Journal: Scientific Reports

Article Title: A convolutional neural network for estimating synaptic connectivity from spike trains

doi: 10.1038/s41598-021-91244-w

Figure Lengend Snippet: Cross-correlograms of real spike trains recorded from PF, IT, and V1 using the Utah arrays. ( a ) An interval of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0 \pm 2$$\end{document} 0 ± 2 ms in the original cross-correlogram was removed to mitigate the shadowing effect, in which near-synchronous spikes were not detected. ( b ) Processing real cross-correlograms. ( c ) The cross-correlograms for which CoNNECT and GLMCC gave the same inference. The fitted GLM functions are superimposed on the histograms. The causal impact from a pre-neuron to a post-neuron appears on the right half in the cross-correlogram.

Article Snippet: Four 96 microelectrode arrays (Utah arrays, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$10 \times 10$$\end{document} 10 × 10 layout, 400 μm pitch, 1.5 mm depth, Blackrock Microsystems, Salt Lake City, USA) were surgically implanted on the IT cortex of the left hemisphere.

Techniques:

Journal: Scientific Reports

Article Title: A convolutional neural network for estimating synaptic connectivity from spike trains

doi: 10.1038/s41598-021-91244-w

Figure Lengend Snippet: Connection matrices and diagrams estimated for spike trains recorded from the prefrontal (PF), inferior temporal (IT), and the primary visual (V1) cortices of monkeys. In the connection diagrams, excitatory and inhibitory dominant units are depicted as triangles and circles, respectively, and units with no outgoing connections or those that innervate equal numbers of estimated excitatory and inhibitory connections are depicted as squares. (rightmost panels) The firing rate and irregularity ( \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_v$$\end{document} L v ) of the putative excitatory and inhibitory units identified by the E–I dominance index. Units that had no innervating connections or those that exhibited vanishing E–I dominance indices are depicted in gray.

Article Snippet: Four 96 microelectrode arrays (Utah arrays, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$10 \times 10$$\end{document} 10 × 10 layout, 400 μm pitch, 1.5 mm depth, Blackrock Microsystems, Salt Lake City, USA) were surgically implanted on the IT cortex of the left hemisphere.

Techniques:

Journal: Scientific Reports

Article Title: A convolutional neural network for estimating synaptic connectivity from spike trains

doi: 10.1038/s41598-021-91244-w

Figure Lengend Snippet: Results of analyzing experimental datasets.

Article Snippet: Four 96 microelectrode arrays (Utah arrays, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$10 \times 10$$\end{document} 10 × 10 layout, 400 μm pitch, 1.5 mm depth, Blackrock Microsystems, Salt Lake City, USA) were surgically implanted on the IT cortex of the left hemisphere.

Techniques:

Journal: Scientific Reports

Article Title: A convolutional neural network for estimating synaptic connectivity from spike trains

doi: 10.1038/s41598-021-91244-w

Figure Lengend Snippet: Hyperparameters of the convolutional neural network.

Article Snippet: Four 96 microelectrode arrays (Utah arrays, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$10 \times 10$$\end{document} 10 × 10 layout, 400 μm pitch, 1.5 mm depth, Blackrock Microsystems, Salt Lake City, USA) were surgically implanted on the IT cortex of the left hemisphere.

Techniques:

Journal: Scientific Reports

Article Title: A convolutional neural network for estimating synaptic connectivity from spike trains

doi: 10.1038/s41598-021-91244-w

Figure Lengend Snippet: The Matthews correlation coefficient (MCC) plotted against the threshold \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\theta$$\end{document} θ for determining the presence and absence of the connection.

Article Snippet: Four 96 microelectrode arrays (Utah arrays, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$10 \times 10$$\end{document} 10 × 10 layout, 400 μm pitch, 1.5 mm depth, Blackrock Microsystems, Salt Lake City, USA) were surgically implanted on the IT cortex of the left hemisphere.

Techniques:

Journal: Scientific Reports

Article Title: A convolutional neural network for estimating synaptic connectivity from spike trains

doi: 10.1038/s41598-021-91244-w

Figure Lengend Snippet: Parameters for neuron models.

Article Snippet: Four 96 microelectrode arrays (Utah arrays, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$10 \times 10$$\end{document} 10 × 10 layout, 400 μm pitch, 1.5 mm depth, Blackrock Microsystems, Salt Lake City, USA) were surgically implanted on the IT cortex of the left hemisphere.

Techniques:

Journal: Scientific Reports

Article Title: A convolutional neural network for estimating synaptic connectivity from spike trains

doi: 10.1038/s41598-021-91244-w

Figure Lengend Snippet: Parameters for synaptic currents and background inputs.

Article Snippet: Four 96 microelectrode arrays (Utah arrays, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$10 \times 10$$\end{document} 10 × 10 layout, 400 μm pitch, 1.5 mm depth, Blackrock Microsystems, Salt Lake City, USA) were surgically implanted on the IT cortex of the left hemisphere.

Techniques: