Remote automated delivery of mechanical stimuli coupled to brain recordings in behaving mice

The canonical framework for testing pain and mechanical sensitivity in rodents is manual delivery of stimuli to the paw. However, this approach is time consuming, produces variability in results, requires significant training, and is ergonomically unfavorable to the experimenter. To circumvent limitations in manual delivery of stimuli, we have created a device called the ARM (Automated Reproducible Mechano-stimulator). Built using a series of linear stages, cameras, and stimulus holders, the ARM is more accurate at hitting the desired target, delivers stimuli faster, and decreases variability in delivery of von Frey hair filaments. We demonstrate that the ARM can be combined with traditional measurements of pain behavior and automated machine-learning based pipelines. Importantly, the ARM enables remote testing of mice with experimenters outside the testing room. Using remote testing, we found that mice habituated more quickly when an experimenter was not present and experimenter presen..., , # Remote automated delivery of mechanical stimuli coupled to brain recordings in behaving mice

Dataset DOI: [10.5061/dryad.cnp5hqcj7](https://doi.org/10.5061/dryad.cnp5hqcj7)

## Description of the data and file structure

### Files and variables

Note: For further information on data analysis, rationale, and methods, see Burdge et al., 2025, ELife.

#### File: 2nd_Cohort_Carragenan.zip

**Description:** Video data for PAWS Carrageenan Experiments Burdge et al., 2025 Figure 3D.  2000 fps video data for baseline and carrageenan mice. Videos labeled based on timepoint, paw stimulate, stimulus, cage number, and mouse number within the cage. Matching metadata files included.

#### File: 500fps.zip

**Description:** Video data for 500 fps PAWS comparison Burdge et al., 2025 Supplementary Figure 3B-E. 500 fps video data for baseline and carrageenan mice. Videos labeled with cb for cotton swab, all others are pinprick.

#### File: Open_Field-_July__24.zip

**Description:** Video data for open...,