This module provides an introduction to the study of International Political Economy (IPE). IPE is a field of research that combines the study of politics and economics, exploring both domestic and international factors that impact preferences, behaviours, and policies relating to economic globalisation. The module will cover major topics of inquiry within IPE such as the politics and policies relating to international trade, international investment, and international finance. You will be introduced to theoretical and empirical research analysing each topic covered. By the end of the term, you should have a firm understanding of IPE as a discipline, including ways in which the field’s insights can inform policy-making.
You should note that POLS0043 is an intermediate Political Science module. Its delivery is based on the assumption that students are familiar with theories and concepts central to the discipline (such as those covered in POLS001 International Conflict and Cooperation, POLS002 Democracy & Authoritarianism, and POLS006 Introduction to Politics), and possess a basic understanding of political institutions. Prior coursework in economics is not required, but is highly recommended.

The module will cover modern methods in quantitative neurophysiology and how experimental data is turned into conclusions about brain function in contemporary...

The module will cover modern methods in quantitative neurophysiology and how experimental data is turned into conclusions about brain function in contemporary research. The module will consist of lectures covering the theoretical and mathematical basis these will be accompanied by Matlab code and example data files that allow the students to practice what was taught in the lectures. There will be a large practical component in the Module. The students will work with real data in the form of large data sets, that cover a wide range of modern neuroscience techniques, ranging from brain imaging, to Neuropixel recordings. The students choose their own data set from neuroscience data sharing websites or databanks or they can use data they generated themselves in previous research activities.

The main focus of this module is to give you theoretical and practical experience in how to conduct research in systems neuroscience. The data analysis methods are state of the art and provide a foundation for future work (PhD in this topic, or industrial settings where such research is performed e.g. pharmaceutical industry).

After taking this module you will be able to:

critically assess the quality and validity of data in neuroscience.
	select the appropriate analysis methods depending on the data structure and the research questions addressed.
	critically assess scientific publications in the field by evaluating the methods used and results provided and appraising the discussion of the results given in the publications.
The module is available to year 4 undergraduate students with a strong background in Neuroscience who meet the pre-requisites in maths/statistics.

Indicative lecture topics:

Review of Statistics
	Spike trains
	LFPs
	Spectral analysis
	Spectrograms and nonstationary signals
	Multiple Timeseries
	Circular statistics, maximum likelihood, local likelihood
	The Singular Value Decomposition
	Dimensionality Reduction
	Confirmatory Analysis of multiple spike trains