πŸ“– Glossary

Common terms used throughout the SimBA documentation. Terms defined here can be cross-referenced from anywhere in the docs with the :term: role (e.g. :term:`ROI` renders as ROI).

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aggregate statistics

Session- or video-level summaries of classifier output (total time, bout counts, mean bout duration, latency, etc.) saved to the project logs.

AMBER

A pose-estimation pipeline for maternal-pup interaction analysis whose tracking data SimBA can import.

anchored ROI
animal-anchored ROI

An ROI (bounding box or shape) attached to, and moving with, an animal or body-part across frames - as opposed to a fixed, frame-static ROI.

annotation
labelling

The process of marking, frame-by-frame, whether a behavior is present or absent in a video. These human labels are the ground truth used to train a classifier.

arena

The experimental enclosure (open field, home cage, box, etc.) in which an animal is recorded. SimBA maps arena pixels to real-world units via px/mm and can restrict analyses to it or to ROIs drawn within it.

background subtraction

A markerless segmentation technique that models the static scene and flags pixels differing from it as the moving animal; the basis of SimBA’s blob tracking.

behavior
target

The action a SimBA classifier is trained to detect (e.g. attack, grooming, freezing). Also referred to as the target.

BENTO

A MATLAB GUI (Caltech) for browsing, annotating and analysing synchronised behavioral, tracking and neural data; SimBA imports its annotations.

blob tracking
contour tracking

Markerless tracking that segments each animal as a single connected region (a blob) via background subtraction, instead of tracking individual body-part keypoints. Useful when full pose estimation is unnecessary or unavailable.

body-part

A single tracked point on an animal (e.g. nose, left_ear, tail_base), produced by pose estimation and stored as x, y (and probability) columns.

BORIS

Behavioral Observation Research Interactive Software β€” a free, open-source event-logging program for manual behavioral coding; SimBA imports its exported annotations.

bounding box

The smallest axis-aligned (or rotated) rectangle that encloses an animal or a set of body-parts; used for overlap, area and proximity computations.

bout

A continuous, uninterrupted episode of a behavior β€” i.e. a run of consecutive frames classified as the same behavior. Bout-level statistics summarise the count, duration and timing of these episodes.

centroid

The geometric centre of a set of body-parts (or a shape); often used as a single location for an animal.

circular statistics

Statistics for angular/directional data (degrees), where 359Β° and 1Β° are close. Used in SimBA for heading, turning and directional analyses.

CLAHE

Contrast Limited Adaptive Histogram Equalization - a local contrast-enhancement step in SimBA’s video tools, used to improve tracking on low-contrast footage.

class imbalance

The common situation where the behavior of interest is present in far fewer frames than it is absent, which can bias a classifier toward predicting β€œabsent”. Addressed with re-sampling (see oversampling, undersampling, SMOTE).

classifier

A supervised machine-learning model (typically a random forest) trained on annotated features to predict the presence of a behavior on each frame.

clustering
embedding

Unsupervised grouping of behavioral data without labels β€” e.g. projecting features with UMAP/t-SNE and clustering the result to discover behavioral motifs.

confusion matrix

A table of predicted vs. true labels (true/false positives and negatives) used to evaluate a classifier.

convex hull

The smallest convex polygon enclosing a set of body-parts; a common basis for animal area, shape and overlap metrics.

cross-validation

Splitting annotated data into train/test folds to estimate how well a classifier generalises to unseen frames, guarding against over-fitting.

cue light

An experimentally controlled light stimulus; SimBA’s cue-light tools detect when each light is on or off and quantify behavior and movement relative to those states.

DeepEthogram

An open-source supervised deep-learning tool that classifies behaviors directly from raw video frames; SimBA can import its predictions as labels.

DeepLabCut
DLC

A popular open-source pose estimation toolbox. SimBA imports DLC tracking data (single- and multi-animal).

directing

An animal orienting toward a target β€” another animal, a body-part or an ROI. SimBA quantifies directing (see directionality) from the angle between an animal’s heading and the target.

directionality

Whether, and where, an animal is facing β€” e.g. toward another animal, a body-part or a ROI.

discrimination threshold
probability threshold

The probability cut-off above which a frame is scored as the behavior. Raising it makes detection stricter (higher precision), lowering it more permissive (higher recall).

egocentric alignment

Re-centering and rotating each frame so a chosen body-part is fixed in position and orientation, removing the animal’s global location/heading from the analysis.

ethogram

A catalogue of the distinct behaviors an animal performs, and (in a session) their occurrence over time.

Ethovision

Noldus EthoVision XT β€” commercial video-tracking and behavioral-analysis software; SimBA can import its exported annotations.

FaceMap

An open-source keypoint/behavioral-motion tracking tool whose output SimBA can import as a pose estimation source.

feature
feature extraction

A numeric quantity computed per frame from pose estimation data (distances, velocities, angles, areas, etc.). Feature extraction turns raw tracking into the inputs a classifier learns from.

feature importance

A ranking of how much each feature contributes to a classifier’s decisions (e.g. Gini importance, permutation importance, or SHAP).

FPS

Frames per second β€” the video frame rate. Required to convert frame counts to seconds and to compute time-based metrics.

FSTTC

Forward Spike Time Tiling Coefficient β€” a measure of the temporal association between two behaviors (how often one tends to follow another within a time window), adapted from spike-train analysis.

