Dynamic network reconfiguration at the transition between motor programs
Lead Research Organisation:
UNIVERSITY OF EXETER
Department Name: Mathematics
Abstract
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Technical Summary
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.
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.
Planned Impact
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.
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.
People |
ORCID iD |
Roman Borisyuk (Principal Investigator) |
Publications
Yousif N
(2020)
A Population Model of Deep Brain Stimulation in Movement Disorders From Circuits to Cells
in Frontiers in Human Neuroscience
Conte D
(2021)
A simple method defines 3D morphology and axon projections of filled neurons in a small CNS volume: Steps toward understanding functional network circuitry.
in Journal of neuroscience methods
Ferrario A
(2021)
From decision to action: Detailed modelling of frog tadpoles reveals neuronal mechanisms of decision-making and reproduces unpredictable swimming movements in response to sensory signals.
in PLoS computational biology
Borisyuk R
(2023)
From phase advance to phase delay: Flexible coordination between neuronal rhythms by the duration of synaptic input
in Physical Review Research
Ferrario A
(2023)
Mechanisms Underlying the Recruitment of Inhibitory Interneurons in Fictive Swimming in Developing Xenopus laevis Tadpoles.
in The Journal of neuroscience : the official journal of the Society for Neuroscience
Varga M
(2020)
Tadpole VR: virtual reality visualization of a simulated tadpole spinal cord
in Virtual Reality
Roberts A
(2019)
The decision to move: response times, neuronal circuits and sensory memory in a simple vertebrate.
in Proceedings. Biological sciences
Description | 1. Our recent publication "From decision to action: Detailed modelling of frog tadpoles reveals neuronal mechanisms of decision-making and reproduces unpredictable swimming movements in response to sensory signals", PLOS Computational Biology 2021 states: Animals constantly receive sensory signals, make decisions and generate behaviours. We see a red light at a pedestrian crossing, stop, and only walk across at a green light. Two systems control this behaviour: the nervous system processes sensory signals and commands the musculoskeletal system to generate motor responses. Most nervous and musculoskeletal systems are too complex to be able to understand even simple behaviours step by step. To simplify the problem, we study responses to touch in young frog tadpoles. Here, detailed information is available on 12 types of brain and spinal cord neurons controlling swimming. To explore how these neurons work, we create two biologically realistic computational models: a CNS model of the nervous system with approximately 2300 neurons generates motor nerve activity and is fed to a virtual tadpole biomechanical model of the whole-body musculoskeletal system to produce movements. Our results suggest that we understand the essence of how simple behaviour is generated. We propose that a simple sensory memory process in the brain, which extends the brief sensory nerve activity, forms the basis for a decision process. This also generates unpredictability in behaviour. 2. Developing spinal circuits generate patterned motor outputs while many neurons with high membrane resistances are still maturing. In the spinal cord of hatchling frog tadpoles we found that the firing reliability in swimming of inhibitory interneurons with commissural and ipsilateral ascending axons was negatively correlated with their cellular membrane resistance. For better understanding the experimental findings, we incorporated the electrical and synaptic properties into a computer swimming model. We found that the model produced robust swimming rhythms, whereas randomizing input synaptic strengths led to the breakdown of swimming rhythms, coupled with less synchronized spiking in the inhibitory interneurons. We conclude that the recruitment of these developing interneurons in swimming can be predicted by cellular input resistances, but the order is opposite to the motor-strength-based recruitment scheme depicted by Henneman's size principle. This form of recruitment/integration order in development before the emergence of refined motor control is progressive potentially with neuronal acquisition of mature electrical and synaptic properties, among which the scaling of input synaptic strengths with cellular input resistance plays a critical role. Journal of Neuroscience 22 February 2023, 43 (8) 1387-1404; DOI: https://doi.org/10.1523/JNEUROSCI.0520-22.2022 |
Exploitation Route | 1. This finding shows importance of the whole body modelling. Currently, this type of modelling is rather rare and our paper is among the first in this direction. 2. This finding suggest a new principle of recruiting neurons in developing neuronal circuits. In addition, this finding demonstrates that combining experiments with detailed computational modelling is crucial for understanding biological principles and mechanism. |
Sectors | Digital/Communication/Information Technologies (including Software),Education,Healthcare,Other |
Description | Life and Physical Sciences interface: Whole animal mathematical and computational modelling of motion |
Amount | £23,690 (GBP) |
Funding ID | BB/X005038/1 |
Organisation | Biotechnology and Biological Sciences Research Council (BBSRC) |
Sector | Public |
Country | United Kingdom |
Start | 03/2023 |
End | 08/2024 |
Title | A simple method defines 3D morphology and axon projections of filled neurons in a small CNS volume |
Description | A simple method defines 3D morphology and axon projections of filled neurons in a small CNS volume: Steps toward understanding functional network circuitry, |
Type Of Material | Improvements to research infrastructure |
Year Produced | 2020 |
