| Unit name | Computational Neuroscience (Teaching Unit) |
|---|---|
| Unit code | SEMT30003 |
| Credit points | 0 |
| Level of study | H/6 |
| Teaching block(s) |
Teaching Block 1 (weeks 1 - 12) |
| Unit director | Dr. M Rule |
| Open unit status | Not open |
| Units you must take before you take this one (pre-requisite units) |
SEMT10002 Computer Programming and Algorithms OR COMS10016 Imperative and Functional Programming or equivalent |
| Units you must take alongside this one (co-requisite units) |
EITHER SEMT30004 Computational Neuroscience (20CP assessment unit). This should be chosen by all non-Computer Science students taking the unit; Computer Science students may not choose this option. OR COMS30081 Topics in Computer Science (examination unit, 20CP), where this unit will contribute 50% to the topics in the exam. This should be chosen by all Computer Science students. Please note that for Computer Science students this unit is available in MINOR form ONLY, assessed as part of “Topics in Computer Science”. Students on other degrees take the 20 credit assessment unit. |
| Units you may not take alongside this one |
None |
| School/department | School of Engineering Mathematics and Technology |
| Faculty | Faculty of Engineering |
Why is this unit important?
This unit aims to provide the student with an understanding of computational principles of biological computations performed in the brain by single neurons and network of neurons, for the following brain processes:
How does this unit fit into your programme of study
This is an optional unit that can be taken in Year 3 of either the Computer Science programmes or the Engineering Mathematics programmes. Within both programmes, this unit goes beyond the traditional analysis of programming and algorithms that students will have covered in earlier years and looks instead to neuroscience and how computations are performed in biological systems. This will introduce ideas around the mathematical and computational modelling of real-world systems that will broaden students’ understanding of what computation can be and build valuable modelling and analysis skills that can be developed further in project work.
An overview of content
The unit gives an introductory overview of the field of computational neuroscience. We study the brain at scales ranging from very small (synapses) to very large (systems).
How will students, personally, be different as a result of the unit
Students will gain insight into how computational neuroscientists understand brain function.
Learning outcomes
On successful completion of this unit, students will be able to:
When the unit is taken by non-Computer Science students alongside the associated 20 credit option that includes coursework, you will also be able to:
4. Develop computational code to analyse and interpret data from neuroscience experiments.
In addition to lectures, this unit is taught with weekly in-class activities designed to encourage engagement, interaction, and problem solving. Activity sessions also include formative exercises to monitor and enhance learning. If taken with coursework, the unit also provides weekly coursework support sessions.
Tasks which help you learn and prepare you for summative tasks (formative):
Weekly classes include formative problem worksheets to group activities to apply your learning and prepare for the exam and/or coursework assessment. Feedback is given via class discussions.
Teaching will take place over Weeks 1-8, with coursework support in weeks 9-11.
Tasks which count towards your unit mark (summative):
For Computer Science students, who must take this unit as a MINOR, the summative assessment will be a contribution of 10 credit points (equivalent to 1 hour of exam time) of questions to the “Topics in Computer Science” exam that will be sat during the winter examination period. This closed-book exam will assess Learning Outcomes 1 to 3.
For all non-Computer Science students, there will be two elements of assessment:
• An end-of-term exam to assess Learning Outcomes 1 to 3 (worth 50% of the unit)
• Coursework (due at the end of unit) that will assess all learning outcomes (worth 50% of the unit)
When assessment does not go to plan
Students will retake relevant assessments in a like-for-like fashion in accordance with the University rules and regulations.
If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.
If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. SEMT30003).
How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours
of study to complete. Your total learning time is made up of contact time, directed learning tasks,
independent learning and assessment activity.
See the University Workload statement relating to this unit for more information.
Assessment
The assessment methods listed in this unit specification are designed to enable students to demonstrate the named learning outcomes (LOs). Where a disability prevents a student from undertaking a specific method of assessment, schools will make reasonable adjustments to support a student to demonstrate the LO by an alternative method or with additional resources.
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit.
The Board considers each student's outcomes across all the units which contribute to each year's programme of study. For appropriate assessments, if you have self-certificated your absence, you will normally be required to complete it the next time it runs (for assessments at the end of TB1 and TB2 this is usually in the next re-assessment period).
The Board of Examiners will take into account any exceptional circumstances and operates
within the Regulations and Code of Practice for Taught Programmes.
