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Psychologia poznawcza


Cognitive science


Cognitive neuroscience



Procesy psychiczne:


umysłowe


emocjonalne


motywacyjne


sensomotoryczne

Wyznaczniki przebiegu procesów:


inteligencja


temperament


osobowość




Cognitive psychology

Wiki


Cognitive psychology

is a
subdiscipline

of

psychology

exploring

internal
mental processes
.

It is the study of how people perceive, remember,
think, speak, and solve problems.
[1]


Cognitive psychology
differs from previous psychological approaches
in
two key ways.



1/
It
accepts the use of the

scientific method
,
(
and
generally
rejects

introspection
[2]

as a valid method of
investigation
.)


2/
It
explicitly acknowledges the existence of internal mental states (such
as

belief
,

desire
,

idea
,

knowledge

and

motivation
).



In
its early years,

critics

held that
the empiricism of cognitive psychology
was incompatible with its acceptance of internal mental states.


However
, the sibling field of

cognitive neuroscience

has provided evidence
of physiological brain states that directly correlate with mental states
-

thus providing support for the central assumption of cognitive psychology.



The
school of thought arising from this approach is known as

cognitivism
.



podręcznik:
Psychologia poznawcza


Nęcka
, Orzechowski, Szymura (
N&S&O
)





Psychologia poznawcza


Psychologia poznawcza a nauki
pokrewne



Umysł i poznanie


Ogólna architektura umysłu



Reprezentacje poznawcze


Obrazowe


Werbalne


Pojęciowe



Wiedza (jawna i niejawna)


Organizacja wiedzy


Nabywanie wiedzy






Elementarne procesy poznawcze


Uwaga


Percepcja



Pamięć



Złożone procesy poznawcze


myślenie


rozumowanie


wnioskowanie


podejmowanie decyzji


rozwiązywanie problemów



Kontrola poznawcza



Język i mowa


Język a poznanie


Przyswajanie języka


Mówienie


rozumienie



Cognitive

psychology

Major research areas



Perception


General
perception


Psychophysics


Attention

and Filter theories
(the ability to focus mental
effort on specific stimuli whilst
excluding other stimuli from
consideration)


Pattern recognition

(the ability
to correctly interpret
ambiguous sensory
information)


Object recognition


Time sensation

(awareness and
estimation of the passage of
time)


Categorization


Category induction and
acquisition


Categorical
judgement

and
classification


Category representation and
structure


Similarity (psychology)


Memory


Aging and memory


Autobiographical memory


Constructive memory


Emotion and memory


Episodic memory


Eyewitness memory


False memories


Firelight memory


Flashbulb memory


List of memory biases


Long
-
term memory


Semantic memory


Short
-
term memory


Spaced repetition


Source monitoring


Working memory


Knowledge
representation


Mental imagery


Propositional encoding


Imagery versus proposition
debate


Dual
-
coding theories


Media psychology


Numerical cognition


Language


Grammar

and

linguistics


Phonetics

and

phonology


Language acquisition


Thinking


Choice

(see also:

Choice theory
)


Concept formation


Decision making


Judgment and decision making


Logic
, formal and
natural

reasoning


Problem solving


History


Ulric

Neisser

coined the term "cognitive psychology" in his book

Cognitive Psychology,

published in
1967
[3][4]

wherein
Neisser

provides a definition of cognitive psychology characterizing people as dynamic
information
-
processing systems whose mental operations might be described in computational terms. Also
emphasizing that it is a "point of view" that postulates the mind as having a certain conceptual structure.
Neisser's

point of view endows the discipline with a scope beyond high
-
level concepts such as "reasoning" that
other works often espouse as defining psychology.
Neisser's

definition of "cognition" illustrates this well:


The term "cognition" refers to all processes by which the sensory input is transformed, reduced, elaborated,
stored, recovered, and used. It is concerned with these processes even when they operate in the absence of
relevant stimulation, as in images and hallucinations... Given such a sweeping definition, it is apparent that
cognition is involved in everything a human being might possibly do; that every
[5]

psychological phenomenon is
a cognitive phenomenon.


