Fig. 2: Exploring PD phenotypes through top 20 behavioural features with insights from XGB model interpretation. | Nature Communications

Fig. 2: Exploring PD phenotypes through top 20 behavioural features with insights from XGB model interpretation.

From: Integrating artificial intelligence and optogenetics for Parkinson’s disease diagnosis and therapeutics in male mice

Fig. 2

a Graphic summary of the top 20 features with schematics of key feature components. Features ranked by their global impact on the XGB model, depicted by blue horizontal bar graphs (from the validation dataset). The colour-coded boxes detail the feature-associated body parts and the PD symptomatic categories. The beeswarm plots (SHAP summary plot) offer local explanations for each feature, with individual dots representing motion clips. The position of each dot is determined by SHAP values (log odds of PD likelihood), reflecting its impact direction and magnitude on model prediction (negative and positive for non-PD [NP] and PD, respectively). The dot colour represents the magnitude of feature value. Clusters of dots denote the prevalence of a feature’s effect on the model output. Limb-associated features are further highlighted with shading. b Representative SHAP force plots for motion clips correctly classified as NP and PD, illustrating the integration of feature impacts on model predictions. Each plot aligns feature contributions (SHAP values) along the x-axis, culminating in the total effect denoted as f(x), with the main features annotated with their rank and feature values. Schematics were created in BioRender. Heo, W. (2025) https://BioRender.com/cykyauz.

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