Postgraduate Programme and Module Handbook 2015-2016 (archived)
Module PSYC41330: Techniques in Cognitive Neuroscience
Department: Psychology
PSYC41330:
Techniques in Cognitive Neuroscience
Type |
Tied |
Level |
4 |
Credits |
30 |
Availability |
Available in 2015/16 |
Module Cap |
|
Prerequisites
Corequisites
Excluded Combination of Modules
Aims
- This module aims to provide students with advanced knowledge of a range of techniques used in cognitive neuroscience research. This will be achieved by providing students with advanced in-depth and hands-on knowledge of a small number of research techniques used in cognitive neuroscience and to outline strengths, weaknesses and appropriateness of a variety of cognitive neuroscience techniques. In addition, this module aims to offer students with advanced knowledge of MATLAB programming language and to provide students with the skills to relate programming skills to cognitive neuroscience research.
Content
- The module uses seminars to develop an understanding of the background behind methodologies currently used in cognitive neuroscience to answer critical questions in the area. The seminars cover both theoretical background to the methodologies and the constraints of experimental design unique to each technique. Techniques to be covered in seminars may include fMRI, TMS, ERP, and animal laboratory. The content for MATLAB programming includes general programming skills programming skills specific to MATLAB and using MATLAB to programme equipment used in cognitive neuroscience research.
Students will also take part in one five hour practical laboratory placements. The workshop will be on a technique of the student's choosing and will be focused on hands-on experience with the technique rather than collecting data for an empirical objective.
Learning Outcomes
- Acquisition of knowledge about the backgrounds to cognitive neuroscience methodologies
- Acquisition of knowledge about the programming language MATLAB and its use in cognitive neuroscience experiments
- Acquisition of knowledge about the particular constraints, limitations and benefits of a variety of cognitive neuroscience techniques
- In depth knowledge of particular techniques in cognitive neuroscience
- Understanding the appropriateness of particular methodologies for answering particular empirical questions
- Be able to use specialised cognitive neuroscience techniques
- Be able to design and write a computer programme with a specific experimental aim
- Development of written communication skills
- Developing the ability to learn independently within broad guidelines
Modes of Teaching, Learning and Assessment and how these contribute to
the learning outcomes of the module
- Seminars introducing students to a variety of techniques in cognitive neuroscience.
Seminars allow student-led discussion and small group teaching which will support the development of practical skills and knowledge about the background to these methodologies. Seminars will allow students to develop their oral communication skills and their ability to learn independently. Students' knowledge of the methodologies will be assessed through a formative essay on a technique. The formative essay will assess the student's written communication skills.
- The laboratory placement will last for five hours and be under the guidance of an experienced researcher. The laboratory placement will assess the students' ability to learn independently and reflects on their own learning. The laboratory placement will be written up as a report critically evaluating the technique. Students' understanding of the appropriateness of particular methodologies for particular empirical questions will be summatively assessed in a written examination.
- MATLAB programming will be taught via workshops. Workshops will allow students to work in small groups for problem based teaching of MATLAB. Workshops will allow for small group teaching and student-led discussion to develop programming skills. Students' understanding of programming using MATLAB will be formatively assessed through the course of the module using problem solving and multiple choice questions and summatively assessed in a class test. Students' ability to design and write a computer programme for a specific experimental aim will be summatively assessed by the completion and submission of such a programme.
Teaching Methods and Learning Hours
Activity |
Number |
Frequency |
Duration |
Total/Hours |
|
Seminars |
7 |
Term 1: twice weekly in weeks 1-3 and once in week 4 |
3 hours |
21 |
|
Lab Placements |
1 |
Term 1 |
5 hours |
5 |
Matlab Workshops |
20 |
Weekly |
3 hours |
60 |
Preparation & Reading |
|
|
|
214 |
|
|
|
|
300 |
Summative Assessment
Component: Examination |
Component Weighting: 25% |
Element |
Length / duration |
Element Weighting |
Resit Opportunity |
Examination |
1 hour |
100% |
|
Component: Assignment |
Component Weighting: 25% |
Element |
Length / duration |
Element Weighting |
Resit Opportunity |
Report |
1500 words |
100% |
|
Component: Class Test |
Component Weighting: 25% |
Element |
Length / duration |
Element Weighting |
Resit Opportunity |
Class Test |
2 hours |
100% |
|
Component: Programing Task |
Component Weighting: 25% |
Element |
Length / duration |
Element Weighting |
Resit Opportunity |
Computer Program |
As required |
100% |
|
2000 word essay on how to use a technique described in the seminars in Term 1
MATLAB will be formatively assessed through the course of the module using problem solving and multiple choice questions
■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University