But
although cognitive psychology is concerned with all human activity rather than some fraction of it, the
concern is from a particular point of view. Other viewpoints are equally legitimate and necessary. Dynamic
psychology, which begins with motives rather than with sensory input, is a case in point. Instead of asking how
a man's actions and experiences result from what he saw, remembered, or believed, the dynamic psychologist
asks how they follow from the subject's goals, needs, or instincts.


Cognitive psychology is
one of the more recent additions to psychological research, having only developed as
a separate area within the discipline since the late 1950s and early 1960s following the "
cognitive revolution
"
initiated by

Noam Chomsky
's 1959 critique
[6]

of behaviorism and empiricism more generally.


The
origins of cognitive thinking such as

computational theory of mind

can be traced back as early
as

Descartes

in the 17th century, and proceeding up to

Alan Turing

in the 1940s and '50s. The cognitive
approach was brought to prominence by

Donald Broadbent
's book

Perception and Communication

in 1958.
Since that time, the dominant

paradigm

in the area has been the

information processing

model of cognition
that Broadbent put forward. This is a way of thinking and reasoning about mental processes, envisioning them
as software running on the computer that is the brain. Theories refer to forms of input, representation,
computation or processing, and outputs. Applied to language as the primary mental knowledge representation
system, cognitive psychology has exploited tree and network mental models. Its singular contribution to

AI

and
psychology in general is the notion of a

semantic network
. One of the first cognitive psychologists,

George
Miller

is well known for dedicating his career to the development of

WordNet
, a semantic network for the
English language. Development began in 1985 and is now the foundation for many machine
ontologi
es.



This way of conceiving mental
processes

has
pervaded psychology more generally over the past few
decades, and it is not uncommon to find cognitive theories within

social psychology
,

personality
psychology
,
abnormal

psychology
, and

developmental psychology
. In fact, the

neo
-
Piagetian

theories
of cognitive development

have fully integrated the developmental conception of changes in
thought with age with

cognitive models

of information processing.
[7]

The application of cognitive
theories to

comparative psychology

has driven many recent studies in

animal cognition
. However,
cognitive psychology dealing with the intervening constructs of the mental presentations is not able
to specify: "What are the non
-
material counterparts of material objects?" For example, "What is
the counterpart of a chair in mental processes, and how do the non
-
material processes evolve in
the mind that has no space?" Further, what are the very specific qualities of the mental causalities,
in particular, when the causalities are processes? The plain statement about information processing
awakes some questions. What information is dealt with, its contents, and form? Are there
transformations? What are the nature of process causalities? How do subjective states of a person
transmute into shared states, and the other way around? Finally, yet importantly, how is it that we
who work with cognitive research are able to conceptualize the mental counter concepts to
construct theories that have real importance in real every day life? Consequently, there is a lack of
specific process concepts that lead to new developments, and create grand theories about the
mind and its abysses.


The information processing approach to cognitive functioning is currently being questioned by new
approaches in psychology, such as

dynamical systems
, and the

embodiment

perspective.


Because of the use of computational metaphors and terminology, cognitive psychology was able to
benefit greatly from the flourishing of research in

artificial intelligence

and other related areas in
the 1960s and



Influential

cognitive

psychologists



John
R. Anderson


Alan
Baddeley


Albert Bandura


Frederic
Bartlett


Elizabeth Bates


Donald
Broadbent


Jerome Bruner


Gordon H.
Bower


Susan

Carey


Noam Chomsky


Fergus

Craik


Antonio
Damasio


Hermann
Ebbinghaus


William
Estes


Michael
Gazzaniga


Dedre

Gentner


Keith

Holyoak


Philip
Johnson
-
Laird


Daniel
Kahneman


Nancy
Kanwisher


Eric
Lenneberg


Elizabeth
Loftus


Brian
MacWhinney


James
McClelland


George
Armitage

Miller


Ken Nakayama


Ulrich
Neisser


Allen
Newell


Allan
Paivio


Seymour
Papert


Charles Sanders Peirce


Jean Piaget


Steven
Pinker


Michael Posner


Henry L.
Roediger

III


Eleanor

Rosch


David
Rumelhart


Eleanor

Saffran


Daniel
Schacter


Roger
Shepard


Herbert Simon


Elizabeth
Spelke


George Sperling


Robert Sternberg


Saul Sternberg


Larry
Squire


Endel

Tulving


Anne

Treisman


Amos
Tversky


Lev

Vygotsky




Cognitive science



Cognitive science

is the interdisciplinary scientific study of mind and its processes.


