A hardware-agnostic, Python-based framework for developing behavioral neuroscience experiments
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Pybehave is an open source software interface and framework for controlling behavioral experiments in neuroscience and psychology built around a hardware-agnostic and highly object-oriented design philosophy.
Pybehave separates code for task design from specific hardware implementations to streamline development, accessibility, and data sharing. This approach, combined with task-specific Graphical User Interfaces (GUIs) enabling user control without external hardware, expedites and simplifies the creation and visualization of complex behavioral tasks. User created task definition files can interact with hardware-specific Source files both written in Python. Any and all local configuration can be handled outside of Python using Address Files and Protocols.
All pybehave tasks are coordinated via a Workstation GUI.
Pybehave software and documentation are available on GitHub.
While pybehave is in principle cross-platform, it has only been extensively tested on Windows. We are happy to support other platforms so log any issues on GitHub if you have trouble installing. Additionally, some Sources are unlikely to work on all platforms.
We recommend installing pybehave in a virtual environment. Pybehave has been tested on Python 3.9, 3.10, and 3.11.
Install pybehave's default PYPI distribution with
pip install pybehave
This distribution does not include any of the dependencies for hardware specific functionality. To install the dependencies for all supported hardware use the following
pip install pybehave[full]
Alternatively, a subset of the dependencies can be downloaded, for example
pip install pybehave[oe,video]
A full list of the optional hardware-specific extras is below
oe # Dependencies for the OpenEphys framework
whisker # Dependencies for communication with WhiskerServer
video # Dependencies for control of connected video systems
serial # Dependencies for communication over serial
ni # Dependencies for communication with NationalInstruments DAQs
hikvision # Dependencies for communication with HikVision DVRs
bo # Dependencies for a Bayesian Optimization framework
Alternatively, you can clone the repository and run from source.
git clone https://github.com/tnelab/py-behav-box-v2.git
cd py-behav-box-v2
pip install .
Hardware-specific extras can be installed by adding square brackets after the '.' similarly to the above.
From the standard install, pybehave can be started by running the pybehave
command from the virtual environment. Alternatively,
if you have installed pybehave into a conda environment on Windows, we've provided an example batch script for starting pybehave in the root
directory (py-behav.bat). This batch script can be copied to the Desktop and the first line should be modified to use the name
of the environment where pybehave was installed. This batch file will also redirect all console outputs to a log file in the
py-behav/logging directory.
Pybehave uses a folder saved on the Desktop to handle all task files and local configuration:
-py-behav
pybehave.ini # Contains all settings for the GUI
-Local
-Tasks # Task python files
-GUIs # Task GUI files
-Sources # User-created sources
-Configurations # Structured CSVs for quickly loading tasks
-TaskName1 # All files associated with a Task called TaskName1
-AddressFiles # AddressFiles for this task
-Protocols # Protocols for this task
-Data # Any data associated with runs of the task
-TaskName2
We've included an example set of task files used by Translational Neuroengineering Lab. If you plan to edit or add tasks, you should make a new repository with the same structure (Tasks and GUIs folders) and include any existing tasks you might need. The contents of this repository should be saved in the Local directory.
Pybehave is explicitly designed in a manner where files for local configuration are separate from the root directory. This ensures that users can easily update to the newest version of the platform without compromising their experimental files. To update, simply pull the latest version from the upstream base pybehave code repository and the repository referenced by the Local folder.
After opening pybehave, you will see a GUI window like that shown above.
Select File->Add Task from the menu bar. Choose your task and a chamber number from the dropdowns or load a Configuration file.
Enter a subject ID in the Subject text box and choose an Address File or Protocol if necessary to set up the local configuration of the task. Alternatively, tasks can be tested without hardware by interacting with elements in the task-specific GUI.
Any event information such as data saving or external communication or pre-task prompts can be configured by right-clicking the chamber widget and selecting Edit Configuration. All data will be saved to the Desktop in the py-behav/TASK_NAME/Data/SUBJECT/DATE folder.
Press the green play button to start the task.
The task can be paused or ended prematurely with the orange pause button or red stop button respectively.
Users interested in expanding functionalities in pybehave are welcome to do so. Issues reports are encouraged through GitHub's issue tracker. See details on how to contribute and report issues in CONTRIBUTING.md.