Computational and Cognitive Neuroscience MSc
Computational and Cognitive Neuroscience MSc
Computational and Cognitive Scientist
Degree program
Master
MAB 2015/7/XI/8
English
4 semesters (2 years)
120
5
40
This programme involves different scientific fields of natural sciences, technological sciences, and humanities as well. The focus of investigations is on the phenomena of cognition - perception, attention, memory, reasoning, thinking, and behaviour - from an interdisciplinary perspective: Anthropology, Artificial Intelligence, Biology, Linguistics, Neuroscience, Philosophy, and Psychology have contributed to its development as core disciplines. The relevance of such an approach gains support from the constant need of building a knowledge-based society.
Tracks/ Specializations:
- Cognitive Models of Science
- Cognitive Neuroscience
MEI:COGSCI
Our master’s programme (Computational and Cognitive Neuroscience, Msc) is part of the Middle European Interdisciplinary master’s programme in Cognitive Science (Mei:CogSci). For more information check the Mei:CogSci homepage. Eligible students can join this programme by spending one mobility semester at one of our partner universities in their 3rd semester. Student interested in the Mei:CogSci programme can also contact us via email for further information: cogsci@ppk.elte.hu.
For visiting students from our Mei:CogSci partner universities we offer multiple courses and research possibilities at ELTE. For more information you can visit our info site.
Our university has longstanding educational and research traditions in a wide area of fields, including both humanities and science, thus providing an appropriate background for a multidisciplinary field such as cognitive science. The skills and knowledge gained during the programme can be applied in a very wide area of basic research, applied research, and jobs outside the academic field. The students will have the opportunity to work with distinguished researchers on various projects in the university laboratories or join research in our partner institutions. They will have the opportunity to participate in international collaborations on research projects, and the chance to do international training with one of our partner universities.
Basic Subject I.
Historical and conceptual introduction to cognitive science from a combined philosophical, psychological, biological and computational point of view. We start with the prehistory of the cognitive paradigm and discuss how cognitivism endeavours to solve its problems. We characterize classic cogsci from the point of view of language, formal systems, and computations and discuss its basic philosophical underpinnings as well as the arising problems. Then we turn to connectionism and the soft computing, brain theory inspired metaphors of the mind, to conclude with the modern picture (and its criticism) in embodiment, the “dynamic hypothesis” as well as the new philosophy of mind.
I. The Nature of Cognitive Science
- From Behaviorism to Cognitivism
- Intentionality, Folk Psy
...
Basic Subjects II. after Psychologist BA
Aim of the course:
The goal of this course is to gain a better understanding of those branches and fundamental concepts of mathematics that are needed most frequently in cognitive scienceIn addition to well-applicable mathematical ideas I also plan to include some fun ideas and proofs that connect to those with practical importance.
Learning outcome, competences knowledge:
- knows the introductory theories of mathematics
attitude:
- Interest for theoretical issues
skills:
- understanding literature that contains mathematical formulas and terminology
- using mathematical knowledge in building computer models (well, at least some, but the more the better).
Content of the course
Topics of the course
- combinatorics
- probability theory
- linear algebra
- the basics of
...
The course offers an introduction to the epistemological tradition in Western philosophy. In addition to some historical investigations introducing central epistemological problems and some of the most essential approaches, the main focus of the course is on more recent advances in 20th century philosophy, with special emphasis on theories of scientific cognition as the paragon of knowledge acquisition.
The course includes a series of lectures and a reading seminar.
The main topics of the course are the followings:
1. Epistemological problems in the history of philosophy
- Plato’s Epistemology, Aristotle on Knowledge, Ancient Scepticism
- The Epistemology of Descartes, Locke, Berkeley, and Hume. The Problem of Induction
- Kant and Kantian Epistemology. A Priori Justification
...
Introduction to cognitive informatics
- What is computational cognitive modelling, types of cognitive modelling, what is computational cognitive modelling good for, multiple levels of cognitive modelling, successes and pitfalls of cognitive modelling
- Introduction to symbolic modelling
- Introduction to connectionist type modelling
- Connectionist vs Symbolic vs Hybrid Modelling
Connectionist Modelling
- What is an artificial neuron and how it transmits information – Activation functions, connection weights, output computation
- McCulloch-Pitts neuronal type
- Learning rules
- Network behaviour
- Worked examples
Learning and memory and knowledge representation, concepts, categories
- Psychological studies and computational models of concept formation, concept learning and k
...
Our words, sentences are about—refer to—things in the world: objects, people, events. Plausibly, the meanings of expressions play a central role in explaining this referential feature: for example, it is in virtue of the meaning of the word ’horse’ that it refers to horses. But what exactly does this role played by meaning consist in? The answer is not at all straightforward. Consider these two sentences:
Mark Twain was a famous novelist.
Samuel Clemens was a famous novelist.
How does the meaning of the first sentence differ from the meaning of the second? After all, both are about the same individual: who was called Samuel Clemens but became famous under the pseudonym ‘Mark Twain’. Yet—according to Gottlob Frege—the two sentences cannot have the same meaning because s
...
Basic Subjects II. after Biologist BSc
The course offers an introduction to the epistemological tradition in Western philosophy. In addition to some historical investigations introducing central epistemological problems and some of the most essential approaches, the main focus of the course is on more recent advances in 20th century philosophy, with special emphasis on theories of scientific cognition as the paragon of knowledge acquisition.
The course includes a series of lectures and a reading seminar.
The main topics of the course are the followings:
1. Epistemological problems in the history of philosophy
- Plato’s Epistemology, Aristotle on Knowledge, Ancient Scepticism
- The Epistemology of Descartes, Locke, Berkeley, and Hume. The Problem of Induction
- Kant and Kantian Epistemology. A Priori Justification
...
The course offers an introduction to symbolic logic and its semantics. The main topics are:
- Propositional logic: Symbolic language and syntactical notions; Propositional calculus and derivability; Truth values and bivalence; Truth tables; Interpretation, Model and Inference
- First order logic: Predicate logic; Quantification and variables; Quantificational calculus; Interpretation and the Universe of discourse; First order models
- Metalogical properties: Semantic soundness and completeness; First order theories; Gödel’s incompleteness theorems, Church’s theorem and Tarski’s results on truth function
- Non-classical logics: Value gaps and multivalent logics; Higher order logics; Modal logics
Learning outcome, competences
knowledge:
- theoretical development of symbolic lo
...
