王晓鸥;赵诗彤;纪鹏;穆宇;

• 1:中国科学院脑科学与智能技术卓越创新中心
• 2:复旦大学类脑智能科学与技术研究院

摘要(Abstract)：

对全脑尺度的神经功能数据进行分析，并结合全脑计算模拟探索感觉运动转导等神经机制，是神经科学的重要方向之一。斑马鱼幼鱼的全脑功能成像为探索全脑的信息编码、处理并输出提供了完整的数据支撑。本文回顾了近期国内外基于斑马鱼功能成像的数据分析及全脑模拟的重要进展。其中，基于统计学的分析方法为解析数据背后的脑活动机制提供了切入点，迅速发展的人工神经网络等辅助实现了全脑模拟计算并解析出集体动力学现象，进而在全脑尺度上阐释了重要群体神经活动产生原理。

关键词(KeyWords)： 计算神经科学;钙荧光成像;功能成像;全脑计算

Abstract:

Keywords:

基金项目(Foundation): 科技创新2030——“脑科学与类脑研究”重大项目（2021ZD0204500）

作者(Authors): 王晓鸥;赵诗彤;纪鹏;穆宇;

参考文献(References)：

• [1]AHRENS M B,ORGER M B,ROBSON D N,et al.Whole-brain functional imaging at cellular resolution using light-sheet microscopy[J].Nature Methods,2013,10(5):413-420.
• [2]DUNN T W,MU Y,NARAYAN S,et al.Brain-wide mapping of neural activity controlling zebrafsh exploratory locomotion[J].Elife,2016,5:e12741.
• [3]AUER T O,DUROURE K,DE CIAN A,et al.Highly efficient CRISPR/Cas9-mediated knock-in in zebrafish by homologyindependent DNA repair[J].Genome Research,2014,24(1):142-153.
• [4]VLADIMIROV N,MU Y,KAWASHIMA T,et al.Light-sheet functional imaging in fictively behaving zebrafish[J].Nature Methods,2014,11(9):883-884.
• [5]ORGER M B,POLAVIEJA G G de.Zebrafsh behavior:opportunities and challenges[J].Annual Review of Neuroscience,2017,40:125-147.
• [6]DUNN T W,MU Y,NARAYAN S,et al.Brain-wide mapping of neural activity controlling zebrafsh exploratory locomotion[J].Elife,2016,5:e12741.
• [7]NAUMANN E A,FITZGERALD J E,DUNN T W,et al.From whole-brain data to functional circuit models:the zebrafish optomotor response[J].Cell,2016,167(4):947-960.
• [8]BAHL A,ENGERT F.Neural circuits for evidence accumulation and decision making in larval zebrafish[J].Nature Neuroscience,2020,23(1):94-102.
• [9]MARQUES J C,LI M,SCHAAK D,et al.Internal state dynamics shape brainwide activity and foraging behaviour[J].Nature,2020,577(7789):239-243.
• [10]FISHER D,OLASAGASTI I,TANK D W,et al.A modeling framework for deriving the structural and functional architecture of a short-term memory microcircuit[J].Neuron,2013,79(5):987-1000.
• [11]CHICCHI L,CECCHINI G,ADAM I,et al.Reconstruction scheme for excitatory and inhibitory dynamics with quenched disorder:application to zebrafsh imaging[J].Journal of Computational Neuroscience,2021,49(2):159-174.
• [12]BURROWS D,DIANA G,PIMPEL B,et al.Single-cell Networks Reorganise to Facilitate Whole-brain Supercritical Dynamics During Epileptic Seizures[EB/OL].(2021-10-16)[2022-12-01].https://www.biorxiv.org/content/10.1101/2021.10.14.464473v1.
• [13]ABBAS F,TRIPLETT M A,GOODHILL G J,et al.A three-layer network model of direction selective circuits in the optic tectum[J].Frontiers in Neural Circuits,2017,11:88.
• [14]TRIPLETT M A,AVITAN L,GOODHILL G J.Emergence of spontaneous assembly activity in developing neural networks without afferent input[J].PLo S Computational Biology,2018,14(9):e1006421.
• [15]KARPENKO S,WOLF S,LAFAYE J,et al.From behavior to circuit modeling of light-seeking navigation in zebrafsh larvae[J].Elife,2020,9:e52882.
• [16]TAO L,LAUDERDALE J D,SORNBORGER A T.Mapping functional connectivity between neuronal ensembles with larval zebrafsh transgenic for a ratiometric calcium indicator[J].Frontiers in Neural Circuits,2011,5:2.
• [17]PNEVMATIKAKIS E A,SOUDRY D,GAO Y,et al.Simultaneous denoising,deconvolution,and demixing of calcium imaging data[J].Neuron,2016,89(2):285-299.
• [18]WANG H,YANG Z,LI X,et al.Single-cell in vivo imaging of cellular circadian oscillators in zebrafsh[J].PLo S Biology,2020,18(3):e3000435.
• [19]ROBSON D N,LI J M.A dynamical systems view of neuroethology:Uncovering stateful computation in natural behaviors[J].Current Opinion in Neurobiology,2022,73:102517.
• [20]RAO R P.Decision making under uncertainty:a neural model based on partially observable markov decision processes[J].Frontiers in Computational Neuroscience,2010,4:146.
• [21]BELLMAN R.A Markovian decision process[J].Journal of Mathematics and Mechanics,1957:679-684.
• [22]MARQUART G D,TABOR K M,HORSTICK E J,et al.High-precision registration between zebrafish brain atlases using symmetric diffeomorphic normalization[J].Giga Science,2017,6(8):gix056.
• [23]NAUMANN E A,FITZGERALD J E,DUNN T W,et al.From whole-brain data to functional circuit models:the zebrafsh optomotor response[J].Cell,2016,167(4):947-960.