It
examines what cognition is, what it does and how it works. It includes research
on how information is processed (in faculties such as perception, language,
memory, reasoning, and emotion), represented, and transformed in
behaviour
,
(human or other animal) nervous system or machine (e.g., computer). Cognitive
science consists of multiple research disciplines, including



psychology
,



artificial
intelligence
,



philosophy
,



neuroscience
,



inguistics
,



anthropology
,



sociology
, and



education
.
[1]



It
spans many levels of analysis, from low
-
level learning and decision mechanisms
to high
-
level logic and planning; from neural circuitry to modular brain
organization.


The
term

cognitive science

was coined by

Christopher
Longuet
-
Higgins

in his 1973
commentary on the

Lighthill

report
, which concerned the then
-
current state
of

Artificial Intelligence

research.
[2]



In
the same decade, the journal

Cognitive Science

and the

Cognitive Science
Society

were founded.
[3]

History


Cognitive
science has a pre
-
history traceable back to ancient Greek philosophical texts (see Plato's

Meno
); and certainly
must include writers such as

Descartes
,

David Hume
,

Immanuel Kant
,

Benedict de Spinoza
,

Nicolas Malebranche
,

Pierre
Cabanis
,

Leibniz

and

John Locke
. But, although these early writers contributed greatly to the philosophical discovery
of

mind

and this would ultimately lead to the development of psychology, they were working with an entirely different
set of tools and core concepts than those of the cognitive scientist.


The modern culture of cognitive science can be traced back to the early

cyberneticists

in the 1930s and 1940s, such
as

Warren McCulloch

and

Walter Pitts
, who sought to understand the organizing principles of the mind. McCulloch and
Pitts developed the first variants of what are now known as

artificial neural networks
, models of computation inspired by
the structure of

biological neural networks
.


Another precursor was the early development of the

theory of computation

and the

digital computer

in the 1940s and
1950s.

Alan Turing

and

John von Neumann

were instrumental in these developments. The modern computer, or

Von
Neumann machine
, would play a central role in cognitive science, both as a metaphor for the mind, and as a tool for
investigation.


In 1959,

Noam Chomsky

published a scathing review of

B. F. Skinner
's book

Verbal Behavior
. At the time,
Skinner's

behaviorist

paradigm dominated psychology: Most psychologists focused on functional relations between
stimulus and response, without positing internal representations. Chomsky argued that in order to explain language, we
needed a theory like

generative grammar
, which not only attributed internal representations but characterized their
underlying order.


In the 1970s and early 1980s, much cognitive science research focused on the possibility of

artificial intelligence
.
Researchers such as

Marvin
Minsky

would write computer programs in languages such as

LISP

to attempt to formally
characterize the steps that human beings went through, for instance, in making decisions and solving problems, in the
hope of better understanding human thought, and also in the hope of creating artificial minds. This approach is known as
"symbolic AI".


Eventually the limits of the symbolic AI research program became apparent. For instance, it seemed to be unrealistic to
comprehensively list human knowledge in a form usable by a symbolic computer program.


The
late 80s and 90s saw the rise of

neural networks

and

connectionism

as a research paradigm. Under this point of view,
often attributed to

James McClelland

and

David
Rumelhart
, the mind could be characterized as a set of complex
associations, represented as a layered network. Critics argue that there are some phenomena which are better captured
by symbolic models, and that connectionist models are often so complex as to have little explanatory power.


