what cognitive psychology is and how it became this way, and

then draw connections to the brain and explain some of its most important parts.

Defining Cognitive Psychology

Cognitive Psychology is a psychological science which is interested in various mind and brain related subfields such as cognition, the mental processes that underlie behavior, reasoning and decision

making.

In the early stages of Cognitive Psychology, the high-tech measuring instruments used today were

unavailable. The idea of scientifically scrutinizing what was going on in a human mind was first

established during the late 19th century.

Psychology Laboratories were based on measuring observable features such as reaction time.

Nonetheless, there was a technique developed called analytic introspection. The latter is a method that

focusses on the subject’s inner processes. Here, the subject has to give precise reports about his or her

mental activity.

During the first half of the 20th century and naturally parallel to behaviorism, the behavioristic

approach became the main issue in psychology. The main emphasis was the examination of outer

expression of inner processes, rather than the mind itself.

Even though behaviorism had established itself as the mainstream, curiosity about the mind was

not diminished. In the 1950s, this inquisitiveness was released in a new science named Cognitive

Science. Cognitive Psychology became one of its subfields. The interdisciplinary approach of

Cognitive Science enabled the use of modern technology and new methods to combine examinations of

public actions (latencies in reaction time, number of recalls) with physiological measurements (EEG

and event-related potentials, fMRI).

Hereby, references and correlations between action and cognition could be made. Cognitive

Psychology is using these methods and additional ones such as Single and Double Dissociation and

brain lesioning to collect evidence for certain features of mental activity. Because of those correlations

that were found, the examination of the human brain and its functions has become one of the main

challenges to Cognitive Psychology.

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Chapter 1

The role of the brain

Examination of brain damage has a long tradition.

The Ancient Romans observed that gladiators with head injuries often lost their mental skills, whereas injuries to

other parts of the body did not have such an effect. It

was inferred that there was a possible link between the

mind and brain. Today, the assumption that the mind is

somehow implemented in the brain is taken for granted,

and even the common-sense understanding presupposes

a relation between mental and neuronal processes.

Subsequently, research on the brain became more and

more important, and the psychological methods being

used shifted to systematic scientific examination of the Figure 1.1 - The resting potential is initially around -70

brain. The crucial question then became: How is this mV relative to the outside of the cell. Once the

relation realized, and what properties of the brain are threshold (-55 mV) is passed, the cell depolarizes and

capable of causing mental and cognitive events?

the polarity reverses up to +40 mV. Subsequently the

cell hyperpolarizes and the voltage becomes more

As it is not possible, in this introductory passage, to negative than the resting potential for a short period.

cover the entire configuration of the brain in an appropriate manner, we will just give a brief summary

of the concepts behind neural signal transduction, and smoothly switch over to the anatomy of the

brain. This in turn will then serve as background information in the attempt to link cognitive functions

to brain structure.

In principle, there are two classes of cells in the human brain: neurons and glia. Both are

approximately equal in distribution, though neurons seem to play the main role in information

processing. The actual signal transduction takes place in different ways. On the one hand, there is mean

electrical conduction, and on the other hand, there are complicated biochemical cascades which

transmit the data. Both variants can be subsumed to the concept of action potentials (Figure 1.1), which

generally carry out the signal transduction from one nerve cell to another.

For better conduction, the axons of the neurons are insulated by a so-called myelin sheath. The

myelin in the human brain is produced by a certain class of glial cell, the oligodendrocytes. This is

important because the decomposition of the myelin sheath is involved in diseases, such as as multiple

sklerosis.

Once the information perceived by the sensory organs is transformed into a sequence of action

potentials the data is, in a way, neutral, since it has no specific qualitive properties which indicate from

which sense the signal was original initiated. But how is the information encoded? In other words, how

can the variety of our conscious experience be caused by simple inhibition and excitation of nerve cells

embedded in an admittedly complex system? Because of the lack of better metaphors, the answer is

often given by comparing the brain to a modern digital computer. Parsing the world into objects,

making inferences, having associative memory and the like can be analyzed by developing

computational models. The underlying paradigm is that the information is represented by the rate of

action potential spikes. How this is exactly realized is the aim of research of biophysics, a subdiscipline

of neurobiology.

