Data for: Plastic vasomotion entrainment in eLife
-
- Sasaki, Daichi
- 作成者
-
- Imai, Ken
- 作成者
-
- Ikoma, Yoko
- 作成者
-
- Matsui, Ko
- 作成者
メタデータ
- 公開日
- 2024-04-16
- DOI
-
- 10.5061/dryad.15dv41p4f
- 公開者
- Dryad
- データ作成者 (e-Rad)
-
- Sasaki, Daichi
- Imai, Ken
- Ikoma, Yoko
- Matsui, Ko
説明
# Data for: Plastic vasomotion entrainment in eLife [https://doi.org/10.5061/dryad.15dv41p4f](https://doi.org/10.5061/dryad.15dv41p4f) Fluorescence image data were collected from the surface of the mouse brain using macro-zoom fluorescence stereo-microscope. The data were analyzed mainly using ImageJ and AxoGraph softwares. Tiff files can be observed and analyzed using ImageJ. [https://imagej.net/ij/](https://imagej.net/ij/) AxoGraph files can be observed and analyzed using AxoGraph. [https://axograph.com/](https://axograph.com/) All original data used for the creation of all figures in the article "Plastic vasomotion entrainment" in eLife are presented in this data set. Further navigation of the data can be inquired to the corresponding author (Ko Matsui, [matsui@med.tohoku.ac.jp](mailto:matsui@med.t)). ## Description of the data and file structure Fig1A.tif \- original tiff data Fig1B.tif \- original tiff data Fig1C.axgx \- waveform data in AxoGraph format Fig1D.axgx \- waveform data in AxoGraph format Fig1D_data.xlsx \- original data in Excel format Fig1E.axgx \- waveform data in AxoGraph format Fig1F.xlsx \- original data in Excel format Fig1G-1_left_interval.axgx \- data in AxoGraph format Fig1G-2_middle_PeakAmp.axgx \- data in AxoGraph format Fig1G-3_right_Width50%.axgx \- data in AxoGraph format Fig2A.tif \- original tiff data Fig2B.tif \- original tiff data Fig2C.axgx \- waveform data in AxoGraph format Fig2D.axgx \- waveform data in AxoGraph format Fig2E.tif \- original tiff data Fig2F.axgx \- waveform data in AxoGraph format Fig2G.axgx \- waveform data in AxoGraph format Fig2H.axgx \- waveform data in AxoGraph format Fig2I.xlsx \- original data in Excel format Fig2J.tif \- original tiff data Fig2K-1_upper.axgx \- waveform data in AxoGraph format Fig2K-2_lower.tif \- powerspectrogram data in tiff format Fig3A.tif \- photo data Fig3B.tif \- original tiff data Fig3C-1_upper_wave-data.axgx \- waveform data in AxoGraph format Fig3C-2_lower_AmplitudeSpectrum.axgx \- powerspetrum data in AxoGraph format Fig3D-1_upper_wave-data.axgx \- waveformdata in AxoGraph format Fig3D-2_lower-left_Pre-spectrogram.tif \- powerspectrogram data in tiff format Fig3D-3_lower-middle_Post-spectrogram.tif \- powerspectrogram data in tiff format Fig3D-4_lower-right_All-spectrogram.tif \- powerspectrogram data in tiff format Fig3E-1_left.axgx \- analyzed data in AxoGraph format Fig3E-2_middle.axgx \- analyzed data in AxoGraph format Fig3E-3_right.axgx \- analyzed data in AxoGraph format Fig3F-1_left_Novice.tif \- original tiff data Fig3F-2_middle_Trained.tif \- original tiff data Fig3F-3_right_Expert.tif \- original tiff data Fig3G.tif \- original tiff data Fig3H.xlsx \- original data in Excel format Fig3I.axgx \- waveform data in AxoGraph format Fig4A-1_left_TexRed.tif \- original tiff data Fig4A-2_right_dYFP.tif \- original tiff data Fig4B.tif \- photo data Fig4C.ai \- mouse brain diagram Fig4D.axgx \- waveform data in AxoGraph format Fig4E.axgx \- waveform data in AxoGraph format Fig4F.axgx \- waveform data in AxoGraph format Fig4G.xlsx \- original data in Excel format Fig4H.axgx \- waveform data in AxoGraph format Fig4I.axgx \- waveform data in AxoGraph format Fig4J.xlsx \- original data in Excel format Fig4K-1_upper_TexRed.axgx \- waveform data in AxoGraph format Fig4K-2_lower_AutoFluo.axgx \- waveform data in AxoGraph format Fig4L.axgx \- powerspetrum data in AxoGraph format Fig4M.xlsx \- original data in Excel format Fig5A-1_upper_wave-data.axgx \- waveform data in AxoGraph format Fig5A-2_lower_AmplitudeSpectrum.axgx \- powerspectrum data in AxoGraph format Fig5B-1_left_wave-data.axgx \- waveform data in AxoGraph format Fig5B-2_right_AmplitudeSpectrum.axgx \- powerspectrum data in AxoGraph format Fig5C-1_left_wave-data.axgx \- waveform data in AxoGraph format Fig5C-2_right_AmplitudeSpectrum.axgx \- powerspectrum data in AxoGraph format Fig5D.xlsx \- original data in Excel format Fig6A.axgx \- waveform data in AxoGraph format Fig6B.xlsx \- original data in Excel format Fig6C.xlsx \- original data in Excel format Fig6D.axgx \- waveform data in AxoGraph format Fig6E.axgx \- waveform data in AxoGraph format Fig6F-1_left_wave-data.axgx \- waveform data in AxoGraph format Fig6F-2_left-upper_EyeTrace-spectrogram.tif \- powerspectrogram data in tiff format Fig6F-3_left-lower_TexRed-spectrogram.tif \- powerspectrogram data in tiff format Fig6F-4_right_wave-data.axgx \- waveform data in AxoGraph format Fig6F-5_right-upper_EyeTrace-spectrogram.tif \- powerspectrogram data in tiff format Fig6F-6_right-lower_TexRed-spectrogram.tif \- powerspectrogram data in tiff format Fig6G.xlsx \- original data in Excel format Fig7A.tif \- schedule data in tiff format Fig7B-1_left.axgx \- waveform data in AxoGraph format Fig7B-2_middle.axgx \- waveform data in AxoGraph format Fig7B-3_right.axgx \- waveform data in AxoGraph format Fig7C-1_upper_EyeTrace.axgx \- waveform data in AxoGraph format Fig7C-2_lower_AutoFluo.axgx \- waveform data in AxoGr ...
The presence of global synchronization of vasomotion induced by oscillating visual stimuli was identified in the mouse brain. Endogenous autofluorescence was used and the vessel “shadow” was quantified to evaluate the magnitude of the frequency-locked vasomotion. This method allows vasomotion to be easily quantified in non-transgenic wild-type mice using either the wide-field macro-zoom microscopy or the deep-brain fiber photometry methods. Vertical stripes horizontally oscillating at a low temporal frequency (0.25 Hz) were presented to the awake mouse and oscillatory vasomotion locked to the temporal frequency of the visual stimulation was induced not only in the primary visual cortex but across a wide surface area of the cortex and the cerebellum. The visually induced vasomotion adapted to a wide range of stimulation parameters. Repeated trials of the visual stimulus presentations resulted in the entrainment of the amplitude of the vasomotion. Horizontally oscillating visual stimulus is known to induce horizontal optokinetic response (HOKR). The amplitude of the eye movement is known to increase with repeated training sessions and the flocculus region of the cerebellum is known to be essential for this learning to occur. Here, we show a strong correlation between the average HOKR performance gain and the vasomotion entrainment magnitude in the cerebellar flocculus. Therefore, the plasticity of vasomotion and neuronal circuits appeared to occur in parallel. Efficient energy delivery by the entrained vasomotion may contribute to meeting the energy demand for increased coordinated neuronal activity and the subsequent neuronal circuit reorganization.
Imaging data were collected using macro-zoom fluorescence stereo microscope. Data were processed using mainly ImageJ and AxoGraph softwares.