• [24]FISHER D,OLASAGASTI I,TANK D W,et al.A modeling framework for deriving the structural and functional architecture of a short-term memory microcircuit[J].Neuron,2013,79(5):987-1000.
• [25]FOX M D,SNYDER A Z,VINCENT J L,et al.The human brain is intrinsically organized into dynamic,anticorrelated functional networks[J].Proceedings of the National Academy of Sciences,2005,102(27):9673-9678.
• [26]LISBERGER S G.Visual guidance of smooth-pursuit eye movements:sensation,action,and what happens in between[J].Neuron,2010,66(4):477-491.
• [27]FINK A J,CROCE K R,HUANG Z J,et al.Presynaptic inhibition of spinal sensory feedback ensures smooth movement[J].Nature,2014,509(7498):43-48.
• [28]GAO P,GANGULI S.On simplicity and complexity in the brave new world of large-scale neuroscience[J].Current Opinion in Neurobiology,2015,32:148-155.
• [29]O’LEARY T,SUTTON A C,MARDER E.Computational models in the age of large datasets[J].Current Opinion in Neurobiology,2015,32:87-94.
• [30]WONG K F,WANG X J.A recurrent network mechanism of time integration in perceptual decisions[J].Journal of Neuroscience,2006,26(4):1314-1328.
• [31]LIN X,ZOU X,JI Z,et al.A brain-inspired computational model for spatio-temporal information processing[J].Neural Networks,2021,143:74-87.
• [32]ERLHAGEN W,SCH?NER G.Dynamic feld theory of movement preparation.[J].Psychological Review,2002,109(3):545.
• [33]INAGAKI H K,FONTOLAN L,ROMANI S,et al.Discrete attractor dynamics underlies persistent activity in the frontal cortex[J].Nature,2019,566(7743):212-217.
• [34]CHURCHLAND M M,CUNNINGHAM J P,KAUFMAN M T,et al.Neural population dynamics during reaching[J].Nature,2012,487(7405):51-56.
• [35]TINBERGEN N.The study of instinct[M].Pygmalion Press,an imprint of Plunkett Lake Press,2020.
• [36]TINBERGEN N.The hierarchical organization of nervous mechanisms underlying instinctive behaviour[M]//Symposia of the Society for Experimental Biology.SAGE Publications Ltd,,1950:305-312.
• [37]CHICCHI L,CECCHINI G,ADAM I,et al.Reconstruction scheme for excitatory and inhibitory dynamics with quenched disorder:application to zebrafsh imaging[J].Journal of Computational Neuroscience,2021,49(2):159-174.
• [38]SEJNOWSKI T J,TESAURO G.The Hebb rule for synaptic plasticity:algorithms and implementations[M]//Neural models of plasticity.Elsevier,1989:94-103.
• [39]YOUNG D L,POON C S.Hebbian covariance learning[J].Advances in Modeling and Control of Ventilation,1998:73-83.
• [40]LI X,WANG W,XUE F,et al.Computational modeling of spiking neural network with learning rules from STDP and intrinsic plasticity[J].Physica A:Statistical Mechanics and Its Applications,2018,491:716-728.
• [41]CHURCHLAND M M,BYRON M Y,RYU S I,et al.Neural variability in premotor cortex provides a signature of motor preparation[J].Journal of Neuroscience,2006,26(14):3697-3712.
• [42]XIE Y,HU P,LI J,et al.Geometry of sequence working memory in macaque prefrontal cortex[J].Science,2022,375(6581):632-639.
• [43]GONCCALVES P J,ARRENBERG A B,HABLITZEL B,et al.Optogenetic perturbations reveal the dynamics of an oculomotor integrator[J].Frontiers in Neural Circuits,2014,8:10.
• [44]JUNG K,KANG J,CHUNG S,et al.Dynamic causal modeling for calcium imaging:Exploration of differential effective connectivity for sensory processing in a barrel cortical column[J].Neuroimage,2019,201:116008.
• [45]KAROLY P J,KUHLMANN L,SOUDRY D,et al.Seizure pathways:A model-based investigation[J].PLo S Computational Biology,2018,14(10):e1006403.
• [46]AVITAN L,PUJIC Z,M?LTER J,et al.Spontaneous activity in the zebrafsh tectum reorganizes over development and is influenced by visual experience[J].Current Biology,2017,27(16):2407-2419.
• [47]PIETRI T,ROMANO S A,PéREZ-SCHUSTER V,et al.The emergence of the spatial structure of tectal spontaneous activity is independent of visual inputs[J].Cell Reports,2017,19(5):939-948.
• [48]BAO X,HU Q,JI P,et al.Impact of basic network motifs on the collective response to perturbations[J].Nature Communications,2022,13(1):1-8.
• [49]JI P,LIN W,KURTHS J.Asymptotic scaling describing signal propagation in complex networks[J].Nature Physics,2020,16(11):1082-1083.