In cognitive psychology, however, the methods used differ. This is because the main interest is not devoted to the organization of single neuron circuits, but rather to the larger, functional units in the

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Cognitive Psychology and the Brain

network.

References

• M. S. Gazzaniga, R. B. Ivry, and G. R. Mangun, Cognitive Neuroscience, Norton &

Company, 1998, ISBN 0393972194

• E. Br. Goldstein, Cognitive Psychology, Wadsworth, 2004, ISBN 0534577261

• M. W Eysenck, M. T. Keane, Cognitive Psychology, Psychology Press, 2005,  ISBN

1841693596 

• M. T. Banich, The Neural Bases of Mental Function, Houghton Mifflin, 1997,  ISBN 0-395-

66699-6 

• E. R. Kandel, J. H. Schwartz, T. M. Jessell, Principles of neural science, 2000,  ISBN 0-07-

112000-9 

Links

PDF file of the "ethics code" of the American Psychological Association

Cognitive Psychology miniscript by Fabian M. Suchanek

Famous papers in the history of cognition

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Wikibooks | 7

Chapter 2

2 PROBLEM SOLVING FROM AN EVOLUTIONARY

PERSPECTIVE

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Introduction

estalt psychologists approach towards problem solving was a perceptual one. That is, for them,

Gthe questions about problem solving were:

• how is a problem represented in a persons mind, and

• how does solving this problem involve a reorganisation or restructuring of this

representation?

Restructuring is basically the process of arriving at a new understanding of a problem situation -

changing from one representation of a problem to a (very) different one. The following story illustrates

this:

Two boys of different age are playing badminton. The older one is a more skilled player, and

therefore it is predictable for the outcome of usual matches who will be the winner. After some time

and several defeats the younger boy finally loses interest in playing, and the older boy faces a problem.

The usual suggestions, according to M. Wertheimer (1945/82), at this point of the story range from

'offering candy' and 'playing another game' to ' not playing to full ability' and 'shaming the younger boy

into playing'. And this is what the older boy comes up with:

He proposes that they should try to keep the bird in play as long as possible - and thus changing

from a game of competition to one of cooperation. They'd start with easy shots and make them harder

as their success increases, counting the number of consecutive hits. The proposal is happily accepted

and the game is on again.

Insight

There are two very different ways of approaching a goal-oriented situation. In one an organism

readily reproduces the response to the given problem from past experience. This is called reproductive

thinking.

The second way requires something new and different to achieve the goal, prior learning is of little

help here. Such productive thinking is (sometimes) argued to involve insight. Gestalt psychologists

even state that insight problems are a separate category of problems in their own right.

Tasks that might involve insight usually have certain features - they require something new and

nonobvious to be done and in most cases they are difficult enough to prevent that the initial solution

attempt is successful. When solving this kind of problems one experiences a so called "AHA-

experience" - the solution pops up all of the sudden. At one time they do not have the answer to a

problem and in the next second it's solved.

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Problem Solving from an Evolutionary Perspective

Fixation

Sometimes, previous experience or familiarity can even make problem solving more difficult. In

effect habitual directions can get in the way of finding new directions. This is called fixation.

Mental Fixedness

One approach to studying fixation was study wrong-answer verbal insight problems. To this,

people tend to give rather an incorrect answer when failing to solve, than to give no answer at all. A

typical example is, when people are told that, on a lake, the area covered by water lilies doubles every

24 hours and that it takes 60 days to cover the whole lake, and are asked: 'How many days does it take

to cover half the lake?' the typical respond is '30 days' (whereas 59 days is correct).

These wrong solutions are due to an inaccurate interpretation, hence representation, of the

problem. This can happen because of 'sloppiness' (a quick shallow reading of the problem and/or weak

monitoring their efforts made to come to a solution). In this case error feedback should help people to

reconsider the problem features, note the inadequacy of their first answer, and find the correct solution.

