Feb 27, 2020
Thigmotaxis_Detection_2018
- Akinori Higaki1,
- Masaki Mogi1,
- Jitsuo Higaki1,
- Masatsugu Horiuchi1
- 1Ehime University Graduate School of Medicine
Protocol Citation: Akinori Higaki, Masaki Mogi, Jitsuo Higaki, Masatsugu Horiuchi 2020. Thigmotaxis_Detection_2018. protocols.io https://dx.doi.org/10.17504/protocols.io.nzqdf5w
License: This is an open access protocol distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Protocol status: Working
We use this protocol and it's working
"Recognition of early stage thigmotaxis in Morris water maze test with convolutional neural network"
https://doi.org/10.1371/journal.pone.0197003
Created: March 23, 2018
Last Modified: February 27, 2020
Protocol Integer ID: 11024
Abstract
We share the minimal dataset for our study "Recognition for Early Stage Thigmotaxis in Morris Water Maze Test with Convolutional Neural Network" here. This study is currently submitted for PLoS one.
any_cropper.txt : Python script for converting bmp images to resized grayscale data.
bin_recog.txt : Python script for distinguishing thigmotaxis from other trajectories.
six_recog.txt : Python script for classifying 6 specific trajectories.
any_recog_data_0309.xlsx : Data used for analysis of mice characteristics.
