Table of Contents
Research to uncover the neural basis behind Path integration. In this project we use virtual reality with freely moving rodents while recording electrophysiological signal from the Hippocampus CA1. Animals are taught to rear at a visible beacon in the virtual arena, retrieve a randomly distributed reward and go back to the original location where the beacon was, but this time in darkness. We focus on understanding how the animal accumulates vectors as it travels to the reward and then when it needs to retrieve/calculate a correct vector to the original location. In this analysis we focus on proving the rearing behavior at the beacon.
- pip
pip install https://github.com/Fabalinks/Multiple_trial_analysisDuring an experimental session 3 files are generated.
position datetime.txt (rotation in quaternion coordinates):
| Time | X rat | Z rat | Y rat | X rotation_rat | Y rotation_rat | Z rotation_rat | Motive Frame | Motive timestamp | Motive session timestamp |
|---|
beacons datetime.txt:
| Time | X rat | Z rat | Y rat | X beacon | Y beacon |
|---|
metadata datetime.txt : Example described
| Recording started on : | 2021-11-15 16:04:08 |
|---|---|
| Computer time was : | 1636988648.44 |
| ITI_time : | 1.5 # time after beacon that beacon is inactive (animal cannot just stand there getting beacons, needs to leave |
| time_in_cylinder : | 60 # required time for animal to stay in beacon - not rearing |
| movement_collection_time : | 0.01 # getting position data supposedly at 100hz. |
| animal_ID : | FS11 |
| background_color : | 000 # just black color on the background |
| circle : | 0.075 #radius of visible beacon presented |
| position_change : | 10 # how many beacons till position changes |
| light_off : | 2 # how many beacons till beacon is invisible |
| Cylinder_color : | grass.png |
| rotation : | 80 #rotation speed for visual perturbation |
| Pellets : | 96 #achieved durign task |
| Beacon : | 217.640997887 # time spent in beacon |
| Sham : | 104.490000248 # time spent in beacon which is in different place and never visible. |
| Distance : | 498.117148451 # in meters |
| Speed : | 31.793808940176444 # cm/s |
| recording lenght : | 1892.398 #in seconds |
| high pellets : | 95 # how many pellets were achieved by standing |
| high_time_in_cylinder : | 0.5 # for how long animal has to rear in cylinder to count. |
| invisible_time : | 60 #how long does animal get before beacon becomes visible (s) |
| invisible_count : | 38 # how many invisible beacons animal achieved |
| invisible_list : | [1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 23, 31, 33, 35, 37, 39, 41, 43, 45, 47, 49, 51, 53, 55, 57, 61, 65, 67, 71, 73, 75, 77, 83, 85, 87, 89, 93, 95] # which beacon number were the invisible ones - later or earlier on? |
| Animal jumped : | -1 # how many times did the animal jump? |
| Recording_started_motive : | 0 # ephys frame number |
| Recording_timestamp_motive : | 0.0 # ephys timestamp |
| Day : | 157 # Which script |
| invisible circle : | 0.15 #how large is the invisible beacon area |
- Fork the Project
- Create your Feature Branch (
git checkout -b analysis/New_stuff) - Commit your Changes (
git commit -m 'Add some New_stuff') - Push to the Branch (
git push origin analysis/New_stuff) - Open a Pull Request
Distributed under the Apache License. See LICENSE.txt for more information.
Fabian Stocek - @fabalinks - stocek@bio.lmu.de
Project Link: https://github.com/Fabalinks/Multiple_trial_analysis