Introduction to cognitive informatics
- What is computational cognitive modelling, types of cognitive modelling, what is computational cognitive modelling good for, multiple levels of cognitive modelling, successes and pitfalls of cognitive modelling
- Introduction to symbolic modelling
- Introduction to connectionist type modelling
- Connectionist vs Symbolic vs Hybrid Modelling
Connectionist Modelling
- What is an artificial neuron and how it transmits information – Activation functions, connection weights, output computation
- McCulloch-Pitts neuronal type
- Learning rules
- Network behaviour
- Worked examples
Learning and memory and knowledge representation, concepts, categories
- Psychological studies and computational models of concept formation, concept learning and k
...
Our words, sentences are about—refer to—things in the world: objects, people, events. Plausibly, the meanings of expressions play a central role in explaining this referential feature: for example, it is in virtue of the meaning of the word ’horse’ that it refers to horses. But what exactly does this role played by meaning consist in? The answer is not at all straightforward. Consider these two sentences:
Mark Twain was a famous novelist.
Samuel Clemens was a famous novelist.
How does the meaning of the first sentence differ from the meaning of the second? After all, both are about the same individual: who was called Samuel Clemens but became famous under the pseudonym ‘Mark Twain’. Yet—according to Gottlob Frege—the two sentences cannot have the same meaning because s
...
Basic Subjects II. after Communication BA
Aim of the course:
The goal of this course is to gain a better understanding of those branches and fundamental concepts of mathematics that are needed most frequently in cognitive scienceIn addition to well-applicable mathematical ideas I also plan to include some fun ideas and proofs that connect to those with practical importance.
Learning outcome, competences knowledge:
- knows the introductory theories of mathematics
attitude:
- Interest for theoretical issues
skills:
- understanding literature that contains mathematical formulas and terminology
- using mathematical knowledge in building computer models (well, at least some, but the more the better).
Content of the course
Topics of the course
- combinatorics
- probability theory
- linear algebra
- the basics of
...
The course starts with an introduction of basic concepts of statistics (distributions and estimation of distribution parameters; hypothesis testing, types of errors, significance, power, and effect size), and continues with methods of univariate statistics (correlation and regression; comparing two or more means; between-subject and within-subject designs; non-parametric methods). Depending on the audience, we can also address more complex methods such as multiple regression, analysis of covariance, MANOVA, and exploratory factor analysis. For carrying out statistical tests we use SPSS and R-Studio.
Learning outcome, competences knowledge:
- use SPSS and R-Studio
attitude:
- More open to the explorative and conceptual analysis
- Statistics is understandable and can be used
...
The course aims to overview the fundamental structural and dynamic principles of neurobiology. First, it decomposes the nervous system into the basic cellular constituents and mechanisms, and then redintegrates them into a large network model of the macroscopic brain. The course will step-by-step introduce neurons, circuitries, systems and macroscopic functional networks. It will review the functional segregation of cortical areas and their association with subcortical structures from systems neuroscience and neuroanatomical point of views. Individual lectures will be devoted to the major neural systems and cortical areas and their relationship to sensory, perceptual, memory, language, motor and executive functions. Finally, the course will cover the basic brain rhythms, EEG,
...
Basic Subjects II. after Philosophy BA
Aim of the course:
The goal of this course is to gain a better understanding of those branches and fundamental concepts of mathematics that are needed most frequently in cognitive scienceIn addition to well-applicable mathematical ideas I also plan to include some fun ideas and proofs that connect to those with practical importance.
Learning outcome, competences knowledge:
- knows the introductory theories of mathematics
attitude:
- Interest for theoretical issues
skills:
- understanding literature that contains mathematical formulas and terminology
- using mathematical knowledge in building computer models (well, at least some, but the more the better).
Content of the course
Topics of the course
- combinatorics
- probability theory
- linear algebra
- the basics of
...
The course starts with an introduction of basic concepts of statistics (distributions and estimation of distribution parameters; hypothesis testing, types of errors, significance, power, and effect size), and continues with methods of univariate statistics (correlation and regression; comparing two or more means; between-subject and within-subject designs; non-parametric methods). Depending on the audience, we can also address more complex methods such as multiple regression, analysis of covariance, MANOVA, and exploratory factor analysis. For carrying out statistical tests we use SPSS and R-Studio.
Learning outcome, competences knowledge:
- use SPSS and R-Studio
attitude:
- More open to the explorative and conceptual analysis
- Statistics is understandable and can be used
...
The course aims to overview the fundamental structural and dynamic principles of neurobiology. First, it decomposes the nervous system into the basic cellular constituents and mechanisms, and then redintegrates them into a large network model of the macroscopic brain. The course will step-by-step introduce neurons, circuitries, systems and macroscopic functional networks. It will review the functional segregation of cortical areas and their association with subcortical structures from systems neuroscience and neuroanatomical point of views. Individual lectures will be devoted to the major neural systems and cortical areas and their relationship to sensory, perceptual, memory, language, motor and executive functions. Finally, the course will cover the basic brain rhythms, EEG,
...
Introduction to cognitive informatics
- What is computational cognitive modelling, types of cognitive modelling, what is computational cognitive modelling good for, multiple levels of cognitive modelling, successes and pitfalls of cognitive modelling
- Introduction to symbolic modelling
- Introduction to connectionist type modelling
- Connectionist vs Symbolic vs Hybrid Modelling
Connectionist Modelling
- What is an artificial neuron and how it transmits information – Activation functions, connection weights, output computation
- McCulloch-Pitts neuronal type
- Learning rules
- Network behaviour
- Worked examples
Learning and memory and knowledge representation, concepts, categories
- Psychological studies and computational models of concept formation, concept learning and k
...
