π Glossaryο
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).
No terms match your filter.
- aggregate statisticsο
Session- or video-level summaries of classifier output (total time, bout counts, mean bout duration, latency, etc.) saved to the project
logs.- AMBERο
A pose-estimation pipeline for maternal-pup interaction analysis whose tracking data SimBA can import.
- anchored ROIο
- animal-anchored ROIο
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.
- annotationο
- labellingο
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.
- arenaο
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 subtractionο
A markerless segmentation technique that models the static scene and flags pixels differing from it as the moving animal; the basis of SimBAβs blob tracking.
- behaviorο
- targetο
The action a SimBA classifier is trained to detect (e.g. attack, grooming, freezing). Also referred to as the target.
- BENTOο
A MATLAB GUI (Caltech) for browsing, annotating and analysing synchronised behavioral, tracking and neural data; SimBA imports its annotations.
- blob trackingο
- contour trackingο
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-partο
A single tracked point on an animal (e.g.
nose,left_ear,tail_base), produced by pose estimation and stored asx,y(and probability) columns.- BORISο
Behavioral Observation Research Interactive Software β a free, open-source event-logging program for manual behavioral coding; SimBA imports its exported annotations.
- bounding boxο
The smallest axis-aligned (or rotated) rectangle that encloses an animal or a set of body-parts; used for overlap, area and proximity computations.
- boutο
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.
- centroidο
The geometric centre of a set of body-parts (or a shape); often used as a single location for an animal.
- circular statisticsο
Statistics for angular/directional data (degrees), where 359Β° and 1Β° are close. Used in SimBA for heading, turning and directional analyses.
- CLAHEο
Contrast Limited Adaptive Histogram Equalization - a local contrast-enhancement step in SimBAβs video tools, used to improve tracking on low-contrast footage.
- class imbalanceο
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 βabsentβ. Addressed with re-sampling (see oversampling, undersampling, SMOTE).
- classifierο
A supervised machine-learning model (typically a random forest) trained on annotated features to predict the presence of a behavior on each frame.
- clusteringο
- embeddingο
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 matrixο
A table of predicted vs. true labels (true/false positives and negatives) used to evaluate a classifier.
- convex hullο
The smallest convex polygon enclosing a set of body-parts; a common basis for animal area, shape and overlap metrics.
- cross-validationο
Splitting annotated data into train/test folds to estimate how well a classifier generalises to unseen frames, guarding against over-fitting.
- cue lightο
An experimentally controlled light stimulus; SimBAβs cue-light tools detect when each light is on or off and quantify behavior and movement relative to those states.
- DeepEthogramο
An open-source supervised deep-learning tool that classifies behaviors directly from raw video frames; SimBA can import its predictions as labels.
- DeepLabCutο
- DLCο
A popular open-source pose estimation toolbox. SimBA imports DLC tracking data (single- and multi-animal).
- directingο
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 animalβs heading and the target.
- directionalityο
Whether, and where, an animal is facing β e.g. toward another animal, a body-part or a ROI.
- discrimination thresholdο
- probability thresholdο
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 alignmentο
Re-centering and rotating each frame so a chosen body-part is fixed in position and orientation, removing the animalβs global location/heading from the analysis.
- ethogramο
A catalogue of the distinct behaviors an animal performs, and (in a session) their occurrence over time.
- Ethovisionο
Noldus EthoVision XT β commercial video-tracking and behavioral-analysis software; SimBA can import its exported annotations.
- FaceMapο
An open-source keypoint/behavioral-motion tracking tool whose output SimBA can import as a pose estimation source.
- featureο
- feature extractionο
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 importanceο
A ranking of how much each feature contributes to a classifierβs decisions (e.g. Gini importance, permutation importance, or SHAP).
- FPSο
Frames per second β the video frame rate. Required to convert frame counts to seconds and to compute time-based metrics.
- FSTTCο
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 plotο
A timeline visualization showing when each behavior occurs across a session as horizontal bars.
- geometryο
Representing animals/arenas as shapes (points, lines, convex hulls, polygons, circles) via Shapely, enabling area, overlap, distance and containment computations.
- heatmapο
A spatial visualization of where an animal spends time (location heatmap) or where a behavior occurs, binned over the arena.