Recently
symbolic and connectionist models have been combined, making it possible to take advantage of both forms of
explanation.
[4
]


Key

findings


Cognitive science has much to its credit. Among other accomplishments,


it
has given rise to models of human

cognitive bias

and

risk

perception, and has
been influential in


the
development of

behavioral finance
, part of

economics
. It has also given rise to


a
new theory of the

philosophy of mathematics
, and


many
theories of

artificial intelligence
,

persuasion

and

coercion
. It has made its
presence firmly known in


T
he

philosophy
of language

and

epistemology

-

a modern revival of rationalism




as
well as constituting a substantial wing of modern

linguistics
.



Fields
of cognitive science have been influential in understanding the brain's
particular functional systems (and functional deficits) ranging from speech
production to auditory processing and visual perception.


It
has made progress in understanding how damage to particular areas of the brain
affect cognition, and it has helped to uncover the root causes and results of
specific
disfunction
, such as

dyslexia
,

anopia
, and

hemispatial

neglect


S
cope


Cognitive science is a large field, and covers a wide array of topics on cognition. However, it should be recognized that cog
nit
ive science is not equally concerned with every topic that might bear on the nature
and operation of the mind or intelligence. Social and cultural factors, emotion, consciousness,

animal cognition
,

comparative

and

evolutionary

approaches are frequently de
-
emphasized or excluded outright,
often based on key philosophical conflicts. Another important mind
-
related subject that the cognitive sciences tend to avoid is
the existence of

qualia
, with discussions over this issue being sometimes limited
to only mentioning
qualia

as a philosophically
-
open matter. Some within the cognitive science community, however, consider these to be vital topics, and
advocate the importance of investigating them.
[7]


Below are some of the main topics that cognitive science is concerned with. This is not an exhaustive list, but is meant to c
ove
r the wide range of intelligent behaviors. See

List of cognitive science topics

for a
list of various aspects of the field.

[
edit
]
Artificial intelligence


"...
One major contribution of AI and cognitive science to psychology has been the information processing model of human thinking
in
which the metaphor of brain
-
as
-
computer is taken quite literally.

."

AAAI


Artificial intelligence (AI) involves the study of cognitive phenomena in machines. One of the practical goals of AI is to im
ple
ment aspects of human intelligence in computers. Computers are also widely used as
a tool with which to study cognitive phenomena.

Computational modeling

uses simulations to study how human intelligence may be structured.
[8]

(See the section on computational modeling in the Research
Methods section.)


There is some debate in the field as to whether the mind is best viewed as a huge array of small but individually feeble elem
ent
s (i.e. neurons), or as a collection of higher
-
level structures such as symbols,
schemas, plans, and rules. The former view uses

connectionism

to study the mind, whereas the latter emphasizes symbolic computations. One way to view the issue is whether it is possible t
o
accurately
simulate a human brain on a computer without accurately simulating the neurons that make up the human brain.

[
edit
]
Attention


Attention
is the selection of important information. The human mind is bombarded with millions of stimuli and it must have a way of dec
idi
ng which of this information to process. Attention is sometimes seen
as a spotlight, meaning one can only shine the light on a particular set of information. Experiments that support this metaph
or
include the

dichotic listening

task (Cherry, 1957) and studies of

inattentional

blindness
(Mack and Rock, 1998). In the dichotic listening task, subjects are bombarded with two different messages, one in each ear, a
nd
told to focus on only one of the messages. At the end of the
experiment, when asked about the content of the unattended message, subjects cannot report it.

[
edit
]
Knowledge, and Processing, of Language


A

well known example

of a

Phrase structure tree
. This is one way of representing human language that shows how different components are organized hierarchically.


The
ability to learn and understand language is an extremely complex process. Language is acquired within the first few years of
lif
e, and all humans under normal circumstances are able to acquire language
proficiently. A major driving force in the theoretical linguistic field is discovering the nature that language must have in
the

abstract in order to be learned in such a fashion. Some of the driving research
questions in studying how the brain itself processes language include: (1) To what extent is linguistic knowledge innate or l
ear
ned?, (2) Why is it more difficult for adults to acquire a second
-
language than it is
for infants to acquire their first
-
language?, and (3) How are humans able to understand novel sentences?


