PY1INM-Introduction to Neuroscience Methods
Module Provider: Psychology
Number of credits: 20 [10 ECTS credits]
Level:4
Terms in which taught: Spring term module
Pre-requisites:
Non-modular pre-requisites:
Co-requisites:
Modules excluded:
Current from: 2020/1
Email: b.chakrabarti@reading.ac.uk
Type of module:
Summary module description:
The module is designed to introduce students to the methods and scientific philosophy of modern human neuroscience. It will introduce key concepts and applications, covering, for example, human neuroimaging, brain stimulation, neuropsychology, psychophysics, psychophysiology, brain-body research, population genetics, and scientific computing. There is a strong emphasis on practical preparation to support further experience with these technologies in the advanced years of the degree.
Aims:
The module aims to introduce students to the variety of technologies and analytical techniques available to modern human neuroscience, and prepare them for practical experience with these methods in the advanced years of the degree.
Assessable learning outcomes:
The module will enable students to:
- Successfully engage with specialist literature
- Extract and communicate key messages from technical information
- Communicate complex ideas clearly and convincingly
Additional outcomes:
The module will prepare students to compete for research placement opportunities in neuroscience labs across the University, as well as UROP and specialised final year projects.
In addition, students will develop the following transferable skills:
- Reading effectiveness; Information retrieval; Critical analysis
- Coping with complexity / uncertainty; Self-management;
- Creativity; Listening; Explaining; Written and oral communication
- Prioritisation, Planning; Problem solving; Team work; Influencing; Arguing/justifying a point
- Sensitivity to ethical issues in research and scientific practice
Outline content:
Examples of the areas covered in the module include: human neuroimaging, brain stimulation, neuropsychology, psychophysics, psychophysiology, brain-body research, population genetics, and scientific computing including programming and data visualisation. The module will also examine research ethics, technical and analytical limitations, and method applications.
Brief description of teaching and learning methods:
The module comprises a mixed methodology:
- Whole group lectures
- Demonstrations
- Practical classes/workshops
Contact Hours:
NB The contact hours in the table below are indicative of the contact hours for students studying this module in the UK, and may vary for students taking this module at branch campuses
Autumn | Spring | Summer | |
Lectures | 30 | ||
Tutorials | 20 | ||
Practicals classes and workshops | 22 | ||
Guided independent study: | |||
Wider reading (independent) | 30 | ||
Wider reading (directed) | 40 | ||
Group study tasks | 58 | ||
Total hours by term | 0 | 0 | |
Total hours for module | 200 |
Method | Percentage |
Written exam | 60 |
Set exercise | 40 |
Summative assessment- Examinations:
This module is assessed via 40% coursework and 60% MCQ exam in the summer
- One MCQ exam (60%) to cover all topics covered in the module
Summative assessment- Coursework and in-class tests:
- Set exercises (40%) which will be based on activities in tutorials
Formative assessment methods:
In class work and end-of-term presentations will be peer-reviewed for formative feedback.
Penalties for late submission:
The Module Convenor will apply the following penalties for work submitted late:
- where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day[1] (or part thereof) following the deadline up to a total of five working days;
- where the piece of work is submitted more than five working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.
You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.
Assessment requirements for a pass:
A mark of 40% overall.
Reassessment arrangements:
Reassessment is by examination in the August resit period
Additional Costs (specified where applicable):
Last updated: 15 June 2020
THE INFORMATION CONTAINED IN THIS MODULE DESCRIPTION DOES NOT FORM ANY PART OF A STUDENT'S CONTRACT.