/Maith2022_ExplorationSTNGPe

Source code of simulations and analyses from Maith, O., Baladron, J., Einhäuser, W., & Hamker, F. H. (2022). Exploration behavior after reversals is predicted by STN-GPe synaptic plasticity in a basal ganglia model. Submitted to iScience.

Primary LanguagePython

Maith2022_ExplorationSTNGPe

Source code of simulations and analyses from Maith, O., Baladron, J., Einhäuser, W., & Hamker, F. H. (2023). Exploration behavior after reversals is predicted by STN-GPe synaptic plasticity in a basal ganglia model. Submitted to iScience.

Authors:

Using the Scripts

Files

  • analyses/
    • folder for analyses of experimental and simulated data
    • analyses scripts can be found in subfolder/1_srcAna/
    • results are saved in subfolder/3_results/
    • for some analyses intermediate data are saved in subfolder/2_dataEv/ for further evaluations
  • psychExp/
  • simulations/
    • includes the scripts to run the simulations with the model to generate all analyzed data
    • script to run a single simulation (parallel.py) can be found in subfolder/1_srcSim/
    • the shell scripts (run.sh) help to run multiple simulations in parallel
    • data are saved in subfolder/2_dataRaw/ and subfolder/4_dataEv/, data generated for the study available at https://doi.org/10.5281/zenodo.6546572

Results Pipelines

Description of the results generated in Python. For several figures, additional image processing software was used to create the final figures (to adjust the layout and/or colors).

Results analysis experimental data simulated data simulations comment
Figure 3 manuscript_global_performance/ and manuscript_global_performance_vps/ yes yes 60 simulations from 014a.../ and 014b.../ each in manuscript_global_performance/ use run.sh (which also generates further figures); in manuscript_global_performance_vps/ run make_plot.py twice, with arguments 0 and 1
Figure 4 manuscript_SRtask_results/ yes yes 60 simulations from 014a.../ and 014b.../ each use run.sh (which also generates further figures)
Figure 5 manuscript_vp_learning_details/ yes no - run make_plot.py twice, with arguments 0 and 1
Figure 6 manuscript_Figure_activities_and_weightchanges/ no yes 60 simulations from 014a.../ and 014b.../ and a single simulation from 007a.../ use run.sh (which also generates further figures), various simulation times are set manually in the analysis (taken from the output file of the simulation), a change of the simulation used requires an adjustment of these times
Figure 7 manuscript_weight_morphing/ no yes 6400 simulations from 013.../
Figure S1 manuscript_SRtask_results/ yes yes 60 simulations from 001e.../ and 001f.../ each use run.sh (which also generates further figures)
Figure S2 manuscript_global_performance/ no yes 60 simulations from 001e.../ and 001f.../ each use run.sh (which also generates further figures)
Figure S3 manuscript_global_performance/ no yes 60 simulations from 014a.../ set weight_plot=True (extra_functions.py line 267)
Figure S4 manuscript_clockwise/ yes no - run make_plot.py twice, with arguments 0 and 1
Figure S5 manuscript_vp_learning_details/ yes no - run make_plot.py with argument 0
Figure S6 manuscript_SRtask_results/ yes yes 60 simulations from 014c.../ and 014d.../ each use run.sh (which also generates further figures)
Figure S7 manuscript_Figure_activities_and_weightchanges/ no yes 60 simulations from 001e.../ and 001f.../ use run.sh (which also generates further figures)
Figure S9 manuscript_statistics/ yes yes - see below

All statistical tests of the study are performed in analyses/manuscript_statistics/ which requires the prior performance of the analyses: manuscript_SRtask_results/ (use run.sh), manuscript_global_performance/ (use run.sh), and manuscript_global_performance_vps/ (with arguments 0 and 1).

Platforms

  • GNU/Linux

Dependencies (given versions used in study)

  • Python >= 3.7.4
  • ANNarchy >= 4.7.1.4
  • matplotlib >= 3.4.1
  • numpy >= 1.21.3
  • pandas >= 1.3.5
  • pingouin >= 0.5.1
  • scikit-learn >= 0.22.2.post1
  • scipy >= 1.7.1
  • tqdm >= 4.36.1