Sussex Neuroscience

Taught modules

Students on the 4-Year PhD Programme can choose from a wide variety of advanced level taught modules across different Schools.

Some relevant modules on offer during the 2018-19 academic year are as follows:

Intelligence in Animals and Machines (Autumn)

The module will develop an understanding of what it means for an animal or a machine to behave intelligently, and how brain and behavioural systems are adapted to enable an animal to cope effectively within its environment. We consider diverse aspects of intelligence including navigation and motor control, tool-use, language, memory and social skills. We ask how these are related to one another and how they are matched to the particular needs of animals. We finally consider what we can learn about intelligence through computational modelling by examining the challenges faced by scientists trying to create artificial systems with the same behavioural capabilities.
As well as the reading list, three papers on current research issues will be given each week to be discussed in seminars.

As well as the reading list, several papers on current research issues will be given each week to be discussed in seminars. In addition, a couple of papers which give you the flavour of the course are:

Shettleworth, S. Clever animals and killjoy explanations in comparative psychology. Trends in Cognitive Sciences, 2010
Webb, B. What does robotics offer animal behaviour? Animal Behaviour, 2000

Linear Models in Statistics (Autumn)

Linear models in statistics consists of a series of lectures and practical classes, mainly aimed at introducing or re-introducing postgraduate students to the general linear model. The lectures (typically 1 per week) are aimed at delivering background theory and the practical classes (also typically 1 per week) are designed around interactive tutorials that put the theory from the lecture into practice using the open source (and free) statistics software R(implimented in RStudio). Through these tutorials students should develop a good working knowledge of RStudio (and R).

Topics may include:
The linear model
Key concepts (parameters, estimation, standard error, confidence intervals)
Hypothesis testing, effect sizes and Bayes factors
Bias and assumptions of the linear model
Categorical predictors in the linear model (ANOVA)
Factorial designs and covariates
Repeated measures deisgns
Multilevel models (HLM)
Growth models
Categorical outcomes (logistic models)
Implimentation of the above in R and RStudio

Mathematics and Computational Models for Complex Systems (Autumn)

This module provides a foundation in mathematical and scientific computing
techniques used in various fields, including artificial intelligence, artificial life,
data science, and computational neuroscience. The topics covered also
provide the necessary theoretical grounding for a number of modules in
Informatics MSc courses, including Adaptive Systems and Machine Learning,

Topics include:
- Vectors and matrices
- Differential calculus
- Numerical integration
- Probability and hypothesis testing
- Dynamical systems theory

Molecular Genetics (Autumn)

The module will cover the application of molecular genetics to the study of processes in model systems and higher eukaryotes. Particular topics will include cell cycle and checkpoint control, recombination and mating type switching in lower eukaryotes, gene mapping and cloning disease genes in higher eukaryotes and the production of transgenic plants and animals.

Neuronal Transduction and Transmission (Autumn)

The module follows a logical progression from sensory transduction, the point of entry of information into the brain, to an analysis of neuron-to-neuron communication through both chemical and electrical synapses. Transduction mechanisms in the visual and auditory modalities are the main focus, though other sensory modalities are also discussed. An overview of synaptic physiology is provided as an introduction to a detailed analysis of pre- and post-synaptic cell and molecular mechanisms. Non-synaptic information processing will also be introduced. Finally the module considers whether there are limits to the molecular reductionism approach to the problem of how the brain works.

Topics in Cognitive Neuroscience (Autumn)

The module introduces students to a wide variety of topics in cognitive neuroscience that are not covered by dedicated modules. Teaching is provided by active researchers and experts in cognitive neuroscience. Students will explore the field through lectures and journal clubs as well as gain opportunities to focus research interests through self-directed presentations and study topics. The aim of the course is to generate the ability to discuss and critique current cognitive neuroscience research through a general well-rounded knowledge of topics, methods and good practice. Topics covered by lectures include (but are subject to change): an introduction to methods, neurophysiology, memory, vision, emotion, embodied cognition, reward and decision-making, animal and genetic models of cognition, dementia, event-related potentials and individual-difference approaches to cognitive neuroscience.

Advanced Research Methods in Psychology (runs throughout the year)

In this module you will learn about various advanced research methods and statistical techniques in psychology, by exploring their theoretical basis and their practical application. The module is typically taught as a set of 2-day workshops in which particular methods are considered in detail. You are expected to study three methods (i.e. attend three workshops) from the selection that is offered. The options available to you are likely to include the following: Discourse Analysis for Psychology; Experiment Generators: Use of Eprime; Eye Tracking; Longitudinal Data Analysis; Measurement of Affective Processing Styles; MATLAB; Meta-Analysis; Multilevel Modelling; Service User Involvement in Clinical Research; Transcranial Magnetic Stimulation (TMS); Categorical Data Analysis; Voice Analysis and Re-Synthesis; Latent Variable Analysis with Mplus, Introduction to R and Randomised Control Trials.

We suggest that this is counted as a Spring option, although some workshops may be scheduled during the Autumn term.

