Calculating DF/F

Calculating DF/F#

This table summarizes Calcium Activity (ΔF/F) detection methods reviewed by Paudel et al. (2024).

Method

How It’s Performed

Pros

Cons

Manual Spike Counting

Visual inspection of raw fluorescence or dF/F traces to count events.

Simple; no code needed.

Subjective; non-scalable; low reproducibility.

dF/F Thresholding

Compute (F − F₀)/F₀ and define a fixed or adaptive threshold for events.

Widely used; compatible with GCaMP, Fluo dyes.

Sensitive to F₀ definition; arbitrary thresholds can bias results.

Z-Score Thresholding

Normalize trace by mean/SD, define events above N standard deviations.

Removes baseline drift; good for noisy data.

Sensitive to noise if SD is low; assumes Gaussian distribution.

Percentile Baseline Subtraction

Use a moving window to define F₀ as low percentile (e.g., 10–20th) of the trace.

Adaptive baseline; handles long-term drift.

Choice of window size/percentile affects sensitivity.

Ratiometric Imaging (Fura, YC2)

Compute ratio of Ca²⁺-sensitive and insensitive fluorophores per ROI.

Controls for volume/motion artifacts; yields [Ca²⁺].

Requires dual excitation/emission; reduced spatial/temporal res.

Photon Counting (Aequorin)

Count emitted photons per ROI/pixel over time; map to Ca²⁺ levels via calibration.

Quantitative; good dynamic range.

Low spatial resolution; complex calibration.

Image Subtraction (Frame-to-Frame)

Compute ΔF = Fₙ − Fₙ₋₁ or F − background to detect sudden changes.

Simple, fast; used for wave detection.

Sensitive to noise; misses gradual changes.

Savitzky-Golay Filtering

Smooth trace to reduce noise while preserving spikes.

Good for noisy signals.

Requires tuning; can mask small or fast events.

Tensor Voting / Cluster Detection

Identify spatially coordinated activity from 2D/3D image stacks.

Detects population events (e.g., waves).

Not standard; needs spatially dense data.

Standard Deviation (SD) Masking

Define active frames/regions where ΔF exceeds N×SD of baseline.

Objective thresholding for event detection.

Threshold choice heavily affects results.

Example ΔF/F trace baseline comparisons

Example of ΔF/F trace showing different baseline choices. Adapted from Fig. 1 of .#