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通过模式化光遗传学刺激实现从计算机模拟神经网络到生物神经网络的神经假体实时通信。

Toward neuroprosthetic real-time communication from in silico to biological neuronal network via patterned optogenetic stimulation.

作者信息

Mosbacher Yossi, Khoyratee Farad, Goldin Miri, Kanner Sivan, Malakai Yenehaetra, Silva Moises, Grassia Filippo, Simon Yoav Ben, Cortes Jesus, Barzilai Ari, Levi Timothée, Bonifazi Paolo

机构信息

Department of Particle Physics and Astrophysics, Weizmann Institute of Science, Rehovot, Israel.

School of Physics and Astronomy, Tel Aviv University, Tel Aviv, 69978, Israel.

出版信息

Sci Rep. 2020 May 5;10(1):7512. doi: 10.1038/s41598-020-63934-4.

Abstract

Restoration of the communication between brain circuitry is a crucial step in the recovery of brain damage induced by traumatic injuries or neurological insults. In this work we present a study of real-time unidirectional communication between a spiking neuronal network (SNN) implemented on digital platform and an in-vitro biological neuronal network (BNN), generating similar spontaneous patterns of activity both spatial and temporal. The communication between the networks was established using patterned optogenetic stimulation via a modified digital light projector (DLP) receiving real-time input dictated by the spiking neurons' state. Each stimulation consisted of a binary image composed of 8 × 8 squares, representing the state of 64 excitatory neurons. The spontaneous and evoked activity of the biological neuronal network was recorded using a multi-electrode array in conjunction with calcium imaging. The image was projected in a sub-portion of the cultured network covered by a subset of the all electrodes. The unidirectional information transmission (SNN to BNN) is estimated using the similarity matrix of the input stimuli and output firing. Information transmission was studied in relation to the distribution of stimulus frequency and stimulus intensity, both regulated by the spontaneous dynamics of the SNN, and to the entrainment of the biological networks. We demonstrate that high information transfer from SNN to BNN is possible and identify a set of conditions under which such transfer can occur, namely when the spiking network synchronizations drive the biological synchronizations (entrainment) and in a linear regime response to the stimuli. This research provides further evidence of possible application of miniaturized SNN in future neuro-prosthetic devices for local replacement of injured micro-circuitries capable to communicate within larger brain networks.

摘要

恢复脑回路之间的通信是创伤性损伤或神经损伤所致脑损伤恢复过程中的关键一步。在这项工作中,我们展示了一项关于在数字平台上实现的脉冲神经元网络(SNN)与体外生物神经元网络(BNN)之间实时单向通信的研究,这两个网络在空间和时间上产生相似的自发活动模式。通过使用经修改的数字光投影仪(DLP)进行图案化光遗传学刺激来建立网络之间的通信,该投影仪接收由脉冲神经元状态决定的实时输入。每次刺激由一个由8×8个方块组成的二值图像组成,代表64个兴奋性神经元的状态。使用多电极阵列结合钙成像记录生物神经元网络的自发活动和诱发活动。图像投射到由所有电极的一个子集覆盖的培养网络的一个子区域中。使用输入刺激和输出放电的相似性矩阵估计单向信息传输(从SNN到BNN)。研究了信息传输与刺激频率和刺激强度的分布之间的关系,这两者均由SNN的自发动力学调节,还研究了与生物网络的同步情况。我们证明了从SNN到BNN的高信息传递是可能的,并确定了一组能够发生这种传递的条件,即当脉冲网络同步驱动生物同步(同步化)且处于对刺激的线性响应状态时。这项研究为小型化SNN在未来神经假体装置中的可能应用提供了进一步证据,这些装置可用于局部替代能够在更大脑网络内进行通信的受损微回路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a989/7200763/fe2c08420cce/41598_2020_63934_Fig1_HTML.jpg

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