Basic Subjects II. after Linguistics BA
Aim of the course:
The goal of this course is to gain a better understanding of those branches and fundamental concepts of mathematics that are needed most frequently in cognitive scienceIn addition to well-applicable mathematical ideas I also plan to include some fun ideas and proofs that connect to those with practical importance.
Learning outcome, competences knowledge:
- knows the introductory theories of mathematics
attitude:
- Interest for theoretical issues
skills:
- understanding literature that contains mathematical formulas and terminology
- using mathematical knowledge in building computer models (well, at least some, but the more the better).
Content of the course
Topics of the course
- combinatorics
- probability theory
- linear algebra
- the basics of
...
The course starts with an introduction of basic concepts of statistics (distributions and estimation of distribution parameters; hypothesis testing, types of errors, significance, power, and effect size), and continues with methods of univariate statistics (correlation and regression; comparing two or more means; between-subject and within-subject designs; non-parametric methods). Depending on the audience, we can also address more complex methods such as multiple regression, analysis of covariance, MANOVA, and exploratory factor analysis. For carrying out statistical tests we use SPSS and R-Studio.
Learning outcome, competences knowledge:
- use SPSS and R-Studio
attitude:
- More open to the explorative and conceptual analysis
- Statistics is understandable and can be used
...
The course aims to overview the fundamental structural and dynamic principles of neurobiology. First, it decomposes the nervous system into the basic cellular constituents and mechanisms, and then redintegrates them into a large network model of the macroscopic brain. The course will step-by-step introduce neurons, circuitries, systems and macroscopic functional networks. It will review the functional segregation of cortical areas and their association with subcortical structures from systems neuroscience and neuroanatomical point of views. Individual lectures will be devoted to the major neural systems and cortical areas and their relationship to sensory, perceptual, memory, language, motor and executive functions. Finally, the course will cover the basic brain rhythms, EEG,
...
Introduction to cognitive informatics
- What is computational cognitive modelling, types of cognitive modelling, what is computational cognitive modelling good for, multiple levels of cognitive modelling, successes and pitfalls of cognitive modelling
- Introduction to symbolic modelling
- Introduction to connectionist type modelling
- Connectionist vs Symbolic vs Hybrid Modelling
Connectionist Modelling
- What is an artificial neuron and how it transmits information – Activation functions, connection weights, output computation
- McCulloch-Pitts neuronal type
- Learning rules
- Network behaviour
- Worked examples
Learning and memory and knowledge representation, concepts, categories
- Psychological studies and computational models of concept formation, concept learning and k
...
Basic Subjects II. after Programmer BSc
The course aims to overview the fundamental structural and dynamic principles of neurobiology. First, it decomposes the nervous system into the basic cellular constituents and mechanisms, and then redintegrates them into a large network model of the macroscopic brain. The course will step-by-step introduce neurons, circuitries, systems and macroscopic functional networks. It will review the functional segregation of cortical areas and their association with subcortical structures from systems neuroscience and neuroanatomical point of views. Individual lectures will be devoted to the major neural systems and cortical areas and their relationship to sensory, perceptual, memory, language, motor and executive functions. Finally, the course will cover the basic brain rhythms, EEG,
...
The course offers an introduction to the epistemological tradition in Western philosophy. In addition to some historical investigations introducing central epistemological problems and some of the most essential approaches, the main focus of the course is on more recent advances in 20th century philosophy, with special emphasis on theories of scientific cognition as the paragon of knowledge acquisition.
The course includes a series of lectures and a reading seminar.
The main topics of the course are the followings:
1. Epistemological problems in the history of philosophy
- Plato’s Epistemology, Aristotle on Knowledge, Ancient Scepticism
- The Epistemology of Descartes, Locke, Berkeley, and Hume. The Problem of Induction
- Kant and Kantian Epistemology. A Priori Justification
...
Our words, sentences are about—refer to—things in the world: objects, people, events. Plausibly, the meanings of expressions play a central role in explaining this referential feature: for example, it is in virtue of the meaning of the word ’horse’ that it refers to horses. But what exactly does this role played by meaning consist in? The answer is not at all straightforward. Consider these two sentences:
Mark Twain was a famous novelist.
Samuel Clemens was a famous novelist.
How does the meaning of the first sentence differ from the meaning of the second? After all, both are about the same individual: who was called Samuel Clemens but became famous under the pseudonym ‘Mark Twain’. Yet—according to Gottlob Frege—the two sentences cannot have the same meaning because s
...
Basic Subjects II. after Engineering BSc
The course aims to overview the fundamental structural and dynamic principles of neurobiology. First, it decomposes the nervous system into the basic cellular constituents and mechanisms, and then redintegrates them into a large network model of the macroscopic brain. The course will step-by-step introduce neurons, circuitries, systems and macroscopic functional networks. It will review the functional segregation of cortical areas and their association with subcortical structures from systems neuroscience and neuroanatomical point of views. Individual lectures will be devoted to the major neural systems and cortical areas and their relationship to sensory, perceptual, memory, language, motor and executive functions. Finally, the course will cover the basic brain rhythms, EEG,
...
The course offers an introduction to the epistemological tradition in Western philosophy. In addition to some historical investigations introducing central epistemological problems and some of the most essential approaches, the main focus of the course is on more recent advances in 20th century philosophy, with special emphasis on theories of scientific cognition as the paragon of knowledge acquisition.
The course includes a series of lectures and a reading seminar.
The main topics of the course are the followings:
1. Epistemological problems in the history of philosophy
- Plato’s Epistemology, Aristotle on Knowledge, Ancient Scepticism
- The Epistemology of Descartes, Locke, Berkeley, and Hume. The Problem of Induction
- Kant and Kantian Epistemology. A Priori Justification
...
Our words, sentences are about—refer to—things in the world: objects, people, events. Plausibly, the meanings of expressions play a central role in explaining this referential feature: for example, it is in virtue of the meaning of the word ’horse’ that it refers to horses. But what exactly does this role played by meaning consist in? The answer is not at all straightforward. Consider these two sentences:
Mark Twain was a famous novelist.
Samuel Clemens was a famous novelist.
