Rodent behavioural data and Matlab codes for repeated textured Novel Object Recognition tests (tNORTs)

How to cite this Dataset

Hayashi, Yurie and Zheng, Ying (2024): Rodent behavioural data and Matlab codes for repeated textured Novel Object Recognition tests (tNORTs). University of Reading. Dataset. https://researchdata.reading.ac.uk/id/eprint/538

Description

This study designed repeated tNORTs to investigate whisker sensitivity of rodents. It consisted of 2 sets of tests. (1) Object bias tests (OBTs). (2) tNORTs. Eight rats were used throughout the study.

The OBTs were conducted in 8 days (Test day1 ~ day8) using 8 different objects (ObjectI ~ ObjectVIII). Each test involved 2 objects of the same shape placed in an arena (positioned at Left and Right).

After OBTs, rats performed five tNORTs (Test1 ~ Test5), with different grit-size sandpapers used for each test. The stopping criterion was when rats failed to discriminate different textures in two tests with finer grit sizes. Each tNORT consisted of a sample phase with two objects (L and R) covered by the same sandpaper, and a test phase with two objects covered by the same sandpaper (F) and a novel sandpaper (N).

The behaviour of the rat was recorded via a video camera for all tests. The video was analysed using ‘The Observer XT’ from Noldus to find rat exploration times (in seconds) of the Left and the Right objects, or the Familiar and Novel objects.

Matlab code used to analyse the data are included with the dataset.

Resource Type:

Dataset

Creators:

Hayashi, Yurie