Our lab studies the nervous system using ideas from control engineering and neurobiology. Nervous systems are messy and built from unreliable components. Yet they still outperform human-designed control systems and computers in many ways. Our goal is to understand what kinds of "engineering-like" principles apply to nervous systems, what makes them adaptive, flexible and robust, how they self-organise during development and why they sometimes malfunction.

Why is control engineering useful for neuroscience? Control engineering is a body of methods for understanding complex and uncertain systems, how they interact, how to model them from data and how to control them using feedback loops. All of these issues are central to neuroscience and to biology in general. Feedback is an especially important principle in nervous systems because they have feedback at every level, whether it is the internal feedback that controls cellular processes in individual nerve cells, or the process by which organisms learn by interacting with the world.

Aside from practical difficulties, two major obstacles stand in the way of a systematic understanding of the brain. First, nervous systems adapt over time. Neural circuits reconfigure to store information and they employ a host of regulatory feedback mechanisms to compensate for growth, ageing and ongoing perturbations and insults that all living systems face. While this adaptive property is crucial for nervous systems to function, it is a serious headache for people trying to study the brain! Secondly, there is huge amount of biological variability in the nervous system: every brain is wired up differently and every nerve cell has its own unique life history and makeup, making it difficult to formulate unifying principles and build predictive models.

We are in an exciting era of neuroscience where engineering principles can finally be applied to living systems. It is now possible to measure and manipulate nervous system function from the level of single neurons to entire brain areas, offering enormous potential benefit to society through bioengineering, biomedical applications an a deeper understanding of nature. For society to reap these benefits we need a principled, systematic understanding of the brain. Just like when fixing a car, we need to know the working principles before we dive under the hood. Medical advances in neuroscience are notoriously slow and based largely on trial-and-error because we lack a basic understanding of the working principles. This can change if we bring new ideas to the table.

Our work focusses on several fundamental questions:

  • What are the feedback mechanisms that allow nervous systems to develop, self-organize and repair themselves? Why do they sometimes fail?
  • How do nervous systems function in spite of variable and noisy components?
  • How can we reverse-engineer such complex, variable and dynamic systems, especially when they can adapt and reconfigure each time we probe them?

We address these questions using computational, theoretical and experimental approaches in multiple species and systems, in close collaboration with experimentalists, engineers and theorists. Please get in touch if you would like to join us!