If, however, people are truly fixated on their incorrect representation, being told the answer is wrong

doesn't help. In a study made by P.I. Dallop and R.L. Dominowski in 1992 these two possibilities were

contrasted. In approximately one-third of the time error feedback led to right answers, so only

approximately one-third of the wrong answers were due to inadequate monitoring.

Functional Fixedness

Functional fixedness concerns the solution of object-use problems. The basic idea is that, when the

usual way of using an object is emphasized, it will be far more difficult for a person to use that object

in a novel manner.

Problem Solving - Modern Approaches

Problem Solving as a Search Problem

The idea of regarding to problem solving as search problems was invented by Alan Newell and

Herbert Simon while trying to design computer programs which could solve certain problems. This led

them to develop a program called General Problem Solver which was able to solve any well-defined

problem that can be formalized like chess or the towers of hanoi, but was not able to solve any real

world problem.

Any given problem consists of two special states namely an initial and a desired final or goal state.

To represent all possible situations between the initial and the goal state, intermediate states were

introduced. Additionally there exist a set of operators to move from one state to another. A solution is a

sequence of actions describing how to reach the goal state. The simplest method to solve a problem,

defined in these terms, is to search for a solution by just trying one possibility after another (also called

trial and error).

As already mentioned, this method of problem solving is not capable of solving real world

problems since it is usually not possible to formalize these problems in such a way that a search

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Chapter 2

algorithm is able to search for a solution.

Means-End Analysis

Another way is to try to divide a problem into smaller ones by creating sub goals. This method is

called means-end analysis and can be best demonstrated with the towers of hanoi problem. The initial

state is a stack of discs of different sizes on a peg. There are three pegs (A, B and C) and the discs are

on the left one. A disc has to be always placed on a bigger one or on an empty peg. The goal is to move

the stack of disks to the right peg, but only one disc can be moved at once. The following recursive

algorithm solves this problem by using the means-end analysis:

1. move n-1 discs from A to C

2. move disc #n from A to B

3. move n-1 discs from C to B

(n is the total number of discs)

With each recursive loop the problem is reduced by one.

This is an important everyday problem solving strategy - like, say, writing this chapter of the book.

We describe one aspect after another to give you, the reader, an overview of the subject that is as

comprehensible as possible.

Analogies

Analogies describe similar structures and interconnect them to clarify and explain certain relations.

In a recent study, for example, a song that got stuck in your head is compared to an itching of the brain

that can only be scratched by repeating the song over and over again.

Restructuring by Using Analogies

One special kind of restructuring, the way already mentioned during the discussion of the Gestalt

approach, is analogical problem solving. Here, to find a solution to one problem - the so called target

problem, an analogous solution to another problem - the source problem, is presented.

An example for this kind of strategy is the radiation problem posed by K. Duncker in 1945:

As a doctor you have to treat a patient with a malignant, inoperable tumor, buried deep inside the

body. There exists a special kind of ray, which is perfectly harmless at a low intensity, but at the

sufficient high intensity is able to destroy the tumor - as well as the healthy tissue on his way to it.

What can be done to avoid the latter?

When this question was asked to participants in an experiment, most of them couldn't come up

with the appropriate answer to the problem. Then they were told a story that went something like this:

A General wanted to capture his enemy's fortress. He gathered a large army to launch a full-scale

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Problem Solving from an Evolutionary Perspective

direct attack, but then learned, that all the roads leading directly towards the fortress were blocked by

mines. These roadblocks were designed in such a way, that it was possible for small groups of the

fortress-owner's men to pass them safely, but every large group of men would initially set them off.

Now the General figured out the following plan: He divided his troops into several smaller groups and

made each of them march down a different road, timed in such a way, that the entire army would

reunite exactly when reaching the fortress and could hit with full strength.

