Neurobiological Rhythms: A Computational Approach

In 1931, the reformed bank robber Wiley Post became the first man to experience jet lag through being the first person to fly around the world, a distance of 15,474 miles in 8 days. Jet lag, which many of us have now experienced, highlights the existence of a circadian clock - and that problems arise when this clock becomes out of phase with its environment. It is now known we have many other biological clocks, acting on different scales of time and space. Regardless of their scale, all these clocks allow us to anticipate changes in our environment, and co-ordinate our interacting bodily functions.  

This module will explore these rhythmic processes of nervous systems, in both health and disease. You will use computational techniques to investigate the basic mechanisms that produce these rhythms as well as examining those which allow these rhythms to coordinate with each other. You will also learn about Dynamic Diseases, the pathological states which arise from the dysfunction of these rhythms.   

It is recommended, though not essential, that students taking this module have completed an A Level or equivalent in Mathematics. CSC2020 Coding for Medical Scientists is recommended for students of Medical Sciences or Neuroscience. NEU1006 (formerly CSC1006) is recommended but not essential for students of Medical Sciences and Biological Sciences. 

This is an optional module for students studying BSc Neuroscience and BSc Medical Sciences (Neuroscience). This module is also open to students from CEMPS, particularly those studying for a BSc in Mathematics or Natural Sciences. It is also open to students studying Biological sciences in CLES. 

This module demonstrates the importance of rhythmic behaviours in the nervous system, explaining both their roles and their mechanisms. You will see first-hand that the apparently contrasting patterns of fast electrical activity, produced by a single neuron, and the slow oscillations generated by large networks of neurons can actually arise from common mechanisms. From this observation you will develop your intuition for how oscillations are controlled, by manipulating them within mathematical models. The module will also describe how oscillators are entrained by periodic stimuli, illustrating how oscillators can therefore coordinate their activities, and what might happen when this coordination is disrupted. These concepts will be demonstrated with reference to phenomena such as rhythmic spiking in single neurons, theta and gamma oscillations in the cortex, and the circadian and sleep cycles.  

Mathematical modelling is an important tool to explore biological oscillators. You will learn and apply basic concepts of mathematical modelling of biological systems during this course. 

Where possible, Neuroscience students will be paired with students from other disciplines, for example Mathematics and Natural Sciences, in order to help each other learn. This innovative approach is based on compelling evidence that this near-peer approach to interdisciplinary study supports the learning of all participants (Evans and Cuffe 2009; Naeger et al. 2013) 

Evans, Darrell J. R., and Tracy Cuffe. 2009. ‘Near-Peer Teaching in Anatomy: An Approach for Deeper Learning’. Anatomical Sciences Education 2 (5):227–33. https://doi.org/10.1002/ase.110. Naeger, David M., Miles Conrad, Janet Nguyen, Maureen P. Kohi, and Emily M. Webb. 2013. ‘Students Teaching Students: Evaluation of a “Near-Peer” Teaching Experience’. Academic Radiology 20 (9):1177–82. https://doi.org/10.1016/j.acra.2013.04.004. 

The module’s precise content will vary from year to year, but the following information gives a detailed description of the typical overall structure. 

The module begins with an introductory lecture and workshop to outline its broad aims, weekly structure, and assessment processes; this session also introduces the scope of using computational models for neuroscientific research. 

In the first two weeks there will be a series of inter-disciplinary small group sessions. In these, for example, Neuroscience students can explore key mathematical concepts under the instruction of students with a background in mathematics. Mathematical students will improve their biological knowledge by working with Neuroscience students. To ensure that all students benefit and have similar learning opportunities, sessions with academic staff will be available for those who need further support. 

For each of the following ten weeks there will be a one-hour lecture and a one-hour workshop during which students use computational models to explore concepts developed in the lecture.  

The final week of the module has a consolidation lecture and workshop, in which students can choose which topic areas they would like to re-visit. 

Students will work in groups of 3-4 students, with at least one Neuroscience and one quantitative student per group. Each group of students will present one paper and perform a project together. 

Students will choose a project at the end of week 6, from a list of projects covering the full range of topics explored in the module. They may also propose their own project, though must check with the module convenor that it is appropriate.  Groups will then spend 6 weeks working on their project, at the end of which each member of the group will complete a 2000 word report interpreting their results. Each group member will receive the same project grade. 

Lectures 

Neuroscience: Exploring the Brain, by Mark Bear, Barry Connors, Mike Paradiso (for Mathematics and Natural Sciences students – read Part 1 Foundations)  

Modeling Life, by Alan Garfinkel, Jane Shevtsov, Yina Guo