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Brain Sciences: From Molecules to Mind

The M.Res. programme consists of a series of six courses, including four taught courses and two research projects:

Molecules to mind

The first aim of the course is to provide students with the knowledge of neuroanatomy and neuronal signaling required to understand the basis and applications of advanced brain imaging techniques: fMRI, MEG, EEG, and TMS. The course also aims to provide students with the critical appraisal skills necessary 1) to understand the use of brain imaging to explore problems in the areas of attention, vision, cognition, and language, and 2) to explore novel techniques to analyse the complex brain signals measured by fMRI, MEG, EEG, and TMS. The course includes reference to the historical aspects of brain imaging, and its relevance to current research questions in the field of brain sciences.

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

  • Have a critical awareness of how the underlying principles of neuronal communication and neuroanatomy underpin brain function as imaged by a variety of advance imaging techniques.
  • Discuss and appraise the literature on functional neuronal circuits and the generation of neuronal oscillations.
  • Critically appraise the pitfalls in the interpretation of MEG and EEG recordings and their neuroanatomical localization.
  • Describe the physical basis of magnetic resonance imaging.
  • By appraising the current literature, discuss the basis of functional MRI and demonstrated an understanding of its application to brain science.
  • Critically appraise the role of TMS in exploring brain function.
  • Design experiments using a range of brain imaging techniques and evaluate the recent experimental advances in the field.

Statistics

This course is designed to provide a detailed understanding of the use of descriptive statistics, ANOVA and regression models. A particular emphasis is put on robust methods and how they can help alleviate problems associated with parametric techniques. The course also gives a non-technical account of hierarchical regression models, multiple regression and multivariate techniques. The course uses the statistical programming language R to demonstrate statistical tools. R is open source and runs on most platforms and operating systems (PC, Mac, Linux).

By the end of this course students will be:

  • Able to describe the importance of and contrast different descriptive statistics;
  • Familiar with the basic mechanisms of bootstrap and permutation techniques and how they can improve on classic parametric techniques;
  • Familiar with basic ANOVA theory and tests of comparisons among means;
  • Familiar with multivariate extensions to the ANOVA, and in particular ANCOVA and MANOVA, and how these analyses can be performed computationally using the R language;
  • Able to explain the basic multiple regression equation, the meaning and the statistical significance of regression coefficients, R2, F ratios;
  • Able to explain the advantages of hierarchical regression models and how to apply these techniques to practical research questions;
  • Able to explain the difference between multivariate and univariate methods in a non-technical manner, and the areas in which these methods are appropriate;
  • Able to use the programming language R to explore datasets, produce figures and apply  statistical tests.

Optional taught courses

You will select two options from a wide range of advanced courses covering topics in neuroscience and psychology including: advanced neuroanatomy, brain development, neuropsychology, brain diseases, neurotransmitters and drugs, neuronal circuits and memory, vision, attention, working memory, brain oscillations, aging, plasticity, fMRI.

The specific aims of this taught courses in neuroscience and psychology are

  • To give students the knowledge, intellectual skills and critical ability needed to evaluate research findings in neuroscience and psychology;
  • To provide students with a detailed knowledge of recent advances in fundamental neuroscience research relevant to brain sciences.

At the end of the courses students will be able to:

  • Summarise and evaluate critically research findings relevant to neuroscience and psychology;
  • Critically evaluate how fundamental research in neuroscience and psychology can inform studies of human brain function and brain disorders;
  • Identify areas where further research is necessary and be aware of the techniques that could be used to pursue the research;
  • Summarise and present research findings in oral form in seminars and workshops and communicate effectively with peers, supervisors and more senior colleagues;
  • Produce a critically evaluated, written synthesis of recent research findings in a specific topic of relevance to neuroscience and psychology;
  • Plan and manage time effectively.

Research projects

The course is designed to give you the experience of performing two cutting-edge research projects in brain science laboratories of international standing, including writing up the results appropriately for peer-reviewed publication, and giving an oral presentation of your results.  Students do two projects in different laboratories, one from January to April (4 months), one from May to August (4 months).

Research methods

This course complements research projects 1 and 2. This course is designed to give students the experience of planning cutting-edge research projects and giving oral presentations of their results. Students are supervised by academic staff in neuroscience and psychological laboratories of international standing.

Students should be capable of performing these stages of research projects in neuroscience and psychology with only limited supervision and using a critical understanding of relevant principles in brain sciences: planning, literature review and obtaining ethical permission.

In particular, students should be able to:

  • Produce a detailed proposal for a research project, specifying motivation for the project, proposed methodology, resource implications and timetable;
  • Competently defend their research work under oral examination.

Additional course elements include attendance at institute research seminars and journal clubs. We also provide a large range of additional training and workshops in various specialist areas. For instance, you will have the opportunity to learn the Matlab programming language, a powerful tool for data analyses.