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4 Publications

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    07/11/22 | FourierNets enable the design of highly non-local optical encoders for computational imaging
    Deb D, Jiao Z, Sims R, Chen AB, Broxton M, Ahrens MB, Podgorski K, Turaga SC

     

    Differentiable simulations of optical systems can be combined with deep learning-based reconstruction networks to enable high performance computational imaging via end-to-end (E2E) optimization of both the optical encoder and the deep decoder. This has enabled imaging applications such as 3D localization microscopy, depth estimation, and lensless photography via the optimization of local optical encoders. More challenging computational imaging applications, such as 3D snapshot microscopy which compresses 3D volumes into single 2D images, require a highly non-local optical encoder. We show that existing deep network decoders have a locality bias which prevents the optimization of such highly non-local optical encoders. We address this with a decoder based on a shallow neural network architecture using global kernel Fourier convolutional neural networks (FourierNets). We show that FourierNets surpass existing deep network based decoders at reconstructing photographs captured by the highly non-local DiffuserCam optical encoder. Further, we show that FourierNets enable E2E optimization of highly non-local optical encoders for 3D snapshot microscopy. By combining FourierNets with a large-scale multi-GPU differentiable optical simulation, we are able to optimize non-local optical encoders 170

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    04/06/22 | Voltage imaging identifies spinal circuits that modulate locomotor adaptation in zebrafish.
    Böhm UL, Kimura Y, Kawashima T, Ahrens MB, Higashijima S, Engert F, Cohen AE
    Neuron. 2022 Apr 06;110(7):1211-1222.e4. doi: 10.1016/j.neuron.2022.01.001

    Motor systems must continuously adapt their output to maintain a desired trajectory. While the spinal circuits underlying rhythmic locomotion are well described, little is known about how the network modulates its output strength. A major challenge has been the difficulty of recording from spinal neurons during behavior. Here, we use voltage imaging to map the membrane potential of large populations of glutamatergic neurons throughout the spinal cord of the larval zebrafish during fictive swimming in a virtual environment. We characterized a previously undescribed subpopulation of tonic-spiking ventral V3 neurons whose spike rate correlated with swimming strength and bout length. Optogenetic activation of V3 neurons led to stronger swimming and longer bouts but did not affect tail beat frequency. Genetic ablation of V3 neurons led to reduced locomotor adaptation. The power of voltage imaging allowed us to identify V3 neurons as a critical driver of locomotor adaptation in zebrafish.

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    03/14/22 | Dimensionality reduction of calcium-imaged neuronal population activity
    Tze Hui Koh , William E. Bishop , Takashi Kawashima , Brian B. Jeon , Ranjani Srinivasan , Sandra J. Kuhlman , Misha B. Ahrens , Steven M. Chase , Byron M. Yu
    bioRxiv. 2022 Mar 14:. doi: 10.1101/2022.03.11.480682

    Calcium imaging has been widely adopted for its ability to record from large neuronal populations. To summarize the time course of neural activity, dimensionality reduction methods, which have been applied extensively to population spiking activity, may be particularly useful. However, it is unclear if the dimensionality reduction methods applied to spiking activity are appropriate for calcium imaging. We thus carried out a systematic study of design choices based on standard dimensionality reduction methods. We also developed a novel method to perform deconvolution and dimensionality reduction simultaneously (termed CILDS). CILDS most accurately recovered the single-trial, low-dimensional time courses from calcium imaging that would have been recovered from spiking activity. CILDS also outperformed the other methods on calcium imaging recordings from larval zebrafish and mice. More broadly, this study represents a foundation for summarizing calcium imaging recordings of large neuronal populations using dimensionality reduction in diverse experimental settings.

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    01/24/22 | Voltage imaging identifies spinal circuits that modulate locomotor adaptation in zebrafish.
    Böhm UL, Kimura Y, Kawashima T, Ahrens MB, Higashijima S, Engert F, Cohen AE
    Neuron. 2022 Jan 24:. doi: 10.1016/j.neuron.2022.01.001

    Motor systems must continuously adapt their output to maintain a desired trajectory. While the spinal circuits underlying rhythmic locomotion are well described, little is known about how the network modulates its output strength. A major challenge has been the difficulty of recording from spinal neurons during behavior. Here, we use voltage imaging to map the membrane potential of large populations of glutamatergic neurons throughout the spinal cord of the larval zebrafish during fictive swimming in a virtual environment. We characterized a previously undescribed subpopulation of tonic-spiking ventral V3 neurons whose spike rate correlated with swimming strength and bout length. Optogenetic activation of V3 neurons led to stronger swimming and longer bouts but did not affect tail beat frequency. Genetic ablation of V3 neurons led to reduced locomotor adaptation. The power of voltage imaging allowed us to identify V3 neurons as a critical driver of locomotor adaptation in zebrafish.

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