In this course we will discuss psychological and neuroscientific studies on visual awareness and voluntary actions. We will select and critically assess influential publications in this field and discuss their wider implications.

10 hours of lectures over a 5 week block

None

There is one piece of coursework worth 100% of the overall mark. The coursework can be chosen from the following list:

1. A critical review on a topic relevant to the course. (2,500 words)

2. An original computer program that performs a specific task relevant to the experimental techniques described in the course.

3. A detailed description of how to analyse data from a specific neuroimaging experiment (e.g. fMRI, EEG).

The aims of this interdisciplinary course is to explain and discuss psychological and neuroscientific studies that investigate visual awareness and voluntary decisions. Working in class, groups, and individually we will cover the main philosophical, psychological, and neuroscientific aspects of research on visual awareness, voluntary and spontaneous actions and decisions, and their implications on the concept of free will. In particular we will analyze and evaluate classic as well as recent studies on the prediction of behaviour. We will highlight new techniques and exemplify potential limitations of this research. At the end of the course students should be able to independently evaluate new research developments in this field and to identify positive and negative implications of emerging applications.

By the end of the course students should be able to:

■ critically evaluate basic philosophical constructs surrounding the idea of awareness, attention, self-awareness, perspective taking and free will as well as pros and cons of different research paradigms, new research and applications in this field.

■ reflect critically on the concept of visual awareness and to recognize associated research paradigms

■ critically evaluate the difference between visual awareness and attention

■ illustrate methodological challenges and limitations when predicting psychological states and behaviour from neuroscientific measurements, basic principles when predicting behaviour (machine learning), and when applying these principles to different domains (e.g., legal, security, market research, learning and teaching)

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.