findchangepts.m function (MathWorks Inc)

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MathWorks Inc findchangepts.m function
Findchangepts.M Function, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/findchangepts%2Em+function/pm40350488-376-30-33
Average 90 stars, based on 1 article reviews

findchangepts.m function - by Bioz Stars, 2026-09

90/100 stars

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Article Title: Robust alternative to the righting reflex to assess arousal in rodents
Article Snippet: We then implemented the findchangepts.m function (from Matlab) to find indices where local mean of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$A$$\end{document} A changed most dramatically through minimizing the sum of residual error of each segmented region.

Article Title: Continuous regimens of cortico-motor integration calibrate levels of arousal during emergence from anesthesia
Article Snippet: We then implemented the findchangepts.m function (from Matlab) to find indices where local mean of A changed most dramatically through minimizing sum of residual error of each segmented region.

Article Title: Naturalistic acute pain states decoded from neural and facial dynamics.
Article Snippet: We sorted the mean feature coefficients from all 100 runs in descending order and estimated the change point in the cumulative summation curve based on mean and slope using the ‘findchangepts.m’ function in Matlab.

Article Title: Response preparation involves a release of intracortical inhibition in task-irrelevant muscles.
Article Snippet: MEP duration was estimated using the MATLAB “findchangepts.m” function in the window from 18ms to 100ms following the TMS artifact.

Article Title: A simple method for detecting chaos in nature
Article Snippet: While Steyn-Ross, Steyn-Ross, and Sleigh’s code for estimating largest Lyapunov exponents using this method requires subjective evaluation of where to fit the line (i.e. finding the non-saturated part of the divergence rate plot), we automated this process by fitting a line from the beginning of the divergence rate plot to the point where its mean abruptly changes, reflecting saturation; this point was determined using Matlab’s findchangepts.m function.

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