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Updated: Feb 24, 2026

Decoding Natural Behavior from Neuroethological Embedding
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Published on: October 3, 2025

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Diferencias individuales en redes neuronales artificiales capturan diferencias individuales en el comportamiento

Herrick Fung, N Apurva Ratan Murty, Dobromir Rahnev

    bioRxiv : the preprint server for biology
    |February 23, 2026
    PubMed
    Resumen

    Las redes neuronales artificiales (ANN) muestran diferencias individuales en el rendimiento, reflejando el comportamiento humano. Esto sugiere que las ANN pueden modelar la variabilidad humana en la percepción y la cognición.

    Palabras clave:
    redes neuronales artificialesdiferencias individualescomportamiento humanomodelado cognitivovariabilidad perceptual

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    Área de la Ciencia:

    • Ciencia Cognitiva
    • Neurociencia Computacional
    • Inteligencia Artificial

    Sus antecedentes:

    • El comportamiento humano exhibe una variabilidad individual significativa.
    • A menudo se asume que las redes neuronales artificiales (ANN) carecen de diferencias individuales.
    • Comprender las fuentes de variabilidad es clave en el modelado cognitivo.

    Objetivo del estudio:

    • Investigar si las instancias individuales de redes neuronales artificiales (ANN) muestran diferencias conductuales.
    • Determinar si las diferencias individuales de ANN imitan la variabilidad conductual humana.
    • Explorar el potencial de las ANN como modelos para la variabilidad humana.

    Principales métodos:

    • Se entrenaron y probaron 60 instancias de ANN en tres arquitecturas para tareas de reconocimiento de dígitos y objetos.
    • Se recopilaron datos conductuales (precisión, confianza, tiempo de respuesta) de ANN y 60 humanos.
    • Se cuantificó la fuerza de la correlación entre las diferencias individuales de ANN y humanas.

    Principales resultados:

    • Múltiples instancias de ANN mostraron diferencias individuales sustanciales en precisión, confianza y tiempo de respuesta.
    • Las diferencias individuales de ANN se correlacionaron consistentemente con las diferencias individuales humanas en tareas y métricas.
    • La fuerza de la correlación entre humanos y ANN se aproximó a los puntos de referencia humanos-humanos.

    Conclusiones:

    • Las ANN, incluso con arquitecturas idénticas, exhiben diferencias individuales que reflejan la variabilidad humana.
    • Los conjuntos de ANN pueden servir como proxies computacionales para estudiar los mecanismos de la variación conductual humana.
    • Esta investigación une la inteligencia artificial y la ciencia cognitiva al modelar las diferencias individuales.