Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

After completing the course, the student will be familiar with

  • principles of MEG and fMRI
  • designing basic neuroimaging experiments
  • conducting fMRI and MEG experiments
  • basic analysis of fMRI and MEG data
  • writing a report on neuroimaging results

Credits: 5

Schedule: 02.09.2024 - 26.11.2024

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Lauri Parkkonen

Contact information for the course (applies in this implementation):

Responsible teacher: Lauri Parkkonen (lauri.parkkonen@aalto.fi), NBE, Otakaari 3

Co-teachers: Mia Liljeström and Linda Henriksson, NBE, Otakaari 3

Course assistants: Mila Nurminen (mila.nurminen@aalto.fi) and Mikael Grön (out until Oct 1, 2024), NBE, Otakaari 3

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content
  • valid for whole curriculum period:

    This course comprises lectures on the physiological basis of MEG and fMRI, the related data analysis, and experimental design as well as a practical part where the students design a neuroscientific experiment (under the guidance of the lecturers), carry out the fMRI and MEG measurements, analyse the acquired data and write a report of the results.

    The course involves human brain imaging measurements that take place on campus in Otaniemi and mostly happen at hours outside of the lecture slot. The exact timing varies from year to year depending on the availability of the neuroimaging infrastructure.

Assessment Methods and Criteria
  • valid for whole curriculum period:

    Students are required to actively participate the group work, measurements and data analysis throughout the course. Assessment is based on the quality of the research plan and its execution as well as on the quality and depth of the analysis and reporting of the results. No exam.

Workload
  • valid for whole curriculum period:

    • contact teaching (lectures, presentations, measurements, analysis clinics):  26 h
    • individual study of background material: 20 h
    • group work for planning and implementing the experiments: 24 h
    • group work for data analysis: 50 h
    • group work for writing the report: 15 h

DETAILS

Study Material
  • valid for whole curriculum period:

    Lecture notes, example data, and example program code 

Substitutes for Courses
Prerequisites

FURTHER INFORMATION

Further Information
  • valid for whole curriculum period:

    Teaching Language: English

    Teaching Period: 2024-2025 Autumn I - II
    2025-2026 Autumn I - II

    Registration:

    The number of participants is restricted, and priority is given to students majoring in Human Neuroscience and Technology and in Biomedical Engineering of the Life Science Technologies master's programme. Students are required to have basic knowledge in neuroscience, brain imaging methods, programming, and signal processing.