FoMo: Model Parameters for Visual Foraging Behavior Analysis

5.5 KB of model parameters from the FoMo generative model for analyzing sequential decision-making in visual foraging tasks. The dataset, authored by Alasdair D. F. Clarke and last updated in May 2026, likely contains interpretable parameters for predicting target-by-target selection behavior. It builds upon a published PLOS Computational Biology paper to incorporate spatial structure into foraging analysis.

Use Cases

• Estimating individual biases in target selection based on the described Bayesian statistical model.
• Predicting participant selection behavior on a target-by-target basis using the generative model parameters.
• Analyzing organized spatial behaviors, such as grid-following strategies, using the spatial-structure parameters.
• Comparing individual differences across a range of descriptive statistics for human and non-human animal behavior.

Strengths

• Model parameters are designed to be interpretable, allowing for understanding of behavioral differences.
• The model incorporates spatial structure, which reportedly improves prediction accuracy for participants using grid-following strategies.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.

Provenance

Source

Alasdair D. F. Clarke via figshare.

Collection Method

Likely generated from the FoMo model applied to visual foraging experiment data.

Freshness

Last updated 2026-05-12 17:48:34; freshness should be verified.