A neuronal network generating flexible locomotor behaviour in a simple vertebrate: studies on function and embryonic self-assembly

How do nervous systems allow animals to behave? The challenge here is immediately clear from the vast numbers of neurons (over 2 billion) in a human brain. Less obvious is the minute scale of nervous systems construction with many neurons only 0.01 mm in diameter. Problems of size and complexity have led to the study of simpler animals like snails and squid which have complex behaviour but many fewer, often larger, neurons. A further remarkable feature of nervous systems is that they must self-assemble rapidly during embryonic development to allow early responses that aid survival. How do they do this? Recent genetic work on development has emphasised fundamental features, common to animals as diverse as nematode worms, fruit flies and vertebrates like us. Detailed research on embryos has shown that vertebrate nervous systems share a common plan particularly in core parts like the spinal cord. We can therefore investigate how nervous systems develop and function in the simplest vertebrates. We study just-hatched, 2 day old frog tadpoles. While only 5 mm long and with less than 2000 neurons, they will swim when touched, struggle when grasped by a predator, and stop and attach when they bump into things: behaviour that aids survival. Exploiting the simplicity of the early tadpole nervous system and new methods that we devised, we have recorded activity from most types of neuron controlling movement and now have a uniquely detailed picture of the neuronal circuits for swimming and struggling. In collaboration with computer scientists and mathematicians, we built simplified models of these circuits and uncovered key principals of operation. This theoretical work emphasised commonality in neuronal circuits controlling movement, from snails to mammals, but revealed gaps in our knowledge. As well as asking how early neuronal circuits work we also want to know how they develop. We found that connections between tadpole neurons are not very specific. Broadly, their nerve fibres simply contact the neurons they encounter as they grow. Since neurons responding to sensory stimuli lie at the top and neurons controlling muscles lie at the bottom, those growing near the top will connect to different neurons to those growing near the bottom. Our mathematical models showed that very simple rules could direct nerve fibre growth to form neuronal circuits able to generate swimming activity when stimulated. In this study we will ask whether the ordered structure of the early tadpole nervous system allows functional neuronal circuits to self-assemble in response to 3 chemical gradients known to control growth of nerve fibres along and around the nervous system. To answer this question we need many more electrical recordings to establish exactly how swimming and struggling are initiated by different skin stimuli. We also need more detailed information on morphology for each neuron type. Our study should reveal how nervous systems 'decide' to initiate movement. Using the morphological information we will build a mathematical model of neuron growth to generate the synaptic connections that different types of neuron make with each other to self-assemble neuronal circuits. Using the physiological information we will build models where the different neurons are connected into functional circuits which we can stimulate to find how they generate the neuronal activity that produces swimming and struggling. Our ultimate aim is to see if simple growth rules can allow the self-assembly of neuronal networks which can 'decide' when and how to respond to sensory stimuli, behaving like a tadpole. By making a 'virtual tadpole' whose movements are controlled by our networks we can actually watch them producing behaviour. If successful, our study will lay a foundation for understanding the way more mature, complex nervous systems control movements and how they develop.

Functional neuronal networks can form rapidly as vertebrates first develop. Molecular biology suggests that hindbrain and spinal cord networks are built on a common plan from organised rows of precursor cells. Detailed studies also show diverse mechanisms that control axon growth and ensure that correct synaptic connections are made. How do these early circuits work and can they form using simple growth rules? In the hatchling Xenopus tadpole our recent work has defined in detail the anatomy, properties and functions of the neurons of the locomotor network in the hindbrain and spinal cord that lets animals swim when touched or struggle when grasped. We will combine our detailed knowledge of circuit structure and function with computer modelling of neuron growth to build a self-assembling locomotor network model, finally visualised as a 'virtual' tadpole, that responds flexibly to stimuli like the real animal. Uniquely in vertebrates, we can critically evaluate our model's success as we know the final motor output and the activity patterns of most network neurons. We will first resolve questions about neuron anatomy and initiation pathway physiology, using modelling to analyse experimental results and generate further questions. We will then test the hypothesis that simple molecular gradients operating during development can direct self-assembly of a minimal functioning neuronal circuit that generates alternating swimming to brief stimuli. Once this proof of principle is established for swimming, we will extend experiments and modelling to test whether (1) continuous stimulation can reconfigure the locomotor network to produce struggling, and (2) longitudinal gradients in synaptic drive can organise the longitudinal spread of activity in swimming and struggling. Our results will show how sensory stimuli initiate distinct locomotor rhythms and provide a platform on which to test hypotheses about how other early vertebrate neuronal networks develop and function.