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Sunday, July 19 • 9:00pm - 10:00pm
P68: Large-scale calcium imaging of spontaneous activity in larval zebrafish reveals signatures of criticality

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Michael McCullough, Robert Wong, Zac Pujic, Biao Sun, Geoffrey J. Goodhill
Neural networks in the brain may self-organise such that they operate near criticality, that is, poised on the boundary between phases of order and disorder [1]. Models of neural networks tuned close to criticality are optimal in terms of dynamic range, information transmission, information storage and computational adaptability [2]. Most experimental evidence for criticality in the brain has come from studies of high resolution neural spiking data recorded from tissue cultures or anaesthetised animals using microelectrode arrays, or from studies of mesoscopic-scale neural activity using magnetic resonance imaging or electroencephalograms. These approaches are inherently limited either by under-sampling of the neural population or by coarse spatial resolution. This can be problematic for empirical studies of criticality because the characteristic dynamics of interest are theoretically scale-free. Recently, Ponce-Alvarez et al. [3] investigated the larval zebrafish as a new model for neural criticality by utilising the unique properties of the organism that enable whole-brain imaging of neural activity in vivo and without anaesthetic. They identified hallmarks of neural criticality in larval zebrafish using 1-photon calcium imaging and voxel-based analysis of neuronal avalanches. Here we addressed two key limitations of their study by instead using 2-photon calcium imaging to observe truly spontaneous activity, and by extracting neural activity time series at single-cell resolution via state-of- the-art image segmentation [4]. Our data comprise fluorescence time series for large populations of neurons from 3-dimensional volumetric recordings of spontaneous activity in the optic tectum and cerebellum of larval zebrafish with pan-neuronal expression of GCaMP6s (n=5; approx. 10000 neurons per fish) (Fig. 1A). Neuronal avalanche statistics revealed power-law relationships and scale-invariant avalanche shape collapse which are consistent with crackling noise dynamics from a 3-dimensional random field Ising model [5] (Fig. 1B-C). Observed power laws were validated using shuffled surrogate data and log- likelihood ratio tests. This result provides the first evidence of criticality in the brain from large-scale in vivo neural activity at single cell resolution. Our findings demonstrate the potential of larval zebrafish as a model for the investigation of critical phenomena in the context of neurodevelopmental disorders that may perturb the brain away from criticality. 1\. Cocchi L, Gollo L L, Zalesky A, Breakspear M. Criticality in the brain: A synthesis of neurobiology, models and cognition. Prog Neurobiol. 2017, 158, 132–152. 2\. Shew W L, Plenz D. The functional benefits of criticality in the cortex. Neuroscientist. 2013, 19(1), 88–100. 3\. Ponce-Alvarez A, Jouary A, Privat M, et al. Whole-brain neuronal activity displays crackling noise dynamics. Neuron. 2018, 100(6), 1446–1459. 4\. Giovannucci A, Friedrich J, Gunn P, et al. CaImAn an open source tool for scalable calcium imaging data analysis. Elife. 2019, 8, e38173. 5\. Sethna J P, Dahmen K A, Myers C R. Crackling noise. Nature. 2001, 410(6825), 242-250.


Michael McCullough

Queensland Brian Institute, University of Queensland

Sunday July 19, 2020 9:00pm - 10:00pm CEST
Slot 04