Cross-modality integration of sensory signals leading to initiation of locomotion

Lead Research Organisation: Plymouth University
Department Name: Sch of Computing, Electronics & Maths

Abstract

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Technical Summary

The brain and spinal cord networks controlling and initiating locomotion in adult vertebrates, especially mammals, are remarkably complex. We will exploit a simple system, the hatchling frog tadpole, where we have defined the neurons and networks generating swimming locomotion. In particular, we have identified the "dIN" reticulospinal neurons which drive swimming. In contrast to other model systems like worm, fly and fish we can study detailed neuron and synapse function using in-situ whole-cell recording. We will show: how different modalities of sensory input converge on the key dIN neuron population; how sensory integration determines the "decision" to swim, taking the state of the tadpole into account; and how the tadpole selects and correctly implements the way swimming starts, from different possible directions and strengths. A 'systems biology' approach will operate across 3 labs at 3 levels: (1) Ca imaging and whole-cell recording will trace sensory pathways to dINs neuron-by-neuron, showing how inputs interact (excitation by skin touch or light dimming, inhibition by head pressure) to control dIN firing and so initiation of swimming; optogenetic silencing will test the role of neuron populations; (2) in situ voltage-clamp will show precisely how membrane currents determine dIN responsiveness, single spiking at rest but pacemaking when NMDARs become activated during swim initiation; (3) our detailed model of a small, coupled dIN population will test the contributions of different currents to spike threshold and synaptically induced firing; our axon growth model (lengthened to include the full range of sensory input pathways) will generate a full network connection map (of ~3000 neurons) which we will map onto a functional model to evaluate our understanding of the swim initiation process. We will extend "decision" theory down to the neuronal level where noisy sensory inputs are integrated and compared to a threshold to choose a suitable course of action.

Planned Impact

The aim of this project is uncover basic principles about how sensory stimuli lead to the initiation of locomotion in animals. If it is successful, the results will benefit the range of scientific communities around the world studying this problem in a wide range of animals from nematode worms and fruit flies to man. The main academic beneficiaries have already been detailed.

If the fundamental principles about the initiation of locomotion and how nervous systems make decisions are revealed the project should additionally provide insights for:
1) medical profession in relation to movement disorders like Parkinsonism and spinal injury restoration.
2) drug companies and charities interested in such disorders.
3) research policy makers who will see the value of choosing the simplest and most appropriate system to investigate each problem. This also helps to reduce the use of adult mammals in research.

Tadpoles are some of the most familiar of animals to the wider public and attract attention across the whole age spectrum. They therefore provide a valuable, highly accessible entry point to explaining specific issues about brain and behaviour, what nervous systems are and how they work to make animals behave. They also provide a context for broader explanations about how scientific research is carried out, the significance of the 'systems biology' approach, and the importance and relevance of projects like ours which use simple model animals. The research will generate good imagery of tadpole behaviour, the growth processes of model nerve cells as they form circuits in the brain, and the activity patterns of all the neurons in the tadpole's nervous system as it responds to stimulation and swims away. These will be suitable to popularise the study of simple model animals and their brains in websites and museums and science centres like '@ Bristol' (where we have already had some participation).

In terms of training, the physiology RAs will learn specific techniques and broad experimental approaches which will prepare them for research careers in any part of academic, medical or pharmaceutical neuroscience. It is critical that the UK continues to train highly skilled electrophysiologists. These techniques remain essential for providing detailed information on the properties and connectivity of neuronal networks at all levels; however, researchers with suitable skills are becoming scarce. All RAs will gain in experience of working as a group, research organisation, data analysis and presenting their results orally and by writing papers. The computational RA will gain experience working and communicating with biologists, while the physiologists will gain closer insight into the use of computer models and communicating with mathematicians, increasing the effectiveness of the systems biology approach.

Since our research is at a fundamental level we would expect that the true impact of our research outputs on understanding of adult animals will be slow and act cumulatively over a period of many years, as our findings encourage targeted studies into equivalent processes in progressively more complex systems. The impacts of researcher training will be more immediate, contributing to a skill base relevant to all sectors.

Lastly, the tadpole research on which this project is based is recognised internationally but is carried out almost entirely in, and identified with, the UK. The two UK labs with the necessary expertise, Bristol and St Andrews, will collaborate on this project. The contribution that the success of research output from this model system makes to international neuroscience raises the profile of UK research in this area.