How does the meaning of the first sentence differ from the meaning of the second? After all, both are about the same individual: who was called Samuel Clemens but became famous under the pseudonym ‘Mark Twain’. Yet—according to Gottlob Frege—the two sentences cannot have the same meaning because s
...
Core Curriculum
On the basis of the classical and modern theories this course gives master level knowledge in cognitive psychology. The main goals of the course are (1) to train basic skills that are necessary to use the concepts of cognitive psychology, (2) to introduce determinant theories, (3) to review the basic methods used in the empirical analyses of cognitive functions. The structure of the course consists of two parts: a general empirical foundation and an intensive discussion about the elements of the cognitive architecture. The overall theory systems and the unique theories of the cognitive fields are discussed equally. The form of the course enhances competence of the students, which will enable them to learn the research results supporting and/or contradicting the theories in
...
To review the most important experimental methods and paradigms of cognitive psychology in the topics of perception, attention, cognitive control, learning, memory, language, thinking and problem solving. The presented exparimental paradigms and the tasks are also useful help for successfully cpmpleting the comprehensive exam.
Learning outcome, competences
knowledge:
- acknowledgeing the genral structure and reason of designing experiments
- introduction to basic experimental paradigms
- undertanding the imponrtance of making experiments
attitude:
- realization of the importance of experimental methods
skills:
- understanding the methodological part of scientific papers
- acquitition of the skill of understanding the visually represented results
- acquisition of
...
On the basis of the classical and modern theories this course gives master level knowledge in cognitive psychology. The main goals of the course are (1) to train basic skills that are necessary to use the concepts of cognitive psychology, (2) to introduce determinant theories, (3) to review the basic methods used in the empirical analyses of cognitive functions. The structure of the course consists of two parts: a general empirical foundation and an intensive discussion about the elements of the cognitive architecture. The overall theory systems and the unique theories of the cognitive fields are discussed equally. The form of the course enhances competence of the students, which will enable them to learn the research results supporting and/or contradicting the theories in
...
- Scientific inquiry: invention and test (Introductory examples for hypotheses, explanations, tests etc.)
- The test of a hypothesis (Experimental and crucial tests. Auxiliary and ad hoc hypotheses.)
- Observation and theory (The Baconian model of science. Novum Organum. Inductive reasoning. Nature and experiment. Observation and experiment. The decuctive-nomological model of explanation. Underdetermination of theories by facts. Observer influence in the various sciences.)
- Positivism (The British Empiricists. Comte and origins of positivism. Mach and empiriocriticism. The Vienna Circle. The fall of positivism: protocol sentences, justification, demarcation. Problems of induction. Fallibilism.)
- Postpositivism (The cumulative view of XIX. century. Kuhn and scientific revolutions.
...
Aim of the course:
Students will be able to write and modify simple scripts, to run experiments, analize data and simulate models.
Content of the course
Topics of the course
- Bases of computer programming
- Python and Matlab
- Experimenting software use: OpenSesame and PsychoPy
- Data analysis with Python: numpy, pandas, scipy, statsmodels, matplotlib
- Simple simulations with Python
Learning outcome, competences
knowledge:
- write and modify simple scripts
- run experiments
attitude:
- comprehensive practical interest
skills:
- experimental designs
Learning activities, learning methods
Lectures and practical
Evaluation of outcomes
earning requirements, mode of evaluation, criteria of evaluation:
requirements
- attendance
- designing Python scripts, analysis or
...
This is an introductory course to computational neuroscience. The main question is how to use mathematics in order to describe the structure, dynamics and function of the neural system. We will learn examples of neural implementation of cognitive functions. A science major is a great advantage for this course but it will provide interesting insight to our up to date understanding of the brain potentially for anyone.
Some chapters of Peter Dayan and LF Abbott: Theoretical Neuroscience (Computational and Mathematical Modeling of Neural Systems) are useful.
Background info: The Encyclopeida of Computational Neuroscience is under development: http://www.scholarpedia.org/article/Encyclopedia_of_Computational_Neuroscience
We will discuss, how the mathematics can be applied to
...
- Introduction: The history of studies on animal thinking. From anecdotal cognitivism to modern cognitive ethology.
- Methods of behaviour observation
- Traditional comparative psychology and ethology as different approaches. Data collection in nature, modern lab. studies, ways of studying human cognition.l
- Understanding physical world: skills and evolutionary compulsions. Object representation abilities, numerical abilities.
- Skills of understanding social worlds. The Machiavellian intelligence. Primate studies and observations on human infants: the emergence of human cognition.
- Levels if intentionality: mentalistic interpretations of others' behaviour. The effect of experimenter on the observations: Clever-Hans effects.
- What is intelligence? A biological approach.
- Measuring
...
The course overviews the fundamental concepts, models and methods of neuropsychology. The course starts with introducing a general neuropsychological framework for acquired deficits, grand syndromes and their relation to cognitive architecture. As it further develops, it examines the neural bases of higher order mental functions, including research from human experimental and human clinical perspectives, while focusing on the balance in presenting knowledge both about the brain and about cognition.
Learning outcome, competences
knowledge:
- appropriate knowledge in the main fields of neuropsychology
- neuropsychlogical assessment and its relation to diagnistics
attitude:
- sensitivity to and interest in noticing neuropsychological phenomena and problems
skills:
The course addresses fundamental issues in the philosophy of mind such as the mind-body problem, consciousness, qualia, introspection, self-understaning/self-ignorance, and intentionality. Classic articles (e.g., by Thomas Nagel, David Rosenthal, and David Armstrong) and texts representing the research of the past decade (e.g., by Van Gulick and E. Schwitgabel) are equally used, for a balanced picture. Topics overlapping with the philosophy of cognitive science (e.g., extended mind, modularity) are also part of the course material. Overviews of the range of positions on each topic are provided by the instructor.
Learning outcome, competences
knowledge:
- broad theoretical knowledge in Philosophy of Mind
attitude:
- comprehensive theoretical interest
skills:
- ability
...
The aim of the curse is to give an introduction to cognitive psychological models of language processing and production, within a broader framework of intentional human communication. The course is necessarily interdisciplinary, as several concepts, models, and evidence from philosophy of language, linguistics, neurolinguistics, neuropsychology, neurosciences and computational modelling will be touched upon, although the major focus will be on psychological models and methodology. Here again specific emphasis will be put on acquired and developmental impairments of intentional communication and language.
