Credit Distribution

  • 1st term: 20,5 credits (17,5 credits' worth of subjects, 1 credit towards the planning of the master's degree final project under the supervision of a CBC faculty member, and 2 credits' worth of seminar activity).
  • 2nd term: 18,5 credits (5,5 credits' worth of subjects, 10 credits of work towards the master's degree final project, and 3 credits' worth of seminar activity).
  • 3rd term: 21 credits (3 credits' worth of subjects, 16 credits of work towards the master's degree final project, and 2 credits' worth of seminar activity).

Structure

MODULE 1: Cognitive Neuroscience and Research Techniques 
Exploration of the most important experiments on the various aspects of human cognition and the results thereof. Presentation of the most common research techniques, procedures, and designs and approaches to data analysis and the interpretation of results.
Subject Description ECTS
Credits		 Term
Data Analysis for Cognitive Neuroscience
  • Programming for experimental data analysis with Matlab or Python.
  • Mathematical methods for univariate and multivariate statistical analysis of neurophysiological, behavioural and neuroimaging.
 2.5 2
Neuroimaging Methods
  • Experimental methodologies for neuroimaging techniques.
  • Mathematical and statistical analysis of neuroimaging data (eg, EEGs, ERPs, fMRI).
 2.5 2
Comparative Cognition
  • General learning mechanisms.
  • Techniques of research in cognitive science with animals.
  • Animal models: psychological processes, language in animal and human research. 
  • Ethical considerations.
 3 1
Early Human Cognition
  • Historical and philosophical foundations of theories of cognition.
  • Infants' understanding of the physical world.
  • Infants' understanding of other minds.
  • Numerical and logical reasoning in infancy.
 3 1
Decision Making: the Brain in Action
  • The neurophysiology of decisions.
  • Perceptual and economic decisions.
  • Planning.
  • Models: diffusion and competition.
 3 1 (2 in 22-23)
Introduction to Computational Neuroscience
  • Spiking neurons.
  • Dynamic Synapses.
  • Cortical networks.
  • Plasticity/Learning.
 3 3
Cognitive Neuroscience of Language
  • How language is represented and processed in the brain.
  • Perception of language.
  • Production of language.
  • The bilingualism: how the brain handles two languages.
 3 1
Cognitive Neuroscience of Perception and Attention
  • Cognitive and neural processes involved in perception.
  • Perceptual mechanisms. 
  • Multisensory aspects of perceptual functions. 
  • Awareness.
 3 1

The Neural Basis of Memory
  • The neurophysiology of memory. 
  • Short and long term memory.
  • Models: attractor models.
 3 2
MODULE 2. Materia: Seminars
Weekly critical and constructive analysis of one or more ongoing experiments, either of a participant in the master's programme or of someone external to it. Tracking of students' designs, methodologies, data analyses, results, and conclusions. 
Subject Description ECTS
Credits		 Term
Seminar
  • Presentation of experimental articles and results. 
  • Analysis of data.
  • Designing of a research project.
 2/3/2 1/2/3
MODULE 3: Master's Degree Final Project 
Subject  Description  ECTS
Credits		 Term
Master Degree Final Project  Research project on a topic related to the Master preparation and completion of a Master' thesis. 1/10/16 1/2/3

 

You can check the syllabus here.

More information

"Plagiarism can be defined as the appropriation of another person’s ideas, words, works, etc. As far as universities are concerned, the term applies to any situation in which someone appropriates something that someone else has created and fails to explicitly acknowledge its source. " (quote from the Code of Ethics, UPF).

From the Master of Brain and Cognition, we note that plagiarism is damaging to the original authors (as it is a form of misappropriation), to the reputation of the masters and the University as a whole, and it leads to unfair advantage amongst students. For these reasons, we are resolved to prevent plagiarism in essays and TFMs. Please note that plagiarism can lead to disciplinary action from the University, above and beyond any measures taken within the Master itself.

You can find more precise definitions and information about what and what is not plagiarism from these resources.

All students are expected to have done the readings before the course starts.You will find below the most updated calendar for the planned classes.

It is mandatory that all students with no strong background on programming and/or statistics do some introductory courses on these subjects before the program starts.

It is mandatory that all students with no strong background on programming do the following introductory Python course *BEFORE* the program starts: https://www.learnpython.org/ (Learn the Basics and Data Science Tutorials)
After completing this course, students must be able to pass the quiz in https://pynative.com/basic-python-quiz-for-beginners/
In the first session of the course "Data Analysis in Cognitive Neuroscience" a similar basic-Python quiz will be passed in class to confirm the basic level required to enter this course.

It is mandatory to read Chapter 2 of the book MATLAB for Neuroscientists: An Introduction to Scientific Computing in MATLAB 1st Edition by Pascal Wallisch, Michael E. Lusignan, Marc D. Benayoun, Tanya I. Baker, Adam Seth Dickey, Nicholas G. Hatsopoulos.  Here are the Instructions to be able to set up Matlab licenses for UPF students.

For basic statistics you can take this online course.

Mandatory reading for the course Early Human Cognition. Sections 1, 2, 3, 6, 10, 11 are mandatory. The other sections are optional. 

It is strongly recommended that all students read:

The Student's Guide to Cognitive Neuroscience, 2nd Edition by Jamie Ward.

And from the following list, working on one of the readings is strongly recommended for those who are less familiar with cognitive neuroscience. We would add that it is even more strongly recommended to complete the reading of any one of these books which cover the basics of the statistical tests that you are most likely to need to understand for your own work (descriptive statistics, t-test, ANOVA, perhaps non-parametric analisys, possibly not necessarily regression). Please keep in mind that you need not buy the book(s). They are available in your libraries.

  1. Cognitive Neuroscience: The Biology of the Mind 4th Edition, by Michael S. Gazzaniga, Richard B. Ivry, George R. Mangun.
  2. Statistical Methods for Psychology (PSY 613 Qualitative Research and Analysis in Psychology) 8th Edition by David C. Howell.
  3. Statistical Methods for Psychology, International Edition 8e, David C. Howell.  And the Author’s webhttps://www.uvm.edu/~dhowell/methods8/ which supports and has supplemental information for the book. 
  4. Cengage Advantage Books: Fundamental Statistics for the Behavioral Sciences 7th Edition.