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Airtrack - plus maze - Bpod version

Vision

We want to do electrophysiological recordings (Neuropixel) on mice performing the plus maze behavior experiment in the Airtrack system (Dominiak et al 2018 / Bergmann et al. 2020). The setup should do the behavior while we record electrophysiological data. Video data is used to monitor eye and whiskers movement.

Changes from version without recording:

  • Recording needs better electrical isolation
  • Markers for platform tracking are now visible from above

people involved

  • Robert Sachdev (supervision)
  • Jens Kremkow (supervision)
  • Fabio Reeh (master student)

People doing similar things in the lab:

  • Moritz (behavior)
  • Jelte, Mik (Neuropixel)
  • Quon
  • Eduardo (lick sensing)

Research roadmap

Hardare change (until July):

- past: using Arduino, Flashlights from below, UV lamps from above

- new lick detection system from workshop (dual lick sensor) : used by Eduardo in another experiment.
- Bpod r2+
- Lightniing (marker detection needs more light): 
    - LED for mouse feedback (same as before)
    - marker needs light : Infrared lamps (we have experience with it for other behavior).


- Fix the lick detector: Eduardo asked the workshop already - current power supply to noisy

Behavior (until September):

  • can the animal move the thing - yes, the 100 gramm heavy platform is good moveable by the mouse
  • train the animal to get reward

Experiments (until Feburary 2026)

  • 2 batch of 3 animals.

Design choices

  • UV lamps on batteries/plugin (noise if not shielded) may be used if infrared does not work.
  • We will try the big platform, a smaller one might be needed to be used later
  • Headpost chosen which does not cover brain areas we want to investigate
  • Use the multi chain version of Neuropixel

Eye/whiskers tracking

  • Video data
  • Post experiment analysis
  • ML analysis with sleap
  • UV marker at the wisker

dependencies

Hardware: - Bpop - neuropixel Software: - Matlab - Spikeglx will be used for data analysis - video data analysis with sleap

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