Overview

To get started we recommend following the tutorial (not yet available) using the example datasets included in /examples. We include image sequences acquired from a Femtonics microscope and standard tiff files of image sequences from a simple epifluorescent microscope along with corresponding CSV's containing stimulus information.

Welcome Window

Creating a new Mesmerize Project

Directory hierarchy of a project

Structure of a Project DataFrame

The Viewer

Opening Image sequences

Defining Stimulus maps

• From mes files
• From csv's

  Importing Stimulus Data automatically from other sources. Mesmerize is flexible enough for you to import stimulus maps from other types of sources which you may be using. In order to import & automatically organize stimulus data from other source you will just need to add an additional elif block to the stimMaps setter method of the ImgData class in /MesmerizeCore/DataTypes. Refer to the property decorator of stimMaps for details on how stimulus data is organized. Briefly, each occurrence of a stimulus looks like this and is stored in a list containing all the occurrences of stimuli in that particular trace/image sequence: [['StimName', <pyqtgraph color object>], (startFrame, endFrame)] Feel free to email us if you need assistance.

Performing Motion Correction using CaImAn

Creation & annotation of ROIs

Data analysis - programmable flowcharts

Types of Nodes

• Data Nodes
  • Load_Proj_DF
  • New Data passthrough
  • Save
  • Load
  • Bypass
• Display Nodes
  • Plot
  • PSD Plot
  • FFT Spectrum
• Definition Nodes
  • Align Stims
  • ROI Selection
  • Genotype selection
  • Peak Detection
  • Custom columns, such as stage
• Signal filter nodes
  • Butterworth filter
  • Savitzsky-Golay filter
  • FFT Filter
  • Derivative
• Statistics
  • Peak Features
  • Curves

Examples:

1. Calcium dynamics in response to noxious stimuli
2. Comparison of calcium dynamics of different cell types

Statistical analysis and plotting

Machine learning and clustering