analysisVR

Analysis and visualization tools for virtual-reality behavior and electrophysiology experiments in rodents.

Start the GUI

From the repository root:

python3 main_analysis.py

The app starts on http://localhost:8050 (or http://0.0.0.0:8050).

Optional log level:

python3 main_analysis.py DEBUG

Installation

python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

Note: main_analysis.py imports baseVR.base_functionality from the parent directory, so ensure the sibling baseVR package is available. Note: You might have to change data source paths depending on the machine you are running this repo on (Debug Logging will tell you where).

Analytics Included in the GUI (Plots + Wrappers)

Session-wise plots

• SessionKinematics (wrapper_SessionKinematics.py): Single-session track-aligned behavior traces/heatmaps (velocity, acceleration, lick, ball/yaw/pitch metrics), with optional event overlays.
• RawSpikes (wrapper_RawSpikes.py): Raw electrophysiology traces with spike overlays for selected shanks, channel groups, and time windows.
• SVMPredictions (wrapper_SVMPredictions.py): SVM decoding performance across sessions for cue/outcome/choice predictors (accuracy or macro-F1).
• CueCorrelation (wrapper_CueCorrelation.py): Population-vector cue correlation (Cue1 vs Cue2) along track position.
• EnsembleEncoding (wrapper_EnsembleEncoding.py): Ensemble activation trajectories aligned to events/intervals, summarized across sessions.
• EnsembleRidgeline (wrapper_EnsembleRidgeline.py): Ridgeline-style view of ensemble activity distributions over intervals/events.
• EnsembleTrialwise (wrapper_EnsembleTrialwise.py): Trial-resolved ensemble dynamics with interval-local temporal structure.
• EnsembleChoiceEncoding (wrapper_EnsembleChoiceEncoding.py): Event-aligned ensemble activity focused on trial choice structure.

Animal-wise plots

• Kinematics (wrapper_AnimalKinematics.py): Multi-session kinematic summaries per animal across the track.
• StayPerformance (wrapper_StayPerformance.py): Session-by-session success/failure and stay-time performance trends.
• StayRatio (wrapper_StayRatio.py): Trial-level reward-zone stay-time distributions and ratio behavior.
• SessionsOverview (wrapper_SessionsOverview.py): Metadata/analytics availability overview across dates and sessions.
• EvolvingStayTime (wrapper_EvolvingStayTime.py): Evolution of R1/R2 stay times across trials and sessions.
• EvolvingStayDecision (wrapper_EvolvingStayDecision.py): Evolution of stay/skip strategy patterns over training.
• TrackFiringRate (wrapper_TrackFiringRate.py): Track-position tuning of firing rates across sessions.
• EvolvingPCSubspace (wrapper_EvolvingPCSubspace.py): Cross-session principal-component and canonical-angle subspace drift.
• TrackwiseEnsembleProj (wrapper_TrackwiseEnsembleProj.py): Trackwise ensemble projection dynamics across sessions.

Data Split Parameters (Behavior / Cue / Outcome)

Most behavior-driven wrappers use shared filtering/grouping controls from dashsrc/plot_components/plot_wrappers/data_selection.py.

• Outcome split:
  • 1 R: Stoping only in correct reward zone
  • 1+ R: Stop in both reward zones
  • no R: non-rewarded outcomes
• Cue split:
  • Cue1 trials
  • Cue2 trials
• Behavior split:
  • R1 choice: stop vs skip
  • R2 choice: stop vs skip
• Session-progress split:
  • 1/3, 2/3, 3/3 (first/middle/last third of trials)

Where supported, data can be split/grouped by:

• Outcome
• Cue
• Part of session
• R1 choice
• R2 choice
• None (no grouping)