Etho: A Python framework for coordinating stimuli, data acquisition, and hardware control in neuroscience experiments

Etho is an open-source Python framework for running behavioral neuroscience experiments that require coordinated stimulus presentation, hardware control, data acquisition, and experiment logging.

It was developed for neuroscience experiments, where multiple hardware devices must operate together with reproducible timing. etho coordinates cameras, National Instruments DAQ hardware, acoustic and optogenetic stimulation, environmental sensors, and external imaging systems through a modular service-based architecture.

The software is designed to make experiments reproducible, configurable, and maintainable by separating:

• experiment logic and hardware (protocol.yaml)
• stimulus definitions (playlist.txt)
• acquisition callbacks and logs

from the underlying device code.

See the documentation for details.

Platform support

etho is tested for behavioral acquisition rigs on Windows. The hardware stack depends on vendor SDKs, which may also work on macOS or Linux but have not been tested with etho. Development, unit tests, and documentation work can be done on macOS or Linux when hardware SDKs are not required.

Installation

Quick installation on a Windows rig from PowerShell:

conda create -n etho -c conda-forge -y python=3.14 uv pip git
conda activate etho
uv pip install etho-python
etho init

etho supports Python 3.10 through 3.14. The Python version to use depends on the hardware SDKs required by the rig. Check the Python versions supported by the required hardware SDKs before installation. For FLIR/Spinnaker, public downloads may list Python 3.10, but FLIR support can provide Python 3.14 bindings.

Some hardware backends require additional vendor SDKs, drivers, and pinned Python or package versions. See the full installation guide.

Usage

Etho can be controlled via a GUI on the Windows rig. Launch it from the activated PowerShell environment with:

conda activate etho
etho gui

Alternatively, experiments can be run from the terminal:

conda activate etho
etho run ".\protocol.yaml" ".\playlist.txt"

Data generated by etho can be inspected, annotated, and analyzed with xarray-behave.

Citation

A JOSS paper describing the software is in preparation. For now, if you use etho or components of it in your research, please check the Cite this repository button in the repository sidebar or cite:

Clemens, J. (2026). Etho: A Python framework for coordinating stimuli, data acquisition, and hardware control in neuroscience experiments. doi:10.5281/zenodo.20110619

The etho software has been used in the following publications:

• Ravindran Nair, S., Palacios-Muñoz, A., Martineau, S., Nasr, M., & Clemens, J. (2026). Sex-specific behavioral feedback modulates sensorimotor processing and drives flexible social behavior. Nature Communications, 17, 4026. https://doi.org/10.1038/s41467-026-72057-9

• Steinfath, E., Khalili, A., Stenger, M., Schultze, B. L., Nair, S. R., Alizadeh, K., & Clemens, J. (2025). A neural circuit for context-dependent multimodal signaling in Drosophila. Nature Communications, 16, 9472. https://doi.org/10.1038/s41467-025-64907-9

• Palacios-Muñoz, A., & Clemens, J. (2025). Drosophila males integrate song and pheromones using context-specific strategies. BioRxiv. https://doi.org/10.1101/2025.07.25.666755

• Vijendravarma, R. K., Narasimha, S., Steinfath, E., Clemens, J., & Leopold, P. (2022). Drosophila females have an acoustic preference for symmetric males. Proceedings of the National Academy of Sciences, 119(13), e2116136119. https://doi.org/10.1073/pnas.2116136119