The study of language processing ranges from the investigation of the sound patterns of speech to the meaning of words and wh
ole

sentences.

Linguistics

often divides language processing
into

orthography
,

phonology

and

phonetics
,

morphology
,

syntax
,

semantics
, and

pragmatics
. Many aspects of language can be studied from each of these components and from their interaction.


The study of language processing in

cognitive science

is closely tied to the field of linguistics. Linguistics was traditionally studied as a part of the humanities, including stu
di
es of history, art and literature. In
the last fifty years or so, more and more researchers have studied knowledge and use of language as a cognitive phenomenon, t
he
main problems being how knowledge of language can be acquired and used,
and what precisely it consists of.

Linguists

have found that, while humans form sentences in ways apparently governed by very complex systems, they are remarkably unaware

o
f the rules that govern their
own speech. Thus linguists must resort to indirect methods to determine what those rules might be, if indeed rules as such ex
ist
. In any event, if speech is indeed governed by rules, they appear to be opaque
to any conscious consideration.

[
edit
]
Learning and development


Learning
and development are the processes by which we acquire knowledge and information over time. Infants are born with little or no

kn
owledge (depending on how knowledge is defined), yet they
rapidly acquire the ability to use language, walk, and recognize people and objects. Research in learning and development aim
s t
o explain the mechanisms by which these processes might take place.


A major question in the study of cognitive development is the extent to which certain abilities are

innate

or learned. This is often framed in terms of the

nature versus nurture

debate. The

nativist

view
emphasizes that certain features are innate to an organism and are determined by its

genetic

endowment. The

empiricist

view, on the other hand, emphasizes that certain abilities are learned from the
environment. Although clearly both genetic and environmental input is needed for a child to develop normally, considerable de
bat
e remains about

how

genetic information might guide cognitive
development. In the area of

language acquisition
, for example, some (such as

Steven Pinker
)
[9]

have argued that specific information containing universal grammatical rules must be contained in the genes,
whereas others (such as Jeffrey Elman and colleagues
in
Rethinking

Innateness
) have argued that
Pinker's

claims are biologically unrealistic. They argue that genes determine the architecture of a learning
system, but that specific "facts" about how grammar works can only be learned as a result of experience.

[
edit
]
Memory


Memory
allows us to store information for later retrieval. Memory is often thought of consisting of both a long
-
term and short
-
term sto
re. Long
-
term memory allows us to store information over prolonged
periods (days, weeks, years). We do not yet know the practical limit of long
-
term memory capacity. Short
-
term memory allows us t
o store information over short time scales (seconds or minutes).


Memory is also often grouped into declarative and procedural forms.

Declarative memory
--
grouped into subsets of

semantic

and

episodic forms of memory
--
refers to our memory for facts and specific
knowledge, specific meanings, and specific experiences (e.g., Who was the first president of the U.S.A.?, or "What did I eat
for

breakfast four days ago?).

Procedural memory

allows us to remember actions and
motor sequences (e.g. how to ride a bicycle) and is often dubbed implicit knowledge or memory .


Cognitive scientists study memory just as psychologists do, but tend to focus in more on how memory bears on

cognitive processes
, and the interrelationship between cognition and memory. One example of
this could be, what mental processes does a person go through to retrieve a long
-
lost memory? Or, what differentiates between th
e cognitive process of recognition (seeing hints of something before
remembering it, or memory in context) and recall (retrieving a memory, as in "fill
-
in
-
the
-
blank")?

[
edit
]
Perception and action


The Necker cube, an example of an optical illusion


Perception
is the ability to take in information via the

senses
, and process it in some way.

Vision

and

hearing

are two dominant senses that allow us to perceive the environment. Some questions in the study
of visual perception, for example, include: (1) How are we able to recognize objects?, (2) Why do we perceive a continuous vi
sua
l environment, even though we only see small bits of it at any one time? One
tool for studying visual perception is by looking at how people process

optical illusions
. The image on the right of a Necker cube is an example of a
bistable

percept, that is, the cube can be interpreted as being
oriented in two different directions.


