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MathWorks Inc computer vision matlab toolbox version 3 50
Overview of the multi-fiber photometry recording system and an example frame during recording (A) The system utilizes a 470-nm LED as a constant light source. The light initially passes through a 472/30-nm single-band bandpass filter, which narrows the excitation light’s wavelength. This excitation light is then reflected by a 495-nm dichroic beamsplitter, designed to reflect light wavelengths below 495 nm while allowing those above to pass. After reflecting off the beamsplitter, the excitation light travels through the recording patch cord, illuminating neuronal sensors like GCaMP6. The emission light produced by these sensors again traverses the recording patch cord, passes through the beamsplitter, and is subsequently filtered by a 535/50-nm single-band bandpass filter. Finally, this filtered light is captured by the camera. The signals recorded are then extracted and analyzed using <t>MATLAB.</t> (B) An example frame from an MFP recording session shows the test mouse freely interacting with the intruder.
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Overview of the multi-fiber photometry recording system and an example frame during recording (A) The system utilizes a 470-nm LED as a constant light source. The light initially passes through a 472/30-nm single-band bandpass filter, which narrows the excitation light’s wavelength. This excitation light is then reflected by a 495-nm dichroic beamsplitter, designed to reflect light wavelengths below 495 nm while allowing those above to pass. After reflecting off the beamsplitter, the excitation light travels through the recording patch cord, illuminating neuronal sensors like GCaMP6. The emission light produced by these sensors again traverses the recording patch cord, passes through the beamsplitter, and is subsequently filtered by a 535/50-nm single-band bandpass filter. Finally, this filtered light is captured by the camera. The signals recorded are then extracted and analyzed using <t>MATLAB.</t> (B) An example frame from an MFP recording session shows the test mouse freely interacting with the intruder.
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Image Search Results


Overview of the multi-fiber photometry recording system and an example frame during recording (A) The system utilizes a 470-nm LED as a constant light source. The light initially passes through a 472/30-nm single-band bandpass filter, which narrows the excitation light’s wavelength. This excitation light is then reflected by a 495-nm dichroic beamsplitter, designed to reflect light wavelengths below 495 nm while allowing those above to pass. After reflecting off the beamsplitter, the excitation light travels through the recording patch cord, illuminating neuronal sensors like GCaMP6. The emission light produced by these sensors again traverses the recording patch cord, passes through the beamsplitter, and is subsequently filtered by a 535/50-nm single-band bandpass filter. Finally, this filtered light is captured by the camera. The signals recorded are then extracted and analyzed using MATLAB. (B) An example frame from an MFP recording session shows the test mouse freely interacting with the intruder.

Journal: STAR Protocols

Article Title: Brain-wide multi-fiber recording of neuronal activity in freely moving mice

doi: 10.1016/j.xpro.2024.102882

Figure Lengend Snippet: Overview of the multi-fiber photometry recording system and an example frame during recording (A) The system utilizes a 470-nm LED as a constant light source. The light initially passes through a 472/30-nm single-band bandpass filter, which narrows the excitation light’s wavelength. This excitation light is then reflected by a 495-nm dichroic beamsplitter, designed to reflect light wavelengths below 495 nm while allowing those above to pass. After reflecting off the beamsplitter, the excitation light travels through the recording patch cord, illuminating neuronal sensors like GCaMP6. The emission light produced by these sensors again traverses the recording patch cord, passes through the beamsplitter, and is subsequently filtered by a 535/50-nm single-band bandpass filter. Finally, this filtered light is captured by the camera. The signals recorded are then extracted and analyzed using MATLAB. (B) An example frame from an MFP recording session shows the test mouse freely interacting with the intruder.

Article Snippet: Download the Piotr’s Computer Vision MATLAB Toolbox Version 3.50 from https://pdollar.github.io/toolbox/ for processing .seq video file. . 37.

Techniques: Produced