Gantt plot

A timeline visualization showing when each behavior occurs across a session as horizontal bars.

geometry

Representing animals/arenas as shapes (points, lines, convex hulls, polygons, circles) via Shapely, enabling area, overlap, distance and containment computations.

heatmap

A spatial visualization of where an animal spends time (location heatmap) or where a behavior occurs, binned over the arena.

hyperparameters

The configurable settings of a classifier fixed before training β€” for a random forest: number of trees, max features, min samples per leaf, split criterion. Set per classifier in the SimBA training interface.

interpolation

Filling in missing body-part coordinates (e.g. dropped/occluded frames) by estimating values from neighbouring frames.

keypoint

Synonym for body-part β€” a tracked point produced by pose estimation.

Kleinberg smoothing
burst detection

A burst-detection algorithm (Kleinberg, 2003) applied to classifier output to merge fragmented detections into coherent bouts and remove noise.

latency

The time from the start of a session (or a trigger) to the first occurrence of a behavior; reported per video in SimBA’s aggregate statistics.

machine results

The per-video CSV files (in project_folder/csv/machine_results) holding the classifier predictions for each frame.

maDLC

Multi-animal DeepLabCut β€” the multi-animal variant of DeepLabCut.

minimum bout length

The shortest allowed bout duration; shorter detected episodes are removed as noise during post-classification smoothing.

multi-animal tracking
identity

Tracking several animals at once while maintaining each individual’s identity across frames (and recovering it after occlusion), e.g. via maDLC or SLEAP.

Observer

Noldus The Observer XT β€” commercial event-logging software for manual behavioral annotation; importable into SimBA.

occlusion

When a body-part is hidden (by another animal, an object or self) and so is poorly tracked or missing β€” often handled by interpolation.

outlier correction

Detecting and correcting implausible body-part coordinates (location- and movement-based) before feature extraction.

oversampling

Re-balancing training data by duplicating (or synthesising) minority-class (behavior-present) frames so the classifier sees them more often. See class imbalance.

p
pose confidence

The probability/likelihood score (0–1) that pose estimation assigns to each tracked body-part, indicating tracking reliability.

path plot

A visualization tracing an animal’s movement trajectory through the arena over time.

pose estimation

Tracking the 2D positions of animal body-parts across video frames, using tools such as DeepLabCut, SLEAP or YOLO.

precision
recall
F1

Standard classification metrics. Precision = fraction of predicted-positive frames that are correct; recall = fraction of true behavior frames detected; F1 = their harmonic mean.

project config

The project_config.ini file at the root of a SimBA project, storing all project settings (paths, body-parts, classifiers, thresholds).

px/mm
pixels per millimeter

The conversion factor between image pixels and real-world millimetres, used to report distances/speeds in physical units. Set per video via a known reference length.

random forest

The default supervised algorithm behind a SimBA classifier: an ensemble of decision trees whose votes give a per-frame behavior probability.

ROI

Region of Interest β€” a user-defined shape (rectangle, circle or polygon) drawn on the video frame, used to quantify time spent, entries, movement and directionality within specific areas.

sequential analysis

Analysing the order and timing of behaviors β€” which tend to precede or follow others (see FSTTC) β€” to uncover behavioral structure.

severity scoring

Grading the intensity of a detected behavior (e.g. attack severity) using movement/feature-based criteria.

SHAP

SHapley Additive exPlanations β€” a model-interpretability method giving each feature a contribution score, used in SimBA to explain why a classifier made a prediction.

SLEAP

An open-source multi-animal pose estimation framework whose output SimBA can import.

sliding window
rolling window

A fixed-length time window slid across the data to compute time-resolved features (e.g. mean velocity over the last 0.5 s).

smoothing

Reducing frame-to-frame jitter in tracking data (e.g. Savitzky–Golay or Gaussian) to stabilise body-part trajectories.

SMOTE

Synthetic Minority Over-sampling Technique β€” generates new synthetic minority-class training examples by interpolating between existing ones, rather than plain duplication. One of SimBA’s oversampling options.

Solomon

Solomon Coder β€” a free manual event-logging / ethogram coding tool; SimBA imports its coded annotations.

spontaneous alternation

A Y- or T-maze assay of spatial working memory, scored as the tendency to visit maze arms in non-repeating sequences. SimBA derives alternation metrics from pose estimation.

SuperAnimal-TopView

A zero-shot, pre-trained top-view mouse pose estimation model (from the DeepLabCut SuperAnimal family) that SimBA can use without user training.

third-party annotation tool

External behavior-annotation software whose frame-by-frame labels SimBA can import and append to extracted features as ground-truth annotation. Supported tools include BORIS, Ethovision, Observer, Solomon, DeepEthogram and BENTO.

time bins

Dividing a session into fixed-duration intervals (e.g. 60 s) to report how metrics change over the course of a recording.

UMAP

Uniform Manifold Approximation and Projection - a dimensionality-reduction method used in SimBA’s unsupervised workflows to embed high-dimensional features into 2-D for clustering and visualization.

undersampling

Re-balancing training data by randomly dropping majority-class (behavior-absent) frames to a target ratio of absent-to-present frames. See class imbalance.

validation

Checking a trained classifier on a held-out or new video β€” including the one-click β€œvalidation video” with the predicted probability overlaid frame-by-frame.

velocity

An animal’s speed of movement (distance per unit time), typically derived from the frame-to-frame displacement of a body-part or centroid, in px/mm-scaled units.

video info

The per-project table (video_info.csv) mapping each video to its FPS, resolution and px/mm.

YOLO

A fast real-time object/keypoint detection model family; SimBA supports YOLO-based detection and pose estimation workflows.