Publications

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Borisyuk R (2016) Forecasting the 2005 General Election: A Neural Network Approach in The British Journal of Politics and International Relations

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Burylko O (2018) Winner-take-all in a phase oscillator system with adaptation. in Scientific reports

 
Description 1. A new population level model of tadpole sensory signal integration and locomotor behaviour mimics a detailed and biologically plausible chain of information processing from external signals to sensors of four sensory pathways, integration and decision-making, action selection and execution and finally, generation of appropriate motor activity and behaviour. We show how the model produces appropriate behaviours in response to a selected scenario, which consists of a sequence of "environmental" signals.
2. We adapted a computational model of the development of neurons in the Xenopus tadpole spinal cord to include interactions between axons. We demonstrate that even relatively weak attraction causes bundles to appear, while if axons weakly repulse each other their trajectories diverge such that they fill the available space. We show how fasciculation can help to ensure axons grow in the correct location for proper network formation when normal growth barriers contain gaps, and use a functional spiking model to show that fasciculation allows the network to generate reliable swimming behaviour even when overall synapse counts are artificially lowered. Although we study fasciculation in one particular organism, our approach to modelling axon growth is general and can be widely applied to study other nervous systems.
Exploitation Route 1) Our modelling of tadpole's initiation of locomotion provide some theoretical insights on mechanisms and principles of locomotion control. We apply these theoretical ideas to models of the basal ganglia for action selection in healthy and Parkinsonian cases where both experimental and theoretical studies strongly support a concept of oscillatory neural activity. These computational studies aim to reveal the neuronal mechanisms of movement and action selection both in the healthy brain, to try to understand how these mechanisms go wrong in disease. Our modelling of oscillatory dynamics shows that partial synchronisation is a powerful theoretical approach and can be used for formulation of new theories on brain functioning.
2) Our study of neuronal mechanism of decision making by tadpole leads to some new theoretical ideas and principles of cognitive information processing. We use mathematical theory of bifurcations to proof that with appropriate parameter values the new oscillatory model demonstrates winner-take-all behaviour. By computer simulations, we show that the model can reproduce reaction times in visual search experiments of various complexities.
Sectors Healthcare,Other

 
Title Improved developmental approach 
Description We improved our existing model of neuron development in the tadpole spinal cord. The new model allows all neurons to grow in parallel, and can include the effects of axon-axon interactions. This allows the model to produce results which more accurately reflect biology. 
Type Of Material Computer model/algorithm 
Provided To Others? No  
Impact A paper describing this work is in preparation. In future we anticipate that there will be a huge impact for this kind of modelling, as it allows us to produce virtual organisms on which experiments can be performed without the use of real animals. 
 
