Computational Cognitive Neuroscience
Year  Semester  Date  Period  Language  In charge 

2016  spring  19.0103.03.  33  English  Aapo Hyvärinen 
Lectures
Time  Room  Lecturer  Date 

Tue 1416  B222  Vadim Kulikov  19.01.201609.02.2016 
Thu 1416  B222  Vadim Kulikov  19.01.201609.02.2016 
Tue 1416  B222  Aapo Hyvärinen  11.02.201603.03.2016 
Thu 1416  B222  Aapo Hyvärinen  11.02.201603.03.2016 
Information for international students
The course is entirely in English.
General
Flow of the course:
On every Thursday, the students are given material (book chapters) to read and exercices to solve (a lot may already be available on this page).
Tuesdays are discussion sessions on the course material. By the evening of the Monday of the following week, each student must send two questions on the material handed out the previous Thursday. The questions will be treated in the Tuesday session by the lecturer and other students.
The solutions to the exercices will be treated in the Thursday sessions (one week after they have been handed out).
The first week is an exception to the above. The first Tuesday session (19th Jan) is an overview and introductory lecture, in which the students will be given background material to read until the following Tuesday. The first Thursday session (21th Jan) is, exceptionally, an extra Q&A session concerning the background material.
Prerequisites:
You need to have done introductory universitylevel courses in:
* linear algebra
* probability
* programming
* statistics or machine learning
Schedule and contents:
The course has two halves, given by the two different lecturers. Material is taken mainly from two books, referred to as NIS and Rojas, see below for links.
1st week Tuesday 19th Jan is introductory, with no material to be read and discussed yet
2nd week, discussed on Tue 26th Jan (and exceptionally on Thu 21st as well)
[This week is about background material. There's a lot of material but you probably know it partly already. Concentrate on those topics you know the least about.]
Neuroscience background:
Rojas book chapter 1, beginning sections of of https://en.wikiversity.org/wiki/Fundamentals_of_Neuroscience (as many as you can take).
Maths background:
NIS chapters 4 and 19
Programming background:
Introduction to Python and NumPy/SciPy, using these links:
http://www.learnpython.org/ (or any similar intro to python)
http://docs.scipy.org/doc/scipy/reference/tutorial/linalg.html
http://docs.scipy.org/doc/scipy/reference/tutorial/stats.html
http://matplotlib.org/users/pyplot_tutorial.html
3rd week, discussed on Tue 2nd Feb:
Perceptron, Multilayer Perceptron, Backpropagation (Rojas book sections 3.1, 3.2, 3.3, 4.1, 4.2, 7.2, 7.3 )
Send two questions on the material by Monday 1st (evening) to Vadim Kulikov.
4th week, discussed on Tue 9th Feb:
Associative memory, Hebbian learning, Hopfield model (Rojas book chapter 12, sections 13.1, 13.2, 13.3, 13.4 )
Send two questions on the material by Monday 8th (evening) to Vadim Kulikov.
5th week, discussed on Tue 16th Feb:
Early visual system: Introduction, basic models, Fourier and Gabor analysis (NIS book chapters 1,2,3 )
Send two questions on the material by the evening of Monday 15th Feb to Aapo Hyvärinen
6th week, discussed on Tue 23rd Feb:
Natural images: Introduction, principal component analysis, sparse coding (NIS book chapters 5,6)
Send two questions on the material by the evening of Monday 22th Feb to Aapo Hyvärinen
Exercises 5 in pdf Code for the exercices (image sampling) Natural image data for the exercices
7th week, discussed on Tue 1st Mar:
Natural images: Independent Component Analysis (NIS book chapter 7); Bayesian inference for pattern recognition see this paper.
Send two questions on the material by the evening of Monday 29th Feb to Aapo Hyvärinen
Completing the course

To get the credits, you should do two projects (by yourself, not groups):

Various topics will be offered
 One for each half of the course
 You can also propose your own topic

Different forms of projects will be possible
 Programming
 Short essay (approx 2000 words)
 Summary of a scientific article (1000 words)
 At least one of the projects must be programming
 (Cancelled: You will also be required to read reports by other students as a form of peer review)
 The deadlines for the two projects are: 21th Feb (note the extension!) and 13th March.
 The assistant taking care of the programming project is Hande Celikkanat, email: hande.celikkanat@helsinki.fi
 See tab "Information on Projects" at the top of this page.

Various topics will be offered
 In addition, participation in the Tuesday Q&A sessions in the sense of sending in two questions by preceding Monday for each session.
 There will be no exam.
 You can get bonus points from the exercises during the first half of the course (Thursdays on weeks 2,3, and 4). The maximum bonus is 7% of the points of the projects. Each exercise problem handed in by 14:15 on the respective Thursday will give you one point, and with 20 points you get the maximum bonus (but you cannot obtain more than 10 points on a single Thursday session).
Literature and material
The course is mainly based on selected chapters from two books (both of which are freely available online):
Neural Networks  A Systematic Introduction by Raul Rojas (called Rojas).
Natural Image Statistics by Hyvärinen, Hurri, Hoyer (called NIS).
The exact chapters used are given above.