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School of Life Sciences

Research Methods for Neuroscience (C1147)

Research Methods for Neuroscience

Module C1147

Module details for 2025/26.

15 credits

FHEQ Level 4

Module Outline

This module explores modern techniques for collecting, analysing and interpreting data in neuroscience, which are essential skills for understanding evidence on the workings of the brain, and to becoming a neuroscientist. It is taught in three parts:
Part 1 - Statistics.
Basic statistical skills needed for neurobiology, including the use of R/R-studio open-source statistical software.

Part 2 - Methods and Data in Neuroscience.
Engagement with primary neuroscience literature or datasets, application of analysis skills, and oral communication.

Part 3 - Physics for Neuroscientists.
Basic mathematics (derivatives, etc) and physics (waves, electrical circuits) necessary for understanding fundamentals of biophysics and neuroscience.

Module learning outcomes

Demonstrate understanding of a range of statistical methods that are commonly used in the biological sciences, and be able to use a modern software package to apply these methods to biological data.

Research and apply methods from a primary neurobiology research paper to obtain and analyse a real or simulated neuroscience dataset, and communicate your findings via scientific media and in class discussions

Describe the basic mathematics and physics needed to understand the operation of the nervous system.

TypeTimingWeighting
Coursework100.00%
Coursework components. Weighted as shown below.
TestT2 Week 5 (2 hours)40.00%
Problem SetT2 Week 11 40.00%
PresentationT2 Week 11 20.00%
Timing

Submission deadlines may vary for different types of assignment/groups of students.

Weighting

Coursework components (if listed) total 100% of the overall coursework weighting value.

TermMethodDurationWeek pattern
Spring SemesterSeminar1 hour00000000001
Spring SemesterOnline Lecture1 hour11110000000
Spring SemesterWorkshop2 hours01111000120
Spring SemesterClass1 hour00000021111
Spring SemesterLecture1 hour22222200000
Spring SemesterLecture1 hour10000323100
Spring SemesterOnline Interactive1 hour00101000000

How to read the week pattern

The numbers indicate the weeks of the term and how many events take place each week.

Dr Doran Amos

Convenor, Assess convenor
/profiles/412189

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