Kaisa_2012_3_photo by Veikko Somerpuro

Enrol
12.8.2019 at 12:00 - 11.9.2019 at 23:59

Timetable

Here is the course’s teaching schedule. Check the description for possible other schedules.

DateTimeLocation
Wed 11.9.2019
09:15 - 11:45
Wed 11.9.2019
13:15 - 15:45
Wed 18.9.2019
09:15 - 11:45
Wed 18.9.2019
13:15 - 15:45
Wed 25.9.2019
09:15 - 11:45
Wed 25.9.2019
13:15 - 15:45
Wed 2.10.2019
09:15 - 11:45
Wed 2.10.2019
13:15 - 15:45
Wed 9.10.2019
09:15 - 11:45
Wed 9.10.2019
13:15 - 15:45
Wed 30.10.2019
09:15 - 11:45
Wed 30.10.2019
13:15 - 15:45
Wed 6.11.2019
09:15 - 11:45
Wed 6.11.2019
13:15 - 15:45
Wed 13.11.2019
09:15 - 11:45
Wed 13.11.2019
13:15 - 15:45
Wed 20.11.2019
09:00 - 10:00
Wed 20.11.2019
10:00 - 15:00
Wed 27.11.2019
09:15 - 11:45
Wed 27.11.2019
13:15 - 15:45
Wed 4.12.2019
09:15 - 11:45
Wed 4.12.2019
13:15 - 15:45
Wed 11.12.2019
09:15 - 14:00

Description

This course is primarily intended for students of the Master’s Programme in Neuroscience, and compulsory in the 60 cr Neuroscience module. It is designed to be studied during the first autumn term in parallel with the courses ”Cellular Physiology” and “Cellular Neurobiology”.

It is recommended that the courses ”Cellular Physiology” and “Cellular Neurobiology” be taken in parallel (or before) this course.

The aim of this course is to provide students with exposure to current trends and methods in neuroscience, and thereby broaden students’ knowledge beyond what is taught on the lecture courses. In addition, students will learn to know better the local neuroscience community.

Periods 1 and 2.

The course consists of thematic days on specific topics. Students will learn to know the local neuroscience community and modern research methods during laboratory visits and excursions, they will be introduced to cutting edge research trends, and they will work on group assignments and presentations.

A minimum of 70% attendance and active participation in in-class discussions and assignments including group work and quizzes, as well as completing independent homework assignments on time are required for passing the course.

Material will be defined during the course and provided by the teachers or via Moodle.

Grading scale 0 – 5. Grading is based on in-class activities and quizzes (50 %) and independent assignments (50 %).

Professor Juha Voipio