{"id":664,"date":"2025-03-29T13:13:51","date_gmt":"2025-03-29T19:13:51","guid":{"rendered":"https:\/\/www.uv.mx\/personal\/aleleon\/?p=664"},"modified":"2025-03-29T15:56:44","modified_gmt":"2025-03-29T21:56:44","slug":"analisis-espacial-de-operaciones-motivacionales-con-diagramas-de-voronoi-ponderados","status":"publish","type":"post","link":"https:\/\/www.uv.mx\/personal\/aleleon\/2025\/03\/29\/analisis-espacial-de-operaciones-motivacionales-con-diagramas-de-voronoi-ponderados\/","title":{"rendered":"Spatial Analysis of Motivation Using Weighted Voronoi Diagrams"},"content":{"rendered":"

We are pleased to share our most recent publication in the journal Computaci\u00f3n y Sistemas<\/em>, titled:<\/p>\n

Spatial Dynamics Behavioral Analysis of Motivational Operations Using Weighted Voronoi Diagrams<\/strong>
\ud83d\udcc4 DOI: 10.13053\/CyS-29-1-5509<\/p>\n

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<\/strong>, it is possible to visualize areas of greatest behavioral relevance and uncover spatial patterns organized according to these variables.<\/p>\n

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\ud83d\udd2c What do we contribute?<\/h3>\n
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    An automated method to segment experimental spaces based on displacement data.<\/p>\n<\/li>\n

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    Clear visual representations of behavioral patterns under different conditions.<\/p>\n<\/li>\n

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    A functional tool for comparative and experimental studies in behavioral science.<\/p>\n<\/li>\n<\/ul>\n

    \ud83d\udc65 This research is a collaboration between the Faculty of Mathematics<\/strong> and the Center for Biomedical Research<\/strong> at the Universidad Veracruzana.<\/p>\n

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    \ud83e\uddea The Experiment<\/h3>\n

    To test this method, we designed an experiment with the following characteristics:<\/p>\n

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    • \n

      Subjects:<\/strong> 6 Wistar rats<\/p>\n<\/li>\n

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      Experimental conditions:<\/strong>
      a) Water deprivation
      b) Food deprivation
      c) Combined deprivation
      d) No deprivation<\/p>\n<\/li>\n

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      Sessions:<\/strong> 24 sessions of 20 minutes each<\/p>\n<\/li>\n

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      Sampling rate:<\/strong> 5 frames per second<\/p>\n<\/li>\n

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      Experimental setting:<\/strong> Open field (92\u00d792 cm) with food and water dispensers<\/p>\n<\/li>\n<\/ul>\n

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      \ud83d\udd0d What is a weighted Voronoi diagram?<\/h3>\n

      In this computational approach:<\/p>\n

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        The space is divided into a uniform grid.<\/p>\n<\/li>\n

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        Generator points are identified based on where the subjects spent the most time.<\/p>\n<\/li>\n

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        These points are assigned a weight proportional to the accumulated time.<\/p>\n<\/li>\n

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        The resulting diagram segments the space into Regions of Behavioral Relevance (RBRs)<\/strong>.<\/p>\n<\/li>\n<\/ul>\n

        These regions reflect the parts of the environment with the highest functional or motivational relevance for the subject.<\/p>\n

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        \ud83c\udfaf What do the diagrams reveal?<\/h3>\n

        The results show how different motivational conditions reorganize spatial behavior in clear and distinct ways:<\/p>\n

        \u2714\ufe0f Food or water deprivation:<\/strong> areas near the corresponding dispenser become dominant.
        \u2714\ufe0f Combined deprivation:<\/strong> effects are not simply additive; food areas are more relevant than water ones.
        \u2714\ufe0f No deprivation:<\/strong> peripheral zones (e.g., corners) become behaviorally relevant, possibly as \u201csafe bases.\u201d<\/p>\n

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        \ud83d\udcca Why is this important?<\/h3>\n

        Each RBR provides key information about the spatial organization of behavior. Analyzing these patterns allows us to:<\/p>\n

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          Identify key activity zones<\/p>\n<\/li>\n

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          Compare behavior distribution across conditions<\/p>\n<\/li>\n

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          Evaluate the impact of Motivational Operations (MOs)<\/strong> on movement and space use<\/p>\n<\/li>\n<\/ul>\n

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          \ud83d\udd01 Key takeaways<\/h3>\n
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          • \n

            Spatial organization of behavior is not symmetrical<\/strong> between food and water deprivation.<\/p>\n<\/li>\n

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            Combined deprivation<\/strong> results in non-additive patterns<\/strong>.<\/p>\n<\/li>\n

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            Behaviorally relevant zones shift dynamically<\/strong> depending on motivational state.<\/p>\n<\/li>\n

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            This method offers a clear visual representation<\/strong> of behavioral patterns in complex settings.<\/p>\n<\/li>\n<\/ul>\n

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            \ud83d\udca1 Applications<\/h3>\n

            This approach is useful across multiple disciplines:<\/p>\n

            \ud83d\udcd0 Experimental Behavior Analysis
            \ud83e\udde0 Neuroscience
            \ud83c\udf31 Behavioral Ecology
            \u2699\ufe0f Computational visualization of behavioral data<\/p>\n

            \n

            \ud83d\udc68\u200d\ud83d\udd2c Authors<\/h3>\n

            Carlos Hern\u00e1ndez-Linares, Porfirio Toledo, Brenda Medina, Varsovia Hern\u00e1ndez, Martha Avenda\u00f1o, V\u00edctor Quintero, Alejandro Le\u00f3n
            \ud83d\udccd Universidad Veracruzana<\/p>\n

            \n

            \ud83d\udce5 Access the full article<\/h3>\n

            \ud83d\udd17 https:\/\/www.cys.cic.ipn.mx\/ojs\/index.php\/CyS\/article\/view\/5509\/3890<\/a>
            \ud83d\udcc4 DOI: 10.13053\/CyS-29-1-5509<\/p>\n