The main topics to be discussed are the followings: General theoretical approaches to the psychology of language, Sentence processing and discourse processing: key phenomena
...
The topic of knowledge representation has strong connection with most fields of cognitive science, e.g. vision, sensory-motor integration, language, memory, reasoning, and imagery processes. The aim of this course is to present a new theoretical viewpoint on categorization and conceptual representation (the so called ‘concept empiricism’ approach of J. Prinz and a similar view of L.W. Barsalou). From this starting point we can discuss all important questions of knowledge representation with special focus on empirical questions, cognitive development, and the connection to other cognitive processes.
Learning outcome, competences
knowledge:
- Current methods and main objectives in the field of knowledge representation
attitude:
- Utilisation of knowledge in scientific com
...
Specialisation in Cognitive Models of Science
The course will focus on some fundamental problems of cognition and communication. Its main methodological tool will be a philosophical analysis of the following concepts: representations, sign, information, knowing and knowledge, virtuality, openness, reality and virtual reality, communication, community, culture, individual vs. social cognition.
Certain elements of cognitive science, information theory, communication theory, theory of culture will be referred and analyzed.
In the representation of the subject matter of knowledge two essentially different strategies can be identified: the free and the bound (bound, non-free, connected, etc.) strategies. As an illustration the physiological vs. cultural representations can be mentioned. These different strategies have
...
This course is an introduction to the core concepts and disciplines of cognitive science. We shall cover important topics in philosophy of mind, language and cognition, cognition and evolution, notions of cognitive architecture and some areas of neuroscience. Our goal is to provide a conceptual foundation around which studies of different disciplines can be organized, and a sense of unity of cognitive science’s world view.
Learning outcome, competences
knowledge:
- broad theoretical knowledge in the field
attitude:
- comprehensive theoretical interest
skills:
- comprehensive methodological knowledge
Content of the course
Topics of the course
- philosophy of mind,
- language and cognition,
- cognition and evolution,
- notions of cognitive architecture
- areas of n
...
The course will provide an overview of the history of Western sciences from its Ancient beginning until the emergence of cognitive sciences in the middle of 20th century. The lectures will focus on the history of scientific thinking instead of the concrete historical events or advancements in scientific disciplines. The history of scientific thinking – following a kind of Lakatosian methodology – will be presented as a historical reconstruction of scientific thinking. (As Lakatos mentioned, the “real history” of science can be identified as footnotes on the “reconstructed” historical process.) The meaning of this reconstruction is clear enough: to present the historical process which eventuated in the formation of cognitive science.
The main topics will be the follow
...
Aim of the course:
Human ethology is an integral part of ethology, which is the biological study of animal behaviour. In this lecture the basic concepts of ethology are discussed in relation to human ethology. We also present an overview on the development of this field and explain how the interaction between ethology and psychology generated a novel discipline of studying human behaviour. We present an integrative approach to behaviour by discussing the importance of studying function, mechanism, development and evolution of behaviour in parallel.
Learning outcome, competences
knowledge:
- Basic concepts of ethology
- Relations of cognitive mechanisms and their malfunctioning
attitude:
- Ability to understand and ask questions in relation to the field
skills:
- Skills
...
„Cognitive anthropology is the study of the relation between human society and human thought.” -Roy D’Andrade, The Development of Cognitive Anthropology
The aim of this course is to present some of the main themes of contemporary cognitive anthropology and the various ways how to use an interdisciplinary approach of cognitive science and anthropology.
Main focuses are:
- introduction of research strategies of contemporary cognitive anthropology;
- introducing research perspectives which are promising in sheding light on muliple relations between human cognition and cultural phenomena.
Topics:
- Anthropology and Representations
- Natural pedagogy: Childhood as a Crucial Period of Acquisition of Cultural Knowledge
- Naiv Theories (Naiv Biology, Naiv Sociology, Naiv Psych
...
The course aims to introduce the main concepts of sociology of knowledge for students of cognitive science and to discuss a set of relevant research. The class will start with an overview of certain ideas of classical authors of the field: Durkheim and Mauss’s ideas on social origins of classification; Mannheim’s views on the connections between class position and worldview; Schütz’s phenomenological sociology; Beger and Luckmann’s conception on the social construction of reality; Garfinkel’s demonstration of the morality of everyday cognition. Then the discussion turns to the topics of social constructionist accounts of various cognitive phenomena. While more mainstream cognitive psychology can be considered as patterned according to a set of “individualist” premises regarding
...
The aim of the course is to offer students the possibility to do intensive, tutored research in order to write a high quality MA thesis, based on well-designed and correctly executed empirical research. The actual topic and schedule of this practical course therefore is highly individualised according to the actual research focus and methodology.
Learning outcome, competences knowledge:
- learning how to do intensive, tutored research
- complex nature of the higher order cognitive mechanisms
attitude:
- sensitivity to the methodological questions
skills:
- ability integrate the different theories related to conceptual representation
Learning activities, learning methods: The form of the course is a colloquium but the activity of the students is highly expected during
...
For more information see below (Specialisation in Cognitive Models of Science and Specialisationin Cognitive Neuroscience).
Specialisation in Cognitive Neuroscience
The two main goals of the course are the demonstration of the methods of cognitive neuroscience, and the presentation of classical and current findings of cognitive and developmental neuroscience. The presentation of physical, biochemical and morphological bases, and historical accounts has the aim that students understand the choice of particular methods, and be able to assess the advantages and disadvantages of them. The presentation of methods is followed by an intensive review of the main findings of cognitive neuroscience both in the fields of cognition (perception, memory, consciousness, language, etc.) and emotion (face perception, prosody, etc.).
The unfolding of the interrelations of brain-cognition-behavior triad is completed by the review of the findings of
...
