Award details

Dynamic network reconfiguration at the transition between motor programs

Reference	BB/T003146/1
Principal Investigator / Supervisor	Dr Wenchang li
Co-Investigators / Co-Supervisors
Institution	University of St Andrews
Department	Psychology
Funding type	Research
Value (£)	440,635
Status	Current
Type	Research Grant
Start date	02/03/2020
End date	01/03/2024
Duration	48 months

Abstract

The activity of a neural network is shaped by its connectome. However, this structure-function relationship is not fixed and may change dynamically, enabling rapid changes in response to new situations. In frog tadpoles, motor circuits that generate forward swimming can produce backward-thrusting struggling if the tadpole is held. Whereas swimming involves a wave of muscle contractions propagating from head to tail, struggling is a slower but powerful rhythm that propagates from tail to head. We propose that dynamic network reconfiguration occurs automatically in the spinal cord as sensory inputs change, without involving neuromodulation or feedback from the brain. Continuous sensory inputs trigger reconfiguration in tadpole motor circuit by recruiting additional groups of neurons while depressing the activity of other groups of neurons. Such recruitment/de-recruitment is achieved through changes in the biophysical properties of the neurons and their synapses. We will define these biophysical changes and determine how they reconfigure motor circuits. The Xenopus tadpole is a unique vertebrate system to study dynamic network reconfiguration because we already know the detailed connectivity of its motor circuits, which is still the main aim of many state-of-art imaging or genetic studies in other model preparations. This will allow us to build computational models of the circuits for both swimming and struggling and analyse the dynamics at the transition between them. In turn, modelling will generate predictions about the reconfiguration mechanism, which will be tested experimentally, e.g. by using optogenetics and in situ dynamic patch clamp recordings. The principles on how vertebrate motor circuits quickly reconfigure their connectome to generate different behaviours will not only address a fundamental neuroscience question, but also potentially provide insights for the design of robots with improved mobility and obstacle avoidance.

Summary

A beautiful ballerina dance can be considered as a continuous chain of motor actions (behaviours) such as jump, forward run, backward run, etc. Neurobiological experiments show that each particular motor behaviour can be characterised by a set of neurons producing a pattern of electrical activity. However, transitions between different patterns are poorly understood. Neurons are interconnected to form a neuronal network but it is not clear how the network can switch from one behaviour to another. What happens in the neuronal network when the forward run in a dance switches to backward? In this project, we will study young frog tadpoles with just two rhythmic motor behaviours: forward swimming and backward struggling. In swimming, alternation in neuron activity on each side leads to rapid waves of muscle contraction propagating from head to tail. If held by a predator, or stuck against an obstacle, the tadpole must quickly escape. In that case, it rapidly switches to the struggling behaviour, during which slower, but more stronger waves propagate from tail to head, leading to a powerful backward movement, which could be critical for survival. Of particular interest to us, is that the neuronal network that produce struggling is the same network that produces swimming. When the tadpole is captured by a predator, the continuous sensation on its skin results in the activation of extra groups of nerve cells while other groups of nerve cells are turned off. This means that the network reconfigures itself automatically to generate a different behaviour, potentially assisting the animal to escape. This fast reconfiguration to produce a different behaviour also occurs in more sophisticated brain networks in higher vertebrates and humans. Neuroscientists are devising new optical imaging methods to monitor the activity of groups of nerve cells in these complicated systems. In the tadpole, however, we can directly record from individual nerve cells in pairs, to measure precisely how their activity and the messages they exchange are altered at the transition between swimming and struggling. Thus, the tadpole provides an unparalleled ability to define and understand exactly what happens during neuronal network reconfiguration. Most fundamental neuronal mechanisms are highly conserved across vertebrate species. The results from tadpoles will be immensely useful to further understanding of more complex brain networks in mammals. The extremely detailed recordings that we can perform on the tadpole will also allow us to build detailed computer models of tadpole neuronal network involved in its motor control. These models will be used to examine the effects of manipulations of the network that are impossible to study experimentally and generate important insights. This way, the models can formulate new hypotheses that may be in turn tested experimentally. Using this combination of models and physiological recordings, we will understand 1) why the struggling waves are more powerful than the swimming waves; 2) why they propagate from tail to head, contrary to the head-to-tail propagation in swimming; and 3) how the neuronal circuit changes itself to produce these distinct behaviours. The findings will have implications beyond basic neuroscience research. For example, the principles could be used to better design robots that need to navigate difficult environments without getting stuck.