Here, the story about the General is the source problem, and the radiation problem is the target

problem. The fortress is analogous to the tumor and the big army corresponds to the highly intensive

ray. Consequently a small group of soldiers represents a ray at low intensity. The solution to the

problem is to split the ray up, as the general did with his army, and send the now harmless rays towards

the tumor from different angles in such a way that they all meet when reaching it. No healthy tissue is

damaged but the tumor itself gets destroyed by the ray at its full intensity.

M. Gick and K. Holyoak presented Duncker's radiation problem to a group of participants in 1980

and 1983. Only 10 percent of them were able to solve the problem right away, 30 percent could solve it

when they read the story of the general before. After given an additional hint - to use the story as help -

75 percent of them solved the problem.

With this results, Gick and Holyoak concluded, that analogical problem solving depends on three

steps:

1. Noticing that an analogical connection exists between the source and the target problem.

2. Mapping corresponding parts of the two problems onto each other (fortress → tumor, army

→ ray, etc.)

3. Applying the mapping to generate a parallel solution to the target problem (using little

groups of soldiers approaching from different directions → sending several weaker rays from

different directions)

Next, Gick and Holyoak started looking for factors that could be helpful for the noticing and the

mapping parts, for example:

Discovering the basic linking concept behind the source and the target problem.

Schema

This basic linking concept (see above) was called problem schema.

To activate a schema, schema induction is necessary.

One successful way to achieve schema induction by Gick and Holyoak: Before letting the

participants solve the radiation problem the instructor gave them two stories to read, the one with the

General and one with a similar outline. Now the participants were asked to write a brief summary about

the similarities of these stories.

When the underlining similarities where indirectly emphasized in this way, 52 percent of the

participants were able to solve the radiation problem without any hints given.

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Chapter 2

How do Experts Solve Problems?

With the term expert we describe someone who devotes large amounts of his or her time and

energy to one specific field of interest in which he, subsequently, reaches a certain level of mastery. It

should not be of a surprise that experts tend to be better in solving problems in their field than novices

(people who are beginners or not as well trained in a field as experts) are. They are faster in coming up

with a solution and have a higher success rate of right solutions. But what is the difference between the

ways experts and nonexperts solve problems? Research on the nature of expertise has come up with the

following conclusions:

• Experts know more about their field,

• their knowledge is organized differently, and

• they spend more time with analyzing the problem.

When it comes to problems that are situated outside the experts' field, their performance often

doesn't differ from that of novices.

Knowledge:

An experiment by Chase and Simon (1973a, b) dealt with the question how well experts and

novices are able to reproduce positions of chess pieces on chessboards, shown to them briefly. The

results showed, that experts were far better in reproducing actual game positions, but that their

performance was comparable with that of a novice when the chess pieces were arranged randomly on

the board. Chase and Simon concluded, that the superiority on actual game positions was due to the

ability to recognize them from the more or less 50,000 patterns stored in an expert's memory. In

comparison, for a good player there may be 1,000 patterns and for a novice only few to none at all.

Organization:

In 1982, M. Chi and her co-workers took a collection of 24 physics problems and presented them

to a group of physics professors, as well as to a group of students with only one semester of physics.

The task was to group the problems based on their similarities.

As it turned out, the students tended to group the problems based on their surface structure

(similarities of objects used in the problem), whereas the professors used their deep structure (the

general physical principles) as criteria.

Analysis:

Experts often spend more time trying to understand the problem before actually trying to solve it.

This way of approaching a problem may often result in what appears to be a slow start, but in the long

run this strategy is much more effective.

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Problem Solving from an Evolutionary Perspective

Divergent Thinking

The term divergent thinking describes a way of thinking that doesn't lead to one goal, but is open -

ended. Problems that are solved this way can have a large number of potential 'solutions' of which none

is exactly 'right' or 'wrong', though some might be more suitable than others. It can be contrasted by

convergent thinking - thinking that seeks to find the correct answer to a specific problem.

Divergent thinking is often associated with creativity, and it undoubtedly leads to many creative

ideas. Nevertheless, researches showed that in the processes that result in original and practical

inventions, things like searching for solutions, being aware of structures, and looking for analogies are

also heavily involved.

