Prof Christopher Yeo
Professor of Behavioural Neuroscience
Neuro, Physiology & Pharmacology
Div of Biosciences
- Joined UCL
- 1st Oct 1999
In analysing how the brain controls behaviour, an ideal approach is to characterise the activity of a real network of neurons with an essential role in the control of an identified behaviour. In selecting such a network for investigation, the cerebellum stands out. Its influence upon behaviour is ubiquitous. Long seen as an important regulator of reflex and voluntary movements, it is now recognized that the cerebellum is critically important in many aspects of sensorimotor control and learning. Recent evidence that cerebellar damage may be associated with dyslexia, autism and disturbances of time estimation have led to suggestions that the cerebellum is also important for cognitive function.
Three special properties recommend the cerebellar neural network for investigation:
First, the cerebellum has prodigious computational power â?" it contains more than half of all the neurons in the brain.
Second, because of its special architecture, the size of this neuronal population does not deter analysis. Cerebellar neurons are arranged in a regularly repeating, geometrical array to form a large set of regularly repeating microcircuits.
The anatomical and physiological similarity of these microcircuits suggests a consistent type of information processing - the cerebellar algorithm.
Third, the microcircuits are mapped in an orderly fashion within the cerebellum. Each receives an appropriate set of sensory inputs but applies the computational result solely to a specific output region. For many cerebellar microcircuits this output is, ultimately, to a small set of motoneurons that control an individual muscle or group of synergist muscles.
These unique features of the cerebellar architecture enable a very special approach to the analysis of behavioural control. A specific target movement can be selected and the properties of the cerebellar neurons contained only in those microcircuits that directly control that movement can be analysed. Since the cerebellum is specifically implicated in learning, a target movement that can be shown to undergo modification through learning can be analysed. This strategy enables us to investigate how, with specified inputs and outputs, local synaptic change in an identified set of cerebellar microcircuits can generate a globally intelligent behaviour.
A leading candidate behaviour for investigation is classical conditioning of the rabbit eyeblink/nictitating membrane response (NMR). Lesion and reversible inactivation studies have revealed its dependence upon the cerebellum but have not revealed how the essential neural plasticity is distributed across and within the cerebellar cortical and nuclear circuitry. Our work in defining how the cerebellum generates this behaviour is at several levels of analysis. We are working to:
1. Describe how plasticity essential for eyeblink/NMR conditioning is partitioned between cortical and nuclear levels.
2. Define whether learning-related cerebellar plasticity has properties similar to previously identified in vitro forms.
3. Analyse how the relevant cerebellar Purkinje cells and nuclear neurons behave during reflex and learned eyeblinks and describe how their activities are related.
4. Determine how Purkinje cell simple and complex spikes change their behaviour as learning proceeds.
5. Use information from the empirical work to make descriptive, and then computational, models of cerebellar action that will explain how local synaptic learning rules result in overall intelligent behaviour.
- Queen Mary and Westfield College
- Doctorate, Doctor of Philosophy | 1977
- Queen Mary and Westfield College
- First Degree, Bachelor of Science (Honours) | 1973