The aim of this course is to present the methods of cognitive neuropsychology and developmental neuropsychology. The developmental neuropsychology part covers the research methodology of the classical and modern adult neuropsychology. The practical is similar to the lecture in its methods, but different in its approach. The exploration of developmental and acquired childhood disorders and patterns are not achievable without the integrated knowledge of the cognitive architecture and the development of the brain. The course gives a methodical basis and trains skills that are necessary in methodology.Main topics: Test and test-systems, The atypical development of perception, Childhood disorders of memory,Language disorders, Disorders of reading and writing, Developmental deficit in
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The course will cover cognitive and computational aspects of human vision that extends beyond biological vision. It will start with a historical overview of major technological inventions that influenced our understanding of human vision. Each lecture will frame the topic according David Marr’s levels of explanations. Then, through a variety of examples the course will step-by-step introduce information theory from Shannon information to the formalism of mutual information and finally the Bayesian model. In the course we will overview the major pathways of visual information processing, discuss the differences between bottom-up, top-down and reverse hierarchy models. Special focus will be given to different perceptual biases, signal detection, choice-probability, game theory and
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This course aims at overviewing the most important methods of developmental research, namely, the special role of observation in developmental psychology. Methodology of observation: design; selection of categories; quantitative attributes of observational variables; methods of recording; instruments; reliability; evaluation.Experiments in developmental research. The natural and the quasi experiments. Cross-sectional and longitudinal strategy, and the possibilities of their combination. Data analysis. Interpretation of results - mediator and moderator effect.
Learning outcome, competences
knowledge:
- Knowledge on the most important models of development
- Current methods and main objectives in Developmental reserach
attitude:
- Utilisation of knowledge in scientific
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The aim of the course is to provide an insight into the problem of knowledge representation. Our goal is to connect viewpoints of cognitive with that of the cultural. We start with the problem of knowledge acquisition, discussing the development of early concepts, the impact of language and subsequently the role of experience (expertise) in forming mental knowledge representations. With the presentation of dynamic conceptual representation models, with the help of discussing scheme and script concepts we connect the cultural and personal nature of knowledge.
knowledge:
- understanding the interaction between knowledge representation systems and the other cognitive mechanisms
attitude:
- comprehensive theoretical interest
skills:
- ability to form new research questions
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Aim of the course:
Human ethology is an integral part of ethology, which is the biological study of animal behaviour. In this lecture the basic concepts of ethology are discussed in relation to human ethology. We also present an overview on the development of this field and explain how the interaction between ethology and psychology generated a novel discipline of studying human behaviour. We present an integrative approach to behaviour by discussing the importance of studying function, mechanism, development and evolution of behaviour in parallel.
Learning outcome, competences
knowledge:
- Basic concepts of ethology
- Relations of cognitive mechanisms and their malfunctioning
attitude:
- Ability to understand and ask questions in relation to the field
skills:
- Skills
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The overall aim of the course is to provide research experience for students in one of several specific domains in cognitive science. The principle task of it is thus to involve interested students to almost all important phases of ongoing research activities, and invite them into cooperative teamwork.
Learning outcome, competences
knowledge:
- get real research experience
- acknowledge and try of the relevant phases of a research
attitude:
- acquisition of the approach of an active researcher
skills:
- comprehensive methodological knowledge
Learning activities, learning methods:
The thesis made by the students about an important study of a field help them to be involved to the problems with the supervisors.
Evaluation of outcomes
Learning requirements, mode of
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For more information see below (Specialisation in Cognitive Models of Science and Specialisationin Cognitive Neuroscience).
The aim of the course is to offer students the possibility to do intensive, tutored research in order to write a high quality MA thesis, based on well-designed and correctly executed empirical research. The actual topic and schedule of this practical course therefore is highly individualised according to the actual research focus and methodology.
Learning outcome, competences knowledge:
- learning how to do intensive, tutored research
- complex nature of the higher order cognitive mechanisms
attitude:
- sensitivity to the methodological questions
skills:
- ability integrate the different theories related to conceptual representation
Learning activities, learning methods: The form of the course is a colloquium but the activity of the students is highly expected during
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Specialisation in Cognitive Models of Science- Required Elective Courses
The two main goals of the course are the demonstration of the methods of cognitive neuroscience, and the presentation of classical and current findings of cognitive and developmental neuroscience. The presentation of physical, biochemical and morphological bases, and historical accounts has the aim that students understand the choice of particular methods, and be able to assess the advantages and disadvantages of them. The presentation of methods is followed by an intensive review of the main findings of cognitive neuroscience both in the fields of cognition (perception, memory, consciousness, language, etc.) and emotion (face perception, prosody, etc.).
The unfolding of the interrelations of brain-cognition-behavior triad is completed by the review of the findings of
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Objectives
The aim of this course is to introduce students to the field of scientific modelling, model synthesis and analysis. As such, less emphasis will be on a "top-down" approach than in standard lecture courses. Students will have an opportunity to decide which topics will shape the direction of the course.
Contents
Topics to be covered:
- History of Complex Systems (Turing, von Neumann, Ulam, Conway, Wolfram)
- Introduction to Cellular Automata (1D/2D CA, rule codes,phenomenological studies, behaviour classes)
- CA Models of Fluid Dynamics (Lattice Gas Automata)
- Self-Organized Criticality (Sandpile Model, Forest fire model)
- Complex systems and emergence in Complex Systems
- Complex Networks, Small World Networks
One or two other topics will also be covered depending
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The main objective of this course is to give an overview on the basics of research methodologies (main points listed below), concentrating on the heterogeneity of disciplines covered by Cognitive Science.
