Durham University
Programme and Module Handbook

Postgraduate Programme and Module Handbook 2022-2023 (archived)

Module PSYC41330: Techniques in Cognitive Neuroscience

Department: Psychology

PSYC41330: Techniques in Cognitive Neuroscience

Type Tied Level 4 Credits 30 Availability Available in 2022/23 Module Cap
Tied to C8K109

Prerequisites

  • None

Corequisites

  • None

Excluded Combination of Modules

  • None

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 practical experience 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 the ability 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, human neuropsychology and animal work. The content for programming includes general programming skills programming skills specific to MATLAB and an introduction to tools and languages used in cognitive neuroscience research. Students will also take part in at least two compulsory five hour practical laboratory placements. The first placement will be on a technique of the student's choosing and will be focused on developing practical experience with the technique rather than collecting data for an empirical objective. The second placement will be on MRI techniques.

Learning Outcomes

Subject-specific Knowledge:
  • Acquisition of knowledge about the backgrounds to cognitive neuroscience methodologies
  • Acquisition of knowledge about relevant programming language(s)
  • 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
Subject-specific Skills:
  • Be able to use specialised cognitive neuroscience techniques
  • Be able to design and write a computer programme with a specific experimental aim
Key Skills:
  • 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 multiple choice test and summative 2 hour exam. The examination will assess the students written communication skills.
  • Two laboratory placement will last for five hours and be under the guidance of an experienced researcher. Students' understanding of the appropriateness of particular methodologies for particular empirical questions will be summatively assessed in a written examination.
  • Programming will be taught via weekly lectures and workshops. Workshops will allow students to work in small groups for problem based teaching. Workshops will allow for small group teaching and student-led discussion to develop programming skills. Students' understanding of programming will be formatively assessed through the course of the module using problem solving and multiple choice questions and summatively assessed in a class test.

Teaching Methods and Learning Hours

Activity Number Frequency Duration Total/Hours
Seminars 8 Term 1: twice weekly in weeks 1-4 3 hours 24
Lab Placements 1 Term 1 or Term 2 5 hours 5
Lab Placements 1 Term 2 5 hours 5
Programming Lectures 20 Weekly 1 hour 20
Programming Workshops 20 Weekly 2 hours 40
Preparation & Reading 206
Total 300

Summative Assessment

Component: Examination Component Weighting: 50%
Element Length / duration Element Weighting Resit Opportunity
Examination 2 hours 100%
Component: Programming Class Test Component Weighting: 50%
Element Length / duration Element Weighting Resit Opportunity
Class Test 1 hour 100%

Formative Assessment:

MCQ tests.


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