Provided To Others? | Yes |
Impact | Background: Fundamental to understanding neuronal network function is defining neuron morphology, location, properties, and synaptic connectivity in the nervous system. A significant challenge is to reconstruct individual neuron morphology and connections at a whole CNS scale and bring together functional and anatomical data to understand the whole network. New method: We used a PC controlled micropositioner to hold a fixed whole mount of Xenopus tadpole CNS and replace the stage on a standard microscope. This allowed direct recording in 3D coordinates of features and axon projections of one or two neurons dye-filled during whole-cell recording to study synaptic connections. Neuron reconstructions were normalised relative to the ventral longitudinal axis of the nervous system. Coordinate data were stored as simple text files. Results: Reconstructions were at 1 µm resolution, capturing axon lengths in mm. The output files were converted to SWC format and visualised in 3D reconstruction software NeuRomantic. Coordinate data are tractable, allowing correction for histological artefacts. Through normalisation across multiple specimens we could infer features of network connectivity of mapped neurons of different types. Paper: Conte D, Borisyuk R, Hull M, Roberts A. (2020) A simple method defines 3D morphology and axon projections of filled neurons in a small CNS volume: Steps toward understanding functional network circuitry, J Neurosci Methods, volume 351, DOI:10.1016/j.jneumeth.2020.109062. |
Title | Codes for neuronal and VT models are described in "From decision to action: Detailed modelling of frog tadpoles reveals neuronal mechanisms of decision-making and reproduces unpredictable swimming movements in response to sensory signals". PLOS Computational Biology, 2021, https://doi.org/10.1371/journal.pcbi.1009654 |
Description | The code of the neuronal (CNS) model is available from ModelDB repository at http://modeldb.yale.edu/267146. The code for the biomechanical Virtual Tadpole (VT) model is available at https://github.com/a-palyanov/sibernetic-vt. |
Type Of Material | Model of mechanisms or symptoms - non-mammalian in vivo |
Year Produced | 2021 |
Provided To Others? | Yes |
Impact | These tools allow the modelling of whole body by combining neuronal and musculoskeletal systems. |
URL | http://modeldb.yale.edu/267146 |
Title | A new model to define the complete connectome of directed connections between neurons of different types. |
Description | To find connections to and from different cell types we use a previously developed probabilistic approach (Ferrario et al., 2018, eLife), where the directed connection from neuron i to neuron j was represented by the Bernoulli variable. We constructed connection probabilities by generating 1000 connectomes using the developmental approach (Roberts et al., 2014, J of Neuroscience) and averaging across connectomes. We used these probabilities to infer the connectivity between populations where there is limited experimental data by hypothesizing anatomical and functional similarities. Using these similarities, we extrapolated from the known connection probabilities in our developmental model and defined connection probabilities pairs of neuronal types with unknown connections. In many cases some anatomical characteristics like the Rostro-Caudal positions of neurons are known. We use this information and define the conditional probability of connection given the distance between neurons. |
Type Of Material | Computer model/algorithm |
Year Produced | 2021 |
Provided To Others? | Yes |
Impact | There are several predictions which follow from our model simulations. For example, connection probabilities and their distributions are predictions for experimental testing. Anatomical measurements of neuronal characteristics and multiple pair-wise recordings can be used to clarify the distribution of connection probabilities. However, currently available measurements and pairwise recordings between sensory pathways and CPG neuronal populations are limited to verify connection probabilities. |
URL | https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1009654 |
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 |
Description | CNS conference |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | 29th Annual Computational Neuroscience Meeting: CNS*2020, from July 18 to July 22, 2020 |
Year(s) Of Engagement Activity | 2020 |
URL | https://www.cnsorg.org/cns-2020 |
Description | Presentation for conference "Linking Mathematics, Experiments and Data" |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Postgraduate students |
Results and Impact | Post-doctoral researcher Saeed Farjami presented a poster "Transitions between Swimming and Struggling: Modelling of nervous and musculoskeletal systems in Xenopus tadpoles". This presentation was accompanied by video showing realistic movements in water of the Virtual Tadpole during struggling (restrained by forceps) and transition to swimming. The poster and video sparkled many questions and discussion with conference attendees. |
Year(s) Of Engagement Activity | 2023 |
Description | Prestigious conference in Moscow |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Invited presentation for a prestigious Moscow workshop at Skoltech (Russian analogue of silicon value) https://www.skoltech.ru/en/2019/11/theoretical-physics-and-mathematics-of-the-brain-bridges-across-disciplines-and-applications/ 5 December 2019 Room E-B4-3006, Skolkovo Institute of Science and Technology Roman Borisyuk, Structural and functional properties of a nervous system: Modelling tadpole locomotor behaviour in response to sensory signals |
Year(s) Of Engagement Activity | 2019 |
URL | https://www.skoltech.ru/en/2019/11/theoretical-physics-and-mathematics-of-the-brain-bridges-across-d... |