A neuronal network generating flexible locomotor behaviour in a simple vertebrate: studies on function and embryonic self-assembly
A neuronal network generating flexible locomotor behaviour in a simple vertebrate: studies on function and embryonic self-assembly
批准号:
BB/G006369/1
负责人:
Roman Borisyuk
金额:
$34.8万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2009
资助国家:
英国
项目状态:
已结题
起止时间:
2009 至 --
中文摘要
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英文摘要
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.
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DOI:
10.1186/1471-2202-15-s1-p94
发表时间:
2014-07-21
期刊:
BMC Neuroscience
影响因子:
2.4
作者:
[Borisyuk R, Merrison-Hort R]
通讯作者:
Merrison-Hort R
DOI:
10.1016/j.biosystems.2017.07.004
发表时间:
2017-11
期刊:
Bio Systems
影响因子:
--
作者:
[Borisyuk R, Merrison-Hort R, Soffe SR, Koutsikou S, Li WC]
通讯作者:
Li WC
Artificial Neural Networks and Machine Learning - ICANN 2012
人工神经网络和机器学习 - ICANN 2012
DOI:
10.1007/978-3-642-33269-2_34
发表时间:
2012
期刊:
影响因子:
--
作者:
[Sporea I]
通讯作者:
Sporea I
DOI:
10.3389/fninf.2011.00020
发表时间:
2011
期刊:
Frontiers in neuroinformatics
影响因子:
3.5
作者:
[Borisyuk R, Al Azad AK, Conte D, Roberts A, Soffe SR]
通讯作者:
Soffe SR
Within-Burst Synchrony Changes for Coupled Elliptic Bursters
耦合椭圆爆发的爆发内同步变化
DOI:
10.1137/090746045
发表时间:
2010
期刊:
SIAM Journal on Applied Dynamical Systems
影响因子:
2.1
作者:
[Azad A]
通讯作者:
Azad A
共 9 条
Life and Physical Sciences interface: Whole animal mathematical and computational modelling of motion
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-
项目类别:Research Grant
-
资助金额:$3.02万
-
财政年份:2023
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负责人:Roman Borisyuk
-
依托单位:
Dynamic network reconfiguration at the transition between motor programs
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Cross-modality integration of sensory signals leading to initiation of locomotion
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负责人:Roman Borisyuk
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依托单位:
国内基金
海外基金
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