FIGURE SUMMARY
Title

3DM: deep decomposition and deconvolution microscopy for rapid neural activity imaging

Authors
Cho, E.S., Han, S., Lee, K.H., Kim, C.H., Yoon, Y.G.
Source
Full text @ Opt. Express
Fig. 1

Fig. 1. Deep decomposition deconvolution microscopy (3DM). (a) Schematic of 3DM hardware. An electrically tunable lens (ETL) is conjugated to the back pupil plane of the objective lens. (b) Schematic of the 3DM algorithm. A raw video consists of a time series of 3-D volumes. Using a bilinear neural network for efficient approximation of RPCA (BEAR), the raw video is decomposed into a low rank component and a sparse component that correspond to the background and the neural activity, respectively. The decomposed sparse component is deconvolved using our 3-D deconvolution network.

Fig. 2

Fig. 2. Neural networks for sparse decomposition and deconvolution. (a) Architecture of BEAR. The network takes the raw video Y and produces the low rank component L. The non-negative sparse component S is obtained as S=ReLU (Y−L). (b) Deconvolution network architecture. The deconvolved images are obtained by feeding the wide-field images to the network.

Fig. 3

Fig. 3. Temporal maximum intensity projection (MIP) of the sparse components of the simulated images. Scale bar, 100 μm. Top, lateral MIP. Bottom, axial MIP. (a) Ground truth. (b) Wide-field image. (c) Direct Richardson-Lucy deconvolution result. (d) Direct network-based deconvolution result. (e) SD-RL result. (f) 3DM result.

Fig. 4

Fig. 4. Imaging whole brain and spinal cord of a larval zebrafish expressing pan-neuronal GCaMP7a using 3DM. (a) Temporal MIP of the raw images. Scale bar, 100 μm. Top, lateral MIP. Bottom, axial MIP. (b) Temporal MIP of Richardson-Lucy deconvolution result. Scale bar, 100 μm. Top, lateral MIP. Bottom, axial MIP. (c) Temporal MIP of SD-RL result. Scale bar, 100 μm. Top, lateral MIP. Bottom, axial MIP. (d) Temporal MIP of the 3DM result. Scale bar, 100 μm. Top, lateral MIP. Bottom, axial MIP. (e) Enlarged views of (a)-(d) showing the optic tectum (boxed area in (a)). Scale bar, 30 μm. (f) Squared norm of the Fourier transform of the images in (a)-(d) displayed in log scale. Top, Fourier transforms of lateral (xy) slices. Bottom, Fourier transforms of axial (xz) slices.

Fig. 5

Fig. 5. Imaging the neuronal activity of a larval zebrafish brain expressing pan-neuronal GCaMP7a using 3DM. (a) Three z-slices (at z=70 μm, 100 μm, 140 μm, counted upwards from top to bottom, z = 0 μm indicates the top surface of the brain) from the deconvolved low rank image (left). Enlarged views of the boxed area with the neuronal activity superimposed on the low rank image at multiple time points (right). Scale bar, 50 μm. (b) Extracted neuronal activities shown as a heat map. (c) Randomly selected neurons and the corresponding extracted neuronal activity. The color of each selected neuron is matched to that of the corresponding activity. Scale bar, 50 μm.

Acknowledgments
This image is the copyrighted work of the attributed author or publisher, and ZFIN has permission only to display this image to its users. Additional permissions should be obtained from the applicable author or publisher of the image. Full text @ Opt. Express
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