Research Methodologies
- Descriptive methods
- Naturalistic observation
- Survey methods
- Case studies
- Archival research
- Experimental methods
- Constants and variables
- Experimental control
- Experimental designs
Learning outcome, competences
knowledge:
- get real research experience
- acknowledge and try of the relevant phases of a research
attitude:
- acquisition of the approach of an active researcher
skills:
- comprehensive methodological knowledge
Learning activities, learning methods
Lectures and interactive discussions
Evaluation of outcomes
Learning
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Main Topics of the course
Scientific Thinking and its Mental Infrastructure
In the Western (academic) world scientific thinking is generally viewed as the most powerful means to tackle different problems and to find the most effective solutions for them. The ability to create good theories in order to describe and explain the phenomena is acknowledged as central to scientific thinking. Accordingly, a kind of objectivity and pure rationalism are attributed to it. But scientific thinking is neither a pure cognitive process nor does it take place in an empty space. In this chapter it is argued that scientific thinking just like any other normal every day type of thinking is to be understood as a cognitive-affective process embedded in a mental infrastructure. This thesis will be
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Specialisation in Cognitive Neuroscience- Required Elective Courses
The course focuses on the neural mechanisms of visual information processing from the sensory to perceptual aspects to it. It starts with the anatomical foundation of the visual and oculomotor system. It will cover the main cellular pathways from the retina through the thalamus and visual cortex to the higher visual cortical areas, including their associations with different of attributes of the visual scene. Transformation between these stages and the receptive field organization at the retinal, LGN and cortical levels will be discussed. The cortical circuitry of visual cortex will be discussed in anatomical and cellular neurophysiological details. The primary segregation and recombination of color, shape, motion and disparity channels will be introduced. The course puts a
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The aim of the course is to give a detailed overview of the relationship between language and cognition within an interdisciplinary framework, but with a strong emphasis on the relevant findings from empirical psychology. A special focus will be set on conceptual cognition and its relationships – both developmental and functional – to linguistic abilities. So, among the topics to be discussed, there will be a balance between phenomena and models of development and mature functions.
In line with the interdisciplinary framework, the philosophical history of the issue will be briefly discussed, including the fundamental questions and approaches elaborated within the philosophical tradition, but the main focus of the course will be set on psychological models: the various mod
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The course reviews the current models of numerical cognition. We cover development of numerical cognition, together with the developmental impairment of those abilities. Relevant aspects of animal cognition is also discussed.
Content of the course
Topics of the course
- development of numerical cognition,
- developmental impairment of those abilities.
- relevant aspects of animal cognition is also discussed.
Learning activities, learning methods
Lectures and interactive discussions
Evaluation of outcomes
Learning requirements, mode of evaluation, criteria of evaluation:
requirements
- attendance
mode of evaluation: examination
The goal of the course is to provide basic knowledge on the (primarily physiological) mechanisms underlying cognitive psychological processes such as learning, memory, attention, sleep, motivation and psychopharmacology. Both elementary aspects and integrative views are covered including the most important methodological (electrophysiology, biochemistry, neuroimaging, etc.) issues. The rationale behind this approach is that the horizon of the interpretation of the findings of basic and applied psychology becomes much wider and their link to principles of natural sciences easier to understand.
Learning activities, learning methods
Lectures and interactive discussions
mode of evaluation: examination
In vivo functional imaging of the brain has dramatically enhanced researchers’ ability to examine the neural correlates of cognition and behavior. In particular functional Magnetic Resonance Imaging (or fMRI) is a particularly attractive technique. fMRI relies on the physical and magnetic properties of brain tissue (in particular blood) which change under conditions of neural activity. This Blood Oxygen Level Dependent (BOLD) contrast is endogenous to the brain and unlike Positron Emission Tomography does not demand the injection of radioactive contrast agents. fMRI (based on BOLD) is therefore a perfectly safe technique for studying brain function, can and is easily applied to the study of diverse populations (including children), and has reasonable spatial (“where in the bra
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The program provides graduates with the necessary theoretical/intellectual and empirical tools to pursue an academic career (Ph.D. program) in cognitive science or in one of the disciplines related to it. Apart from basic research graduates in cognitive science increasingly find work in applied research: prospective career fields include the IT-sector (interaction design, usability, knowledge management, etc.), education, and biomedical and clinical research, as well as economy. The generic skills (such as teamwork, ability to communicate, reflection and evaluation skills, ability to quickly learn and adapt) acquired by graduates are of use in a variety of careers in the private sector. Graduates of cognitive science are especially suited to work in highly interdisciplinary area, bringing experience in mediating between disciplines. These include the fields of IT and education (see above), as well as the areas of consulting, human resources, and science writing.
- Human Resources employee
- Researcher
- IT expert
2,100 EUR
2,100 EUR
120 EUR (non-refundable)
120 EUR (non-refundable)
Entrance exam fee: 120 EUR (non-refundable)
Entrance exam fee: 120 EUR (non-refundable)
2,100 EUR
120 EUR (non-refundable)
Entrance exam fee: 120 EUR (non-refundable)
Yes
02, Sep, 2025
10, Jul, 2025
No
Entry requirements
A) Full acknowledgement is given for the following degrees: a Bachelor’s degree in: Psychology, Computer Engineering, Software Engineering, Biology, Liberal Arts: Philosophy Specialisation; college degrees (as according to the Hungarian higher education system before 2006): Psychology, Information Technology, Computer Programmer Mathematician, Teacher of Computer Science, Teacher of Biology, Biology Laboratory Operator; university degrees (as according to the Hungarian higher education system before 2006): Psychology, Information Technology, Computer Programmer Mathematician, Teacher of Informatics, Applied Plant Biology, Applied Zoology, Biophysics, Biology, Molecular Biology, Teacher of Biology, Aesthetics; Ethics, Anthropology and Social Studies, Philosophy.
If you have any of the degrees listed above or you are going to obtain a degree by the time of the results announcement, you do not have to do anything else but send a copy of the degree certificate (hereinafter diploma).
Please note that the degrees described above as well as the full acknowledgement are only for degrees obtained in Hungary. If your degree was obtained outside Hungary, it must be submitted for evaluation (see below). However, the above list will give you an idea of what degrees can be accepted.
B) Conditionally accepted Bachelor’s degrees which will be considered in the first place: Liberal Arts: Communications and Media Studies, Business Information Technology, Applied Economics, Economic Analysis, Hungarian Linguistics and Literature: Language Technology specialisation and Theoretical Linguistics specialisation, Pedagogy, Biochemical Engineering, Chemical Engineering, Architecture, Civil Engineering, Mechanical Engineer, Mechatronics Engineering, Electrical Engineer, Economist in Business Administration and Management, Technical Manager, Mathematics, Communication and Media Science, Economist in Economic and Financial Mathematical Analysis. In the case of these degrees they must fulfil the following credit requirements: at least 10-12 credits (ECTS) which can be recognized from the earlier studies in at least three of the following fields: mathematics, statistics; informatics; epistemology; logic; linguistics; physiology and anatomy. (Besides the degrees listed above, any other degree can be accepted if it fulfils the 12 ECTS requirement.)
