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Course Catalog 2010-2011
LTT-6306 Neuroinformatics, 5 cr |
Person responsible
Jarno Tanskanen
Lessons
Study type | P1 | P2 | P3 | P4 | Summer | Implementations | Lecture times and places |
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Requirements
Active participation in lectures and seminars, accepted exercise reports, seminar report, and oral seminar presentation.
Completion parts must belong to the same implementation
Principles and baselines related to teaching and learning
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Learning outcomes
After completing the course students can explain how neuroinformatics integrates different disciplines to work together towards understanding the operation of the brain. They can recognize fundamental methods related to neuroinformatics. They can also explain deeper some selected neuroinformatics topics based on expert guest lectures, exercises, and seminar presentations and written reports.
Content
Content | Core content | Complementary knowledge | Specialist knowledge |
1. | Definition of neuroinformatics. | ||
2. | Neuroscientific measurements and data types. | ||
3. | Neuroinformatics databases, data mining, and data sharing. | ||
4. | Brain imaging and atlases. | ||
5. | Select topics in neuroscience and associated data processing. |
Evaluation criteria for the course
To pass the course, all learning activities need to be passed.
Assessment scale:
Evaluation scale passed/failed will be used on the course
Partial passing:
Study material
Type | Name | Author | ISBN | URL | Edition, availability, ... | Examination material | Language |
Book | Databasing the Brain, from Data to Knowledge | S. H. Koslow and S. Subramaniam, Eds. | Suomi | ||||
Lecture slides | Lecture slides | Several authors | On the Internet. | Suomi | |||
Online journal | Articles from online journals. | Suomi |
Additional information about prerequisites
To complete the course successfully students need to have adequate knowledge on the topics covered in the course.
Prerequisite relations (Requires logging in to POP)
Correspondence of content
Course | Corresponds course | Description |
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Additional information
The course is lectured every second year. The course is taught in the academic year 2010-2011.
The course is recommended to be taken at the final stage of MSc degree studies or during the PhD studies.
Suitable for postgraduate studies
More precise information per implementation
Implementation | Description | Methods of instruction | Implementation |
Lectures |
Contact teaching: 0 % Distance learning: 0 % Self-directed learning: 0 % |