Vertical slice

Mouse Visual Contrast Training

IBL trainingChoiceWorld visual contrast slice with OpenAlyx provenance, canonical trials, and descriptive psychometric summaries for one public training-session table.

Run in your browser

Mouse trainingChoiceWorld · psychometric + chronometric

One unbiased trainingChoiceWorld session: compute P(right) and median response time per signed contrast level.

Pyodide + scipy run locally; first load downloads ~12 MB.

Mouse trainingChoiceWorld · psychometric + chronometric

Pyodide 0.26.4

One unbiased trainingChoiceWorld session: compute P(right) and median response time per signed contrast level.

Python (df is a pandas DataFrame loaded from the trials CSV; ⌘/Ctrl-Enter to run)
Click run to start

Runs entirely in your browser. First click downloads ~10 MB of Pyodide and pandas; subsequent runs reuse the cached runtime.

Metrics

Trials 646
Response trials 646
No-response trials 0
Prior contexts 11
Summary rows 33

Slice profile

Operational variables for cross-slice comparison.

Species
mouse
Modality
visual
Stimulus metric
signed contrast
Evidence type
static
Choice type
2afc
Response modality
wheel
Source data level
processed-trial
Analysis outputs
training-session psychometric fits
Data scope
one OpenAlyx trainingChoiceWorld public session
Canonical axis
right contrast positive, left contrast negative

Reproduce locally

Copy this recipe to rebuild the slice's artifacts on your machine at the exact commit deployed here.

Reproduce locally

Run the slice pipeline at this commit

git clone https://github.com/aeronjl/behavtaskatlas.git
cd behavtaskatlas
git checkout ec14ee5
uv sync --extra ibl
uv run behavtaskatlas mouse-visual-contrast-unbiased-download
uv run behavtaskatlas mouse-visual-contrast-unbiased-harmonize
uv run behavtaskatlas mouse-visual-contrast-unbiased-analyze
uv run behavtaskatlas mouse-visual-contrast-unbiased-report

Extras group ibl pulls in the analysis dependencies for this family. Recipe pinned to commit ec14ee5 so a teammate runs the same code path the deploy used.

Artifacts

Slice has a generated local report; the analysis pipeline ran cleanly and produced trial-level output, plots, and provenance.
  • Report HTML mouse_visual_contrast_unbiased/6a6442d1-dd7d-4717-b7b1-5874aefbd6fc/report.html
  • Analysis result JSON mouse_visual_contrast_unbiased/6a6442d1-dd7d-4717-b7b1-5874aefbd6fc/analysis_result.json
  • Psychometric SVG mouse_visual_contrast_unbiased/6a6442d1-dd7d-4717-b7b1-5874aefbd6fc/psychometric.svg
  • Canonical trials CSV mouse_visual_contrast_unbiased/6a6442d1-dd7d-4717-b7b1-5874aefbd6fc/trials.csv
  • Slice notes ../vertical_slices/mouse_visual_contrast_unbiased/README.md
  • Analysis record ../analyses/mouse_visual_contrast_unbiased.yaml