Overview of the content for Day 1 of this course.
Best practices: the tips and tricks on how to get your Miniscope to work and how to get your experiments off the ground.
"Balancing size & function in compact miniscopes" was presented by Tycho Hoogland at the 2021 Virtual Miniscope Workshop as part of a series of talks by leading Miniscope users and developers.
"Computational imaging for miniature miniscopes" was presented by Laura Waller at the 2021 Virtual Miniscope Workshop as part of a series of talks by leading Miniscope users and developers.
This lecture introduces neuroscience concepts and methods such as fMRI, visual respones in BOLD data, and the eccentricity of visual receptive fields.
This tutorial walks users through the creation and visualization of activation flat maps from fMRI datasets.
"Online 1-photon vs 2-photon calcium imaging data analysis: Current developments and future plans" was presented by Andrea Giovannucci at the 2021 Virtual Miniscope Workshop as part of a series of talks by leading Miniscope users and developers.
This tutorial demonstrates to users the conventional preprocessing steps when working with BOLD signal datasets from fMRI.
In this tutorial, users will learn how to create a trial-averaged BOLD response and store it in a matrix in MATLAB.
This tutorial teaches users how to create animations of BOLD responses over time, to allow researchers and clinicians to visualize time-course activity patterns.
This tutorial demonstrates how to use MATLAB to create event-related BOLD time courses from fMRI datasets.
In this tutorial, users learn how to compute and visualize a t-test on experimental condition differences.
"Ensemble fluidity supports memory flexibility during spatial reversal" was presented by William Mau at the 2021 Virtual Miniscope Workshop as part of a series of talks by leading Miniscope users and developers.
How to start processing the raw imaging data generated with a Miniscope, including developing a usable pipeline and demoing the Minion pipeline
The direction of miniature microscopes, including both MetaCell and other groups.
Overview of the content for Day 2 of this course.
Summary and closing remarks for this three-day course.
You will learn about working with calcium imaging data, including image processing to remove background "blur," identifying cells based on thresholded spatial contiguity, time series filtering, and principal components analysis (PCA). The MATLAB code shows data animations, capabilities of the image processing toolbox, and PCA.
You will learn about working with calcium imaging data, including image processing to remove background "blur," identifying cells based on thresholded spatial contiguity, time series filtering, and principal components analysis (PCA). The MATLAB code shows data animations, capabilities of the image processing toolbox, and PCA.
You will learn about working with calcium imaging data, including image processing to remove background "blur," identifying cells based on thresholded spatial contiguity, time series filtering, and principal components analysis (PCA). The MATLAB code shows data animations, capabilities of the image processing toolbox, and PCA.