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% FreezingFree in-browser calculator

Fear Conditioning % Freezing Calculator.

Upload velocity traces or enter pre-scored freezing data. Get % freezing per epoch (baseline, CS, ITI, context, cued), bout analysis, and session time courses.

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Validated2026-04-05
CitableMethods and citation included

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Load example Fear Conditioning data to see the full workflow

Freezing Detection Settings

Session Epochs

EpochStart (s)End (s)Duration
Baseline0120120s
CS112015030s
ITI115024090s
CS224027030s
ITI227036090s
CS336039030s
Post-US39048090s

Upload Velocity Trace

CSV with columns for time and velocity (cm/s). Optionally include animal_id and group columns.

When to use

  • Detect freezing from velocity trace data using configurable threshold and minimum bout duration
  • Compute % freezing per epoch (baseline, CS, ITI, context, cued) with preset or custom epoch definitions
  • Analyze freezing bout structure: count, mean duration, and latency to first freeze per epoch
  • Compare % freezing across treatment groups with SEM error bars
  • Visualize freezing time course across sessions (30-second bins)
  • Enter pre-scored freezing data when automated velocity traces are not available
  • Export per-animal and group summary results to CSV

Do not use for

  • Real-time video scoring — use ConductVision or dedicated scoring software (Video Freeze, FreezeFrame) to generate velocity or freezing data first
  • Fear-potentiated startle, which measures startle amplitude rather than freezing
  • Active avoidance or shuttle box tasks, where the behavioral readout is escape/avoidance rather than freezing

Calibrate your freezing threshold against manual scoring

The velocity threshold (default 0.05 cm/s) and minimum bout duration (default 1.0 s) should be validated against expert hand-scoring for your specific apparatus and video system. Even small changes in threshold can substantially shift percent freezing values. Run a calibration experiment comparing automated vs. manual scoring on 5-10 animals before committing to a threshold.

Report epoch definitions explicitly in your methods

Percent freezing values are meaningless without knowing the epoch boundaries. Always report the exact start and end times for each epoch. For cued tests, specify both the pre-CS baseline duration and the CS presentation duration. Inconsistent epoch definitions between studies make cross-study comparisons impossible.

Pre-CS baseline in cued test should be low

During a cued test in a novel context (Context B), the pre-CS baseline freezing should be low (typically < 20%). High baseline freezing suggests generalized fear (the animal fears the novel context) or inadequate context differentiation. If baseline freezing is high, your context manipulation may be insufficient — check chamber odor, floor texture, lighting, and visual cues.

Distinguish immediate vs. 24-hour fear memory

Freezing during training reflects immediate acquisition. Freezing during a 24-hour context or cued test reflects consolidated long-term memory. These are dissociable: some manipulations impair consolidation without affecting acquisition. Always test at the appropriate retention interval for your question.

Account for locomotor effects of drug treatments

Drugs that reduce locomotor activity can artificially inflate freezing scores. If your treatment affects general locomotor activity (test in an open field), consider whether apparent freezing increases reflect true fear enhancement or motor suppression. Reporting both freezing and general activity in the same animals strengthens your interpretation.

Resources

  • Shock grid impedance tested with multimeter
  • Shock intensity verified (typically 0.5-0.7 mA for mice)
  • Tone generator calibrated (dB meter at animal level)
  • Chamber cleaned with designated scent (e.g., 70% ethanol)
  • Context B has distinct floor, walls, and scent
  • Ventilation fan running
  • Video recording at ≥15 fps for scoring
  • Freezing threshold validated with pilot animals
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Method

Freezing is detected when velocity falls below the specified threshold for at least the minimum bout duration. Percent freezing per epoch equals total freezing time within the epoch divided by epoch duration, multiplied by 100. Bout analysis counts distinct freezing episodes and computes mean bout duration and latency to first freeze within each epoch. Session time course divides the session into 30-second bins and computes percent freezing per bin. Group statistics use sample standard deviation (n-1 denominator) for SEM. All computation is client-side — no data leaves your browser.

2

Validated

Last validated 2026-04-05. Calculations are designed for planning and documentation support; verify procurement decisions against manufacturer specifications or institutional SOPs.

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How to cite

How to Cite

ConductScience Fear Conditioning Percent Freezing Calculator (v1.0). ConductScience, Inc. 2026. Available at: https://conductscience.com/tools/fear-conditioning-percent-freezing-calculator

This tool performs mathematical calculations on user-provided data. It does not replace scientific judgment regarding experimental design, exclusion criteria, or statistical analysis.

What Is Fear Conditioning?

Fear conditioning is one of the most widely studied learning paradigms in behavioral neuroscience, dating to the foundational work of Pavlov and later formalized for rodent research by Fanselow (1980) and others. In a typical experiment, a mouse or rat is placed in a conditioning chamber and exposed to pairings of a conditioned stimulus (CS, usually a pure tone of 2-10 kHz) with an unconditioned stimulus (US, usually a brief foot shock of 0.5-1.0 mA). After even a single CS-US pairing, the animal learns that the CS predicts the US and subsequently displays a defensive freezing response to the CS alone. Freezing — the complete cessation of all movement except breathing — is the canonical measure of conditioned fear in rodents. The paradigm is valued for its simplicity, its well-characterized neural circuitry (centered on the amygdala, hippocampus, and prefrontal cortex), and its translational relevance to anxiety disorders and PTSD in humans.

Measuring Freezing: From Manual Scoring to Automated Detection

Historically, freezing was scored by trained observers using time-sampling methods: every 5-10 seconds, the observer recorded whether the animal was frozen or moving. While reliable when inter-rater agreement is verified, this approach is labor-intensive and subject to observer bias. Modern automated systems detect freezing from video using either pixel-change algorithms (e.g., Video Freeze, FreezeFrame) or pose-estimation/velocity tracking (e.g., DeepLabCut, ConductVision). Automated methods compare movement or velocity against a threshold: if the animal's velocity drops below a near-zero cutoff (typically 0.05 cm/s) for a minimum duration (typically 1 second), that period is classified as freezing. Validation studies show strong correlation (r > 0.95) between automated and expert manual scoring when thresholds are properly calibrated (Anagnostaras et al., 2000). The key parameters to report are the detection method, velocity or pixel-change threshold, and minimum bout duration.

Session Epoch Design: Training, Context, and Cued Tests

A complete fear conditioning experiment typically involves three sessions across two days. Day 1 is training (acquisition): the animal is placed in the conditioning chamber (Context A) and after a baseline habituation period (2-3 minutes), receives 3-5 CS-US pairings with inter-trial intervals (ITIs) of 60-120 seconds. Freezing during each CS presentation should increase across trials, reflecting within-session acquisition. Day 2 begins with a context test: the animal is returned to Context A for 5 minutes with no CS or US presentations. Freezing during this period reflects contextual fear memory and depends on hippocampal function. Later on Day 2 (or Day 3), a cued test is conducted: the animal is placed in a novel context (Context B — different chamber, floor texture, odor, lighting) for a pre-CS baseline period (2-3 minutes), then the CS is presented continuously or repeatedly. Freezing during the CS in Context B reflects cued (tone) fear memory and depends on amygdalar function. Analyzing freezing within each epoch across these sessions reveals the specificity and strength of the fear memory, and dissociates hippocampal from amygdalar contributions.

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