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An introduction to Cognitive Sciences Pierre De Loor [email protected] www.enib.fr/~deloor

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Page 1: An introduction to Cognitive Sciences · 2018. 9. 5. · –Python library : numpy, pandas, scify, scikit-learn 2017 Pierre De Loor - Introduction to cognitive ... 2017 Pierre De

An introduction to Cognitive Sciences

Pierre De Loor

[email protected]

www.enib.fr/~deloor

Page 2: An introduction to Cognitive Sciences · 2018. 9. 5. · –Python library : numpy, pandas, scify, scikit-learn 2017 Pierre De Loor - Introduction to cognitive ... 2017 Pierre De

What are cognitives sciences ?

• Human knowledge, How does it work ?

Pierre De Loor - Introduction to cognitive sciences 22017

Page 3: An introduction to Cognitive Sciences · 2018. 9. 5. · –Python library : numpy, pandas, scify, scikit-learn 2017 Pierre De Loor - Introduction to cognitive ... 2017 Pierre De

What are cognitive sciences ?

Philosophy

Psychology

Linguistic

Computer Sciences

Neurosciences

Anthropology

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Page 4: An introduction to Cognitive Sciences · 2018. 9. 5. · –Python library : numpy, pandas, scify, scikit-learn 2017 Pierre De Loor - Introduction to cognitive ... 2017 Pierre De

Some classical (unresolvable?) questions

• What difference beetwen human and animals ?• Is it necessary to speak a langage for thinking ?• Can we understand the functionning of the brain ? If yes, how ? And so

what ?• Can we understand our own functionning (circularity of cognitive science)

?• How is organised the memory ?• How can we learn ?• How can we recognize a shape or a music ?• What is the role of the body in cognition ?• Is the environment more important than the brain ?• What is consciousness, is it in the brain ?• Does colors exist objectively ?• What is the link beetween objective and subjective view ??• Is the culture a fundation of human cognition ?

Pierre De Loor - Introduction to cognitive sciences 42017

Page 5: An introduction to Cognitive Sciences · 2018. 9. 5. · –Python library : numpy, pandas, scify, scikit-learn 2017 Pierre De Loor - Introduction to cognitive ... 2017 Pierre De

This course

• Is an introduction,

• One part about SC and Cognitive Psychology

• The next part discutes more general advancesin cognitive sciences (in philosophy, psychology, neurosciences, biology and computer sciences)

• Evaluation : Practical work &

Pierre De Loor - Introduction to cognitive sciences 52017

Page 6: An introduction to Cognitive Sciences · 2018. 9. 5. · –Python library : numpy, pandas, scify, scikit-learn 2017 Pierre De Loor - Introduction to cognitive ... 2017 Pierre De

Before cognitive sciences

BiologySenseMindRepresentations

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Page 7: An introduction to Cognitive Sciences · 2018. 9. 5. · –Python library : numpy, pandas, scify, scikit-learn 2017 Pierre De Loor - Introduction to cognitive ... 2017 Pierre De

Before cognitive sciences

• Behaviorism in opposition to Philosophy

• Introspection can’t be objective and can’t explain « the human »

• Representations are … representations, the mind is a black box and we cannot affirm representations in it

• We can just observe the link beetween stimulus and behavior : behaviorism

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Page 8: An introduction to Cognitive Sciences · 2018. 9. 5. · –Python library : numpy, pandas, scify, scikit-learn 2017 Pierre De Loor - Introduction to cognitive ... 2017 Pierre De

Before cognitive sciences

• Behaviorists : Watson 1908, Thorndike 1911, Pavlov 1927, Skinner 1938

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Page 9: An introduction to Cognitive Sciences · 2018. 9. 5. · –Python library : numpy, pandas, scify, scikit-learn 2017 Pierre De Loor - Introduction to cognitive ... 2017 Pierre De

Return of representations

• Tolman ~1930 : Representation of the maze is inevitable …

Reward is not

necessary : latent

learning

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Page 10: An introduction to Cognitive Sciences · 2018. 9. 5. · –Python library : numpy, pandas, scify, scikit-learn 2017 Pierre De Loor - Introduction to cognitive ... 2017 Pierre De