Impact Summary

The aim of this project is to uncover fundamental principles about switching mechanisms between motor programs. The results will directly benefit a range of neuroscience communities listed in the Academic Beneficiaries section and contribute to improvement of UK shortage of skilled electrophysiologists. The following text outlines impacts beyond neuroscience research. 1) Neuroscience education of general public: This is the main societal impact of our project. Frog tadpoles are among the most familiar animals to the public and attract attention across different age groups. Therefore, they provide a valuable entry point to explain how the vertebrate embryo develops, and how the nervous system is organized and controls behavior. Also, tadpoles provide context for explaining how scientific research is carried out. Thus, using a simple animal is an important societal advantage of our research project. Recently our colleagues from Bristol setup the tadpole website (http://tadpoles.org.uk/) for neuroscience education of general public. This website has been attracting on average 70 visitors every day, totaling around a quarter million a year. We will update this webpage using our new results on struggling. Xenopus tadpoles go through metamorphosis to develop into frogs. A couple of years ago, our St-Andrews colleagues Prof Keith Sillar and Isobel Maynard had started to send spare tadpoles to local schools that the students can observe the metamorphosis process. This activity has received a huge enthusiasm from both students and teachers. With Isobel's recent retirement, Dr Li and Prof Sillar will continue to participate in this outreach activity. 2) Knowledge exchange with clinically applied researchers and potentially pharmaceutic companies: Development of effective clinical tools to tackle movement disorders and spinal injuries rely on understanding the basic principles underlying motor behaviours and the transition between them. This is immensely difficult in mammals.Using tadpoles presents opportunities to obtain novel, deeper insights that relate to these conditions. Both medical practitioners and pharmaceutical companies need insights from basic research to guide their own research activities and design new medicines. Direct communication with these parties can bridge gaps and help to produce better drugs. 3) Knowledge exchange with the robotic industry: Robots are taking over many tedious jobs in industrial and domestic settings. Robots that use mechanical legs for movement can go through surfaces that wheeled robots cannot enter. However, they require better stability and motion control. One difficult problem to address is what happens when a robot is stuck. Work on tadpole locomotion has shown that design details such as nonlinearities can have profound impact on robustness of motor outputs. By revealing how tadpoles quickly and robustly switch between motor programmes when the need arises, our work can potentially lead to more robust, novel robot designs. 4) Knowledge exchange with research policy makers and funding bodies: Due to their evolutionary closeness to humans, mammals have been the favorite for investigating many neuronal system functions and conditions. However, many discoveries have proven the value of choosing the simplest and most appropriate system for investigation of specific questions. Communicating the findings from this project to funding decision-makers will help to support the use of model animals and reduce experiments with adult mammals. Indeed, using tadpoles as a model animal to study motor control is internationally recognized but is carried out almost entirely in the UK. With Prof Roberts's and Dr Soffe's retirement, the tadpole research has been shifting to Scotland (Prof Keith Sillar, Drs Wen-Chang Li and Hong-Yan Zhang). The success of research outputs from this model system will continue to raise the profile of UK research.

Committee	Research Committee A (Animal disease, health and welfare)
Research Topics	Neuroscience and Behaviour, Systems Biology
Research Priority	X – Research Priority information not available
Research Initiative	X - not in an Initiative
Funding Scheme	X – not Funded via a specific Funding Scheme

Associated awards:

BB/T002352/1 Dynamic network reconfiguration at the transition between motor programs

BB/T002549/1 Dynamic network reconfiguration at the transition between motor programs

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