Skip to main content
Pembroke

From Brain to Behaviour

Dr Guillaume Hennequin 

Our brains enable all we do, think, and remember, yet we know little about how this happens and why it sometimes fails. Neuroscience is emerging as one of the main scientific frontiers of this century, with nations investing massively into brain research. Are PKP students going to see the mystery of their brains resolved in their lifetime?

The good news is: recent breakthroughs in biology have enabled scientists to record brain activity at a scale they could only dream of 15 years ago. The bad news is: big data is very difficult to make sense of! This is where theoretical neuroscientists kick in: trained in mathematics, physics, engineering, machine learning, or other quantitative fields, they work to develop new conceptual frameworks, develop models of brain function, and provide efficient computational tools for neural data analysis.

This course will give a thorough, yet approachable, introduction to theoretical neuroscience, highlighting the key areas where it has already made seminal contributions, and introducing students to modern themes. We will begin with a basic introduction to the biology of nerve cells, and work our way towards compact mathematical descriptions of the behaviour of single neurons and neural networks.

We will go through various types of networks, and investigate how they may support specific computations such as perception or decision-making. Each (group of) lecture(s) will be complemented by practical programming exercises, to be run conveniently in the browser during the seminars, thus giving students a chance to explore models of neurons and networks in detail.

Programming will be done in OCaml (http://ocaml.org), offering students a unique opportunity to learn a modern functional programming language in a stimulating scientific context. Training in OCaml will be provided during the seminars.

Intended Audience

This course is intended for students from any scientific field with an interest in neuroscience and quantitative approaches to biology in general.

Previous Knowledge

A good working knowledge of basic calculus, statistics, and linear algebra is required, but more advanced mathematical concepts will be introduced in the lectures where necessary. Students with little or no background in quantitative subjects should be prepared to put in extra work.

Transferable Knowledge and Skills

The neuroscience knowledge developed in this introductory course will enable students to confidently navigate the vast neuroscience literature, and get a better, critical appreciation of what is commonly referred to as "Artificial Intelligence".

The functional programming skills developed during the seminars will be widely applicable to any fields of science.

 


Dr Guillaume Hennequin 

Dr Guillaume Hennequin is a University Lecturer in Computational Neuroscience at the Engineering Department, and a fellow of Pembroke College. He leads a research group working at the intersection of neuroscience and engineering to uncover the fundamental principles by which the dynamics of brain circuits give rise to intelligent behaviour. One of the core mission of his lab is to understand how neurons work together to control movement.