SOW-BKI108
Brain for Artificial Intelligence
Course infoSchedule
Course moduleSOW-BKI108
Credits (ECTS)6
CategoryB1 (First year bachelor)
Language of instructionEnglish
Offered byRadboud University; Faculty of Social Sciences; Artificial Intelligence;
Lecturer(s)
Contactperson for the course
L.E.C. Jacques
Other course modules lecturer
Coordinator
dr. F.T.M. Léoné
Other course modules lecturer
Examiner
dr. F.T.M. Léoné
Other course modules lecturer
Academic year2018
Period
SEM2  (04/02/2019 to 12/07/2019)
Starting block
SEM2
Course mode
full-time
Remarks-
Registration using OSIRISYes
Course open to students from other facultiesNo
Pre-registrationNo
Waiting listNo
Placement procedure-
Aims
At the end of the course, as a student, you
  • acquired basic knowledge on brain mechanisms, neural functioning, the peripheral nervous system for perception and motor control, and imaging techniques.
  • can place cognitive neuroscience within Artificial Intelligence and know the relevance of neuroscience findings for robotics and engineering, brain reading, modelling and large-scale brain simulation.
  • are inspired and can form an articulated opinion on the state of the AI-neuroscience interaction on four big questions:
  1. How can we read and influence the brain?
  2. How can we calculate like and stimulate the brain?
  3. How can we let a robot interact with the world?
  4. How can we raise a baby robot?
  • can organize, understand, and learn a large set of information and self-organize his/her learning, individually, in teams, and in the class as a whole.
Content
Understanding the human brain is one of the last frontiers of science. Hence not surprisingly, many research groups and companies spend much time and resources into the cognitive neuroscience. This, in turn, results in many novel and exciting findings, which fuel public interest. I.e., cognitive neuroscience is hot, as can be seen from the wide range of newspaper articles, books, movies, and series alluding to the brain.

In the context of AI, neuroscience is a constant source of inspiration, ranging from artificial neural networks to cognitive robotics. Vice versa, AI techniques are extremely useful in the understanding of the brain, by allowing advanced brain imaging analysis and modelling (parts of) the human brain. Not surprisingly, many AI graduates from Nijmegen keep the brain as inspiration later in their career, either when working in industry or as researchers in the Artificial Intelligence and Cognitive Neuroscience domain. This course offers you the basic knowledge of brain mechanisms to build upon and draw inspiration from in the rest of your career.

In ‘Brain for AI’, the emphasis here will be on acquiring the basic knowledge. Follow-up courses will dive deeper in many of the in-depth applications (e.g., Brain-Computer Interfacing, Cognitive Robotics, Neural Networks, Computational and Formal Modelling). At the end of the course, you sufficiently understand the current knowledge on the human brain to build upon in future courses and your career.

All topics discussed will be connected to the four main questions mentioned.
 
Additional comments
The main part of the course is centered on the four questions, which are discussed in blocks of three weeks. In such a block, the first week there is a lecture to introduce the topic, the other two weeks workgroup meetings.

The workgroup meetings focus on helping you acquire the knowledge in the course and understand and discuss the links between the parts of knowledge in teams. The first workgroup meetings of each block is focused on discussion and exchange to acquire the knowledge and know what to focus on. In the second workgroup, students need to answer questions of different difficulty levels in a defense-like setup.

For the workgroups, reading of the book is required. The course will provide helpful tools and tips to acquire the knowledge. Moreover, in each block students are asked to prepare the defense in a team in their way of choice and submit the associated preparation document.

The course starts and ends with an additional lecture. The first lecture is for introduction in the course and intro the brain, the last for closure of the course. Note that the contents of the course surpass the content of the book, as many links to AI are drwan, especially in the lectures.

Levels
AI-B1

Test information
The course will end with a written exam. Questions will focus on factual knowledge and insights in the applications and relations with AI.

Example exams are available from the start of the course onwards.

The assignments per block will also be part of the final grade. The weighting is as follows:
50% assignments per block
50% final exam (needs to be sufficient to pass)

Prerequisites
There are no special prerequisites.

Contact information
Dr. F. Léoné, E: f.leone@donders.ru.nl; Tel:024-361 6126

Recommended materials
Book
An Introduction to Brain and Behavior 5th Edition, by Bryan Kolb, Ian Q. Whishaw, G. Campbell Teskey. The 4th edition is not recommended, as it differs significantly on a few topics.
Course material
Note that the lectures largely do not cover the book, but instead add content on the links between neuroscience and AI.

Instructional modes
Lecture

Remark
The course consists of 7 lectures.

Working group

Contribution to group work
Attendance at second workgroup each block is required to get points for the defence.

Remark
The course consists of 8 workgroup meetings. For Attendance, check Brightspace.

Tests
Exam
Test weight50
OpportunitiesBlock HER, Block SEM2, Block SEM2

Assignments
Test weight50
OpportunitiesBlock SEM2