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SUMMARY:Modeling traffic jam and growth process of neurons using isogeomet
 ric analysis and physics-informed neural network - Yongjie Jessica Zhang (
 Carnegie Mellon University)
DTSTART:20230802T101500Z
DTEND:20230802T111500Z
UID:TALK202426@talks.cam.ac.uk
DESCRIPTION:The motor-driven intracellular transport plays a crucial role 
 in supporting a neuron cell&rsquo\;s survival and function\, with motor pr
 oteins and microtubule (MT) structures collaborating to promptly deliver t
 he essential materials to the right location in neuron. The disruption of 
 transport may lead to the onset of various neurodegenerative diseases. To 
 study how neurons regulate the material transport process and have a bette
 r understanding of the traffic jam formation\, we develop a PDE-constraine
 d optimization model and an isogeometric analysis (IGA) solver to simulate
  traffic jams induced by MT reduction and swirl. We also develop a novel I
 GA-based physics-informed graph neural network (PGNN) to quickly predict n
 ormal and abnormal transport phenomena in different neuron geometries. The
  IGA-based PGNN model contains simulators to handle local prediction of bo
 th normal and two MT-induced traffic jams in pipes\, as well as another si
 mulator to predict normal transport in bifurcations. B&eacute\;zier extrac
 tion is adopted to incorporate the geometry information into the simulator
 s to accurately compute the physics informed loss function with PDE residu
 als. Moreover\, a GNN assembly model is adopted to tackle different neuron
  morphologies by assembling local prediction into the entire geometry. The
  well-trained model effectively predicts the distribution of transport vel
 ocity and material concentration during traffic jam and normal transport w
 ith an average error less than 10% compared to IGA simulations.\n&nbsp\;\n
 To model neuron growth\, we develop a new computational framework and an o
 pen-source software package "NeuronGrowth_IGAcollocation&rdquo\; based on 
 the phase field method. Neurons consist of a cell body\, dendrites\, and a
 xons. Axons and dendrites are long processes extending from the cell body 
 and enabling information transfer to and from other neurons. There is high
  variation in neuron morphology based on their location and function\, thu
 s increasing the complexity in mathematical modeling of neuron growth. We 
 propose a novel phase field model with isogeometric collocation to simulat
 e different stages of neuron growth by considering the effect of tubulin. 
 The stages modeled include lamellipodia formation\, initial neurite outgro
 wth\, axon differentiation\, and dendrite formation considering the effect
  of intracellular transport of tubulin on neurite outgrowth. By incorporat
 ing neurite features from experiments\, we can demonstrate similar reprodu
 ction of neuron morphologies at different stages of growth and allow exten
 sion towards the formation of neurite networks. Based on the IGA simulatio
 n data\, a CNN model is also built to efficiently predict the growth proce
 ss.\n&nbsp\;\nREFERENCES\n\nLi\, Y. J. Zhang.&nbsp\;Isogeometric Analysis-
 Based Physics-Informed Graph Neural Network for Studying Traffic Jam in Ne
 urons.&nbsp\;Computer Methods in Applied Mechanics and Engineering\, 403:1
 15757\, 2023.\nLi\, Y. J. Zhang.&nbsp\;Modeling Intracellular Transport an
 d Traffic Jam in 3D Neurons Using PDE-Constrained Optimization.&nbsp\; Jou
 rnal of Mechanics\, 38:44-59\, 2022.\nLi\, Y. J. Zhang.&nbsp\;Modeling Mat
 erial Transport Regulation and Traffic Jam in Neurons Using PDE-Constraine
 d Optimization.&nbsp\;Scientific Reports\, 12:3902\, 2022.\nQian\, A. Pawa
 r\, A. Liao\, C. Anitescu\, V. Webster-Wood\, A. Feinberg\, T. Rabczuk\, Y
 . J. Zhang.&nbsp\;Modeling Neuron Growth Using Isogeometric Collocation Ba
 sed Phase Field Method.&nbsp\;Scientific Reports\, 12:8120\, 2022.\nQian\,
  A. S. Liao\, S. Gu\, V. Webster-Wood\, Y. J. Zhang. Biomimetic IGA neuron
  growth modeling with neurite morphometric features and CNN-based predicti
 on. Computer Methods in Applied Mechanics and Engineering\, 2023.\n
LOCATION:Seminar Room 1\, Newton Institute
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