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Methods in Neuroscience

Module description

This module will introduce you to essential methods and skills needed for your development as a neuroscientist. You will learn about the scientific method, from the history and philosophy of neuroscience to the contemporary research landscape. You will receive training in different aspects of experimental design, hypothesis testing, data analysis and presentation. In addition, you will be introduced to key science communication skills such as how to find and read scientific research literature, scientific writing, and presentation skills. This module will have a strong emphasis throughout on ethics, research integrity and reproducibility in science.

This is a compulsory module for BSc Neuroscience students.

This module is not suitable for non-specialist students.

Module aims - intentions of the module

This module aims to provide a foundation of key neuroscience skills. This module introduces the key principles of safe laboratory practices, experimental design and basic laboratory techniques, data handling, analysis, and presentation, and key the skills of literature searches and scientific communication. You will gain a good working knowledge of scientific writing, critical appraisal and referencing, and effective visual representation and statistical analysis of experimental data. These skills will be applied throughout your degree programme.

Intended Learning Outcomes (ILOs)

ILO: Module-specific skills

On successfully completing the module you will be able to...

• 1. Demonstrate knowledge of what it means to work safely in the laboratory and to gain competence in basic laboratory procedures
• 2. Understand the theory of statistical analysis of neuroscience data.
• 3. Understand basic methods used in neuroscience and their application.

ILO: Discipline-specific skills

On successfully completing the module you will be able to...

• 4. Demonstrate knowledge of how to design a good experiment, with a focus on ethics, integrity, and reproducibility.
• 5. Perform data handling and exploration, basic statistical analysis, and presentation of neuroscience data
• 6. Comprehend and explain current scientific knowledge, with appropriate referencing.

ILO: Personal and key skills

On successfully completing the module you will be able to...

• 7. Demonstrate professional conduct in laboratory and other environments
• 8. Use on-line literature databases to gather scientific information.
• 9. Communicate to expert and non-expert audiences using written, oral, and visual means

Syllabus plan

Whilst the module’s precise content may vary from year to year, an example of an overall structure is as follows:

Lectures
There is a lecture most weeks, covering the topics described below and delivered by a suitably qualified member of staff. In the first week, there is an introductory lecture to describe the module in detail, including the Intended Learning Outcomes (ILOs), assessment procedures, laboratory practical, workshops, and other practicalities.

Lectures may explore the following topics:

• History and philosophy of science
• Ethical issues in neuroscience research
• Principles of experimental design
• Methods in neuroscience
• Statistics, data handing and data presentation
• Key research skills and scientific communication

Laboratory Practicals
Throughout the year there will be seven laboratory practical sessions, with the first practical focussing on laboratory safety.

In term 1, you will learn the basics of laboratory safety and basic laboratory techniques. Examples of topics that may be covered include:

• Laboratory safety and record-keeping
• Pipetting
• Dilutions
• Laboratory calculations and making stock solution

In term 2, you will have the opportunity to apply the knowledge and skills gained in term 1 to a series of laboratory practicals related to common laboratory techniques. Examples of techniques that may be covered include:

• Neural cell culture
• Cell imaging and microscopy
• Basic molecular biology e.g., polymerase chain reaction (PCR)

Statistics Workshops
These sessions aim to provide you with key data handling and analysis skills. Across seven workshops during the module, you will perform statistical analysis along with a lecturer who will provide practical demonstrations. Indicative topics that may be covered include:

• Data handling and data types
• Measures of significance
• Basic statistical methods
• Assumptions of statistical tests
• Data interpretation
• Data visualisation

Small Group Seminars
In nine facilitated seminars interspersed regularly through the module, you will work with others to review and consolidate your learning on the topics covered in lectures. During these sessions, you will work together in groups to discuss a variety of topics and complete tasks including:

• Evaluating scientific papers and modes of science communication
• Reviewing laboratory key skills
• Carrying out data interpretation exercises
• Discussing specific focus points set by the lecturers

At the end of the module, you will be assessed on the content of the lectures and seminar sessions in a final exam made up of multiple-choice answer and data interpretation questions. In the final week of the module there is a one-hour exam information and preparation lecture.

Learning activities and teaching methods (given in hours of study time)

Details of learning activities and teaching methods

Formative assessment

Summative assessment (% of credit)

Details of summative assessment

Details of re-assessment (where required by referral or deferral)

Re-assessment notes

Students who are resubmitting an item of coursework as a result of referral in the module will submit the same assessment e.g., practical write-up of the term 2 practicals or an abstract of a paper.

If the student misses 5 or more seminars and has a relevant ILP, they must obtain a deferral of the seminar participation component. In the case of deferral of the seminar contribution assessment, students will be required to choose three of the six selected question/task sets and answer all questions or perform all tasks attributed to them. Students with Individual Learning Plans referencing difficulties in group participation will be offered the option to do the re-assessment in lieu of a seminar contribution score.

Please also refer to the TQA section on Referral/Deferral: http://as.exeter.ac.uk/academic-policy-standards/tqa-manual/aph/consequenceoffailure/

Indicative learning resources - Basic reading

“Statistics for dummies” – Rumsey, ISBN 9781119293521

“Statistics II for dummies” – Rumsey, ISBN 9780470543863

“Writing for Science Students” - Boyle & Ramsey,â?¯ISBN 9781137571519 

“Critical thinking skills: effective analysis, argument and reflection” – Cottrell, ISBN 9781137550521

Indicative learning resources - Web based and electronic resources

Statistics website https://rgs212.gitlab.io/neurostatsuoe/

Key words search

Safety, laboratory skills, statistics, research skills, scientific communication, scientific writing, presentation skills, experimental design, data analysis, study skills, neuroscience