Cognitive psychology

• Observing the behavior of human to explain

– Experimentations / Analysis

– Models (simulation/prediction)

– Epistemological postulate : Environment -> Information -> Processing -> Behavior

– This epistemological postulate is discuted by philosophy and critiquized by recent fields of cognitives sciences

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Page 11: An introduction to Cognitive Sciences · 2018. 9. 5. · –Python library : numpy, pandas, scify, scikit-learn 2017 Pierre De Loor - Introduction to cognitive ... 2017 Pierre De

Main fields in cognitive psychology

• Precursor : Nativism (Chomsky ~1968)

– All human own a generic langage. It is the only way to explain that we can speak different langages.

– By the studies of different langage, and their link with the environment, Psychologists can explainthis generic langage

– By the studies of the evolution from baby to adult we can find how this generic langage is progressively transformed

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Page 12: An introduction to Cognitive Sciences · 2018. 9. 5. · –Python library : numpy, pandas, scify, scikit-learn 2017 Pierre De Loor - Introduction to cognitive ... 2017 Pierre De

Main fields in cognitive psychology

• Piagitian field : constructivism

• Action for understanding

• Assimilation - Equilibration - Accomodation

• Abstraction

Piaget 1896-1980

Studies of the « stages » of

cognitive capabilities

of childrens

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Page 13: An introduction to Cognitive Sciences · 2018. 9. 5. · –Python library : numpy, pandas, scify, scikit-learn 2017 Pierre De Loor - Introduction to cognitive ... 2017 Pierre De

Main fields in cognitive psychology

• Examples of Piaget’s phases studies

– 0-2 years – sensorimotor phase -> scheme.

• 6 mounth : If i can’t touch the object it doesn’t exist

– 2-7 years – preoperatory phase

– Concrete operation (7-11 years)

– Formal operation (11 years and +)

Quantity

preservation

Numbers

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Page 14: An introduction to Cognitive Sciences · 2018. 9. 5. · –Python library : numpy, pandas, scify, scikit-learn 2017 Pierre De Loor - Introduction to cognitive ... 2017 Pierre De

Main fields in cognitive psychologie

• Ecological field

– Role of environnment

• Social (Vygotski ~ 1934)– thoughts evolve along with know-how

– Social interactions allow the internalisation of thoughts

• Physic– Gestalttheorie: there are links beetween us and the shape of

things. We are able to detect « interesting » shapes

– Affordances : Environnement help us to resolve problems. No complex reasoning is necessary because object « indicates » what to do.

Pierre De Loor - Introduction to cognitive sciences 142017

thoughts

Page 15: An introduction to Cognitive Sciences · 2018. 9. 5. · –Python library : numpy, pandas, scify, scikit-learn 2017 Pierre De Loor - Introduction to cognitive ... 2017 Pierre De

Main fields in cognitive psychologie

• Example of gestalttheorie items

We can detect the

shape from the ground

but here there are 2

possible

shapes/grounds.

Square is a « good

mental shape » and we

can detect him even if it

is not present.

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Main fields in cognitive psychologie

• Example : affordance (Gibson)

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The work of a researcher in cognitive science

• The natural sciences do not imagine or create, they discover

Theory Hypotheses Observable

Experimentation

validation

Model

Debate in the community

Epistemic Debate

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3 kinds of observables

• Neuronal activity

• Immediat behavior

• Activity

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Page 19: An introduction to Cognitive Sciences · 2018. 9. 5. · –Python library : numpy, pandas, scify, scikit-learn 2017 Pierre De Loor - Introduction to cognitive ... 2017 Pierre De

Neuronal activity

• EEG / MEG : electrical activity (+ dynamic)

Example : After 400 ms there is

a different activity if

The subject recognizes something

• fMRI : oxygen (+ localisation)Example :

Brain area’s activations

According to congruence image / sound

• The brain do something but what exactly ?

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Page 20: An introduction to Cognitive Sciences · 2018. 9. 5. · –Python library : numpy, pandas, scify, scikit-learn 2017 Pierre De Loor - Introduction to cognitive ... 2017 Pierre De

Some examples in neurosciences

From Mario Liotti & Anthony Herdman, Simon

Fraser University et Down Syndrome

Research Foundation

Owen, A. M., Coleman, M. R., Boly, M., Davis, M. H., Laureys,

S., Jolles, D., & Pickard, J. D. (2007). Response to Comments

on “Detecting Awareness in the Vegetative State.” Science,

315(5816), 1221–1221.

