Journal: Progress in Earth and Planetary Science

Article Title: Deformation mechanisms and fluid conditions of mélange shear zones associated with seamount subduction

doi: 10.1186/s40645-024-00641-y

Figure Lengend Snippet: Fig. 5 Micritic limestone lenses in the BLM. Panels b–e were generated using MTEX software (Hielscher and Schaeben 2008; Mainprice et al. 2014). a Microcrystalline calcite (Cc) with radiolarian tests showing partial recrystallization to calcite. b Histogram of microcrystalline calcite grain size calculated from the diameter of reconstructed EBSD grains. c Histogram of grain orientation spread (GOS) of calcite, showing a low degree of intragranular misorientation. d GOS map of calcite on EBSD band contrast image of the micritic limestone. A given pixel within each of the calcite grains is colored by the angular degree of intragranular misorientation relative to the mean orientation of the parent grain. Most white grains correspond to chlorite and albite grains, identified by EBSD indexing and optical microscopy. Unindexed pixels are black. e CPO pole figures of microcrystalline calcite grains. CPO is plotted as equal-area, upper hemisphere projections. The crystal directions shown here were selected to examine the possibility of deformation under low-temperature calcite slip systems (De Bresser and Spiers 1997). The M-index (m) indicates that the fabric intensity is very weak (Skemer et al. 2005). Grains are plotted with the X-direction parallel to lineation and the Z-direction normal to foliation. N represents the number of measured points. f Micritic limestone (Cc) and basalt lenses in green chloritic matrix with S–C fabric showing top-to-SE shear sense. Dark seams contain Fe and Ti oxide minerals

Article Snippet: Quantitative analyses of EBSD data, including map analyses (e.g., grain reconstruction, grain size, and misorientation), CPO pole figures, and orientation distribution functions (e.g., M-index), were carried out using the MTEX toolbox for MATLAB (Hielscher and Schaeben 2008; Mainprice et al. 2014).

Techniques: Generated, Software, Recrystallization, Microscopy, Shear

Journal: Cell

Article Title: Cerebellar neurodynamics predict decision timing and outcome on single-trial level

doi: 10.1016/j.cell.2019.12.018

Figure Lengend Snippet: KEY RESOURCES TABLE

Article Snippet: ​ REAGENT or RESOURCE SOURCE IDENTIFIER Experimental Models: Organisms/Strains Tg( elavl3:H2B-GCaMP6s ) ( Vladimirov et al., 2014 ) N/A Tg(gSA2AzGFF152B) ( Takeuchi et al., 2015 ) N/A Tg(Huc:H2B-GCaMP6s; GAD1b:RFP) ( Freeman et al., 2014 ; Satou et al, 2013 ) N/A Tg(UAS:GCaMP6s) ( Filosa et al, 2016 ) N/A Software and Algorithms μManager Open Imaging https://micro-manager.org/ MATLAB (Behavioral and imaging analysis, modeling) MathWorks https://www.mathworks.com/products/matlab.html FIJI (ImageJ) (Image Processing) NIH http://fiji.sc Custom data-processing pipeline for LFM data ( Prevedel et al, 2014 ) https://static-content.springer.com/esm/art%3A10.1038%2Fnmeth.2964/MediaObjects/41592_2014_BFnmeth2964_MOESM189_ESM.zip Demixed Principal Component Analysis (dPCA) ( Kobak et al, 2016 ) https://github.com/machenslab/dPCA t-Distributed Stochastic Neighbor Embedding (t-SNE) ( Maaten and Hinton, 2008 ) https://lvdmaaten.github.io/tsne/ Independent Component Analysis (FastICA) ( Hyvarinen and Oja, 2000 ) https://research.ics.aalto.fi/ica/fastica/ Scanlmage ( Pologruto et al, 2003 ) http://scanimage.vidriotechnologies.com/display/SIH/ScanImage+Home CalmAn-MATLAB ( Giovannucci et al, 2019 ) https://github.com/flatironinstitute/CaImAn-MATLAB DeepLabCut 2.0 ( Nath et al, 2019 ) https://github.com/AlexEMG/DeepLabCut Open in a separate window KEY RESOURCES TABLE Whole-brain Ca 2+ imaging and decision making in larval zebrafish on the single-trial level Pre-motor bifurcation and trial-by-trial changes of functional connectivity Cerebellar activity predicts decision outcome and decision time >10 s before movement Hemisphere difference encodes decision; joint hemisphere activity encodes timing

Techniques: Software, Imaging