brain-python-interface (a.k.a. bmi3d)

This the unstable python 3 branch. It may not yet do what you want it to do.

This package contains Python code to run electrophysiology behavioral tasks, with emphasis on brain-machine interface (BMIs) tasks. This package differs from other similar packages (e.g., BCI2000--http://www.schalklab.org/research/bci2000) in that it is primarily intended for intracortical BMI experiments.

This package has been used with the following recording systems:

• Omniplex neural recording system (Plexon, Inc.).
• Blackrock NeuroPort

Code documentation can be found at http://carmenalab.github.io/bmi3d_docs/

Getting started

Dependencies

Linux/OS X

(none at this time) 16.04 64bit

#python version 3.7.8

Windows

Visual C++ Build tools (for the 'traits' package)

Installation

git clone -b unstable_py3 https://github.com/carmenalab/brain-python-interface.git
cd brain-python-interface
pip3 install -r requirements.txt
pip3 install -e .

set up the database

cd db
python3 manage.py makemigrations
python3 manage.py migrate
python3 manage.py makemigrations tracker
python3 manage.py migrate                  # make sure to do this twice!

start server

python3 manage.py runserver

Setup

Once the server is running, open up Chrome and navigate to localhost:8000/setup

• Under 'subjects', make sure at least one subject is listed. A subject named 'test' is recommended for separating exploration/debugging from real data.

• Under 'tasks', add a task to the system by giving it the python path for your task class. See documentation link above for details on how to write a task. There are a couple of built in tasks to help you get started.

  • For example, you can add the built-in task 'riglib.experiment.mocks.MockSequenceWithGenerator' just to check that the user interface works
  • If you want to try something graphical, you can add the built-in task 'built_in_tasks.passivetasks.TargetCaptureVFB2DWindow'. This will be a 'visual feedback' task in which a cursor automatically does the center-out task, a standard task in motor ephys.

Run a task

Navigate to http://localhost:8000/exp_log/ in chrome. Then press 'Start new experiment' and run your task.

Papers which have used this package

• Ramos Murguialday et al., A Novel Implantable Hybrid Brain-Machine-Interface (BMI) for Motor Rehabilitation in Stroke Patients. IEEE NER 2019
• Khanna P. and Carmena J.M. (2017) Beta band oscillations in motor cortex reflect neural population signals that delay movement onset. eLife 6:e24573. doi:10.7554/eLife.24573.
• Moorman H.G., Gowda S. and Carmena J.M. (2017) Control of redundant kinematic degrees of freedom in a closed-loop brain-machine interface. IEEE Transactions on Neural Systems and Rehabilitation Engineering 25(6), pp. 750-760. doi:10.1109/TNSRE.2016.2593696.
• Shanechi M.M., Orsborn A.L., Moorman H.G., Gowda S., Dangi S., and Carmena J.M. (2017) Rapid control and feedback rates in the sensorimotor pathway enhance neuroprosthetic control. Nature Communications 8:13825. doi:10.1038/ncomms13825.
• Dangi S., Gowda S., Moorman H.G., Orsborn A.L., So K., Shanechi M. and Carmena J.M. (2014) Continuous closed-loop decoder adaptation with a recursive maximum likelihood algorithm allows for rapid performance acquisition in brain-machine interfaces. Neural Computation 12, pp. 1-29.