| Unit name | Neural Systems and Computation |
|---|---|
| Unit code | PHPHM0017 |
| Credit points | 20 |
| Level of study | M/7 |
| Teaching block(s) |
Teaching Block 2 (weeks 13 - 24) |
| Unit director | Dr. Paul Chadderton |
| Open unit status | Not open |
| Units you must take before you take this one (pre-requisite units) |
Neurophysiology (PHPH20009) and Techniques in Neuroscience (PHPH20007) |
| Units you must take alongside this one (co-requisite units) |
None |
| Units you may not take alongside this one |
None |
| School/department | School of Physiology, Pharmacology & Neuroscience |
| Faculty | Faculty of Life Sciences |
Why is this unit important?
To understand the brain, it necessary to integrate neuroscientific principles at multiple levels. This unit will focus on computational descriptions of neural systems linking unitary elements of the nervous system – neurons – to high-level brain dynamics. Biological phenomena underlying movement, sensation and cognition will be explored at the levels of single cells, small networks, and brain regions. It will further be shown how decoding of neural dynamics can be used to drive prostheses and brain-machine interfaces. Computational approaches will be applied in two ways in this unit:
1) to understand and link neural processing mechanisms at different levels
2) to explore how models are used to generate and test hypotheses about neural function.
How does this unit into your programme of study?
This unit aims to unite knowledge and understanding that has developed across multiple levels and disciplines in the preceding 3 years of the programme. It is a fact that neuroscience and psychology research increasingly relies upon computational methods and foundations; a key goal of this unit is the introduction of computational principles and approaches relevant for these fields. This unit also looks towards to the current and developing field of brain machine interfaces which is relevant for students with professional interests in either the application or development of such devices.
An overview of content
This unit bridges the gap between our understanding of neuronal dynamics in small circuits and large-scale activity of the brain that can be measured using EEG. Students will finish this unit with an excellent understanding of:
1) how different neural circuit elements contribute to information processing,
2) computation approaches to model these mechanisms, and
3) how recordings of neural activity are applied to brain machine interface (BMI) applications.
A key emphasis of the unit will be on neural oscillatory activity, including different mechanisms to support oscillatory behaviour, and its relevance for brain function and decoding. This unit will give students an appreciation of tools and computational approaches that can be used to test hypotheses about neural systems in vivo and in silico.
How will students, personally, be different as a result of the unit?
Students will be able to interpret data in neural circuit physiology, develop hypotheses and design experiments to investigate and model mechanisms of sensorimotor processing at multiple levels. Students will gain practical exposure to computational modelling environments and explore how different properties of neural circuitry including connectivity motifs and excitation/inhibition balance influence neural dynamics. They will further understand the current state-of-the-art in terms of BMI applications.
Learning Outcomes
This unit will involve traditional lectures, lecture-associated tasks, reading and understanding primary literature, and seminars and workshops which will include discussions groups. The traditional lectures and lecture-associated tasks, along with students’ knowledge of neurophysiological systems from year 1 and 2, will give students the background knowledge to understand fundamental principles of neural circuit computation.
Students will attend three practical computational workshops – these have been designed to enable students to explore modelling environments without the expectation of any prior technical knowledge in this area. Teaching assistants will be on hand to provide guidance in these sessions. These tasks will specifically be targeted at helping students build familiarity and confidence with computational modelling, and to develop conceptual understanding for the timed assessment.
Tasks which help you learn and prepare you for summative tasks (formative):
This unit will include discussion sessions, workshops and revision sessions, all targeted towards the timed assessment. The computational modelling element will include three workshop sessions that link to relevant seminars, and where students will be guided through a set of activities in Python – these will be purely formative but will help students gain conceptual understanding necessary for the timed assessment.
Tasks which count towards your unit mark (summative):
Timed assessment (100%)
The unit will be assessed through a timed assessment in the summer assessment period, which contributes 100% of the unit mark and consists of two sections. In Section A (50%), students will be expected to answer one essay question from a choice of two, which will assess their knowledge and critical understanding of the field, and their ability to gather information from the primary scientific literature. In Section B (50%), students will be expected to answer one multi-part compulsory question assessing data handling/data interpretation and experimental design skills.
When assessement does not go to plan:
Timed assessment (100%)
The re-assessment task for the timed assessment (100% of unit mark) will be in the same format as the initial timed assessment. In Section A (50%), students will be expected to answer one essay question from a choice of two, which will assess their knowledge and critical understanding of the field, and their ability to gather information from the primary scientific literature. In Section B (50%), students will be expected to answer one multi-part compulsory question assessing data handling/data interpretation and experimental design skills.
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. PHPHM0017).
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 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.