- hyperparametersο
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.
- interpolationο
Filling in missing body-part coordinates (e.g. dropped/occluded frames) by estimating values from neighbouring frames.
- keypointο
Synonym for body-part β a tracked point produced by pose estimation.
- Kleinberg smoothingο
- burst detectionο
A burst-detection algorithm (Kleinberg, 2003) applied to classifier output to merge fragmented detections into coherent bouts and remove noise.
- latencyο
The time from the start of a session (or a trigger) to the first occurrence of a behavior; reported per video in SimBAβs aggregate statistics.
- machine resultsο
The per-video CSV files (in
project_folder/csv/machine_results) holding the classifier predictions for each frame.- maDLCο
Multi-animal DeepLabCut β the multi-animal variant of DeepLabCut.
- minimum bout lengthο
The shortest allowed bout duration; shorter detected episodes are removed as noise during post-classification smoothing.
- multi-animal trackingο
- identityο
Tracking several animals at once while maintaining each individualβs identity across frames (and recovering it after occlusion), e.g. via maDLC or SLEAP.
- Observerο
Noldus The Observer XT β commercial event-logging software for manual behavioral annotation; importable into SimBA.
- occlusionο
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 correctionο
Detecting and correcting implausible body-part coordinates (location- and movement-based) before feature extraction.
- oversamplingο
Re-balancing training data by duplicating (or synthesising) minority-class (behavior-present) frames so the classifier sees them more often. See class imbalance.
- pο
- pose confidenceο
The probability/likelihood score (0β1) that pose estimation assigns to each tracked body-part, indicating tracking reliability.
- path plotο
A visualization tracing an animalβs movement trajectory through the arena over time.
- pose estimationο
Tracking the 2D positions of animal body-parts across video frames, using tools such as DeepLabCut, SLEAP or YOLO.
- precisionο
- recallο
- F1ο
Standard classification metrics. Precision = fraction of predicted-positive frames that are correct; recall = fraction of true behavior frames detected; F1 = their harmonic mean.
- project configο
The
project_config.inifile at the root of a SimBA project, storing all project settings (paths, body-parts, classifiers, thresholds).- px/mmο
- pixels per millimeterο
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 forestο
The default supervised algorithm behind a SimBA classifier: an ensemble of decision trees whose votes give a per-frame behavior probability.
- ROIο
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 analysisο
Analysing the order and timing of behaviors β which tend to precede or follow others (see FSTTC) β to uncover behavioral structure.
- severity scoringο
Grading the intensity of a detected behavior (e.g. attack severity) using movement/feature-based criteria.
- SHAPο
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.
- SLEAPο
An open-source multi-animal pose estimation framework whose output SimBA can import.
- sliding windowο
- rolling windowο
A fixed-length time window slid across the data to compute time-resolved features (e.g. mean velocity over the last 0.5 s).
- smoothingο
Reducing frame-to-frame jitter in tracking data (e.g. SavitzkyβGolay or Gaussian) to stabilise body-part trajectories.
- SMOTEο
Synthetic Minority Over-sampling Technique β generates new synthetic minority-class training examples by interpolating between existing ones, rather than plain duplication. One of SimBAβs oversampling options.
- Solomonο
Solomon Coder β a free manual event-logging / ethogram coding tool; SimBA imports its coded annotations.
- spontaneous alternationο
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-TopViewο
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 toolο
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 binsο
Dividing a session into fixed-duration intervals (e.g. 60 s) to report how metrics change over the course of a recording.
- UMAPο
Uniform Manifold Approximation and Projection - a dimensionality-reduction method used in SimBAβs unsupervised workflows to embed high-dimensional features into 2-D for clustering and visualization.
- undersamplingο
Re-balancing training data by randomly dropping majority-class (behavior-absent) frames to a target ratio of absent-to-present frames. See class imbalance.
- validationο
Checking a trained classifier on a held-out or new video β including the one-click βvalidation videoβ with the predicted probability overlaid frame-by-frame.
- velocityο
An animalβs 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 infoο
The per-project table (
video_info.csv) mapping each video to its FPS, resolution and px/mm.- YOLOο
A fast real-time object/keypoint detection model family; SimBA supports YOLO-based detection and pose estimation workflows.