LEARNING OUTCOMES
After this course the student can
(1) list approaches for analyzing and modeling functional brain imaging data
(2) explain the difference between decoding and encoding models
(3) analyze brain imaging data using different approaches
(4) choose appropriate analysis or modeling approach to new data
(5) critically review scientific literature on brain decoding .
Credits: 5
Schedule: 10.01.2023 - 22.02.2023
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Linda Henriksson
Contact information for the course (applies in this implementation):
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 gives an overview of advanced approaches for analyzing and modeling human brain imaging data. The student will learn the main differences between univariate and multivariate analyses, and between encoding and decoding models. The students will also apply the different techniques to real data. The course will also give basic knowledge about the functional organization of the human visual system which will be used as a case example of how the different techniques are used in the context of neuroscientific questions.
Assessment Methods and Criteria
valid for whole curriculum period:
Project works, homework, portfolio, exam.
Workload
valid for whole curriculum period:
Lectures/contact teaching 24 h, Reading and homework 30 h, Project works 60 h, Compiling a portfolio 8 h, Getting ready for exam 8 h, Exam
DETAILS
Substitutes for Courses
valid for whole curriculum period:
Prerequisites
valid for whole curriculum period:
FURTHER INFORMATION
Further Information
valid for whole curriculum period:
Teaching Language : English
Teaching Period : 2022-2023 Spring III
2023-2024 No teachingEnrollment :
This course is primarily for students of the Human Neuroscience and Technology major. Only a limited number of other students can participate.