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Problems of neurosciences

• Granularity, dynamic, observables ???

• 150 000 000 000 neurons

• Local exchanges but also global phenomena (oscillation)

• Role of the endocrine systemPierre De Loor - Introduction to cognitive sciences 212017

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A question for the next part of this course

Is it serious to think that neuroscience

could explain :

- « What it is like to see, to

undersdand, to love, to suffer ... »

- First person experience,

- Phenomenal consciousness

Phylosophy (phenomenology) and enaction

will help to answer

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Immediat observable

• Answer

– Fast : possibility to test a lot of people

– But it is not always easy to « classify » an answer

• Time response

– Easy

– But some perturbations are possible : order of exercices, tiredness, concentration

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Example of problem of obervation of Immediat behavior [Zibetti 2000]

• Hypothesis : Actions are perceived relative to a goal

• Observables : the answer of people who don’t seethe goal of an action on a video : A man who go toward a bakery and push the door.

• 4 examples of answers,

– I saw a man who buy bred

– I saw a man who enter a bakery

– I saw a man who goes toward a bakery

– A man entered in a shop, he wanted something

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Page 25: An introduction to Cognitive Sciences · 2018. 9. 5. · –Python library : numpy, pandas, scify, scikit-learn 2017 Pierre De Loor - Introduction to cognitive ... 2017 Pierre De

Example of problem of obervation of Immediat behavior [Zibetti 2000]

• Is a « unvisible » goal attributed by the observer ?– I saw a man who buy bred

– I saw a man who enter a bakery

– I saw a man who goes toward a bakery

– A man entered in a shop, he wanted something

• How many are true or false relative to the hypothesis ?

• Classically, more than one « judges » are sollicited and compared [Cohen, 1960]

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Activity observation

• for problem solving, psychologists

generally equate activity with state graphs,

• It is also possible to refine observations, for example with eye tracking,

• Verbalization

– Very informative

– But subjective bias

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Page 27: An introduction to Cognitive Sciences · 2018. 9. 5. · –Python library : numpy, pandas, scify, scikit-learn 2017 Pierre De Loor - Introduction to cognitive ... 2017 Pierre De

Cognitive psychologist is a statistician

• It is important to evaluate the possibility of bias (order of exercices, natural variability, links beetwen variables …)

• It is important to evalutate the « robustness » of the results.

• Example of factors to evaluate– S : Subject (each subject is different)

– O : order (if some exercices, the order of these exercices)

– D : duration (in limited time)

– E : number of trials

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Page 28: An introduction to Cognitive Sciences · 2018. 9. 5. · –Python library : numpy, pandas, scify, scikit-learn 2017 Pierre De Loor - Introduction to cognitive ... 2017 Pierre De

Cognitive psychologist is a statistician

• E : nb trials – D : duration

e1 e2

d1 d2

result

No influence of D or E

e1 e2

influence of E

e1 e2

influence of D

e1 e2

influence of D and E

e1 e2

influence of D and E

But interaction D*E

e1 e2

No influence of D and E

But interaction D*E

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Page 29: An introduction to Cognitive Sciences · 2018. 9. 5. · –Python library : numpy, pandas, scify, scikit-learn 2017 Pierre De Loor - Introduction to cognitive ... 2017 Pierre De

Cognitive psychologist is a statistician

• ANOVA : Variance Analysis

• Null hypothesis Test, p_value

• Software for psychologist :

– Statview

– Statistica

– R

– Python library : numpy, pandas, scify, scikit-learn

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Choice of a test

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Practical work

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Next step ... Next week

2017 Pierre De Loor - Introduction to cognitive sciences 32

Page 33: An introduction to Cognitive Sciences · 2018. 9. 5. · –Python library : numpy, pandas, scify, scikit-learn 2017 Pierre De Loor - Introduction to cognitive ... 2017 Pierre De

An introduction to Cognitive Sciences

session 2

Pierre De Loor

[email protected]

www.enib.fr/~deloor