Drugs, Brain and Behaviour (Spring)

Drugs, Brain and Behaviour offers students an overview to the psychological, pharmacological, neurobiological and neurophysiological bases of drug use, abuse and contemporary understanding of addiction and (some mental conditions), and has a strong natural science (neuroscience) orientation. The acute and long-term effects of selected drugs of abuse on behaviour, mood, cognition and neuronal function are discussed, using empirical findings and theoretical developments from both human- and non-human subject studies on the neurobiological- and psychological basis of drug action and addiction. The course will discuss the anatomical, neurochemical and cell-molecular mechanisms targeted by psychoactive drugs, and their distribution, regulation and integration in the broader central nervous system. The focus is on potentially addictive drugs, and the major classes are discussed, including: opiates (heroin, morphine), psychomotor stimulants (amphetamine, cocaine), sedative-hypnotics (alcohol, barbiturates, chloral hydrate), anxiolytics (benzodiazepines), marijuana, hallucinogens (LSD, mescaline), and hallucinogenic-stimulants (MDA, MDMA). Critically, with the knowledge of the basic neurobiological and behavioural pharmacology of these drugs 'in hand¿, contemporary theories and understanding of mental conditions, substance abuse and addiction are considered, focusing on key concepts related to (drug) experience-dependent neuroplasticity, drug-induced neurotoxicity, associative learning, neuronal ensembles and the synaptic basis of learning and plasticity, habit formation and impulse-control. This module builds on knowledge gained in the core psychology modules C8003: Psychobiology and C8518: Brain and Behaviour. Students who are not enrolled on the BSc Psychology course at Sussex are expected to be familiar with the material covered in these modules.

Foundations of Neuroscience (Part 2- Spring)

This two-term module offers an introduction to cellular, molecular and systems neuroscience including cellular physiology, synaptic transmission, developmental neurobiology and neural circuitry. The Spring half of the module is available to SN PhD students and is based on the undergraduate lecture series "Neural Circuits", together with dedicated seminars and assessments for Masters students, based on the primary research literature. Topics covered include:
- Organisation and modulation of central pattern generator (CPG) circuits
- Advanced techniques for monitoring and manipulating neural circuits
- Modelling of neural circuits
- Sensory and motor functions of spinal cord circuits
- Brain circuits underlying motor control
- Circuits underlying non-associative and associative learning
- Addiction and learning circuits
- Defects in circuits
- Development of neural circuits

Functional Magnetic Resonance Imaging (Spring)

This module provides an advanced level of theoretical and practical knowledge in the technique of functional magnetic resonance imaging (fMRI). Topics covered include the physical and physiological basis of MRI and fMRI; different study designs in functional imaging research; stages of pre-processing and analysis of data; and interpretation of results. It is expected that students will be able to make a contribution to a real, ongoing fMRI study in terms of observing and/or participating in its execution and contributing to the analysis of the study. Students will gain hands-on experience of Statistical Parametric Mapping (SPM) software for analysing fMRI data that is invaluable for future research in this area.

Neuronal Plasticity and Gene Regulation (Spring)

This module will consider how cellular and molecular mechanisms interact in the regulation of neural functions underlying plasticity. Particular emphasis will be placed on mechanisms that mediate the acquisition, processing and storage of information by the nervous system. The role of unconventional neurotransmitters such as endogenous nitric oxide and endocannabinoids in neuronal plasticity will also be discussed. This will be followed by lectures on unconventional molecular mechanisms controlling gene expression in the CNS. Specifically, we will review the recent advances in our understanding of how epigenetic regulation and non-coding RNAs contribute to functional plasticity in the nervous system.

Protein Form and Function (Spring)

Proteins underlie all biological processes. The question is how? The PFF module will help you puzzle over this question: the fields of protein folding, engineering and design are in their infancies, and we have much to learn before we fully understand and can manipulate proteins. What is clear, however, is that protein structure is central to protein function. This module will provide a sense of how protein structures are related to each other and of how these structures relate to protein function. More importantly, however, this module will equip you with the necessary knowledge and skills to allow you to learn about and appreciate the remarkable class of molecule.

The first part of the PFF module necessarily re-covers some of the subject matter visited in first and second-year modules. However, aspects of protein structure are covered in much more detail. In particular, a number of sessions are used to introduce computational and experimental techniques that are essential for studying proteins. This work provides the basis for the in depth discussion of the evolution of proteins, the specifics of protein functions such as protein interactions and protein regulation and finally how proteins fold and how misfolding can lead to disease.

Sensory Function and Computation (Spring)

Comparing the organisation of sensory modalities reveals common conceptual principles underlying how sensory information is processed and transformed, as well as mechanisms characteristic to each modality, which correspond to the distinct ways in which the nervous system extracts signals from different types of physical energy. This module will teach fundamental concepts in sensory coding: feature detection, adaptive representations, coding by spike rates and timing, and population coding. It will incorporate seminars as well as workshops where computer code will be introduced and used to analyse and simulate sensory coding by neurons.

Structure and Function in the Brain (Spring)

The aim of the module is to reveal the anatomical substrates on which the processing of sensory information and the generation of motor commands depend. Specific attention will be paid to the relationship between structure and function. The module will cover the development of the anatomical features of the nervous system and will give a comparative interpretation of the anatomy of brain regions and their cellular components using a variety of examples including vertebrate and invertebrate models. The module will provide basic knowledge of the main techniques used to study the functional anatomy of the brain at systems, cellular and molecular levels.