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Locomotor Pattern Classification

Classify how animals move, not just where

Automated detection of thigmotaxis, center avoidance, wall-hugging, scanning, and directed movement — spatial strategies that carry more information than distance alone.

Locomotor Pattern Classification
8
Locomotor strategies classified
33ms
Frame-level strategy assignment
3
Validated paradigms (OF, WM, BM)
0
Manual expert classification needed
The problem

Movement strategy is more informative than total distance but harder to measure

Two animals with identical total distance can show very different spatial strategies — one exploring the center, the other hugging the walls. Strategy classification traditionally requires an expert to manually categorize trajectory segments, limiting throughput.

  • Thigmotaxis ratio requires defining wall zones and computing proportional time — a custom analysis per arena
  • Strategy transitions within a session (e.g., thigmotaxis → exploration) require temporal segmentation of the trajectory
  • Manual strategy classification by expert raters limits throughput to 5-10 sessions per hour
The solution

Trajectory feature extraction with automatic strategy labeling

ConductVision segments trajectories into behavioral epochs and classifies each segment using spatial features: wall proximity, angular velocity, path tortuosity, and directionality. Eight named strategies are assigned automatically.

  • Eight strategies: thigmotaxis, wall-hugging, center exploration, scanning, directed movement, circling, immobility, erratic
  • Temporal dynamics: see when and how often the animal switches strategies within a session
  • Arena-agnostic: works in open field, water maze, Barnes maze, and custom arenas
Endpoints

Locomotor strategy outputs

Strategy classification per epoch

Strategy classification per epoch

Each trajectory segment labeled with strategy type, duration, and spatial features used for classification.

CSVJSON
Strategy summary statistics

Strategy summary statistics

Proportion of session time in each strategy, number of strategy transitions, and dominant strategy by time bin.

CSV
Strategy transition matrix

Strategy transition matrix

Markov transition probabilities between strategies — which strategy follows which, and how this changes across sessions.

CSVPNG
Applications

Paradigms using locomotor pattern analysis

Anxiety

Open field thigmotaxis quantification

Thigmotaxis ratio is the most widely used open field anxiety measure. Automated strategy classification provides it without custom zone definitions.

Measures
  • Thigmotaxis ratio
  • Center exploration time
  • Strategy transition frequency
Spatial learning

Water maze strategy evolution

Track the transition from random search to scanning to directed swimming across training days — a more sensitive learning measure than latency.

Measures
  • Strategy type per trial
  • Day of strategy transition
  • Scanning-to-directed shift
Motor disorders

Circling and stereotypy detection

Unilateral lesion models produce characteristic circling patterns. Automated classification detects and quantifies circling without manual observation.

Measures
  • Circling frequency
  • Circling direction bias
  • Circling bout duration
Aging

Age-related strategy simplification

Aged animals use fewer strategy types and show reduced strategy switching. Pattern classification reveals cognitive rigidity.

Measures
  • Strategy diversity index
  • Transition rate by age
  • Dominant strategy shift
Compared to typical systems

How ConductVision differs

FeatureConductVisionTypical systems
Strategy classificationAutomated, 8 typesManual expert, 2-3 types
Temporal dynamicsWithin-session transitions trackedSingle strategy per trial
Arena compatibilityAny arena shapeCircular mazes only (water maze)
Transition analysisMarkov transition matrixNot available
ThroughputReal-time, unlimited5-10 sessions per hour (manual)

See movement strategy, not just movement distance

Upload open field or maze recordings for automatic locomotor strategy classification.