Spatial Analysis of Motivation Using Weighted Voronoi Diagrams

  • Alejandro León Maldonado

We are pleased to share our most recent publication in the journal Computación y Sistemas, titled:

Spatial Dynamics Behavioral Analysis of Motivational Operations Using Weighted Voronoi Diagrams
📄 DOI: 10.13053/CyS-29-1-5509

This work proposes a novel computational approach to analyze how behavior is distributed in space when motivational conditions change, such as food deprivation, water deprivation, or both. Using weighted Voronoi diagrams, it is possible to visualize areas of greatest behavioral relevance and uncover spatial patterns organized according to these variables.

🔬 What do we contribute?

  • An automated method to segment experimental spaces based on displacement data.

  • Clear visual representations of behavioral patterns under different conditions.

  • A functional tool for comparative and experimental studies in behavioral science.

👥 This research is a collaboration between the Faculty of Mathematics and the Center for Biomedical Research at the Universidad Veracruzana.

🧪 The Experiment

To test this method, we designed an experiment with the following characteristics:

  • Subjects: 6 Wistar rats

  • Experimental conditions:
    a) Water deprivation
    b) Food deprivation
    c) Combined deprivation
    d) No deprivation

  • Sessions: 24 sessions of 20 minutes each

  • Sampling rate: 5 frames per second

  • Experimental setting: Open field (92×92 cm) with food and water dispensers

🔍 What is a weighted Voronoi diagram?

In this computational approach:

  • The space is divided into a uniform grid.

  • Generator points are identified based on where the subjects spent the most time.

  • These points are assigned a weight proportional to the accumulated time.

  • The resulting diagram segments the space into Regions of Behavioral Relevance (RBRs).

These regions reflect the parts of the environment with the highest functional or motivational relevance for the subject.

🎯 What do the diagrams reveal?

The results show how different motivational conditions reorganize spatial behavior in clear and distinct ways:

✔️ Food or water deprivation: areas near the corresponding dispenser become dominant.
✔️ Combined deprivation: effects are not simply additive; food areas are more relevant than water ones.
✔️ No deprivation: peripheral zones (e.g., corners) become behaviorally relevant, possibly as “safe bases.”

📊 Why is this important?

Each RBR provides key information about the spatial organization of behavior. Analyzing these patterns allows us to:

  • Identify key activity zones

  • Compare behavior distribution across conditions

  • Evaluate the impact of Motivational Operations (MOs) on movement and space use

🔁 Key takeaways

  • Spatial organization of behavior is not symmetrical between food and water deprivation.

  • Combined deprivation results in non-additive patterns.

  • Behaviorally relevant zones shift dynamically depending on motivational state.

  • This method offers a clear visual representation of behavioral patterns in complex settings.

💡 Applications

This approach is useful across multiple disciplines:

📐 Experimental Behavior Analysis
🧠 Neuroscience
🌱 Behavioral Ecology
⚙️ Computational visualization of behavioral data

👨‍🔬 Authors

Carlos Hernández-Linares, Porfirio Toledo, Brenda Medina, Varsovia Hernández, Martha Avendaño, Víctor Quintero, Alejandro León
📍 Universidad Veracruzana

📥 Access the full article

🔗 https://www.cys.cic.ipn.mx/ojs/index.php/CyS/article/view/5509/3890
📄 DOI: 10.13053/CyS-29-1-5509