Description Collaborations to study swimming and struggling of Xenopus tadpoles 
Organisation Swiss Federal Institute of Technology in Lausanne (EPFL)
Country Switzerland 
Sector Public 
PI Contribution This BBSRC Project is a collaboration between the University of Exeter and University of St Andrews (Roman Borisyuk have moved to the University of Exeter). Thus, there are two collaborators in Exeter - Dr Joel Tabak and Prof Roman Borisyuk. Our neurobiological collaborator is Dr Wenchang Li, University of St Andrews. Also, Prof Alan Roberts and Dr Steve Soffe (University of Bristol) provide consultancy for the current project. Our role in Exeter involves computational modelling of the tadpole nervous system. We hope that our new results will lead to new insights into the structure and function of this system and, in particular, on switching between swimming and struggling. From 2022 we establish a new collaboration with the lab of Prof Auke Ijspeert ( https://people.epfl.ch/auke.ijspeert), EPFL. This collaboration was supported by BBSRC grant: Life and Physical Sciences interface: Whole animal mathematical and computational modelling of motion.
Collaborator Contribution Our partners in University of St Andrews provide experimental neurobiological data that we can use to refine our computational models. They also participate directly in our modelling and adjustment of the model, and provide the questions that need to be answered using modelling. Recently our collaborators from the University of St Andrews recorded new spiking and Ventral Root (VR) activities of identified neurons participated in struggling. This data provide a new opportunity for computational and mathematical modelling to deeper understand swimming and struggling behaviour and transitions between them. To deeper understand the mechanism of transition we use the bio-mechanical virtual tadpole (VT) model. This modelling presents a first attempt to build a detailed biologically realistic 3-dimensional model of a whole animal's body and show how its locomotor behaviour is controlled by neuronal networks. The VT model reconstructs detailed physical and anatomical measurements of the shapes and mass distribution of organs like the notochord, muscles and belly in real tadpoles. We place the reconstructed virtual body in "water" and feed patterns of motoneuron spiking from the neuronal model to the muscle segments of the VT model to drive "virtual" swimming and struggling movements. Videos demonstrate that VT model simulations produce realistic swimming and struggling behaviour as well as transitions between them. Thus, combining neuronal and biomechanical modelling we can produce movements in the 3D water pool. Experimental recordings in an immobilised tadpole sculpt the CNS model and provide questions and hypotheses for simulations. CNS model outputs will are used to activate muscles in the VT model and generate movements. The output of the VT model provides the feedback to experiments and the CNS model. Thus, we suggest a new approach to experimental and theoretical studies of movement, where multiple computational experiments with CNS and VT models can produce new insights on how a nervous system generates appropriate movement in response to input signals from different sensory modalities. Collaborators from EPFL are leading experts in bio-mechanical modelling and robotics and this new collaboration will help us to exchange experiences, methods and discuss new modelling and future collaboration.
Impact Multi-disciplinary: Neurobiology, Computing and Mathematics, Computational Neuroscience, Bio-mechanical modelling. Most of the papers and other publications listed in this submission are a result of this collaboration between Exeter and St Andrews. This collaboration with St Andrews (and previously with Bristol) resulted in 3 BBSRC grants to study the nervous system of the young Xenopus tadpole.
Start Year 2022
 
Description Collaborations to study swimming and struggling of Xenopus tadpoles 
Organisation University of St Andrews
Country United Kingdom 
Sector Academic/University 
PI Contribution This BBSRC Project is a collaboration between the University of Exeter and University of St Andrews (Roman Borisyuk have moved to the University of Exeter). Thus, there are two collaborators in Exeter - Dr Joel Tabak and Prof Roman Borisyuk. Our neurobiological collaborator is Dr Wenchang Li, University of St Andrews. Also, Prof Alan Roberts and Dr Steve Soffe (University of Bristol) provide consultancy for the current project. Our role in Exeter involves computational modelling of the tadpole nervous system. We hope that our new results will lead to new insights into the structure and function of this system and, in particular, on switching between swimming and struggling. From 2022 we establish a new collaboration with the lab of Prof Auke Ijspeert ( https://people.epfl.ch/auke.ijspeert), EPFL. This collaboration was supported by BBSRC grant: Life and Physical Sciences interface: Whole animal mathematical and computational modelling of motion.
Collaborator Contribution Our partners in University of St Andrews provide experimental neurobiological data that we can use to refine our computational models. They also participate directly in our modelling and adjustment of the model, and provide the questions that need to be answered using modelling. Recently our collaborators from the University of St Andrews recorded new spiking and Ventral Root (VR) activities of identified neurons participated in struggling. This data provide a new opportunity for computational and mathematical modelling to deeper understand swimming and struggling behaviour and transitions between them. To deeper understand the mechanism of transition we use the bio-mechanical virtual tadpole (VT) model. This modelling presents a first attempt to build a detailed biologically realistic 3-dimensional model of a whole animal's body and show how its locomotor behaviour is controlled by neuronal networks. The VT model reconstructs detailed physical and anatomical measurements of the shapes and mass distribution of organs like the notochord, muscles and belly in real tadpoles. We place the reconstructed virtual body in "water" and feed patterns of motoneuron spiking from the neuronal model to the muscle segments of the VT model to drive "virtual" swimming and struggling movements. Videos demonstrate that VT model simulations produce realistic swimming and struggling behaviour as well as transitions between them. Thus, combining neuronal and biomechanical modelling we can produce movements in the 3D water pool. Experimental recordings in an immobilised tadpole sculpt the CNS model and provide questions and hypotheses for simulations. CNS model outputs will are used to activate muscles in the VT model and generate movements. The output of the VT model provides the feedback to experiments and the CNS model. Thus, we suggest a new approach to experimental and theoretical studies of movement, where multiple computational experiments with CNS and VT models can produce new insights on how a nervous system generates appropriate movement in response to input signals from different sensory modalities. Collaborators from EPFL are leading experts in bio-mechanical modelling and robotics and this new collaboration will help us to exchange experiences, methods and discuss new modelling and future collaboration.
Impact Multi-disciplinary: Neurobiology, Computing and Mathematics, Computational Neuroscience, Bio-mechanical modelling. Most of the papers and other publications listed in this submission are a result of this collaboration between Exeter and St Andrews. This collaboration with St Andrews (and previously with Bristol) resulted in 3 BBSRC grants to study the nervous system of the young Xenopus tadpole.
Start Year 2022
 