The study of

haptic

(
tactile
),

olfactory
, and

gustatory

stimuli also fall into the domain of perception.


Action is taken to refer to the output of a system. In humans, this is accomplished through motor responses. Spatial planning

an
d movement, speech production, and complex motor movements are all aspects
of action.



Research methods


Many different methodologies are used to study cognitive science. As the field is highly interdisciplinary, research often cu
ts
across multiple areas of study, drawing on research methods
from

psychology
,
neuroscience
,

computer science

and

systems theory
.

[
edit
]Behavioral experiments


In order to have a description of what constitutes intelligent behavior, one must study behavior itself. This type of researc
h i
s closely tied to that in

cognitive psychology

and

psychophysics
. By measuring
behavioral responses to different stimuli, one can understand something about how those stimuli are processed. Lewandowski an
d
Strohmetz

(2009) review a collection of innovative uses of behavioral
measurement in psychology including behavioral traces, behavioral observations, and behavioral choice.
[10]

Behavioral traces are pieces of evidence that indicate behavior occurred, but the actor is not present
(e.g., litter in a parking lot or readings on an electric meter). Behavioral observations involve the direct witnessing of th
e a
ctor engaging in the behavior (e.g., watching how close a person sits next to another
person). Behavioral choices are when a person selects between two or more options (e.g., voting behavior, choice of a punishm
ent

for another participant).


Reaction time.

The time between the presentation of a stimulus and an appropriate response can indicate differences between two cognitive pr
oc
esses, and can indicate some things about their nature. For
example, if in a search task the reaction times vary proportionally with the number of elements, then it is evident that this

co
gnitive process of searching involves serial instead of parallel processing.


Psychophysical responses.

Psychophysical experiments are an old psychological technique, which has been adopted by cognitive psychology. They typically

i
nvolve making judgments of some physical
property, e.g. the loudness of a sound. Correlation of subjective scales between individuals can show cognitive or sensory bi
ase
s as compared to actual physical measurements. Some examples include:


sameness judgments for colors, tones, textures, etc.


threshold differences for colors, tones, textures, etc.


Eye tracking
.

This methodology is used to study a variety of cognitive processes, most notably visual perception and language processing. T
he

fixation point of the eyes is linked to an individual's focus of
attention. Thus, by monitoring eye movements, we can study what information is being processed at a given time. Eye tracking
all
ows us to study cognitive processes on extremely short time scales. Eye
movements reflect online decision making during a task, and they provide us with some insight into the ways in which those de
cis
ions may be processed.

[
edit
]Brain imaging


Image
of the human head with the brain. The arrow indicates the position of
the
hypothalamus
.


Brain imaging involves analyzing activity within the brain while performing various cognitive tasks. This allows us to link b
eha
vior and brain function to help understand how information is processed. Different
types of imaging techniques vary in their temporal (time
-
based) and spatial (location
-
based) resolution. Brain imaging is often
used in

cognitive neuroscience
.


Single photon emission computed tomography

and

Positron emission tomography
. SPECT and PET use radioactive isotopes, which are injected into the subject's bloodstream and taken up by the brain. By
observing which areas of the brain take up the radioactive isotope, we can see which areas of the brain are more active than
oth
er areas. PET has similar spatial resolution to
fMRI
, but it has extremely poor
temporal resolution.


Electroencephalography
. EEG measures the electrical fields generated by large populations of neurons in the cortex by placing a series of electrode
s o
n the scalp of the subject. This technique has an extremely
high temporal resolution, but a relatively poor spatial resolution.


Functional magnetic resonance imaging
.
fMRI

measures the relative amount of oxygenated blood flowing to different parts of the brain. More oxygenated blood in a particul
ar

region is assumed to correlate
with an increase in neural activity in that part of the brain. This allows us to localize particular functions within differe
nt
brain regions.
fMRI

has moderate spatial and temporal resolution.


Optical imaging
. This technique uses infrared transmitters and receivers to measure the amount of light reflectance by blood near different
are
as of the brain. Since oxygenated and deoxygenated blood
reflects light by different amounts, we can study which areas are more active (i.e., those that have more oxygenated blood).
Opt
ical imaging has moderate temporal resolution, but poor spatial resolution. It
also has the advantage that it is extremely safe and can be used to study infants' brains.


