This course provides an introduction to the neuroscience of decision making in the human and non-human primate brains. In particular it provides an overview of the brain networks as well as the mechanistic details of how perceptual and reward-based decisions are implemented in the brain.

2 hours per week for 5 weeks

Examination 100% you will answer 1 question from a choice of 3

This course provides an introduction to the neuroscience of decision making, in particular the neural principles underlying perceptual as well as reward- and value-based decisions. Perceptual decisions involve choices based on ambiguous sensory evidence whereas reward- and value-based decisions hinge largely on probabilistic evidence and subjective preferences associated with potential choices. In addition, the role of training in perceptual decision making and the influence of reinforcement-learning in reward-based choices are discussed in the context of optimising decision-related processing. Important methodological considerations on how the relevant neural data are collected and analysed, including some computational modelling work, are also explored. The course draws mostly on recent research reports from both the human and non-human primate literature to illustrate the brain networks and the fundamental principles underlying decision-related processing and their relevance to interpreting neurophysiological and neuroimaging experiments and to understanding brain function in health and disease.

By the end of this course students will be able to:

■ critically evaluate the main principles guiding different forms of decision making problems (e.g. perceptual vs reward-based decisions), identify the relevant brain networks implementings such decisions and explain how these can go astray in brain trauma or disease

■ critically evaluate the main principles and neural networks involved in reinforcement learning during perceptual and reward-based decision making

■ critically evaluate the main principles of sequential sampling models of decision making

■ design simple behavioural paradigms to probe the behavioural and neural correlates of decision making and recognise how interventional techniques (TMS, electrical stimulation, brain lesions) are used to establish causal relationships in neural networks

■ critically evaluate the influence of important decision modulators (e.g. confidence, speed-accuracy-tradeoff, expert advice, risk, time, genes, etc) on behavioural choice

■ distinguish different analytical approaches for data analysis and different human neuroimaging techniques for data acquisition and appraise their (dis-) advantages

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