Title Fireflies: Software for interactively exploring dynamical systems using GPU computing 
Description Fireflies exploits the power of graphical processing unit (GPU) computing to produce spectacular interactive visualizations of arbitrary systems of ordinary differential equations. In contrast to typical phase portraits, Fireflies draws the current position of trajectories (projected onto 2D or 3D space) as single points of light, which move as the system is simulated. Due to the massively parallel nature of GPU hardware, Fireflies is able to simulate millions of trajectories in parallel (even on standard desktop computer hardware), producing "swarms" of particles that move around the screen in real-time according to the equations of the system. 
Type Of Technology Software 
Year Produced 2015 
Open Source License? Yes  
Impact Visualisations produced by this software have been used as part of our undergraduate teaching. 
URL https://bitbucket.org/rmerrison/fireflies
 
Title Simulation of Neural Activity Patterns with Python (SNAPPy) 
Description This software was developed by us for simulation of the tadpole spinal cord. However, the software was designed to be very flexible and allow modelling of other neuronal circuits beyond the tadpole. 
Type Of Technology Software 
Year Produced 2014 
Open Source License? Yes  
Impact The software has been used (by Dr Merrison-Hort) to develop a model of the mammalian basal ganglia as part of his PhD work (not based on any funding body award). The results obtained from this model were published in Frontiers in Computational Neuroscience. 
 
Description BBC News on line publication about new BBSRC grant 
Form Of Engagement Activity A magazine, newsletter or online publication
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Media (as a channel to the public)
Results and Impact BBC news England: Tadpole brains studied to help understand Parkinson's


http://www.bbc.co.uk/news/uk-england-25076279

Public engagement
I was interviewed by local media
Year(s) Of Engagement Activity 2013
 
Description PyPlym 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Industry/Business
Results and Impact The postdoctoral fellow on this grant presented our work at a local "PyPlym" event, about the use of the Python programming language. The audience ranged from those just learning to program to professional developers from industry. As well as technical details on how our research uses Python, the talk included a brief overview of computational neuroscience.
Year(s) Of Engagement Activity 2016
URL https://www.meetup.com/PyPlym/
 
Description School Visit (Clyst Vale) 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Schools
Results and Impact Approximately 15 sixth form students (members of the college's "Science Club") attended my talk about our work modelling the tadpole nervous system. The talk described the basics of neuroscience and computational modelling, and (according to their teacher) fit in very well with the subjects they were currently learning about in lessons. The students engaged well with the talk, and my subsequent demo of an interactive virtual reality "tour" of the tadpole spinal cord.
Year(s) Of Engagement Activity 2016
 
Description Talk about computational modelling of the tadpole at SciBar event 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Public/other audiences
Results and Impact Dr Merrison-Hort gave a talk to the general public at the Plymouth "SciBar" event. The talk sparked a long discussion amongst the audience about the possibilities of computational neuroscience, and about neuroscience in general.

Not aware of any.
Year(s) Of Engagement Activity 2014
 
Description Virtual reality tadpole demonstrations 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Public/other audiences
Results and Impact In collaboration with the university's Interactive Systems Studio we have developed a virtual reality tour of the tadpole nervous system that teaches users the basics of neuroscience and how this simple animal behaves. We have demonstrated this system at numerous events, from international scientific conferences (e.g INCF World Congress in Neuroinformatics 2016) to local science events for the general public (e.g. Plymouth University Robotics Open Evening). Many people, of all ages, have tried out the system and learnt something about our research and neuroscience in general.
Year(s) Of Engagement Activity 2015,2016