Magnetoencephalography
.

MEG measures magnetic fields resulting from cortical activity. It is similar to

EEG
, except that it has improved spatial resolution since the magnetic fields it measures are not as
blurred or attenuated by the scalp,
meninges

and so forth as the electrical activity measured in EEG is. MEG uses SQUID sensors to detect tiny magnetic fields.

[
edit
]Computational modeling


A Neural network with two layers.


Computational models

require a mathematically and logically formal representation of a problem. Computer models are used in the simulation and exp
er
imental verification of different specific and
general

properties

of

intelligence
. Computational modeling can help us to understand the functional organization of a particular cognitive phenomenon. There ar
e t
wo basic approaches to cognitive modeling.
The first is focused on abstract mental functions of an intelligent mind and operates using symbols, and the second, which fo
llo
ws the neural and associative properties of the human brain, and is called
subsymbolic
.


Symbolic modeling

evolved from the computer science paradigms using the technologies of

Knowledge
-
based systems
, as well as a philosophical perspective, see for example "Good Old
-
Fashioned Artificial
Intelligence" (
GOFAI
). They are developed by the first cognitive researchers and later used in

information engineering

for

expert systems

. Since the early 1990s it was generalized in

systemics

for the
investigation of functional human
-
like intelligence models, such as

personoids
, and, in parallel, developed as the

SOAR

environment. Recently, especially in the context of cognitive decision making, symbolic
cognitive modeling is extended to

socio
-
cognitive
approach

including social and organization cognition interrelated with a sub
-
symbolic not conscious layer.


Subsymbolic

modeling

includes

Connectionist/neural network models
.

Connectionism relies on the idea that the mind/brain is composed of simple nodes and that the power of the system comes prima
ri
ly
from the existence and manner of connections between the simple nodes.

Neural nets

are textbook implementations of this approach. Some critics of this approach feel that while these models approach
biological reality as a representation of how the system works, they lack explanatory powers because complicated systems of c
onn
ections with even simple rules are extremely complex and often less
interpretable than the system they model.


Other approaches gaining in popularity include the use of

Dynamical systems

theory and also techniques putting symbolic models and connectionist models into correspondence (Neural
-
symbolic
integration).
Bayesian models
, often drawn from

machine learning
, are also gaining popularity.


All the above approaches tend to be generalized to the form of integrated computational models of a synthetic/abstract intell
ige
nce, in order to be applied to the explanation and improvement of individual
and social/organizational

decision
-
making

and

reasoning
.

[
edit
]Neurobiological methods


Research methods borrowed directly from

neuroscience

and

neuropsychology

can also help us to understand aspects of intelligence. These methods allow us to understand how intelligent behavior is
implemented in a physical system.


Single
-
cell recording


Direct brain stimulation


Animal models


Postmortem studies


[
edit
]


Notable
researchers


See also:

List of cognitive scientists




Some
of the more recognized names in cognitive science are usually either the most controversial or the most cited.
Within philosophy familiar names include



Daniel
Dennett

who writes from a computational systems perspective,



John
Searle

known for his controversial

Chinese Room
,


Jerry
Fodor who advocates

functionalism
, and



Douglas
Hofstadter
, famous for writing

Gödel, Escher, Bach
, which questions the nature of words and thought. In the
realm of linguistics,



Noam
Chomsky

and



George
Lakoff

have been influential (both have also become notable as political commentators).


In

Artificial
intelligence
:


Marvin
Minsky
,



Herbert
Simon
,



Allen
Newell
, and



Kevin
Warwick

are prominent.



Popular
names in the discipline of psychology include



James
McClelland

and

Steven Pinker
.


Anthropologists



Dan
Sperber
,


Edwin
Hutchins
,



Scott
Atran
,


Pascal
Boyer

and



Joseph
Henrich

have been involved in collaborative projects with cognitive and social psychologists, political scientists
and evolutionary biologists in attempts to develop general theories of culture formation, religion and political
association
.