The requirement, i. e. the existence of the credits listed above is established through a preliminary examination of the credits which must be initiated by the applicant in the form of a free-text request.
If the applicant takes their final examination during the current semester and their degree certificate (diploma) is not issued before the application deadline, a certification is required, which verifies that the applicant will presumably receive a degree. In case of being accepted as a student, however, the applicant must present the diploma upon enrolment at the latest.
The educational and outcome requirements are defined by the Ministry of Human Capacities (Regulation No. 18/2016. (VIII. 5.)) . The details of the application and admission process are defined by the Organisational and Operational Regulations of ELTE.
Language requirements
Minimum level of language proficiency (oral) (A1-C2): C1
Minimum level of language proficiency (written) (A1-C2): C1
Further comments:
The language of instruction for the entire programme is English, so a very good command of English is required during the oral entrance exam and throughout the whole programme. The language knowledge is assessed and evaluated during the interview, the Faculty of Education and Psychology doesn't require an official language certificate.
| Document | Comment |
| Online application form | - |
| Bachelor-level degree | - |
| Transcript of records | - |
| CV | - |
| Motivation letter | The letter should contain approximately 2000 characters. You should explain your experiences and ideas, how you met the field of cognitive science, why you thought it would be suitable for you, what your aim is with the MSc degree, how you would imagine your career, which area you are interested in and what further studies you might plan. |
| Copy of the main pages of the passport (needs to be valid) | - |
| Copy of application fee transfer | - |
| Entrance exam fee | - |
|
Reference work |
The reference work can be any work which you wrote within the field of psychology, linguistics, OR cognitive science (research paper, seminar paper, research report, published article, poster, study etc.). You can also write a new paper for the current application, which can be an improved version of an earlier work. If the work has been published or has been presented during your studies, please indicate on the paper where it was published or within what context it was written and presented. The maximum length should be 15 pages (without the appendices, and there are no requirements for form). If the work was co-authored, you must indicate their participation in the paper in percent (%). The reference work must be in English.- |
| An official English translation of the certificates and the records if the language of the original is not English. It can be a translation from the university too. | - |
The application starts in the online application system. Students need to register in the system, fill in the online application form, upload the required documents and follow the instructions during the application process.
The application and the entrance exam fee should be transferred to the following account:
- Name of Bank: Magyar Államkincstár (Hungarian State Treasury)
- Address of Bank: Budapest, Váci út 71, Hungary – 1139
- Holder of the account: Eötvös Loránd Tudományegyetem
- Account No.: 10032000-01426201-00000000
- SWIFT Code: HUSTHUHB
- IBAN Number: HU03 1003 2000 0142 6201 0000 0000
- On the transfer order please put down your full name and “AB01 B102 AB1P17/09”!
The deadline for application means the deadline of submission of the full and complete application package in the online system.
- Period 1: 25 February
- Period 2: 25 March
- Period 3: 25 April
- Period 4: 27 May
- Period 5: 15 July
The application procedure includes 5 periods in order to give the applicants the freedom to submit their application when it’s most suitable for them. The applicants of each period have the same chance to get admittance for the programme. However, please note, that the Faculty of Education and Psychology ELTE reserves the right to cancel the entrance periods in case the number of the admitted applicants reaches the limit during the previous entrance periods.
When the university receives the full application package and it is checked by the Student Affairs and Registrar’s Office an entrance exam date option will be sent in the online application system after the application deadline for the relevant period. Please, check your messages in the application system, and the e-mail address that is linked to the account regularly.
Procedure of the entrance examination
The applications are examined by the Admission Board and applicants are notified of the outcome of the selection in the online application system. Admission letters are sent out in the online application system.
Based on Section 34 of Government decree 423/2012 (XII. 29.) on the admission to higher education institutions, the higher education institution regulates the admission requirements and the method of ranking in the case of a Master’s programme, but the applicant can be admitted only if he/she achieves at least 50% of the maximum points. According to ELTE’s Admission Regulations if an applicant receives 0 points in any of the requirements of the admission procedure listed below, they cannot be accepted to the programme.
The oral examination is an interview with the applicant about his/her professional background, scientific interests, and professional plans. The entrance exam can be taken personally or via an MS Teams meeting. (The application does not need to be downloaded, the meeting is accessible through the browser.)
Evaluation and results
You can obtain a maximum of 100 points for the MSc in Cognitive Science programme according to the following:
1. Reference work (a maximum of 60 points): detailed description above.
2. Interview (a maximum of 40 points): an interview in English about the professional background of the applicant, his/her scientific interests and professional plans based on the CV and letter of motivation. If you cannot attend personally, you can request an entrance examination via MS Teams meetingafter you receive the schedule in which case we will request a copy of your passport or personal ID for identification purposes.
Results and the official decision will be announced within a month after the entrance exam date, in the application system.
Type of entrance examination: oral
Further details of selection and evaluation:
The ranking is based on a total evaluation of the academic excellence (based on the submitted documents) and the results of the entrance exam.
Dr. Ildikó KIRÁLY
Head of Department of Cognitive Psychology
Violetta FRANK
International Admission Coordinator
E-mail: admission@ppk.elte.hu
TEL: +36 1 461 4500 / 3499
Postal address: 1075 Budapest Kazinczy utca 23-27.
Faculty of Education and Psychology
Faculty of Education and Psychology
Campus Tour Join our student guide, Peter Enim (PhD student at the Doctoral School of Psychology) for a tour at the Faculty of Education and Psychology, Eötvös Loránd University (ELTE), Budapest, Hungary.
Campus Tour Join our student guide, Peter Enim (PhD student at the Doctoral School of Psychology) for a tour at the Faculty of Education and Psychology, Eötvös Loránd University (ELTE), Budapest, Hungary.
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