The Evolutionary Perspective

In 1831 Charles Darwin began to develop the evolutionary theory which was meant to explain why

there are so many different kinds of species. This theory also is important for psychology because it

explains how species were designed through evolution and what their goals are. By knowing the goals

of species it is possible to explain and predict behaviour.

Natural Selection

The mechanism of natural selection is the basic and most important one of which were introduced

by the theory of evolution. It is this process that makes organisms with superior traits more likely to

survive and reproduce. Without natural selection the growth of populations is exponential. For example

an organism that reproduces once a day will create a population of about 229 organisms within a month.

In natural populations this is not the case and most populations are relatively stable, since most

organisms do not have as many offspring as they might have. This is caused by the environment.

Hence, if an individual is better at finding food or avoiding predators it is more likely that it will

survive. This ability which enables the individual to survive will be passed on to the next generation.

On the other hand if an individual fails to survive its disadvantages will not be passed on to the next

generation. Over many generations this natural selection will lead to individuals that are better adapted

to their environment. This process may also be called "reproduction of the fittest". Natural selection

can only work if there are random changes in the genetic process, also called mutations. Only if these

mutations are significant, natural selection can choose which version better solves the problem of

"staying in the game of evolution".

As traits can only spread through reproduction, natural selection is a very slow process. The time

until an individual is able to reproduce is called the generation time (approx. 20 years for humans).

Evolution is such a slow process since natural selection can only choose from existing alternatives.

That is, until a new trait becomes common it has to develop and spread in the whole population which

of course takes much time.

Adaptation As a Result of Natural Selection

Variations in individuals are constantly tested whether they help to survive in the environment or

not. This variation can be of any kind, for example an enhancement of the body or a new behaviour that

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enables the individual to solve certain problems which are necessary to survive or aids reproduction.

These variations are called adaptations because they adapt the individual to its environment.

Adaptations are structurally complex and support reproduction.

Psychological Adaptation

Evolutionary psychologists think of the mind as a modular system. This perspective on modularity

was mainly developed by Leda Cosmides and John Tooby. It is based on the assumption that the mind has evolved by natural selection and therefore should solve the same problems as other organs namely

survival and reproduction. Each module of our mind is responsible for one task (e.g. face recognition)

and can be adapted by natural selection. So behaviour is not adapted directly but rather indirectly by

modifying the underlying neuronal networks to produce adaptive behaviour.

Adaptations May Be Out-of-Date

A disadvantage of the slow evolutionary process is that when the environment changes quickly,

adaptive functions and behaviour may be out-of-date. The result is that organisms are better adapted to

the past and this is an important point if we think about human social behaviour and the development of

cultures (see chapter Evolutionary Perspective on Social Cognitions for details).

Sexual Selection

Besides the theory of natural selection there is another one called the theory of sexual selection. It

states that there is also a kind of selection between individuals of the same sex which leads to a

development and spread of traits in males or females.

Sexual selection depends on the success of certain individuals over others of the same sex, in relation to the

propagation of the species; while natural selection depends on the success of both sexes, at all ages, in relation

to the general conditions of life. — Charles Darwin, 1871

A famous example for sexual selection is the peacock.

The evolution of its tail cannot be explained by natural

selection only because it is neither very helpful to find food

nor does it help to avoid predators, even the opposite is the

case. But it makes the peacock more attractive to the

opposite sex and therefore conducts to reproduction due to

the fact that this oversized tail can only be worn by a male

that is strong enough to wear a disadvantage.

Altruism

Natural selection favours the strong and selfish who

acts in his own interest. But there are other traits like

altruism which are very common in human behaviour and it Darwin argued that the female peahen chose to

seems that they cannot be explained by natural selection mate with the male peacock who had the most

only. With regard to a whole group traits can be beautiful plumage in her mind (intersexual

selection).

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characterized as

• increasing the fitness of the individual (self) or