Cognitive neuroscience
,
wiki


Cognitive
neuroscience

is an academic field concerned with the scientific study of
biological substrates underlying

cognition
,
[1]

with a specific focus on the neural substrates
of mental processes.


It
addresses the questions of how psychological/cognitive functions are produced by the
brain. Cognitive neuroscience is a branch of both

psychology

and
neuroscience
,
overlapping with disciplines such as

physiological psychology
,

cognitive
psychology

and

neuropsychology
.
[2]

Cognitive neuroscience relies upon theories
in

cognitive science

coupled with evidence from

neuropsychology
, and

computational
modelling
.
[2]


Due to its multidisciplinary nature, cognitive neuroscientists may have various
backgrounds. Other than the associated disciplines just mentioned, cognitive
neuroscientists may have backgrounds in these disciplines:
neurobiology,

bioengineering
,

psychiatry
,

neurology
,

physics
,

computer
science
,

linguistics
,

philosophy

and

mathematics
.


Methods employed in cognitive neuroscience include experimental paradigms
from

psychophysics

and

cognitive psychology
,

functional
neuroimaging
,

electrophysiology
,

cognitive genomics

and

behavioral genetics
. Studies of
patients with cognitive deficits due to brain

lesions

constitute an important aspect of
cognitive neuroscience (see

neuropsychology
). Theoretical approaches
include

computational neuroscience

and

cognitive psychology
.


History


Before
the 1980s, interaction between neuroscience and cognitive science was
scarce
.

The term 'cognitive neuroscience' was coined by George Miller and Michael
Gazzaniga

"in
the back seat of a New York City
taxi

"toward
the end of the 1970s.


Cognitive
neuroscience began to integrate the newly laid theoretical ground in
cognitive science, that emerged between the 1950s and 1960s, with approaches in
experimental psychology, neuropsychology and neuroscience. (Neuroscience was not
established as a unified discipline until
1971).


In
the very late 20th century new technologies evolved that are now the mainstay of
the methodology of cognitive neuroscience, including

TMS

(1985) and

fMRI

(1991).


Earlier
methods used in cognitive neuroscience includes

EEG

(human EEG 1920)
and

MEG

(1968).


Occasionally
cognitive neuroscientists utilize other brain imaging methods such
as

PET

and

SPECT
. In some animals

Single
-
unit recording

can be used. Other methods
include

microneurography
, facial

EMG
, and eye
-
tracking
.


Integrative
neuroscience

attempts to consolidate data in databases, and form unified
descriptive models from various fields and scales: biology, psychology, anatomy, and
clinical practice.



List of
cognitive

neuroscientists

Language


Steven
Pinker


Elizabeth Bates


Brian
MacWhinney


Thomas
Bever


Marta Kutas


Laura
-
Ann
Petitto


Morton
Gernsbacher

Memory


Daniel
Schacter


Endel

Tulving


Nancy
Kanwisher


James
McGaugh


Alexander Luria


Morris
Moscovitch


Larry
Squire

Vision


David
Marr


Stephen
Kosslyn


Roger
Shepard


Brian
Wandell


Jerome
Lettvin


David
Hubel


Torsten

Wiesel

Learning and
Connectionism


David
Rumelhart


James
McClelland


Jeffrey
Elman


Annette

Karmiloff
-
Smith


Yuko

Munakata


Mark Johnson


Donald O.
Hebb

Laterality


Roger
Wolcott

Sperry


Michael
Gazzaniga


Wilder
Penfield


Stephen
Kosslyn


Elkhonon

Goldberg


Norman
Geschwind



Emotion


John
Cacioppo


C. Sue Carter


António

Damásio


Richard Davidson


Jean
Decety


Joseph E.
LeDoux


Jaak

Panksepp


Stephen
Porges

Other
/
Misc
.
Categories


Brian
Butterworth


Stephen
Grossberg


Eric
Kandel


George
Ojemann


Isabelle
Peretz


Michael Posner


Vilayanur

S.Ramachandran


Leslie
Ungerleider