neurobeam 0.3.0

Creator: bradpython12

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Description:

neurobeam 0.3.0

PROBE (Python Repo)














PROBE is an open-source software-hardware system for behavioral experiments in head-fixed rodents using a low-cost, modular experimental rig. The software is primarily written in python to allow easy distribution, use, and end-user modification with bits of C/C++ glued in for low-latency performance. An optional GUI is largely handled by your GPU to allow real-time streaming of ongoing behavior and data acquisition without disrupting your experiments. Currently PROBE is only supported on windows. Triggers dependent on neural activity require access to a raw-stream of imaging data. PROBE only offers native support for PrairieView at this time, but if you have a raw stream it should work. In constrast, software communication with spatial light modulators or hardware-triggered stimulation for optogenetic actions should be platform-independent.
More information on hardware implementation can be found here.
Integration Tests
Make sure to launch prairie_mock_server.exe if conducting integration tests with PrairieView. This is automatically launched if calling prairie_probe_test.exe but NOT any other testing application/suite including google tests
Software Reminders
These things aren't listed in TODOs
Remember to test on Prairie-1 Workstation-3. It has an old Xeon processer so it will be a good test of performance of single-thread performance on a slow processor.
Remember to double-check for potential race conditions.
Remember to refactor GUI aesthetic and import logo before pushing here from WRD repo
Remember to update badge links before ever making public--just placeholders from WRD repo. Figure out whether I need to do anything special for distribution of C++ lib, executables, & Node.js in a pypi package. Figure out whether anti-viruses will get grumpy from having an executable in a pypi package.
Hardware Reminders
The sucrose preference robotic spout-swapper has not been tested.
Try to test on a nicer NI-DAQ. Might be able to achieve higher best-case performance since they have hardware-timed digital I/O and I won't have to call those in-between analog-input callbacks.
Take a second look at the PCB scheme and see if I can simplify the connection from / to DAQ. I probably won't re-fabricate since I did that out-of-pocket, but some optimization there will make building much simpler/more flexible.
Development Statistics (PyCharm Repo)
~75,000 Lines
~75% Coverage
0 Linting Errors
Developmentn Statistics (CLion Repo)
~25,000 Lines
~20% Coverage
0 Linting Errors
Supported Pre-Configured Behaviors



Module
Task
Description
Recipe
Pilot




Disk or Wheel
Locomotion
Hyperactivity & Motor Function
x
x



Acoustic Startle
Hearing, Habituation, & Sensitization
x
x



Pre-Pulse Inhibition
Sensorimotor Gating
x
x



Go No-Go
Learning & Memory




Linear Track
Navigation
Learning & Memory




Burrow
Shelter Seeking
Anxiety





Sucrose Preference
Anhedonia





Attentional Set-Shifting
Behavioral Flexibility





Go No-Go
Learning & Memory





Trace Fear Conditioning
Learning & Memory





Delay Fear Conditioning
Learning & Memory





Instrumental Learning
Learning & Memory

License

For personal and professional use. You cannot resell or redistribute these repositories in their original state.

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